No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Integrative Tracking Control Strategy for Robotic Excavation
Abstract
Automated excavation is hard to achieve due to several inherent problems such as resistive force acting against the bucket, non-homogenous dynamics of various excavation media, and nonlinearities of the excavator’s hydraulics system. To deal with this issue, this paper provides an integrative control strategy for successful autonomous excavation that considers the mutually associated factors, i.e., position, contour, and force control. For the position tracking, a non-linear PI controller was designed to track the position of individual actuators of the excavator and thereby control the bucket tip’s position. In addition, the contour control technique was applied to achieve an optimal excavation path to minimize contour errors. Finally, to compensate for the ground resistive force during digging tasks, a force impedance controller was designed along with the time-delayed control that reduces the effect of dynamic uncertainties. Experimental results with a modified mini-wheeled excavator show that the developed integrative tracking control strategy can provide a comprehensive solution to improving the tracking performance for autonomous excavation that can simultaneously deal with the critical components of position, contour, and force control.
... They performed simulations and experiments with electro-hydraulic valve current values as control inputs [4]. Reginald et al. integrated impedance control, nonlinear PI, time-delay control, and cross-coupling compensation into the controller to achieve integrative control of position, force, and contour [20]. ...
... From Eq. (20), the observation error index converges to zero, and the convergence rate is related to ( ,̇). The acceleration signal in Eq. (18) will bring measurement noise or second-order differential error, so it is necessary to eliminate thëterm by constructing state variables. ...
... From Eq. (20), it is clear that the convergence performance of the observation error is determined by the gain matrix ( ,̇). As a result, it is necessary to reasonably design ( ,̇) so that ( ,̇) meets the requirements. ...
In construction automation, excavators frequently undertake intricate contouring tasks, including precise leveling and surface shaping. However, the absence of a dynamic model and error estimation approach for curved contours in existing solutions can significantly reduce operational precision. To address these challenges, a free-shape contour control method based on cross-coupling and double error pre-compensation is presented. The double error is a linear combination of tracking error and contour error. The curve contour error is calculated using a parameter-based backward approximation method. Furthermore, nonlinear disturbance observer and sliding mode control are combined to deal with the lumped disturbance. Simulation and platform experiment results demonstrate that the proposed controller has smaller chattering and contour error under loaded and extreme operating conditions. The control method provides an effective solution for excavators to complete different types of contour tasks. For further study, hydraulic system modeling will be considered to improve the performance of control system.
... However, hydraulic excavator systems are complex electromechanical-hydraulic integrated systems with nonlinear and multi-constrained characteristics. Meanwhile, dead zones, valve hysteresis, fluid leakages and mechanical wear of hydraulic valves lead to certain delays and errors in the trajectory control of hydraulic actuators [2]. The actuators on a classic excavator are controlled by a professional operator using joysticks, and the digging operation is completed based on his observations. ...
... x pl K pl = P c Q pl = K pq x pl − K pv P pv (2) Machines 2023, 11, 10 5 of 25 where x pl is the pilot valve spool displacement, K pl , K pq and K pv are the pilot valve spring stiffness, flow coefficient, and flow pressure coefficient, respectively, and Q pl and P pv are the load pressure and load flow of pilot valve, respectively. ...
Accurate control of excavator trajectory is the foundation for the intelligent and unmanned development of excavators. The excavator operation process requires multiple actuators to cooperate to complete the response action. However, the existing control methods to realize a single actuator of the excavator can no longer meet the practical demand. Based on this, a hybrid adaptive quantum particle swarm optimization algorithm (HAQPSO) is proposed to tune the proportional integral derivative (PID) controller parameters for enhancing the trajectory control accuracy of excavator actuators. To increase particle randomization and search speed and avoid the local convergence of QPSO, the QPSO is combined with circle chaotic mapping, Gaussian mutation operators, and adaptive adjustment factors, while the linear transformation of the contraction-expansion coefficient (CE) is improved to the dynamic adjustment mode. Through the interface block, a co-simulation platform for the load-sensitive system excavator is constructed, and trajectory experiments of multiple actuator compound actions are carried out. The simulation results show that—compared with ZN-PID, PSO-PID, and QPSO-PID—the trajectory error accuracy of the boom is improved by 26.59%, 32.95%, and 9.44%, respectively, which proves the high control accuracy of HAQPSO-PID in controlling the trajectory of multiple actuators.
... Then, these combined values become the input to the inverse kinematic block in the control system. In Figure 22, which shows the entire control design, the inverse kinematic output is sent to the PID controllers, which regulate the stroke of each actuator [35]. ...
This study’s goals are divided into two categories. The first is to design and build an excavator equipped with parallel electrical linear actuators. The second is to generate and test a PSO-based and a PFM-based path for this excavator in order to save energy by reducing energy consumption, improve the digging accuracy by minimizing the deviation between the desired and dug surfaces of the ground, and prevent colliding with subsurface objects. For this purpose, computer vision was employed to improve monitoring and verification. Five types of experiments were carried out in this investigation. The first two and the other three examined the impact of energy conservation in PSO- and PFM-based path generation, respectively. Finally, the results from these experiments were compared to identify and show the effect of optimal path generation.
... In multi-criteria decision making, cluster analysis is a potent technique that groups similar alternatives according to their attributes or performance across various criteria. It is an unsupervised learning technique made to find naturally occurring clusters or groupings within a dataset without the requirement for any pre-established labels or desired results [29]. It is crucial to remember that cluster analysis does not offer a clear ranking of options or information on preferences. ...
The comprehensive performance of unmanned excavators is crucial for the development and optimization of the field of construction machinery. To effectively improve the unmanned excavator to meet the needs of the market, it is imperative to quantify the evaluation method of the comprehensive performance of unmanned excavators. In this study, an evaluation method combining a fuzzy analytic hierarchy process and multivariate image area analysis method is proposed. Firstly, based on the feature extraction of the signal stability of the unmanned excavators, fifteen evaluation indexes were proposed. Then, the case study is used to obtain the scores corresponding to these indexes. The fuzzy analytic hierarchy process is applied to determine the relative weight of the selected evaluation criteria, in which the uncertain and imprecise judgments of decision makers are converted into fuzzy numbers. At the same time, the braking performance of the three types of unmanned excavators was comprehensively evaluated and ranked using the multivariate image area analysis method as an empirical example. Finally, a weight analysis is performed to check the robustness of the ranking results. The results show that the proposed method is effective and feasible. It provides a reference for the performance improvement and efficiency optimization of unmanned excavators.
This paper presents a bucket-filling controller for autonomous excavation. The key innovation of this controller is that it can react to the encountered soil conditions and adapt the excavation behavior online without the explicit knowledge of soil properties while respecting machine limitations to avoid stalling. At the same time, the controller takes into account the current terrain elevation and adheres to a maximum-depth constraint to achieve a desired design. The controller is trained entirely in simulation with Reinforcement Learning (RL). A simple analytical soil model based on the Fundamental Equation of Earth-Moving (FEE) is used to simulate ground interactions. To learn an appropriate excavation strategy for a wide variety of scenarios, soil parameters, as well as other properties of the environment, are randomized extensively during training. We test and evaluate the controller on a 12 t excavator with a conventional two-stage hydraulic system in a wide range of different soil conditions. Additionally, we show the excavation of a complete trench by integrating the controller into an autonomous excavation planning system. The experiments demonstrate that the controller can robustly adapt the excavation trajectory based on the encountered conditions and shows competitive performance compared to a professional machine operator. Video: https://youtu.be/rQKUk9nKaCk.
Traditional modeling methods for digging load of excavators are often computationally expensive and require prior knowledge of soil parameters, which severely limits their engineering applications. According to the digging load characteristics in typical digging tasks, this paper presents an intelligent prediction method for digging load based on radial basis function (RBF) neural networks. The recursive least-squares (RLS) algorithm is used for weights updating. Back propagation neural network (BPNN), coupled discrete element method (DEM) and multi-body dynamics (MBD) simulation, and analytical model are applied for comparative studies. The simulation results illustrate that the RBF neural network model outperforms other comparative models in terms of prediction accuracy and computational cost. The hardware-in-loop (HIL) experiments are conducted to validate the proposed approach. Experimental results demonstrate that the error in the dynamic behavior of the excavator under the predicted digging load is less than 7%. This paper lays the foundation for digging load prediction in intelligent excavators.
To address the universal single-rod electrohydraulic system (EHS), a block-strict-feedback model is constructed for the position control loop design. Different from the previous strict-feedback controllers used in EHS, the proposed controller avoids the model order-reduction problem and relaxes the strict-feedback model assumption for the single-rod EHS encountered by the existing results. Hence, all the dynamic physical states of single-rod EHS are directly used in control design. Since the hydraulic parametric uncertainties and the external load would degrade the output tracking performance of EHS, an adaptive control is proposed to guarantee all system states globally and uniformly bounded with parameter adaptation. The constraint holding technique called prescribed performance constraint (PPC) is adopted to improve the output response and to achieve a desirable performance. The effectiveness of the proposed controller is demonstrated by a comparison with the strict-feedback controller via both simulation and experiments.
The pivotal steering ability of vehicles is important in the case of narrow steering space. In this study, a pivot steering system for the rescue vehicle is designed, and the 1D + 3D co-simulation model is established based on automatic dynamic analysis of mechanical systems (Adams) and advanced modelling environment for performing simulation of engineering systems (AMESim). The dynamic analysis of the pivot steering system has been compared with the theoretical calculations, which proved the correction of the model. In addition, through the simulation, the authors can hold the conclusion that the tyre cornering stiffness has a great influence on the pivot steering system.
For electro-hydraulic system of large flow and overloading, established position and pressure closed-loop control in accordance with the conventional hydraulic servo system theory that system control algorithm is complicated and difficult to implement. This article presents a method which gives priority to position closed-loop control and establishes the corresponding relation between pressure of hydraulic cylinder and load by collecting the pressure signal from rear cavity and rod cavity of hydraulic cylinder; meanwhile, applied position-pressure conversion formula will turn dynamic pressure signal into position signal and compensate the transformed position signal to the master position closed loop of the electro-hydraulic servo system which could achieve the position-pressure master-slave control. The simulation results show that the control method is correct, effective, and feasible. The results indicate that the method can achieve online converting between position and pressure which are different variables and improve the response speed and control precision of the system.
As the advances in computer control technology keep emerging, robotic hydraulic excavator becomes imperative. It can improve excavation accuracy and greatly reduce the operator’s labor intensity. The 12-ton backhoe bucket excavator has been utilized in this research work where this type of excavator is commonly used in engineering work. The kinematics model of operation device (boom, arm, bucket, and swing) in excavator is established in both Denavit-Hartenberg coordinates for easy programming and geometric space for avoiding blind spot. The control approach is based on trajectory tracing method with displacements and velocities feedbacks. The trajectory planning and autodig program is written by Visual C++. By setting the bucket teeth’s trajectory, the program can automatically plan the velocity and acceleration of each hydraulic cylinder and motor. The results are displayed through a 3D entity simulation environment which can present real-time movements of excavator kinematics. Object-Oriented Graphics Rendering Engine and skeletal animation are used to give accurate parametric control and feedback. The simulation result shows that a stable linear autodig can be achieved. The errors between trajectory planning command and simulation model are analyzed.
Slope excavation is one of the most crucial steps in the construction of a hydraulic project. Excavation project quality assessment and excavated volume calculation are critical in construction management. The positioning of excavation projects using traditional instruments is inefficient and may cause error. To improve the efficiency and precision of calculation and assessment, three-dimensional laser scanning technology was used for slope excavation quality assessment. An efficient data acquisition, processing, and management workflow is presented in this paper. Based on the quality control indices, including the average gradient, slope toe elevation, and overbreak and underbreak, cross-sectional quality assessment and holistic quality assessment methods are proposed to assess the slope excavation quality with laser scanned data. An algorithm has also been established to calculate the excavated volume with laser-scanned data. A field application and a laboratory experiment were carried out to verify the feasibility of these methods for excavation quality assessment and excavated volume calculation. The results show that the quality assessment indices can be obtained rapidly and accurately with design parameters and scanned data, and the results of holistic quality assessment are consistent with those of cross-sectional quality assessment. In addition, the time consumption of this method in an excavation project quality assessment can be reduced by 70%−90%, as compared with the traditional method. The excavated volume calculated with the scanned data only slightly differs from measured data, demonstrating the applicability of the excavated volume calculation method presented in this study.
This paper presents the trajectory control of a 2DOF mini electro-hydraulic excavator by using fuzzy self tuning with neural
network algorithm. First, the mathematical model is derived for the 2DOF mini electro-hydraulic excavator. The fuzzy PID and
fuzzy self tuning with neural network are designed for circle trajectory following. Its two links are driven by an electric
motor controlled pump system. The experimental results demonstrated that the proposed controllers have better control performance
than the conventional controller.
This paper presents a practical nonsingular terminal sliding-mode (TSM) tracking control design for robot manipulators using time-delay estimation (TDE). The proposed control assures fast convergence due to the nonlinear TSM, and requires no prior knowledge about the robot dynamics due to the TDE. Despite its model-free nature, the proposed control provides high-accuracy control and robustness against parameters variations. The simplicity, robustness, and fast convergence of the proposed control are verified through both 2-DOF planar robot simulations and 3-DOF PUMA-type robot experiments.
The generalized Jacobian matrix was introduced for dealing with end-effector control in space robots. One of the applications of this Jacobian is to be used in Jacobian transpose control to generate joint torques given end-effector position error. It would be misleading, however, to consider the transpose of this Jacobian as a mapping from end-effector force/moment to controlled joint torques for underactuated systems or floating base robots. This paper explains why it does not represent the mapping and provides a simple example. Later, the correct mapping is provided using the dynamically consistent Jacobian inverse and then a method to compute the actuated-joint torques is explained given the desired end-effector force. Finally, the effect of using the generalized Jacobian in the Jacobian transpose control is analyzed.
A position-based impedance controller for excavator-type
manipulators has been developed in our laboratory. This paper describes
the proposed impedance controller and presents supporting experimental
results. First, the problem of impedance control for a single hydraulic
actuator is addressed and a method is presented for stability analysis.
Steady-state position and force tracking of the closed loop system is
also studied. Then, the desired impedance of the end-effector (bucket of
the excavator) is mapped onto the hydraulic cylinders using the arm
Jacobian and accurate estimates of the arm inertial and gravity terms. A
nonconservative method is presented for predicting stability of the
multivariable closed loop system. Experiments with an instrumented mini
excavator (for the single cylinder case) show that the designed
impedance controller has a good performance
Earth-moving machines such as hydraulic excavators are usually
used for carrying out contact tasks. Impedance control can be employed
as an approach for achieving compliant motion in such tasks. This paper
describes a position-based impedance controller that has been developed
in our laboratory for excavator-type manipulators, and presents the
supporting experimental results. First, the problem of impedance control
for a single hydraulic cylinder is addressed and a method is presented
to analyze the system stability. The steady-state position and force
tracking accuracy of the closed-loop system is also studied. Next, the
problem of impedance control for a multi-link hydraulic excavator is
addressed and the arm Jacobian and accurate estimates of the arm
inertial terms are employed to map the desired impedance of the
end-effector (bucket of the excavator) onto the hydraulic cylinders.
Various contact experiments carried out using an instrumented
mini-excavator demonstrate that the proposed impedance controller has
very good performance for both single-link and multilink cases
A simple robust compliant-motion-control technique is presented for a robot manipulator with nonlinear friction. The control technique incorporates both time-delay-estimation technique and ideal velocity feedback; the former is used to cancel out soft nonlinearities, and the latter serves to reduce the effect of hard nonlinearities, including Coulomb friction and stiction. The proposed controller has a simple structure and yet provides good online friction compensation without modeling friction. The robustness of the proposed method has been confirmed through comparisons with other controllers in 2-DOF SCARA-type industrial robot experiments.
This article introduces a novel control strategy for the uncertain eye-to-hand system, which is considered to work with unknown model of constraint surface and uncalibrated camera model. Besides, the uncertain dynamics and kinematics are also included in the system. In order to be closer to the real robot system, we also consider it with dead-zone inputs situation. So the parameter intervals and slopes of the dead-zone model is also unknown. Hence, a novel adaptive image-based visual servoing (IBVS) and force control approach is put forward. The control method of unknown force and uncalibrated camera model is achieved by adaptive control. The solution of unknown dead-zone inputs is completed by designing a inverse smooth model of dead-zone inputs to offset the nonlinear affect due to the actuator constraint, and the whole system is proved that the force tracking control and image position converge to zero asymptotically. Finally, the MATLAB simulation is set up and the experiment shows the validity of the proposed scheme.
In electro-hydraulic system (EHS), there exist typical lumped uncertainties due to the uncertain hydraulic parameters and unknown external load, which usually decline the output dynamic performance. To address this problem, this paper proposes a neural adaptive control for single-rod EHS to improve the dynamic tracking performance of the cylinder position under these lumped uncertainties. A Radial-Basis-Function (RBF) neural network is constructed to train the unknown model dynamics caused by lumped uncertainties and obtain the self-learning models. Moreover, an adaptive estimation law is used to self-tune the trained-node weights and the self-learning models are online optimized to enhance the robustness of the neural adaptive controller. The effectiveness of the proposed controller has been verified by comparative simulation and experimental results with the other typical control methods.
For high control performance of cable-driven manipulators, we design a new adaptive time-delay control (ATDC) using enhanced nonsingular fast terminal sliding mode (NFTSM). The proposed ATDC uses time-delay estimation (TDE) to acquire the lumped dynamics in a simple way and founds a practical model-free structure. Then, a new enhanced NFTSM surface is developed to ensure fast convergence and high control accuracy. To acquire good comprehensive performance under lumped uncertainties, we propose a novel adaptive algorithm for the control gain which can regulate itself based on the control errors timely and accurately. Benefitting from the TDE and proposed enhanced NFTSM surface and adaptive control gain, our proposed ATDC is model-free, fast response, and accurate. Theoretical analysis concerning system stability and control precision and convergence speed are given based on Lyapunov theory. Finally, the advantages of our ATDC over existing methods are verified with comparative experiments.
A time-delayed control (TDC) method is known as a simple, robust and non model-based control scheme that requires the fast sampling time, the accurate measurement of joint acceleration signals, and the accuracy of the inertia model of a robot manipulator. Among them, sampling time and acceleration signals are hardware dependent and can be solved. Then a user specified inertia model becomes a key role for the performance of TDC. When the selection of the diagonal element of the inertia matrix of a robot manipulator is used, the ill selection of the constant inertia matrix may lead to the poor tracking performance as well as instability. In addition, an appropriate selection of an inertia matrix for different tasks of the robot is not easy. Therefore, in this paper, an intelligent way of using a neural network is proposed to compensate for the deviation of the constant inertia matrix of a robot manipulator. The role of the neural network is to improve the tracking performance of a robot manipulator by compensating for the deviated error of the inertia matrix while satisfying the stability bound. Simulation studies of a three link robot are presented to confirm the proposal.
This paper investigates the fuzzy position/force hybrid control for a class of 5-degree-of-freedom (DOF) redundantly actuated parallel robots. The position control law is designed based on the proportional-integral-differential (PID) for the 5-DOF redundantly actuated parallel robot. The fuzzy proportional-integral (PI) redundant actuation force control law is designed based on the position/force hybrid control structure for the 5-DOF redundantly actuated parallel robot. The optimum driving force is obtained in the presence of interference, and the force tracking performance of the fuzzy PI controller is better than the conventional PI controller under the interference condition. Based on the fuzzy position/force hybrid controller, the tracking performance of the closed-loop system for the 5-DOF redundantly actuated parallel robot is improved by using the fuzzy position/force hybrid controller and the interference is eliminated effectively in the control system design. Finally, the co-simulation results of ADAMS and MATLAB/SIMULINK are given to show the effectiveness and advantages of the proposed methods compared with the conventional PI controller.
In this paper, we propose a novel adaptive time-delay control (ATDC) for accurate trajectory tracking of cable-driven robots. The designed ATDC utilizes time- delay estimation (TDE) to estimate the lumped dynamics of the system, and provides an attractive model-free structure. Then, a robust control is designed for ATDC with fractional-order nonsingular terminal sliding mode (FONTSM) dynamics. Afterwards, a novel nonlinear adaptive law is proposed for the control gains to improve the control performance. Thanks to TDE and FONTSM dynamics, the proposed ATDC is model-free and highly accurate. Benefiting from the proposed nonlinear adaptive law, suppression of chattering issue and enhanced control performance have been obtained simultaneously. Stability is analyzed based on Lyapunov approach. Then, practical experiments have been performed to illustrate the advantages of our ATDC.
This work showcases the development and results of a model-predictive controller (MPC) for a marine active-heave compensation (AHC) system. The system utilizes a common hydraulic 4-way, 3-position proportional valve where the hysteresis, dead-band and non-linear properties have been overcome to directly control a radial piston motor in the experimental test setup. The MPC controller, with a set-point prediction algorithm, is used to actuate the unloaded hydraulic test system and the results are compared to a tuned Proportional-Integral-Derivative (PID) controller operating the same experimental setup. The MPC controller is found to track a variety of test cases and references while outperforming the tuned PID controller for all experiments. Additionally, a MATLAB Simulink model of the experimental setup is created and validated. Within the simulator, a load is then applied to the winch to test how the MPC and PID performance compare under loaded operating conditions. Based on the results of these tests, simulations of an MPC controller running in parallel with a Proportional-Integral (PI) controller are carried out for both the unloaded and loaded scenarios. For the conditions tested in this research, the resulting simulations suggest that the MPC-PI controller is able to decouple up to 99.6% of the transmitted motion.
The traditional constant impedance control is a simple but effective method widely used in many fields including contact force tracking. Using this method, the location of the environment relative to the robot and the stiffness of the environment must be known, and usually the desired force is constant. However, for applications in dynamic contact force tracking in uncertain environment, it is not an effective solution. In this paper, a new adaptive variable impedance control is proposed for force tracking which has the capability to track the dynamic desired force and compensate for uncertainties (in terms of unknown geometrical and mechanical properties) in environment. In this study, the contact force model of robot end-effector and the environment is analyzed. Specifically, the contact force is used as the feedback force of a position-based impedance controller to actively track the dynamic desired force in uncertain environment. To adapt any environment stiffness uncertainties, a modified impedance control is proposed. To reduce the force tracking error caused by environment location uncertainty, an adaptive variable impedance control is implemented for the first time by adjusting the impedance parameters on-line based on the tracking error to compensate the unknown environment and the dynamic desired force. Furthermore, stability and convergence of the adaptive variable impedance control are demonstrated for a stable force tracking execution. Simulations and experiments to compare the performance of force tracking with the constant impedance control and the adaptive variable impedance control, perspectively, are conducted. The results strongly prove that the proposed approach can achieve better force tracking performance than the constant impedance control.
In order to achieve excellent trajectory tracking performances, an improved genetic algorithm (IGA) is presented to search for the optimal proportional-integral-derivative (PID) controller parameters for the robotic excavator. Firstly, the mathematical model of kinematic and electro-hydraulic proportional control system of the excavator are analyzed based on the mechanism modeling method. On this basis, the actual model of the electro-hydraulic proportional system are established by the identification experiment. Furthermore, the population, the fitness function, the crossover probability and mutation probability of the SGA are improved: the initial PID parameters are calculated by the Ziegler-Nichols (Z-N) tuning method and the initial population is generated near it; the fitness function is transformed to maintain the diversity of the population; the probability of crossover and mutation are adjusted automatically to avoid premature convergence. Moreover, a simulation study is carried out to evaluate the time response performance of the proposed controller, i.e., IGA based PID against the SGA and Z-N based PID controllers with a step signal. It was shown from the simulation study that the proposed controller provides the least rise time and settling time of 1.23 s and 1.81 s, respectively against the other tested controllers. Finally, two types of trajectories are designed to validate the performances of the control algorithms, and experiments are performed on the excavator trajectory control experimental platform. It was demonstrated from the experimental work that the proposed IGA based PID controller improves the trajectory accuracy of the horizontal line and slope line trajectories by 23.98% and 23.64%, respectively in comparison to the SGA tuned PID controller. The results further indicate that the proposed IGA tuning based PID controller is effective for improving the tracking accuracy, which may be employed in the trajectory control of an actual excavator.
This paper presents a novel planning and control approach for autonomous excavation that is independent of the soil composition and goes beyond a single dig. In contrast to existing work, which is mostly based on position trajectories for the bucket motion, we define a single dig cycle directly by an end-effector force-torque trajectory. This trajectory applied to different types of soil, resulting in bucket motions that are used by expert operators to adapt to different terrain. Thereby, we can overcome the limitations of current approaches that suffer from the fact that soil interaction forces are dominant and immensely hard to predict or estimate. The end-effector forces and motion of the redundant excavator arm are controlled using a hierarchical optimization approach. Additionally, a large scale iterative planner is proposed to consecutively execute single digs until a desired ground geometry is achieved. The shown simulation results include multi dig excavations that precisely recreate the desired ground shapes. Practical tests are to follow.
Contouring control is a fundamental control of industrial robots for various jobs such as welding, painting and inspection. Adaptability to working objects and environmental conditions is strongly desired for the contouring control, in order to make robot operation easy and to extend application fields of robotics. In this paper, autonomous contouring control and obstacle avoidance are discussed as representative problems for the adaptive contouring control.
During the virtual development and experimental testing of advanced construction machinery, automation approaches for automated task execution can prove very valuable. In this paper, modeling and automation approaches for a hydraulic mini excavator are developed. In particular, a physical model for detailed system analysis and a simplified Hammerstein model for controller tuning are developed and validated with measurement data from the mini excavator. For attitude estimation of the excavator, inertial measurement units and extended Kalman filters are used in a sensor fusion framework. The control concept for automation is based on a virtual driver consisting of a state machine for task coordination as well as offset-free model predictive controllers (MPCs) for decentralized and robust tracking control of all motion axes. The constrained MPC optimization problems are solved in real time by means of the accelerated proximal gradient method. Experimental results from the mini excavator prove the developed control approach to be valuable for virtual development and automated testing during the commissioning of hydraulic machinery.
For the hot and difficult issues of trajectory automatic control based on single bucket hydraulic excavator, this paper introduce the control method of combining RBF neural network with traditional PID. By setting up the mathematical model of machine-electricity-hydraulic control system, using the MATLAB-Simulink simulation analysts to get the conclusion that based on RBF neural network PID control is superior to the conventional PID control. This control method can make the system have the adaptability, automatically adjust the control parameters, adapt to the changes in the charged process, improve the control performance and reliability and provide a theory basis to further realize the excavator trajectory intelligent control.
This paper addresses the position control of valve-controlled cylinder system employed in hydraulic excavator. Nonlinearities such as dead zone, saturation, discharge coefficient and friction existed in the system are highlighted during the mathematical modeling. On this basis, simulation model is established and then validated against experiments. Aim for achieving excellent position control performances, an improved particle swarm optimization (PSO) algorithm is presented to search for the optimal proportional-integral-derivative (PID) controller gains for the nonlinear hydraulic system. The proposed algorithm is a hybrid based on the standard PSO algorithm but with the addition of selection and crossover operators from genetic algorithm in order to enhance the searching efficiency. Furthermore, a nonlinear decreasing scheme for the inertia weight of the improved PSO algorithm is adopted to balance global exploration and local exploration abilities of particles. Then a co-simulation platform combining the simulation model with the improved PSO tuning based PID controller is developed. Comparisons of the improved PSO, standard PSO and Phase Margin (PM) tuning methods are carried out with three position references as step signal, ramp signal and sinusoidal wave using the co-simulation platform. The results demonstrated that the improved PSO algorithm can perform well in PID control for positioning of nonlinear hydraulic system.
For a robotic excavator, there is no operator in the cab while it is working, so the moving trajectory of the bucket teeth is planned in advance. For such a multi-joint machine, the coordinate motion control algorithm must be properly designed to achieve high tracking precision. However, due to uncertainty of the load and fluctuation of the speed, the multi-actuator system cannot work stably, resulting in tracking errors. To improve tracking performance, a cross-coupled pre-compensation algorithm is put forward in this paper. It is combined with nonlinear proportional-integral controllers to optimize the control parameters of the actuators. Experiments are performed on a 3.5-ton exactor. The results show that the proposed control algorithm is effective for improving the tracking accuracy.
This paper presents a three-dimensional path tracking strategy for a hydraulic excavator. It mainly aims to design the controller for allowing the excavator to follow typical working motions of a skillful operator such as leveling and truck loading. The performance of the designed controller is verified through real-time experiments using a 21-ton class excavator in which displacement sensors, electro-proportional pressure reducing valves, and communication devices are incorporated. Basically, proportional-derivative (PD) controller with dead zone compensation is used to control the cylinder displacements and swing angle. In order to enhance the performance, a linear quadratic outer-loop is introduced for boom, arm, and bucket joints, which compensates reference inputs of the nonlinear PD controller. Experiments of individual joints show that the designed outer-loop can provide faster rise time than the nonlinear PD controller itself. Furthermore, experimental results demonstrate the feasibility of the proposed algorithm for achieving autonomous compliant motions of both leveling and truck loading.
In this work the authors address the problem of robustness of the classic PI controller implemented in a Hydraulic Servo-Actuator (HSA), by presenting a strategy based on the definition of a linear model of the system and the identification of its parameters for different working points. The variation of these parameters is considered as a measure of parametric uncertainty of the linear model. These uncertainties along with the definition of a nominal plant are used to analyze the robustness of the system implementing the Small Gain Theorem. Theoretical and experimental results show that a PI controller can provide robustness to the HSA.
Download for free until sept 12th from:
http://authors.elsevier.com/a/1RQ0t3RugWGajp
The dead-band in the electro-hydraulic proportional control valve is one of the main factors that affect its dynamic performance. Especially in the pilot stages of two-stage directional flow control valves, the insistent dead-band will result in a conservative valve controller design. In this paper, a detailed dead-band model describing the relationship between pilot valve spool and the flow rate of the pilot control valve is proposed. And an improved dead-band description involved with the housing clearance of the valve spool is developed to prove the dead-band uncertainty for a single valve system. Then a simple and effective method is proposed to detect the varying dead-band values in the pilot stage. This method is specially designed with a limited main spool displacement and short time interval so that it can be used for online detection without affecting the hydraulic system where the two-stage valve is involved. With the regular dead-band inverse function, comparative experimental results show that this method is effective to attenuate the large trajectory tracking error caused by the varying dead-band. This dead-band detection also can be applied to other electro-hydraulic proportional valve-controlled position control systems with unknown dead-bands.
This paper presents electro-hydraulic servo systems of a robotic excavator with a contour control algorithm. It is very important to precisely move the bucket tip of the excavator to a desired trajectory. There have been many studies to accurately control the bucket dealing with the non-linearity in the hydraulic boom, arm, and bucket cylinders. Beginning with these conventional methods, a new method that focuses on keeping contours rather than just following position commands is presented. In the leveling work, for example, it is more important to maintain linear contour than chasing a position goal. The contour control shares the control effort to make the bucket stay on the path, while slightly sacrificing the position tracking accuracy. After the kinematics of the excavator system were analyzed, the contour control algorithm was developed. The algorithm was applied to leveling work with a real excavator. The experiments showed better performance than using position control alone.
Designing a quick, very accurate and robust position controller for industrial hydraulic manipulators is a challenging problem. The controller must contend with many nonidealities that exist in such systems—nonlinear dynamics, hydraulic flow deadband, and stiction are all present. This paper documents step-by-step development and implementation of a novel nonlinear proportional-integral (NPI) controller in an attempt to deal with these issues. A number of modifications are performed on the integral portion of a conventional proportional-integral (PI) controller, each displaying improved performance over the last. The final NPI controller is shown to improve position tracking accuracy by a factor of five, relative to a conventional PI controller, without sacrificing regulation accuracy or robustness. The experiments are performed on the up-down revolute axis of an instrumented Unimate MK-II hydraulic manipulator.
Aiming at the hot topic of automatic control of hydraulic excavator, the electro-hydraulic control system of excavator mechanism is developed. According to the nonlinearity and uncertainty of the excavator mechanism control system, a fuzzy plus PI controller which combines the advantages of fuzzy logic and conventional PI control is developed, a fuzzy rule based soft-switch method is adopted to achieve smooth switching. This combined controller which we call it Fuzzy-PI soft-switch controller is demonstrated to have better response property than conventional PID and fuzzy controller respectively.
The working environment of the construction industry becomes harder and the operator qualities go lower. Moreover NFC (negative flow control) is one of the pump control types of the hydro-mechanical excavator, of which discharged flow rate of the pump is controlled by the pressure developed at the orifice of center-bypass line in a main control valve. In general, the NFC type excavator has some limitations in getting the high fuel efficiency and a good controllability. In order to solve these problems, we need an intelligent excavating system. One way to design an intelligent excavating system is converting the traditional-hydraulic system to an electro-hydraulic system. We are still in process, but we have developed the algorithms for the position control already, and also the remote control system is ready to test using the intelligent robotic excavator.
In this paper, a simple force tracking algorithm for robot manipulators is presented. In the framework of impedance control formulation, the controller can deal with uncertainties from unknown environment and unknown robot dynamics. Uncertainties in the robot dynamics are compensated by the time-delayed joint space control method. The damping characteristic of the environment which is usually ignored in the impedance force formulation is considered. The stability of the impedance function is analyzed and assured under uncertain environment. Extensive simulation studies are presented for testing the performance of the impedance function.
To use construction machines effectively in the dark, severe weather, or
hazardous and/or unhealthy environments, their operations should be
controlled automatically. It can be realized if the kinematics and
dynamics of the machine are understood. To help achieve this goal, the
kinematics of specific construction machines -- excavators (backhoes and
loaders) -- are investigated here. A systematic procedure is presented
to assign Cartesian coordinate frames for the links (joints) of an
excavator. Then, the homogeneous transformation matrices that relate two
adjacent coordinate frames are given. The kinematic relations of the
pose (position and orientation) of the bucket, the joint shaft angles,
and the lengths of the cylinder rods in the hydraulic actuators for an
excavator are studied. Explicit expressions for the forward and backward
(inverse) kinematic relations are presented. Then, the corresponding
kinematic velocity relations for the excavators are developed. The
kinematic relations presented provide the foundation for engineers to
realize the automatic computer-controlled operations of the machine.
Automation of excavation work calls for a robotic system able to perform the planned digging work that is responsive to interaction forces experienced during excavation. The development of automated excavation control methods requires a dynamic model to describe the evolution of the excavator motion with time. The joint torques of the boom mechanism are generated by hydraulic rams that also affect the torques at other joints. Analyzing each link in succession as a free body and applying the Newton-Euler formulation in the local coordinate frame, a dynamic model for an excavator can be derived in a straightforward manner. The model presented in this paper is intended for further development of an automated excavation control system for terrestrial, lunar, and planetary excavation.
It is shown that robot manipulator control can be accomplished
using simple decentralized linear time invariant time-delayed joint
controllers instead of the complicated computed torque control scheme.
This means that all the online computational problems associated with
computing robot inverse dynamics can be avoided, and the robot control
problem is essentially reduced to that of computing n linear
proportional-derivation controls for n joint subsystems. The
proposed control technique employs a time-delayed control with a
specially designed constant diagonal gain matrix to decouple and
linearize the robot joint dynamics so that linear centralized joint
control can be achieved. It is shown that the proposed controller is
stable, and the value of the special gain matrix can be selected based
on a sufficient condition of stability presently developed. However, the
establishment of this sufficient condition requires knowledge of the
inertial matrix of the robot. It is also shown that the controller is
robust in the presence of payload uncertainty. A two-link planar robot
is presented to illustrate the controller design procedures and the
performance of the controller
In robotic excavation, hybrid position/force control has been proposed for bucket digging trajectory following. In hybrid position/force control, the control mode is required to switch between position- and force-control depending on whether the bucket is in free space or in contact with the soil during the process. Alternatively, impedance control can be applied such that one control mode is employed in both free and constrained motion. This paper presents a robust sliding controller that implements impedance control for a backhoe excavator. The control law consists of three components: an equivalent control, a switching control and a tuning control. Given an excavation task in world space, inverse kinematic and dynamic models are used to convert the task into a desired digging trajectory in joint space. The proposed controller is applied to provide good tracking performance with attenuated vibration at bucket–soil contact points. From the control signals and the joint angles of the excavator, the piston position and ram force of each hydraulic cylinder for the axis control of the boom, arm, and bucket can be determined. The problem is then how to find the control voltage applied to each servovalve to achieve force and position tracking of each electrohydraulic system for the axis motion of the boom, arm, and bucket. With an observer-based compensation for disturbance force including hydraulic friction, tracking of the piston ram force and position is guaranteed using robust sliding control. High performance and strong robustness can be obtained as demonstrated by simulation and experiments performed on a hydraulically actuated robotic excavator. The results obtained suggest that the proposed control technique can provide robust performance when employed in autonomous excavation with soil contact considerations.
The control of a robotic excavator is difficult from the standpoint of the following problems: parameter variations in mechanical structures, various nonlinearities in hydraulic actuators and disturbance due to the contact with the ground. In addition, the more the size of robotic excavators increase, the more the length and mass of excavator's links; the more the parameters of a heavy-duty excavator vary. A time-delay control with switching action (TDCSA) using an integral sliding surface is proposed in this paper for the control of a 21-ton robotic excavator. Through analysis and experiments, we show that using an integral sliding surface for the switching action of TDCSA is better than using a PD-type sliding surface. The proposed controller is applied to straight-line motions of a 21-ton robotic excavator with a speed level at which skillful operators work. Experiments, which were designed for surfaces with various inclinations and over broad ranges of joint motions, show that the proposed controller exhibits good performance.
This paper is concerned with adaptive position control using artificial neural networks (ANNs). The hydraulic system to be investigated consists of a 4/3 way proportional valve, a differential cylinder and a variable load force. This force results from a mass-spring-damper system. The main problem in this configuration is the large dead zone in the valve. Assuming that the cylinder and the load force can be linearly modelled as a second-order system and an integrator, the dynamic model of the hydraulic system can be described as a series connection of a static input non-linearity (dead zone) and a linear system. For the control of such a Hammerstein system, it is proposed to use an inverse of the input non-linearity for compensation and a linear adaptive controller for the resulting system. In our new scheme, we use an ANN instead of a fixed inverse non-linearity. A key feature of this approach is that the ANN can describe several types of non-linear functions without structural changes. To control the linear part of the system, an adaptive LQ controller is used.
The excavation of foundations, general earthworks and earth removal tasks are activities which involve the machine operator in a series of repetitive operations, suggesting opportunities for the automation through the introduction of robotic technologies with subsequent improvements in machine utilisation and throughput. The automation of the earth removal process is also likely to provide a number of other benefits such as a reduced dependence on operator skills and a lower operator work load, both of which might be expected to contribute to improvements in quality and, in particular, the removal of the need for a local operator when working in hazardous environments.
The Lancaster University Computerised Intelligent Excavator or LUCIE has demonstrated the achievement of automated and robotic excavation through the implementation of an integrated, real-time, artificial intelligence based control system utilising a novel form of motion control strategy for movement of the excavator bucket through ground. Having its origins in the systematic observation of a range of machine operators of differing levels of expertise, the control strategy as evolved enables the autonomous excavation of a high quality rectangular trench in a wide variety of types and conditions of ground and the autonomous removal of obstacles such as boulders along the line of that trench.
The paper considers the development of the LUCIE programme since its inception and sets out in terms of the machine kinematics the evolution and development of the real-time control strategy from an implementation on a one-fifth scale model of a back-hoe arm to a full working system on a JCB801 360° tracked excavator.
Analysis of inertial effect on control performance of a time-delayed controller for a robot manipulator
- S Jung