In this paper, a new approach to design nonlinear adaptive PI multi-controllers, for SISO systems, based on neural local linear principal components analysis (PCA) models is proposed. The PCA neural networks only implements the integral term of the PI multi-controller, a proportional term is added to obtain a PI structure. A modi ed normalized Harris performance index is used for evaluating the controller performance. Some experimental results obtained with a nonlinear three tank benchmark model are presented, showing the adaptive PI-PCA multicontroller performance compared to neural linear PI controllers.
|Name||Lecture Notes in Electrical Engineering (LNEE)|
|Publisher||Springer International Publishing|
|Conference||11th Portuguese Conference on Automatic Control|
|Period||21/07/14 → 23/07/14|
- nonlinear adaptive PI control
- principal component analysis