Multiple-model-and-neural-network-based nonlinear multivariable adaptive control |
| |
Authors: | Yue FU;Tianyou CHAI |
| |
Affiliation: | Key Laboratory of Integrated Automation of
Process Industry, Ministry of Education, Northeastern University,
Shenyang Liaoning 110004, China;Research Center of Automation, Northeastern
University, Shenyang Liaoning 110004, China |
| |
Abstract: | A multivariable adaptive controller feasible for implementation on
distributed computer systems (DCS) is presented for a class of
uncertain nonlinear multivariable discrete time systems. The
adaptive controller is composed of a linear adaptive controller, a
neural network nonlinear adaptive controller and a switching
mechanism. The linear controller can provide boundedness of the
input and output signals, and the nonlinear controller can improve
the performance of the system. The purpose of using the switching
mechanism is to obtain the improved system performance and stability
simultaneously. Theory analysis and simulation results are presented
to show the effectiveness of the proposed method. |
| |
Keywords: | Adaptive control Neural network Multiple models Switching |
|
| 点击此处可从《控制理论与应用》浏览原始摘要信息 |
|
点击此处可从《控制理论与应用》下载全文 |
|