Disturbance Observer-Based Minimum Entropy Control for a Class of Disturbed Non-Gaussian Stochastic Systems

• Published in: IEEE transactions on cybernetics Vol. 52; no. 6; pp. 4916 - 4925
• Main Authors: Tian, Bo, Wang, Yan, Guo, Lei
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Control algorithms; Control systems; Control theory; Controllers; Couplings; Decoupling; Disturbance observer (DO); Disturbance observers; Entropy; entropy optimization; exogenous disturbance; Feedback control; Heuristic algorithms; non-Gaussian system; Nonlinear systems; Optimization; Performance analysis; Performance indices; Probability density function; probability density function (PDF); Random noise; Randomness; stochastic distribution control (SDC); Stochastic systems
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2020.3024997

In this article, a novel control algorithm is developed for a class of nonlinear stochastic systems subject to multiple disturbances, including exogenous dynamic disturbance and general non-Gaussian noise. An observer is designed to estimate the exogenous disturbance, and then the disturbance compensation is incorporated into a feedback control strategy for the non-Gaussian system. Considering the ability of entropy in randomness quantification, a performance index is established based on the generalized entropy optimization principle. Furthermore, it is adjusted to be available for the controller solution, which also solves the coupling between two kinds of disturbances. On this basis, the optimal controller is provided in a recursive way, with which the closed-loop stability and good antidisturbance ability can be guaranteed simultaneously. Compared with the existing studies on the non-Gaussian stochastic systems, the proposed control algorithm has merits in multiple disturbances decoupling and enhanced antidisturbance performance. Finally, a simulation example is given to demonstrate the effectiveness of theoretical results.