For proper manual aircraft control, the pilot has to perceive the motion state of the aircraft. In this perception process both the visual and the vestibular systems play an important role. To understand this perception process and its impact on a pilot's control behavior a descriptive model was developed. The single-channel information-processor model was applied as the basic structure of the final model. Three groups of experiments were performed to refine the model structure and to define the majority of the model parameters. The model has been evaluated by measuring the control behavior in tracking tasks.
A pilot's perception of variables presented on the Electronic Flight Instrument System, EFIS, was investigated. A stimulus response technique was used to determine the accuracy and speed of the perception process. By varying the exposure time of the stimuli, it is shown that the perception of a variable's magnitude is faster and more accurate than the perception of the first derivative or rate of that variable. Results of experiments on roll and pitch attitude perception, the influence of scale division, and the perception of the indicated airspeed, are shown.
The availability of pressure information of a hydraulic actuator
makes it possible to improve the quality of vehicle power transmission
via precise feedback control and to realize on-board fault diagnosis.
However, the high cost of a pressure sensor has not allowed its
widespread deployment despite such apparent advantages. This paper
presents an observer-based algorithm to estimate the pressure output of
a hydraulic actuator in a vehicle power transmission control system. The
proposed algorithm builds on more readily available slip velocity and
the models of a hydraulic actuator and a mechanical subsystem. The
former is obtained empirically via system identification, while the
latter is derived physically. The resulting robust observer is
guaranteed to be stable against possible parametric variations and
torque estimation errors. The hardware-in-the-loop studies demonstrate
the viability of the proposed algorithm in the field of advanced vehicle
power transmission control and fault diagnosis
Magnetic levitation systems have recently become the focus of many
research interests not only because they are most suitable for high
precision engineering applications but also due to the fact that they
represent a difficult challenge to control engineers. As a result, most
previous studies have focused on the control stabilization problem. In
this paper, we address the issue of performance with respect to
uncertainty in order to achieve a desired rigidity. The proposed
controller is an adaptive backstepping controller. The adaptive
backstepping controller provides system stability under model
uncertainty, and achieves the desired servo performance. The experiments
show that the proposed control achieves a superior behavior than other
Time-optimal control strategies of the on-off type can be used to bring batch reactor temperature to the set point in the minimum time. A practical controller implementing this control strategy in industry is the dual-mode controller. When well tuned, this controller shows excellent system performance for various batch reactors. However, because time-optimal control is a kind of open loop control strategy, the dual-mode controller may be sensitive to process variations. For robust control, the dual-mode controller is modified here with an iterative learning technique. This iterative learning dual-mode controller requires minimal information from the previous batch runs and can be incorporated in the existing dual-mode controller with minimal effort.
We propose two advanced control algorithms, the LMS adaptive filter and fuzzy CMAC neural network, to counteract the chatter problem for a lathe machine. Experimental results are also included. Approximately 20 dB reduction in chatter has been achieved. We have also developed a multi-DSP board which can be used to implement any type of intelligent controllers to machine systems. Other potential applications of the proposed methods are to milling and boring machines
A data-driven model-free control design method has been proposed
in Hjalmarsson et al. (1994). It is based on the minimization of a
control criterion with respect to the controller parameters using an
iterative gradient technique. In this paper, we extend this method to
the case where both the plant and the controller can be nonlinear. It is
shown that an estimate of the gradient can be constructed using only
signal based information. It is also shown that by using open loop
identification techniques, one can obtain a good approximation of the
gradient of the control criterion while performing fewer experiments on
the actual system
Recently the Time Delay Control (TDC) method has been proposed as a promising technique in the robust control area, where the plants have nonlinear dynamics with parameter variations and substantial disturbances are present. TDC method, however, requires the measurements of all the state variables, together with their derivatives. This requirement imposes a severe limitation on the applications to most real systems. In order to solve this measurement problem, we proposed an observer design method that can stably reconstruct the state variables and their derivatives. Then, for a simulation study, the controller/observer based on our design method has been applied to a nonlinear plant, the result of which confirmed that the controller/observer performs satisfactorily as predicted. Finally we made experimentations on a DC servo motor that is subject to substantial amount of inertia variations and external disturbances. The results showed that the controller/observer performs quite robustly under those variations and disturbances, and is much less sensitive to sensor noise than the controller using numerical differentiations.
This paper describes how to control strip gauge, looper angle, and
strip tension for a hot strip finishing mill and the application result.
This is based on the optimal servo theory and the model decoupling
method. In the finishing mill process, there exists mutual interaction
among strip gauge, looper angle, and strip tension. Conventionally, each
of them is controlled independently. To improve the control performance,
multivariable control considering this interaction is applied to all
Hybrid vehicles use two energy sources for their propelling. Usually an internal combustion engine (ICE) is used with one or more electric machine(s) (EM). The problem is then to split the driver power demand between the ICE and the EM in order to minimize a criterion, usually the fuel consumption. A global optimization algorithm based on optimal control theory is recalled. The obtained results are optimal but can only be obtained in simulation. For real time control purpose, this optimization algorithm is applied on a receding horizon. The main problem is then to choose the variables to be predicted on this horizon. By analyzing the optimization algorithm, it is shown that the prediction of the future driving conditions (vehicle speed and driver torque demand) is not necessary. Therefore, under some assumptions, a real time control is possible.
Pressure screens are primarily used for contaminant removal. More recently, they have been used for fibre fractionation to produce pulp that is more uniform and of higher quality. Careful control is required for the safe operation of pressure screens, and for providing the required flows and level of cleanliness without failure. This is particularly important in fibre fractionation where optimal separation occurs when screens are operated as close as possible to the failure limit. Current control strategies are based on linear univariate control techniques. However, because the process is nonlinear and strongly coupled, univariate linear controllers are likely to perform very poorly when tight control is required. This kind of control requires an accurate model of the system. We describe a nonlinear dynamic model of pressure screens. Different methods were used to estimate the unknown parameters of the model, which was then validated against real data. Furthermore, we propose a simple nonlinear multivariate control strategy based on a static nonlinear model. For performance evaluation, we compare a conventional control strategy to the proposed strategy in simulation, and in pilot plant experiments
It is widely and frequently observed that industrial robots
conducting fast motion involve serious residual vibration, the period of
which varies with time. To this problem, this paper presents a practical
solution by providing a practical design and application of time-varying
input shaping technique (TVIST) for an industrial robot. To suppress the
time-varying vibration, at first, a guideline for designing practical
TVIST is presented. Following the guideline, then, we design TVIST for a
large size 6 degrees of freedom industrial robot. In doing so, a simple
yet effective equation is derived from robot dynamic equations to
estimate the time-varying period. Furthermore, a simple payload
adaptation scheme is also included. The TVIST thus designed is
experimented on the industrial robot under spatial motion and payload
variation conditions. The experimental results show that the residual
vibration is reduced to less than 10% of original one in magnitude,
demonstrating that the efficiency of the TVIST does not compromise its
The application of gain-scheduled control to a pilot-scale solar power plant is described. A field of parabolic collectors focus the solar radiation onto a tube where oil is pumped through in order to collect the solar power. The control problem is to keep the temperature of the oil leaving the field at its desired value by manipulating the oil pump flow rate. It is shown that gain-scheduling can effectively handle the plant nonlinearities, using high-order local linear ARX models that form the basis for the design of local linear controllers using pole placement.
An optimal-tuning nonlinear PID controller design strategy is proposed for hydraulic systems. After an analysis of these systems, an analytic physical dynamical model with dead-zone nonlinearity is derived. A nonlinear PID control scheme with the inverse of the dead zone is introduced to overcome the dead zone in the hydraulic systems. An optimal PID controller is designed to satisfy some desired time-domain performance requirements. Using an estimated process model, the optimal-tuning PID control provides optimal PID parameters even when the process dynamics are time variant. This strategy is implemented in an environment composed of dSPACE, MATLAB, SIMULINK and Real-Time Workshop. The performance of the controller is demonstrated on a hydraulic position control test rig.
The paper demonstrates that a self-learning neurofuzzy controller is able to regulate the temperature in a liquid helium cryostat. In order to simplify the task of commissioning the controller, a strategy for choosing the user-selected parameters from an equivalent proportional-plus-integral controller (PI) is derived. Experimental results which illustrate the potential of the proposed control scheme are presented. The performance of the self-learning neurofuzzy controller is also compared with that of a commercial gain-scheduled PI controller.
This paper deals with an efficient application of a model-based predictive control scheme in parallel mechanisms. A predictive functional control strategy based on a simplified dynamic model is implemented. Experimental results are shown for the H4 robot, a fully parallel structure providing 3 degrees of freedom (dof) in translation and 1 dof in rotation. Predictive functional control, computed torque control and PID control strategies are compared in complex machining tasks trajectories. Tracking performance and disturbance rejection are enlightened.
Although conventional PID-like SISO controllers are still most common in industry, there is a growing need for more advanced controller structures in order to comply with ever tighter performance requirements. In this paper we consider positioning devices in IC-manufacturing for which position-dependent plant dynamics are a performance limiting factor. We suggested to employ recently developed linear parameter varying (LPV) control techniques for designing position-dependent controllers that adapt themselves in order to achieve optimal closed-loop performance. Our main emphasis is on presenting a practical LPV design procedure which covers plant modeling, controller synthesis and actual implementation for an electromechanical positioning device, an advanced wafer-scanner. Our experimental results reveal that performance can be improved by LPV control if compared to a classical SISO design. We highlight a variety of troublesome aspects within the design cycle that lack a systematic theoretically founded solution and that limit the possible performance improvement achievable by LPV control.
This paper deals with fault detection and isolation (FDI) of smart actuators combining the benefits of bond graph modelling with external models. An external model is a generic method which can be used to specify and verify the functional specifications of smart equipment. It uses the concept of services provided to the user and the organization of operating modes as a state graph with the logical conditions (depending on available services) required to move from one operating mode to another. One drawback of the external model is that it describes the system in terms of functions without taking into account the dynamics of the equipment. In addition, the availability of the services is not determined by FDI procedures. The integration of the bond graph methodology as a graphical and multi-disciplinary modelling tool quantifies the services by associating one or more bond graph elements to each service. Furthermore, the causal and structural properties of the bond graph methodology can be used to design FDI algorithms (i.e. the generation of fault indicators) to determine the availability of the services. This information is used to determine the transition conditions in the state graph. This technique has been applied to monitor a complex pneumatic servo-positioner.
In this paper, a Lyapunov-based control algorithm is developed for force tracking control of an electro-hydraulic actuator. The developed controller relies on an accurate model of the system. To compensate for the parametric uncertainties, a Lyapunov-based parameter adaptation is applied. The adaptation uses a variable structure approach to account for asymmetries present in the system. The coupled control law and the adaptation scheme are applied to an experimental valve-controlled cylinder. Friction modeling and compensation are also discussed. The experimental results show that the nonlinear control algorithm, together with the adaptation scheme, gives a good performance for the specified tracking task. The original adaptive control law is then simplified in several stages with an examination of the output tracking at each stage of simplification. It is shown that the original algorithm can be significantly simplified without too significant a loss of performance. The simplest algorithm corresponds to an adaptive velocity feedback term coupled with a simple force error feedback.
A comparison between receding horizon control (RHC) approaches is presented for the longitudinal axis control of an F-16 aircraft. The results suggest that the flexibility provided by a scheduled RHC scheme based on flight condition-dependent linear prediction models is a necessary requirement for achieving good performance as opposed to a single LTI model-based method. The scheduled scheme offers an attractive alternative to a full nonlinear model-based RHC approach by trading off an acceptable degradation in performance to modest computational complexity and real-time implementability.
A backstepping approach is used in this paper to design a nonlinear controller for force control of a single-rod electrohydraulic actuator. The control design guarantees the convergence of the tracking error. The implementation of the control design requires system states for feedback, but in this case only the force output is available. To overcome this problem, a PI observer is used to estimate the states of the system. Experimental results have illustrated the success of the observer-based backstepping controller. The results are also compared to those obtained with conventional P and PI controllers. It can be shown that the observer-based backstepping controller has a relatively better tracking performance.
This paper describes the flight testing of a suite of controllers designed using linearisations extracted from a new nonlinear model of the Bell 205 helicopter. Details of the controller designs are presented, together with a comprehensive analysis of simulation and flight-test results. These are complemented by an evaluation of qualitative and quantitative handling qualities information against the design standard ADS-33. The most notable achievements of the work were: (1) stability was achieved for all controllers tested and, moreover, some of them yielded desirable handling qualities from the first test onwards, and (2) a high degree of consistency between desk-top simulation and flight-test results was observed. Achieved performance was generally satisfactory and future planned flight tests will build on these results with the aim to increase performance further. The paper discusses various aspects of controller design and presents an analysis of the results obtained. The likely direction of further work is also discussed.
This paper describes the development and validation of a nine-degree-of-freedom (DOF) helicopter model, and the use of this model in designing H∞ optimal controllers for testing on an experimental fly-by-wire helicopter. The model includes rotor flapping dynamics and an inflow correction factor. Its use has led to improvements (with respect to earlier designs based on a different model) in the robustness properties of the resulting controller. For example, the need for predictor-type filters in the feedback path has been eliminated. Flight-test results are presented. Discrepancies still remain between predicted and achieved performance, but overall handling quality ratings have improved with respect to a previous H∞ design, and clear improvements have been obtained in pitch and roll attitude control: e.g. an increase in roll axis bandwidth from 1.9 to 2.5 rad/s.
This paper presents a Year-2000 (Y2K) status report of mechatronics. The Y2K definition of mechatronics is “the synergetic integration of physical systems with information technology and complex-decision making in the design, manufacture and operation of industrial products and processes.” Mechatronics may be interpreted as the best practice for synthesis of engineering systems, and it covers a broad area and scope. Vehicle lateral control for automated highway systems, hard disk drives and media handling mechanisms for printing engines are reviewed as examples of mechatronics research. Engineering students should be exposed to mechatronics and to the culture of working in teams.
The current vehicle-highway system has reached a plateau in its ability to meet the demand for moving goods and people. This paper sketches an architecture for an automated highway system or AHS. The architecture can be realized by several designs that differ in terms of performance and sophistication. One design is described that could triple capacity and reduce travel time, guarantee collision-free operation in the absence of malfunctions, limit performance degradation in the case of faults, and reduce emissions by half. Evidence suggesting that the design can be implemented is summarized. It is indicated how the design can be adapted to different urban and rural scenarios and how a standard land-use model can show the impact of AHS on urban density. A summary of the progress of the National Automated Highway Systems Consortium is provided. The paper concludes with a critique of AHS.
In 1996, 52 million vehicles were produced worldwide. By 2005, many predict that over 65 million will be produced because of the strengthening economies throughout the world and the individual's desire for personal mobility. The automobiles of the 1990s are at least 10 times cleaner and twice as fuel efficient as the vehicles of the 1970s. These advancements were due in large part to distributed microprocessor-based control systems. Furthermore, the resultant vehicles are safer, more comfortable, and more maneuverable. The environmental challenges of the 21st century will require advances of the same order of magnitude. In particular, next generation vehicles will be more “electrified” and designed by total systems approaches, involving new materials, alternative fuels, and new powertrains — all enabled by modern control systems and design techniques.
This paper considers iterative learning control law design for both trial-to-trial error convergence and along the trial performance. It is shown how a class of control laws can be designed using the theory of linear repetitive processes for this problem where the computations are in terms of linear matrix inequalities (LMIs). It is also shown how this setting extends to allow the design of robust control laws in the presence of uncertainty in the dynamics produced along the trials. Results from the experimental application of these laws on a gantry robot performing a pick and place operation are also given.
In web transport systems, the main problem is to control the web velocity and tensions independently, to prevent web breaks, folding, or damage. Interesting results have been obtained using multi-variable control strategies. Unfortunately, most of the existing methodologies are either not systematic or deal with the tracking and disturbance rejection problems as a whole, and not separately. This paper presents a complete methodology in order to design two-degrees-of-freedom (2DOF) controller. The feedforward part is based on a reference model allowing operators to obtain the desired tracking performances (in particular, web tensions and velocity decoupling). The feedback part ensures robustness and disturbance rejection and is designed using two high-level tuning parameters only, thanks to the Standard State Control (SSC) methodology. However, the system dynamics change greatly during the winding/unwinding process due to the winder/unwinder radius and inertia variations. Therefore, a gain-scheduling controller is derived from the interpolation of consistent realizations of the H2 controllers obtained at different points of the operating domain. The resulting controller is tested on a realistic simulator first, and after discretization, on a 3-motor web-handling experimental platform.
High-speed machining offers substantial economic benefits due to increased metal cutting productivity. Critical to realizing this technology's promise are the intertwined challenges of spindle dynamic stiffness and cutting process stability. Active magnetic bearings enable greater spindle dynamic stiffness through higher attainable bearing surface speeds, and also provide a means for enhancing cutting process stability. Herein, experimental results from two test rigs are presented illustrating the potential of magnetic bearings for the active suppression of machining chatter. Application challenges and controller design issues are examined in detail.
CIGRÉ Study Committee 38 deals with power system analysis and techniques. This paper gives the current status of the work in relation to making networks more effective. New equipment and new principles for system control are mentioned, as well as new concepts for investigating system reliability. The purpose is to define strategies for making networks more effective in the future.
Fuzzy logic control techniques are investigated for applications in the intelligent re-entry flight control of the ESA–NASA crew return vehicle. Three PD-Mamdani fuzzy controllers are constructed to control the inner-loop attitude dynamics, simulated by a fully nonlinear 3 degree-of-freedom simulator of the CRV. Each controller uses an angle tracking error and its derivative to calculate a commanded control surface deflection of the simulator. The input-domains are partitioned with 5 membership functions, resulting in 25 fuzzy rules for each rule-base. The output-domains are partitioned with 9 membership functions. The Mamdani controllers use a standard max–min inference process and a fast center of area method to calculate the crisp control signals. Simulation results show the ability to track a reference trajectory with acceptable performance, though the real strength of a nonlinear fuzzy logic controller is yet to be proven with more demanding benchmark trajectories.
This paper presents an augmented reality system that has been developed to reconstruct 3D scenes from a single camera's view. The camera is supposed to be calibrated in the world frame of reference. The 3D-model is known and correctly matched to its 2D-image. A 3D-object pose recovery algorithm that combines three methods to reach a better robustness and accuracy has been developed. A comparison between these methods is given, as well as a discussion about their advantages and drawbacks. Some experimental results on real images that demonstrate the robustness and the accuracy of the proposed system are presented as well as the visual command of a robot based upon the reconstructed scene.
A 3D spatial grid for exploiting the range and direction information inherent in sonar range data is presented. Special attention is given to the real time performance of the representation, and encouraging results have been demonstrated by computer simulations and sonar experiments.
In order to support the planning, monitoring and control of space–time critical processes, such as factory logistics or airport resource allocation, the IT system needs a user interface, which provides a good overview about the planned process, and it's actual state. Traditional systems use 2D graphics like Gantt charts and event networks, which show the duty and action sequences very well but not the spatial relationship on the airport. The idea to overcome this problem is to combine 2D with 3D visualization. We analyzed the requirements of such a visualization based on the application example of airport resource management and developed a demonstration prototype. This paper gives a short description of our preliminary results.
This paper presents a novel predictive control scheme for a series-parallel hybrid bus. The proposed scheme uses information from GPS together with a data record of the driving along the bus route to schedule the charging and discharging of the energy storage system. Switching between hybrid and pure electric mode is optimized in a receding horizon scheme based on a prediction model that reflects the uncertainty of the future driving.The benefits of the proposed predictive control scheme are shown by a simulation study on measured driving data along a bus route. The simulations show that the predictive control scheme achieves both lower fuel consumption and better control of the energy storage system than can be achieved with a non-predictive controller.
In this paper a new approach to the design of an active four-wheel-steered (4WS) control system is introduced. The problems of the conventionally used LQ-controller-based virtual model following control strategies are analyzed, and several problems are addressed. Two main problems of the LQ controller are highlighted: the external disturbance rejection, and the robustness of the controlled system in the face of parametric uncertainties. In the paper a combined Robust Linear Quadratic Regulator (RLQR) and H∞ controller design is presented for an active WS vehicle. The applicability of this kind of controllers is proven in this particular design case.
A novel, practically implementable robust Distributed Active Power Control (DAPC) technique is presented for IEEE 802.15.4 wireless sensor networks by using Quantitative Feedback Theory (QFT). The proposed DAPC framework is based on tracking a target Received Signal Strength Indicator (RSSI) where the effects of radio channel uncertainty and interference between sensor nodes are considered as an unknown output disturbance. The key features of this technique are summarized as follows: (1) quantifiable improvements are achieved in terms of outage probability and power consumption, (2) exact information in relation to the network operating conditions, e.g., radio channels gains and interference between users, is not required, and (3) the proposed graphical design environment simplifies the trade-off between system performance metrics. Experimental results are provided that highlight the effectiveness of the proposed approach when compared with some existing DAPC techniques.
The necessity of integrating diversified functions and areas in modern manufacturing systems requires, due to its complexity, powerful and sophisticated methods, techniques and tools for the acquisition, modelling, processing, storage and dissimination of information. Recent progress in computer science, knowledge engineering, modelling and simulation, as well as in other related fields has to be closely monitored in order to identify, adopt, and eventually implement research results into the manufacturing systems of tomorrow. An important forum for the presentation and discussion of research results and advanced industrial implementation in the field of information technology in manufacturing was the 7th IFAC/IFIP/IFORS/IMACS/ISPE Symposium on Information Control Problems in Manufacturing Technology held in Toronto, May 25–28, 1992. This paper gives a condensed presentation of the problems in this area, and introduces a block of selected papers from the symposium.
This paper presents the application of a nonlinear controller, using a predictive control strategy, to the distributed collector field of a solar power plant at the Plataforma Solar de Almerı́a (Spain). The design procedure of the controller uses the mathematical input–output model of the plant to find a controller output, using a search strategy that minimizes the cost function for a given prediction horizon. From the basic physical relations that are valid for the heating process of the oil inside the piping different nonlinear models have been deduced for this plant. The parameters of these models are estimated on-line in order to compensate for time-varying effects and modelling errors. The controller has been used in connection with these models to form an adaptive control system and has been applied to the plant. The results of experiments that were carried out in 1998 are presented.
This paper focuses on failure detection in the electrical flight control system of Airbus aircraft. Fault tolerance is designed into the system by the use of stringent processes and rules, which are summarized below. Monitoring of the system components is part of this fault-tolerant design. This paper covers the particular case of oscillatory failure monitoring in the electrical flight control system. The main characteristics and consequences of these failures are presented. The detection of oscillatory failures on the A380 is considered, together with the concept of analytical redundancy to detect these failures. A nonlinear actuator model is used to generate a residual on which the failure is detected by oscillation counting. Real application and benefits of the overall method are also presented. The results are highly satisfactory and the overall method is currently implemented on A380 flight control computers.
In manufacturing processes, human error and abnormal operation often result in excessive loads on the servomechanisms. To prevent the abnormal load from damaging the work piece or tool, it is important to find a means to detect the abnormal load so that an appropriate response can be performed. To estimate the load on the servomechanism, two types of torque observer structures are presented in this study. Based on the information obtained from the torque observer, criteria are proposed to determine whether the servomechanism is under the abnormal load, while the Wavelet analysis is employed to enhance the ability of abnormal load detection. Experimental results indicate that the presented observer structures are able to estimate the external torque accurately. In addition, the structure combined with Wavelet analysis is capable of identifying abnormal load events in servomechanisms.
This paper presents the design of a robust R–S–T controller of a variable speed pitch regulated wind turbine (VSPRWT) for above rated wind speeds (ARWS). An introduction of the subject and a state of the art review for controllers in ARWS are carried out. Afterwards, the studied VSPRWT and its validated model are presented. Then, the operating zone and control scheme are described. This system is non-linear and its linearising allows for the analysis of its behaviour, thereby obtaining the discrete-time control model as well as defining the controller's concrete objectives. The digital controller, which is designed following the pole assignment with sensitivity function shaping method, provides satisfactory simulation trial results.
This paper presents a rate-based controller for throttling available bit rate (ABR) input rates in high speed asynchronous transfer mode (ATM) networks with significant propagation delays. First, a Smith predictor based controller is analyzed in terms of performance and stability. Saturation issues are handled with anti-windup techniques. Performance is improved by means of the feedback of an estimate of the ABR disturbance. This reduces the average queue level, guaranteeing the shortest delays possible while keeping the channel fully occupied. Finally, sensitivity to delay estimation errors is analyzed, and the limitations of the proposed controller are discussed.
Two controllers for an active dynamic vibration absorber are designed to reduce the vibration to zero at specified frequencies and to non-resonant levels at the others. One of them contains a disturbance observer and asymptotically realizes a feedforward control of disturbance cancellation. It preserves the regulation property independent of perturbations in the primary system, but is sensitive to those in the absorber system. The other incorporates a disturbance model into its feedback loop. It preserves the regulation property in the presence of perturbations in both the primary and absorber systems. The designed controllers are studied experimentally.
The main objective of the proposed work is to perform stator flux and torque high dynamics response related to specific railway requirements such as anti-slid re-adhesion control. Moreover, this type of application takes into account DC bus voltage and current limitations. In addition, systems controlled by pulse width modulation (PWM) line side converters, injects harmonic current into the feeding overhead line. Therefore, it is necessary to consider an additional harmonic constraint (harmonic shape) as an entire part of the global control system in order not to interfere with signaling systems. Consequently, the high dynamics control objectives must be considered together with the PWM constraint and voltage/current limitations, as a single control task. Real-time simulation as well as experimental results for a specific railway test bench will be presented to highlight the performances of such control algorithm.
Adjustable speed electrical drives are undergoing a rapid transition from DC to AC machines in all fields of application, from the smallest to the largest power ratings. This has been made possible by the development of semiconductors in the complementary forms of macroelectronics and microelectronics, providing suitably processed power for the motors as well as intelligence for the complex control functions. In contrast to DC drives, there is a choice of many different combinations of power converters and AC machines, each having particular advantages; also, various types of control exist but for high-dynamic performance drives, a common principle of control has emerged. The review describes the results of the rapid evolution from innovative ideas to advanced industrial equipment, and points to future developments in the field of AC drive control.
The permanent magnet AC motor drive (PMAC) is a multivariable, non-linear, closely coupled system subject to saturation due to finite DC supply voltage and hard current limits for protection of the drive hardware. Model following controls can be applied to this class of motor with PI current controllers enabling tracking of quadrature current command values. The presence of a finite supply voltage constraint results in reduced system performance when the current regulators saturate. A dynamic model reference controller is presented which includes the currents and voltage limits, constraining the magnitude of the command signals, operating the system to just within the bound of saturation, allowing the PI controllers to accurately track the commanded values and retain control of the current vectors. This regime ensures maximum possible dynamic performance of the system. The system and controller is simulated and experimentally verified, controller gain being found by Monte Carlo simulation.
A distributed model predictive control (DMPC) approach based on distributed
optimization is applied to the power reference tracking problem of a hydro
power valley (HPV) system. The applied optimization algorithm is based on
accelerated gradient methods and achieves a convergence rate of O(1/k^2), where
k is the iteration number. Major challenges in the control of the HPV include a
nonlinear and large-scale model, nonsmoothness in the power-production
functions, and a globally coupled cost function that prevents distributed
schemes to be applied directly. We propose a linearization and approximation
approach that accommodates the proposed the DMPC framework and provides very
similar performance compared to a centralized solution in simulations. The
provided numerical studies also suggest that for the sparsely interconnected
system at hand, the distributed algorithm we propose is faster than a
centralized state-of-the-art solver such as CPLEX.
An advanced attitude observer for rigid bodies evolving in 3D-space using GPS-velocity and INS measurements has been proposed recently in the literature without specifying its domain of convergence and stability. With respect to conventional solutions, which do not involve linear velocity measurements, this observer is better adapted for vehicles subjected to important linear accelerations. The present paper proposes further modifications yielding two other attitude observers with rigorous semi-global convergence and stability results. Simulation results illustrate the compared performance of the three solutions and classical methods.
This paper shows the design and implementation of a fuzzy control system used to reduce the vertical motion of a TF-120 fast ferry. The system increases the comfort of the passengers and crew by reducing the main cause of seasickness. The aim of this controller—which is based on a fuzzy model of the ship behaviour—is to decrease the pitch acceleration by controlling the position of some actuators and varying their working angles. Experiments have been carried out on a ship scaled-down replica. The motion sickness incidence has been evaluated and results have proved to be highly satisfactory.