随机部分可积拟哈密顿系统的概率密度追踪控制

目前非线性随机系统的控制方法存在设计复杂,计算成本高,以及缺乏稳定性或收敛性证明等缺点,针对这些问题,本文在作者前期研究的基础上发展了一种全新的针对部分可积的非线性随机系统的反馈控制,使得受控系统输出的稳态概率密度逼近事先给定的目标概率密度,并利用Lyapunov函数法证明受控系统的收敛性.数学仿真结果证明了这种方法的可行性和正确性.

Tracking control for stationary probability density of stochastic partial integrable system

Current control methods for nonlinear stochastic system have the shortcomings such as complex design procedures, high costs, and lack of stability and convergence proof. Therefore, based on the equivalent nonlinear system method for obtaining the approximate stationary solutions of the nonlinear stochastic systems, this paper proposes an innovative design procedure for the feedback control of stochastic nonlinear system. The control aims at making the statistical information of the output steady state probability density function (SPDF) follow those of a target SPDF. Moreover, Lyapunov function method is presented to verify the convergence of the controlled systems. Simulation results are also given to illustrate the feasibility and efficiency of this innovative design procedure.