Minimum entropy incremental control for nonlinear stochastic systems with non-Gaussian disturbances and uncertain parameters

摘要

In this paper, the problem of controller design for a general nonlinear stochastic system is investigated. The randomness of the considered stochastic system comes from external excitations and system parameters. To achieve minimum entropy control, the probability density function (PDF) of the tracking error is given by using recursive method firstly. Then, a new performance index is formulated, which contain the entropy of the tracking error, the mathematical expectation of the squared error and the control energy. A recursive optimization control algorithm is obtained by minimizing the performance index. Stability analysis is established and encouraging simulation results are included to illustrate the efficiency of the proposed method.