作者：
COOK, PA[a]Control Systems Centre
Department of Electrical Engineering and Electronics University of Manchester Institute of Science and Technology Manchester M60 1QD U.K.
Several versions of a discrete-time model-referenceadaptivecontrol scheme are applied to a simulation model of an unknown plant, in order to investigate the effect of modifications intended to enhance the robustness...
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Several versions of a discrete-time model-referenceadaptivecontrol scheme are applied to a simulation model of an unknown plant, in order to investigate the effect of modifications intended to enhance the robustness of the system. It is found that, in this application, the simplest form of the algorithm appears to be the most effective, provided that the sampling rate, referencemodel and adaptation gain are appropriately chosen.
A new robust model reference adaptive control scheme is proposed to achieve robustness to bounded disturbance. A key feature of this scheme is that the knowledge of neither the upper bound on the disturbance nor the u...
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A new robust model reference adaptive control scheme is proposed to achieve robustness to bounded disturbance. A key feature of this scheme is that the knowledge of neither the upper bound on the disturbance nor the upper bound on the norm of the matching controller parameters is required. Another advantage of the scheme is its zero output error tracking.
A structure of a self-tuning time optimal control system which achieves a good and fast adaptation by using a referencemodel and a sensitivity model is described- A procedure of determination fhe time optimal control...
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A structure of a self-tuning time optimal control system which achieves a good and fast adaptation by using a referencemodel and a sensitivity model is described- A procedure of determination fhe time optimal control algorithm parameters by using the referencemodel and the sensitivity model is elaborated. A way of including an unmodelled dynamics and external disturbance is proposed. Simulation results indicate that the proposed structure provides very good adaptation to variations of system parameters within only two to three stepwise changes of the referent input.
The problems of synthesis and analysis of model reference adaptive control for systems with active learning are considered New active adaptivecontrol algorithms for systems with implicit and explicit referencemodel ...
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The problems of synthesis and analysis of model reference adaptive control for systems with active learning are considered New active adaptivecontrol algorithms for systems with implicit and explicit referencemodel are designed. The interconnections between direct and indirect active adaptivecontrol systems are discussed and it is shown that the suggested method is uniformal for both types of systems. The convergence properties of the designed algorithms are analysed. Using the martingale convergence theory the solutions for global stability of the algorithms are presented. A simulated example is used to demonstrate the potential and superiority of the algorithms.
control systems for robotic manipulators have been investigated for several years. The difficulty in designing a controller for a robotic manipulator is due to the highly nonlinear, time-varying dynamics. Closed-loop ...
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control systems for robotic manipulators have been investigated for several years. The difficulty in designing a controller for a robotic manipulator is due to the highly nonlinear, time-varying dynamics. Closed-loop constant gain controllers are effective when the robot is expected to perform a limited range of operations. In the case of a mobile robot, the commanded tasks are not likely to be repetitive. Thus, another method of control is desired to overcome the effects of the nonlinear time-varying dynamics. Several adaptivecontrol methods have been applied to robotic manipulators. The adaptivecontrollers are successful at trajectory tracking in the presence of the nonlinear time-varying dynamics. Some of these methods are computationally demanding, therefore, most of the current research focuses on efficient adaptivecontrol methods. In particular, the area of decentralized adaptivecontrol is gaining popularity. This method involves reducing a dynamic system into subsystems, each with an individual controller. This method is more efficient since the controllers can operate simultaneously. In this study, a decentralized model reference adaptive controller (MRAC) was designed for a four-degree-of-freedom mobile robot. The performance of the decentralized MRAC controller was compared to that of a constant gain state feedback controller. The decentralized MRAC control strategy proved to be an efficient method of control for a mobile robot that is superior to state feedback control when the robot is performing highly nonlinear time-varying tasks. Also, the computational load for each subsystem of the decentralized controller was less than the computational load of the state feedback controller.
control systems for robotic manipulators have been investigated for several years. Thedifficulty in designing a controller for a robotic manipulator is due to the highlynonlinear, time-varying dynamics. Closed-loop co...
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control systems for robotic manipulators have been investigated for several years. The
difficulty in designing a controller for a robotic manipulator is due to the highly
nonlinear, time-varying dynamics. Closed-loop constant gain controllers are effective
when the robot is expected to perform a limited range of operations. In the case of a
mobile robot, the commanded tasks are not likely to be repetitive. Thus, another method
of control is desired to overcome the effects of the nonlinear time-varying dynamics.
Several adaptivecontrol methods have been applied to robotic manipulators. The
adaptivecontrollers are successful at trajectory tracking in the presence of the nonlinear
time-varying dynamics. Some of these methods are computationally demanding,
therefore, most of the current research focuses on efficient adaptivecontrol methods. In
particular, the area of decentralized adaptivecontrol is gaining popularity. This method
involves reducing a dynamic system into subsystems, each with an individual controller.
This method is more efficient since the controllers can operate simultaneously.
In this study, a decentralized model reference adaptive controller (MRAC) was
designed for a four-degree-of-freedom mobile robot. The performance of the
decentralized MRAC controller was compared to that of a constant gain state feedback
controller. The decentralized MRAC control strategy proved to be an efficient method of
control for a mobile robot that is superior to state feedback control when the robot is
performing highly nonlinear time-varying tasks. Also, the computational load for each
subsystem of the decentralized controller was less than the computational load of the state
feedback controller.
Recently, a discrete-time model reference adaptive controller for non-minimum phase systems, called a 2-Delay model reference adaptive controller (2D-MRAC), has been proposed. However, this method only ensures the asy...
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Recently, a discrete-time model reference adaptive controller for non-minimum phase systems, called a 2-Delay model reference adaptive controller (2D-MRAC), has been proposed. However, this method only ensures the asymptotic model-following at the sampling instances, and the inter-sampling responses of the controlled system are not taken into consideration. In this paper, two extensions of 2D-MRACs arc proposed- a 2D-MRAC with internal input model and one with zero phase 2-delay inputs. These 2D-MRACs can provide the control system with not only the model-following property but also more reduced input amplitude for all non-minimum phase plant and a class of the desired outputs.
It is well known that undesirable transient responses and tracking performances have been frequently observed in traditional model reference adaptive control (MRAC) problems, especially for multivariable plants with u...
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It is well known that undesirable transient responses and tracking performances have been frequently observed in traditional model reference adaptive control (MRAC) problems, especially for multivariable plants with unmodeled dynamics and output disturbances. In this paper, a new robust model reference adaptive control using variable structure design (VSD) is proposed to investigate the solution. Based on a definition of generalized relative degree (GRD) for multivariable plants, the general case for plants with arbitrary GRD is completely solved. It is shown that, even when the uncertainties are presnet, global stability and robustness of the closed-loop control system are achieved. Furthermore, without any persistence of excitation, the tracking errors will, at least asymptotically, converge to zero for GRD-one plants and to a small residual set for plants with any higher GRD. With a suitable choice of initial control parameters, the tracking errors can even be driven to zero in finite time for GRD-one plants and to a small residual set exponentially for plants with any higher GRD. Copyright (C) 1996 Elsevier Science Ltd.
The problem addressed is one of model reference adaptive control (MRAC) of asymptotically stable plants of unknown order with zeros located anywhere in the s-plane except at the origin. The referencemodel is also asy...
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The problem addressed is one of model reference adaptive control (MRAC) of asymptotically stable plants of unknown order with zeros located anywhere in the s-plane except at the origin. The referencemodel is also asymptotically stable and lacking zero(s) at s = 0. The control law is to be specified only in terms of the inputs to and outputs of the plant and the referencemodel. For inputs from a class of functions that approach a non-zero constant, the problem is formulated in an optimal control framework. By successive refinements of the sub-optimal laws proposed here, two schemes are finally design-ed. These schemes are characterized by boundedness, convergence and optimality. Simplicity and total time-domain implementation are the additional striking features. Simulations to demonstrate the efficacy of the control schemes are presented.
A new adaptive digital control scheme for the robotic manipulator is proposed in this paper. Digital signal processors are used in implementing real time adaptivecontrol algorithms to provide an enhanced motion for r...
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A new adaptive digital control scheme for the robotic manipulator is proposed in this paper. Digital signal processors are used in implementing real time adaptivecontrol algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the adaptivemodelreferencecontrol theory. The adaptivecontroller consists of the adaptive feedforward and feedback controller and PI type time-varying control elements. The control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptivecontroller is illustrated by simulation and experimental results for a SCARA robot.
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