A model following adaptive control system for CSIM is presented in this paper. A dynamic mathematical model of slip control based system is obtained. With the help of model reducing technique, full order model is ...A model following adaptive control system for CSIM is presented in this paper. A dynamic mathematical model of slip control based system is obtained. With the help of model reducing technique, full order model is reduced to simplify the design without degrading much of the performance. Model following adaptive control laws in discrete form are derived. These laws satisfy the hyperstability condition for taking care of the load and machine parameter changes of the drive. A microprocessor 8098 is used to develop the speed controller. The implementation of the control system uses only available variables of the reference model and the controlled plant. Experimental results are given to demonstrate the good performance of the system.展开更多
The synchronization problem under two cases is considered. One is that the bound on the uncertainty existing in the controller is known, the other is that the bound is unknown. In the latter case, the simple adaptatio...The synchronization problem under two cases is considered. One is that the bound on the uncertainty existing in the controller is known, the other is that the bound is unknown. In the latter case, the simple adaptation laws for upper bound on the norm of the uncertainty is proposed. Using this adaptive upper bound, a variable structure control is designed. The proposed method does not guarantee the convergence of the adaptive upper bound to the real one but makes the system asymptotically stable.展开更多
The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and c...The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertain-ties in both the system's structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some 'critical values' and establishing some 'Impossibility Theorems' for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.展开更多
The paper addresses optimization of a performance function which either is optimized via stabilizing and controlling the underlying unknown system or is directly optimized on the basis of its noise-corrupted observati...The paper addresses optimization of a performance function which either is optimized via stabilizing and controlling the underlying unknown system or is directly optimized on the basis of its noise-corrupted observations. For the first case the unknown system is identified and then the indirect adaptive control approach is applied to optimize the performance function. For the second case the stochastic approximation method is used to optimize the objective function, and it appears that a number of problems arising from applications may be reduced to the one solvable by this approach. The paper demonstrates some basic results in the area, but with no intention to give a complete survey.展开更多
文摘A model following adaptive control system for CSIM is presented in this paper. A dynamic mathematical model of slip control based system is obtained. With the help of model reducing technique, full order model is reduced to simplify the design without degrading much of the performance. Model following adaptive control laws in discrete form are derived. These laws satisfy the hyperstability condition for taking care of the load and machine parameter changes of the drive. A microprocessor 8098 is used to develop the speed controller. The implementation of the control system uses only available variables of the reference model and the controlled plant. Experimental results are given to demonstrate the good performance of the system.
文摘The synchronization problem under two cases is considered. One is that the bound on the uncertainty existing in the controller is known, the other is that the bound is unknown. In the latter case, the simple adaptation laws for upper bound on the norm of the uncertainty is proposed. Using this adaptive upper bound, a variable structure control is designed. The proposed method does not guarantee the convergence of the adaptive upper bound to the real one but makes the system asymptotically stable.
基金This work is supported by the National Natural Science Foundation of China and the National Key Project of China.This paper is based on the presentation at the International Symposium on"Intervention and Adaptation in Complex Systems"held in Beijing from
文摘The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertain-ties in both the system's structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some 'critical values' and establishing some 'Impossibility Theorems' for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.
基金This research is supported by the National Natural Science Foundation of China and the Ministry of Science and Technology of China.
文摘The paper addresses optimization of a performance function which either is optimized via stabilizing and controlling the underlying unknown system or is directly optimized on the basis of its noise-corrupted observations. For the first case the unknown system is identified and then the indirect adaptive control approach is applied to optimize the performance function. For the second case the stochastic approximation method is used to optimize the objective function, and it appears that a number of problems arising from applications may be reduced to the one solvable by this approach. The paper demonstrates some basic results in the area, but with no intention to give a complete survey.
