Adaptive Fuzzy Control for Nontriangular Stochastic High-Order Nonlinear Systems Subject to Asymmetric Output Constraints

• Published in: IEEE transactions on cybernetics Vol. 52; no. 2; pp. 1280 - 1291
• Main Authors: Fang, Liandi, Ding, Shihong, Park, Ju H., Ma, Li
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.02.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Adaptive control; Adaptive fuzzy control; Adaptive systems; adding a power integrator; Algorithms; asymmetric output constraints; Asymmetry; barrier Lyapunov function (BLF); Computer Simulation; Control algorithms; Control systems design; Control theory; Feedback control; Fuzzy control; Liapunov functions; Lyapunov methods; Neural Networks, Computer; Nonlinear Dynamics; Nonlinear systems; Nonlinearity; nontriangular stochastic nonlinear systems; Stochastic processes; Stochastic systems
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2020.3000920

In this article, an adaptive fuzzy control design strategy is presented for <inline-formula> <tex-math notation="LaTeX">p </tex-math></inline-formula>-norm nontriangular stochastic high-order nonlinear systems with asymmetric output constraints and unknown nonlinearities. To prevent the violation of the asymmetric output constraint, a novel barrier Lyapunov function (BLF) is constructed. Then, combining the constructed BLF with adding a power integrator approach, the adaptive fuzzy control algorithm is developed by the backstepping technique. Simultaneously, the rigorous proof displays that the designed controller can ensure that all variables of the closed-loop system are bounded in probability with the achievement of the output constraint. Eventually, the theoretical result is further demonstrated via the simulation results.