一类非线性非最小相位系统的直接自适应控制

针对一类不确定的离散时间非线性非最小相位动态系统,提出了一种基于神经网络和多模型的直接自适应控制方法．该控制方法由线性直接自适应控制器,神经网络非线性直接自适应控制器以及切换机构组成．线性控制器用来保证闭环系统输入输出信号有界,非线性控制器用来改善系统性能．切换策略通过对上述两种控制器的切换,保证闭环系统输入输出有界的同时,改善了系统性能．理论分析以及仿真结果表明了所提出的直接自适应控制方法的有效性．

Direct adaptive control for a class of nonlinear non-minimum phase systems

A direct adaptive control approach is proposed for a class of uncertain discrete time nonlinear non-minimum phase dynamical systems.The direct adaptive control approach is composed of a linear direct adaptive controller,a neural network nonlinear direct adaptive controller and a switching mechanism.The linear controller ensures the boundedness of the input and output signals,and the nonlinear controller improves performance of the system.By using the switching scheme,we demonstrated that both improved performance and stability are achieved simultaneously.Theoretical analysis and simulation results show the effectiveness of the proposed method.