Nonlinear adaptive decoupling generalized predictive control using neural networks and multiple models
基于神经网络与多模型的非线性自适应广义预测解耦控制

A nonlinear adaptive decoupling generalized predictive control approach based on neural networks and mul- tiple models is proposed for a class of nonlinear multivariable discrete time dynamical systems.The control approach is composed of a linear robust decoupling generalized predictive controller,a neural network nonlinear decoupling generalized predictive controller and a switching mechanism.The linear robust decoupling generalized predictive controller ensures the boundedness of the input and output signals in the closed-loop system,and the neural network nonlinear decoupling generalized predictive controller improves the performance of the system.By using the switching scheme between the linear and nonlinear controllers,it is demonstrated that the stability and the improved system performance can be achieved simultaneously.Stability and convergence analysis are also given.Finally,simulation examples are presented to show the effectiveness of the proposed method.