关键词: 概率密度函数, 保性能, 线性矩阵不等式, 神经控制器

Abstract: Aiming at the conservative problem of uncertain discrete-time output Probability Density Fuctions（PDFs）control systems, guaranteed cost control algorithm based on Linear Matrix Inequality(LMI)neural control was proposed, to which added state feedback controller of additive gain. In controller design, neural controller was used to tune the additive gain so that the guaranteed cost was reduced, and feasibility conditions for guaranteed cost control algorithm were derived by using LMI. The examples were used to demonstrate that the proposed algorithm could reduce the conservation of system and improve the stability and robustness of system.

Key words: probability density fuctions, guaranteed cost, linear matrix inquality, neurocontroller, additive gain