Anti-Disturbance Tracking Control of non-Gaussian Stochastic Distribution Systems with Input Saturation

This paper discuss the anti-disturbance tracking control problem of non-Gaussian stochastic systems subject to input disturbance and actuator saturation. The objective is to control the conditional probability density functions (PDFs) of the system output to follow a given target function. Following the square root B-spline modeling to output PDFs, the PDF tracking is the transformed to a constrained dynamical tracking control for weight vectors. Moreover, the disturbance observer based control (DOBC) method is applied to estimate the unknown exogenous disturbances and the PI-type anti-disturbance controller is then designed by using the polytopic representation of saturation function. Finally, the favorable stability, dynamic tracking performance and robustness of the stochastic distribution systems can be guaranteed by using convex optimization theory. Simulation results are given to demonstrate the efficiency of the proposed approach.