基于Kleinman迭代算法的非线性系统自适应控制器设计

Adaptive Controller Design of a Class of Nonlinear Systems Based on Kleinman Iterative Algorithm

应用Kleinman迭代算法,研究了一类非线性系统的在线自适应控制器设计问题.基于神经网络线性微分包含技术,对此类非线性系统进行建模描述.并在不利用系统后续参数矩阵的情况下,应用Kleinman迭代算法进行反复迭代,求解系统的Riccati方程.进而设计系统的自适应控制器,并证明了该算法的收敛性.最后通过数值仿真验证了该算法的可行性.

Based on the Kleinman iterative algorithm, the online adaptive controller design problem of a class of nonlinear systems is studied in this paper. The neural network linear differential inclusion technique is firstly used to model the studied nonlinear systems. Then, without considering the dynamic parameter matrix of the system, the Riccati equation is solved by means of the Kleinman iterative algorithm. Subsequently, the adaptive controller is designed and the convergence of the algorithm is proved. Finally, a numerical simulation example is given to illustrate the feasibility of the algorithm.