任意转换下带有未知迟滞的随机非线性系统自适应跟踪控制方案

Adaptive Tracking Control of Uncertain Switched Stochastic Nonlinear Systems with Unknown Hysteresis

主要研究了任意转换下带有未知迟滞的随机非线性系统的自适应跟踪控制问题。采用变量分离方法对状态变量进行分解,使其在任意转换之下逼近于一个光滑函数。通过把径向基函数神经网络普遍近似性能与自适应反步法相结合,构造出一个在任意转换之下的自适应神经控制算法。所设计的控制器保证了所有闭路系统信号半全局一致有界,并且,跟踪误差最终收敛到一个原点小邻域内,提出的方案更好地保证了在任意转换之下系统的稳定性。

This paper is concerned with the problem of adaptive tracking control of unceitain switched stochastic nonlinear systems with unknown direction hysteresis. In this p ap e r , the method of separation of variables is employed to decompose the state variables, and thus a smooth function is approximated to under arbitrary transformation. An adaptive neural con-trol algorithm under arbitrary transformation is established through the combination of the neural network universal approximation performance of the radial basis function （RBF）with adaptive inverse footwork. The designed controller ensures the uniform boundedness of the semi-global of all closed circuit systems ,and the tracking error converge is reduced to a small neighborhood of the original point. Inshort , the solutions put forward in the paper bet ter guarantee the system stability under arbitrary transformation.