Output feedback control for Nonlinear Nonaffine Discrete-Time Systems and Application

摘要：

A nonlinear output feedback controller is proposed in this paper based on neural networks. A compound neural network is constructed to identify the dynamic nonlinear system including single-input-single-output (SISO) system and multiinput- multi-output (MIMO) system. One part of the CNN is a linear feedforward neural network (LFNN), which as used to approximate the nonlinear system. The other part is a recurrent neural network, which can shorten the difference between the LFNN and the real nonlinear process. Because the current control input is not included in the input vector of RNN, the inverse control laws of SISO and MIMO nonlinear systems can be easily obtained by CNN approximated models. The computation work is small since no further training is required for the inverse controller. Simulation studies have shown that this scheme is simple and affects good control accuracy and robustness.

关键词： Feedback linearization Neural network control Nonlinear discrete-time system MIMO nonlinear system

作者: Zhang Yan Xie Feng Xu Weiwei Yang Peng

作者单位: School of Control Science and Engineering, Hebei University of Technology, Tianjin, China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 654-659

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）