Nonlinear Dynamic Decoupling Controller Using Multiple Neural Network Models
For a discrete-time nonlinear MIMO system, a novel multiple models neural network dynamical decoupling controller is designed in this paper. At each equilibrium point, the system is expanded into two terms: linear term and nonlinear term. The linear term is identified using one Neural Network and the nonlinear term is identified by the other trained online, which compose one system model. Then, all models, which are got at all equilibrium points, compose the multiple models set. At each instant, the best model is chosen as the system model according to the switching index. To design the controller accordingly, the nonlinear term and the interactions of the best model selected is viewed as measurable disturbance and eliminated by the use of the feedforward strategy. Finally, by the choice of the polynomial matrices, the dynamic decoupling controller can be got. The simulation example shows that the better system response can be got even when the system changes among these equilibrium points.
Yihui Zheng Hui Yang Xin Wang Jianguo Jiang
Center of Electrical & Electronic Technology Shanghai Jiao Tong University Shanghai, P.R.China 20024 School of Electrical & Electronic Engineering East China Jiao Tong University Nanchang, Jiangxi, P.R Department of Electrical Engineering Shanghai Jiao Tong University Shanghai, P.R.China 200240
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）