H∞ tracking-based sliding mode control foruncertain nonlinear systems via an adaptive fuzzy-neural approach

摘要

A novel adaptive fuzzy-neural sliding-mode controller withnH∞ tracking performance for uncertain nonlinear systemsnis proposed to attenuate the effects caused by unmodeled dynamics,ndisturbances and approximate errors. Because of the advantages ofnfuzzy-neural systems, which can uniformly approximate nonlinearncontinuous functions to arbitrary accuracy, adaptive fuzzy-neuralncontrol theory is then employed to derive the update laws fornapproximating the uncertain nonlinear functions of the dynamical system.nFurthermore, the H∞ tracking design technique and thensliding-mode control method are incorporated into the adaptivenfuzzy-neural control scheme so that the derived controller is robustnwith respect to unmodeled dynamics, disturbances and approximate errors.nCompared with conventional methods, the proposed approach not onlynassures closed-loop stability, but also guarantees annH∞ tracking performance for the overall system based onna much relaxed assumption without prior knowledge on the upper bound ofnthe lumped uncertainties. Simulation results have demonstrated that theneffect of the lumped uncertainties on tracking error is efficientlynattenuated, and chattering of the control input is significantly reducednby using the proposed approach