초록
영어
A stable neural network control scheme for unknown non-linear systems is developed in this paper. While the control variable is optimised to minimize the performance index, convergence of the index is guaranteed asymptotically stable by a Lyapnov control law. The optimization is achieved using a gradient descent searching algorithm and is consequently slow. A fast convergence algorithm using an adaptive learning rate is employed to speed up the convergence. Application of the stable control to a single input single output (SISO) non-linear system is simulated. The satisfactory control performance is obtained.
목차
Abstract
1. Introduction
2. NN stable control strategy
3. Process description
4. NN adaptive control of the process
5. Conclusions
References
1. Introduction
2. NN stable control strategy
3. Process description
4. NN adaptive control of the process
5. Conclusions
References
저자정보
참고문헌
자료제공 : 네이버학술정보