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Modeling and controller design of manta-type unmanned underwater test vehicle
Abstract
This paper describes the mathematical model and controller design for Manta-type unmanned underwater test vehicle (MUUTV)
with 6 DOF nonlinear dynamic equations. The mathematical model contains hydrodynamic forces and moments expressed in terms
of a set of hydrodynamic coefficients which were obtained through the PMM (planar motion mechanism) test. Based on the 6 DOF
dynamic equations, numerical simulations have been performed to analyze the dynamic performance of the MUUTV. In addition,
using the mathematical model PID and sliding mode controller are constructed for the diving and steering maneuver. Simulation
results show that the control performance of the MUUTV compared with that of NPS (Naval Postgraduate School) AUV II.
... Some researchers were interested at developing simulators to evaluate ROV controlling algorithms. In the work of (Lee et al., 2009), Lee et al. constructed a simulation program to study ROV control methods. In the experiments given in (Miskovic et al., 2006), a specialized micro-ROV is used for comparing auto-piloting methods. ...
... The auto-piloting and auto-balancing experiments are inspired by the work of (Miskovic et al., 2006), (Lee et al., 2009), (Tehrani et al., 2010), (Hsu et al., 2000), and (De Souza and Maruyama, 2007). In these researches, their simulators support only fundamental graphic display functions. ...
Remotely Operated Vehicles (ROVs) are widely used in underwater explorations and constructions. When navigating under the sea, the motions and stabilities of ROVs are influenced by various forces. Operating ROVs to capture images, grasp samples, avoid obstacles, and examine man-made facilities is challenging. This paper proposes an innovative simulator to train users to handle ROVs. Conventional simulators only can mimic undeformable ROVs. Their educational capabilities are limited. The proposed simulator is developed based on advance mathematics models and is able to emulate a ROV equipped with movable robot arms. Therefore, it can perform more realistic and meaningful simulations to enhance the training courses. We deduce a voxel-based method to calculate the mass properties of the ROV. Thus, the hydrodynamic effects caused by its robot arms can be calculated in real time. A numerical algorithm is also invented to coordinate the propellers to produce required forces and moments. Hence, the ROV can attain specified velocities, positions, and orientations under the influences of loads, sea currents, and moving robot arms. Furthermore, an artificial intelligence engine is integrated into the system to perform auto-piloting, auto-balancing, and command interpretation such that the simulator is more user friendly. Besides, the system is augmented with an interactive user interface and a graphics engine to display simulation progressions and information to increase its usability.
... Also, position autopilots are designed by similar controllers (Zanoli and Conte (2003)). More complicated autopilots are designed with PID techniques and sliding mode control techniques as in Lee, Sohn, Byun and Kim (2009). Optimal kinematic control for an autonomous underwater vehicle and a particular set of optimal motions which trace helical paths is discussed in Biggs and Holderbaum (2009). ...
... (2003)). More complicated autopilots are designed with PID techniques and sliding mode control techniques as in Lee, Sohn, Byun and Kim (2009). Optimal kinematic control for an autonomous underwater vehicle and a particular set of optimal motions which trace helical paths is discussed in Biggs and Holderbaum (2009). ...
In this study, an optimal autopilot algorithm is developed for 3D motion of SAGA which is an unmanned underwater survey vehicle. Firstly, a nonlinear mathematical model for SAGA is obtained. The structure of the mathematical model of the vehicle comes from a Newton-Euler formulation. The resultant nonlinear system is then controlled by PID controllers. These PID controllers are designed for 3D motion which is realized by a suitable combination of right, left and vertical thrusters. The optimal control problem is that the vehicle is supposed to reach the desired position and rotation with desired velocity by consuming minimum energy. This problem is solved with a genetic algorithm. All of this study is performed in a Matlab/Simulink environment.
... The mathematical model of the underwater vehicle is comprised of a vehicle body, thrusters and control surfaces. To simulate the 3-D motion, the mathematical model is presented with 6DOF equations of motion [3]. The hydrodynamic coefficients are obtained from PMM (Planar Motion Mechanism) test and estimation [1,4]. ...
... Abkowitz and Feldman presented equations of motion which are more close to a real situation [5,6]. The motion of underwater vehicles is analyzed by considering two coordinate systems which are a body-fixed frame and earth-fixed frame as shown in Fig. 4. The proposed 6DOF mathematical model of the MUUV is referred in [3] and the simulation program is developed using MATLAB/ SIMULINK as shown in Fig. 5. We analyzed the dynamic performances using the developed simulation program. ...
This paper describes the mathematical modeling, control algorithm, system design, hardware implementation and experimental test of a Manta-type Unmanned Underwater Vehicle (MUUV). The vehicle has one thruster for longitudinal propulsion, one rudder for heading angle control and two elevators for depth control. It is equipped with a pressure sensor for measuring water depth and Doppler Velocity Log for measuring position and angle. The vehicle is controlled by an on-board PC, which runs with the Windows XP operating system. The dynamic model of 6DOF is derived including the hydrodynamic forces and moments acting on the vehicle, while the hydrodynamic coefficients related to the forces and moments are obtained from experiments or estimated numerically. We also utilized the values obtained from PMM (Planar Motion Mechanism) tests found in the previous publications for numerical simulations. Various controllers such as PID, Sliding mode, Fuzzy and are designed for depth and heading angle control in order to compare the performance of each controller based on simulation. In addition, experimental tests are carried out in a towing tank for depth keeping and heading angle tracking.
... The appearance design of the micro AUV is relatively simple, there is no need to consider too many hydrodynamic coefficients. Hence, ignoring the nonlinear terms with less impact, we can describe the dynamic equation of micro AUV as the form in the study of Lee et al. 28 The nonlinear dynamic motion equation of an underactuated AUV can be conveniently expressed as ...
Accurate formation maintenance and safe formation transformations are significant challenges for multiple autonomous underwater vehicle (multi-AUV) dense formations. To address these problems, an innovative control method for a multi-AUV dense formation is proposed. First, a model predictive controller (MPC) that considers AUV input constraints and external disturbances is designed such that a multi-AUV dense formation can accurately maintain a desired formation while tracking a reference trajectory. After that, at the kinematics level, an optimal path for a safe and efficient multi-AUV dense formation transformation is generated based on the Hungarian method. Furthermore, considering an underactuated and nonlinear AUV dynamics model at the dynamics level, a potential function based on collision avoidance is established. It is added to the MPC objective function to further guarantee the potential of the formation transformation. Finally, a multi-AUV dense formation maintenance simulation shows that the proposed method can guarantee higher trajectory tracking accuracy than other algorithms. A multi-AUV dense formation transformation simulation shows that the proposed method avoids the occurrence of cross paths and a safe distance between AUVs is always maintained. The above results demonstrate that multi-AUV dense formations can achieve accurate maintenance and safe transformations, and the proposed method is feasible and effective.
... It is also used to maintain the vehicle's state trajectory on its surface for all subsequent times. This method guarantees that the output tracking error converges to zero in a finite time (Bessa,Dutra & Kreuzer, 2008, Seung, et al, 2009. In this paper, the control law is based upon the linear model. ...
This paper focuses on hydrodynamic modeling and control of spheroidal underwater vehicle. The vehicle considered in this paper is appendage free and unstable. Water jet propulsion system is used in this vehicle. The dynamics of the vehicle is highly unstable due to munk moment. The spheroidal shape underwater robot is used in nuclear reactor inspection, port security inspection, defence and ocean surveillance where external appendages are not required. A new and innovative control technique, Sliding mode based model predictive control is introduced in this paper. Sliding mode control technique is used to stabilize the vehicle and once the vehicle model is stabilized it is easy to apply Model Predictive Control (MPC). Model Predictive control technique is used to control the heading of spheroidal underwater vehicle. Simulation results show that the Sliding mode based predictive control performance is better than simple PD control and state feedback controller.
... Position autopilots are also designed by the same controllers Zanoli and Conte (2003). More complicated autopilots are designed with PID and sliding mode control techniques Lee et al. (2009). The parking problem of unmanned underwater vehicle is addressed using the velocity field control (VFC) and path tracking of autonomous underwater vehicle is performed with VFC algorithm Thanasit Suasan (2015). ...
In this study, a velocity field control algorithm and an optimal autopilot algorithm are developed for horizontal parking system motion of Fologa which is an autonomous unmanned underwater survey vehicle and manufactured by Graaltech Ltd., Genoa, Italy. Firstly, a nonlinear mathematical model for Fologa is obtained. The structure of the mathematical model of the vehicle comes from a Newton-Euler formulation. The resultant nonlinear system is then controlled by PID controllers. These PID controllers are designed for horizontal parking motion which is realized by a suitable combination of rear and front lateral thrusters. The velocity field control and optimal control problem is that the vehicle is supposed to reach the desired position and rotation by consuming minimum energy. Velocity field control is solved with developed velocity field vector notation. Optimal control problem is solved with a genetic algorithm. The performance and consuming energy of velocity field control and optimal control are compared. All of this study is performed in a Matlab/Simulink environment.
... [5] addresses depth and steering control of AUV using SMC in open control platform, the authors use a linearized model for the corresponding state control, stability of other states is not mentioned. [6] Technology,Islamabad,Pakistan m.farhanhanif58@gmail.com is also provided in [7] for a 6 Degree of Freedom (DOF) model linearized under several conditions. Velocity tracking for a nonlinear model of AUV using SMC is presented by [8]. ...
... The final controller was functioning well while the submarine operated at periscope depth under a heavy sea, over a wide speed range [13]. S.K. Lee et al. presented a 6-DOF Manta type unmanned underwater test vehicle with its diving and steering controls being governed by mathematical model PID and Sliding mode control [14]. Another efficient multivariable system was designed by E. Liceaga-Castro et al. ...
Ocean has attracted the attention of the researchers owing to its importance on environmental issues, resources, scientific works and military tasks requiring critical control operations of the submarine to achieve the desired objectives. This paper represents the performance comparison of various controllers for the depth control of the submarine employing the stern plane actuation technique which actuates the stern plane motor to achieve the desired depth. The controllers such as PI Controller, Fuzzy logic based Controller (FLC) and Type 2 Fuzzy Logic based Controllers (T2FLC) have been applied for the depth control operation of the submarine and the simulation has been carried out based on quantitative performance analysis of the controllers using various performance criteria in MATLAB Simulink © environment. The results obtained in terms of Stern plane angle, Rate of change of Depth and Actual depth, indicate that the T2FLC provides better performance than other controllers used.
... Beberapa tahun terakhir telah banyak penelitianpenelitian di berbagai penjuru dunia tentang sistem pengontrolan dari UUV, telah banyak peningkatan bila dilihat dari awal munculnya UUV. Mulai dari yang pengontrolan klasik menggunakan PID [3], lalu berkembang lagi menggunakan SMC (Sliding Mode Control) [4,5] , fuzzy, adaptive, dan yang terbaru menggunakan kontrol robust seperti H infinity atau LPV [6]. Dalam penulisan penelitian ini, penulis mecoba untuk menuliskan model matematika dari ROV itu sendiri [1,2] , Dikarenakan model yang didapat masih non linier, diperlukan linierisasi untuk membuatnya mudah dikontrol. ...
... To simulate the 3-D motion, the mathematical model is presented with 6DOF equations of motion. 2 The hydrodynamic coefficients are obtained from the PMM (Planar Motion Mechanism) test and estimation. 3 The proposed 6DOF mathematical model of the MUUV is referenced in Ref. 2 and the simulation program is developed using MATLAB/SIMULINK. ...
This paper describes the dynamic modeling, structural analysis, implementation and experimental test of a Manta-type Unmanned Underwater Vehicle (MUUV). Various controllers such as PID, Sliding mode, and Fuzzy and H∞ controllers are designed for depth and heading control in order to compare the performance of each controller based on simulation. In addition, experimental tests are carried out in a towing tank for depth keeping and heading angle tracking.
Underwater vehicles are known as complex systems with extremely nonlinear nature, and it makes them hard to control and steer. Due to uncertainty in model, strong disturbances cause by water streams, etc. Control of such devices is a hard task to accomplish in providing a precise mathematical model of a dynamic system that is the most important step in analysis and design of an autopilot. In present study, a ROV which its motion can be described in 3D space with six degrees of freedom has been considered. In spite of a great level of complexity caused by hydrodynamic forces and moments which have a highly nonlinear nature, a precise mathematical model of DST-R-100-4 with all effects of hydrodynamics terms, added mass, buoyancy forces and so on has developed. The model equations and parameters are extracted from related references. Considering the variation of system’s parameters and lack of knowledge about the variation ranges of them, an adaptive pole placement strategy is employed in order to control and achieve an acceptable performance. For this reason, online identification based on RLS method is realized and model parameters can be updated in each sampling time. To investigate the performance of the controller, simulations are performed in presence of variant parameters of the dynamic model and external disturbances. Results show a suitable performance for the designed controller.
In general, the diving dynamics of an autonomous underwater vehicle (AUV) has been derived under various assumptions on the motion of the vehicle in vertical plane. Usually, pitch angle of AUV is assumed to be small in maneuvering, so that the nonlinear dynamics in the depth motion of the vehicle could be linearized. However, a small-pitch-angle is a somewhat strong restricting condition and may cause serious modeling inaccuracies of AUV’s dynamics. For this reason, many researchers concentrated their interests on the applications of adaptive control methodology to the motion control of underwater vehicle. In this chapter, we directly resolve the nonlinear equation of the AUV’s diving motion without any restricting assumption on the pitch angle in diving model. The proposed adaptive neuro-fuzzy sliding mode controller (ANFSMC) with a proportional + integral + derivative (PID) sliding surface is derived so that the actual depth position tracks the desired trajectory despite uncertainty, nonlinear dynamics and external disturbances. In the proposed control structure, the corrective term is approximated by a continuous fuzzy logic control and the equivalent control is determined by a feedforward neural network. The weights of the neural network are updated such that the corrective control term of the ANFSMC goes to zero. The adaptive laws are employed to adjust the output scaling factor and to compute PID sliding surface coefficients. Finally, the lyapunov theory is employed to prove the stability of the ANFSMC for trajectory tracking of diving behaviors. Simulation results show that this control strategy can attain excellent control performance.
At first, Kalman filter was adopted for data preprocessing of underwater vehicle's simulation test. Then, least square support vector machines was applied to identifying the coefficients in the equations of planar maneuvering motion of underwater vehicles. The identification results were compared with those by using traditional least square method. It proves that the least square support vector machines is more effective.
In this paper we address the design and implementation of a fuzzy sliding mode control (FSMC) scheme for depth control of autonomous underwater vehicles (AUV's). The proposed scheme is compared with classical sliding mode control (SMC). At first we examine the response of sliding mode control based on ackermann formula for diving model. SMC is adequate for controlling depth of AUV's, since it offers robustness in the presence of uncertainties parameters and environmental disturbances. However the main drawback is the chattering effect that stimulates high frequency vibration that can damage the actuators. An SMC can give good transient response, however the steady state performance is poor due to the presence of discontinuous control which causes chattering hence we focus on designing of FSMC for controlling depth maneuver. Next we describe the design scheme of FSMC in which mamdani type fuzzy inference system is employed. The proposed control method enhances the ability of fuzzy logic control (FLC) so that the minimal number of fuzzy inference rule is systematically obtained even the plant parameters are unknown. Comparative study between the both control laws is presented through numerical simulation. An illustrative example shows that good transient and steady state response can be obtained by applying proposed control strategy.
Ahstract- This paper describes the mathematical modeling, control algorithm, system design, hardware implementation and experimental test of a Manta-type Unmanned Underwater Vehicle (MUUV). The vehicle has one thruster for longitudinal propulsion, one rudder for heading angle control and two elevators for depth control. It is equipped with a pressure sensor for measuring water depth and Doppler Velocity Log for measuring position and angle. The vehicle is controlled by an on-board PC, which runs with the Windows XP operating system. The dynamic model of 6DOF is derived including hydrodynamic forces and moments acting on the vehicle, while the hydrodynamic coefficients related to the forces and moments are obtained from experiments or estimated numerically. We also utilized the values obtained from PMM (Planar Motion Mechanism) tests found in the previous publications for numerical simulations. Various controllers such as PID, Sliding mode, Fuzzy and Hen controllers are designed for depth and heading angle control in order to compare the performance of each controller based on simulation. In addition, experimental tests are carried out in towing tank for depth keeping and heading angle tracking.
Autonomous Underwater Vehicle (AUV) system is one difficult controlled system because of its imprecise nonlinear math description and its complex disturbances. The motions of AUV are coupled with each other so the design of control law is stiff. In this paper, AUV model is departed into several subsystem models meanwhile some control laws are conceived for every subsystem. Furthermore, one controller database gathered with these control laws is designed to conveniently select some optimized control algorithms for different AUV motional requirement. These optimized algorithms are achieved based on minimizing the cost function of every subsystem and the robust capability to disturbances. Simulations results validate the controller database works well and show beautiful control results compared with other control algorithm with consistent control parameters.
This paper describes depth, heading and speed control of an underwater vehicle that has four stern thrusters of which forces are coupled in the diving and, steering motion, as well as the speed of the vehicle. The optimal linear quadratic controller is designed based on a linearized- state space model, developed by combining the dynamic equations of speed, steering and diving motion. The designed controller gives provides an optimal thrust distribution, minimizing the given performance index to control speed, depth and heading simultaneously. To validate the performance of the controller, a simulation and tank-test are carried out with DUSAUV (Dual Use Semi-Autonomous Underwater Vehicle), developed by KORDI as a test-bed for testing new underwater technologies. Optimal gains of the controller are tuned, using a computer simulation environment with a nonlinear 6-DOF numerical DUSAUV model, developed by PMM (Planner Motion Mechanism) test. To verify the performance of the presented controller in experiment, a tank-test with DUSAUV is carried out in the ocean engineering basin in KORDI. The experimental results are also compared with the simulation results to investigate the accordance of the numerical and the real mode
Mathematical model for coupled motions of Manta-type Unmanned Undersea Vehicle(UUV) moving with six degrees of freedom, is formulated. Furthermore, a calculation method for estimating the linear hydrodynamic derivatives acting on UUV, is proposed, and some of the estimated linear hydrodynamic derivatives are compared with results of captive model experiment. Based on linear dynamic model of UUV, a study was made to examine dynamic stability and turning ability in horizontal plane. And directional stability and required elevation rudder angles for neutrally operating in vertical plane, are also discussed. ??? ???????牡????敲楮最
Standard equations of motion are presented for use in submarine simulation studies being conducted for the U. S. Navy. The equations are general enough to simulate the trajectories and responses of submarines in six degrees of freedom resulting from various types of normal maneuvers as well as for extreme maneuvers such as those associated with emergency recoveries from sternplane jam and flooding casualties. Information is also presented pertaining to the hydrodynamic coefficients and other input data needed to perform simulation studies of specific submarine designs with the standard equations of motion.
Depth and heading control of an AUV are considered for the
predetermined depth and heading angle. The proposed control algorithm is
based on a sliding mode control using estimated hydrodynamic
coefficients. The hydrodynamic coefficients are estimated with the help
of conventional nonlinear observer techniques such as sliding mode
observer and extended Kalman filter. By using the estimated
coefficients, a sliding mode controller is constructed for the combined
diving and steering maneuver. The simulation results of the proposed
control system are compared with those of control system with true
coefficients. It is demonstrated that the proposed control system makes
the system stable and maintains the desired depth and heading angle with
sufficient accuracy
The Manta Test Vehicle (MTV) has been built by the US Navy as the
prototype of a new class of unmanned underwater vehicles (UWs). The
paper presents the complete nonlinear dynamics model of the MTV and
discusses the design of its control system. As MTV's first in-water
trial is still to come, performance is shown through simulated
runs
A six-degree-of-freedom model for the maneuvering of an underwater
vehicle is used and a sliding-mode autopilot is designed for the
combined steering, diving, and speed control functions. In flight
control applications of this kind, difficulties arise because the system
to be controlled is highly nonlinear and coupled, and there is a good
deal of parameter uncertainty and variation with operational conditions.
The development of variable-structure control in the form of sliding
modes has been shown to provide robustness that is expected to be quite
remarkable for AUV autopilot design. It is shown that a multivariable
sliding-mode autopilot based on state feedback, designed assuming
decoupled modeling, is quite satisfactory for the combined speed,
steering, and diving response of a slow AUV. The influence of speed,
modeling nonlinearity, uncertainty, and disturbances, can be effectively
compensated, even for complex maneuvering. Waypoint acquisition based on
line-of-sight guidance is used to achieve path tracking
Controller Design for an Autonomous Underwater Vehicle Using Estimated Hydrody-namic Coefficients
- J Y Kim
J. Y. Kim, Controller Design for an Autonomous Underwater Vehicle Using Estimated Hydrody-namic Coefficients, J. of Ocean Engineering and Technology, 20 (6) (2006) 7-17.