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 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 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.
