Stable multi-input multi-output adaptive fuzzy control

摘要: A stable indirect adaptive controller is presented which uses Takagi-Sugeno fuzzy systems, conventional or a class of neural networks to provide asymptotic tracking reference signal vector for continuous time multi-input multi-output (MIMO) square nonlinear plants with poorly understood dynamics. The scheme allows the inclusion priori knowledge about plant dynamics in terms exact mathematical equations linguistics. We prove that without such can "learn" how control plant, bounded internal signals, and achieve asymptotically inputs. do not impose any initialization conditions on controller, guarantee convergence error zero.