Asymptotic Tracking Control With Bounded Performance Index for MIMO Systems: A Neuroadaptive Fault-Tolerant...

It is technically challenging to maintain stable tracking for multiple-input-multiple-output (MIMO) nonlinear systems with modeling uncertainties and actuation faults. The underlying problem becomes even more difficult if zero tracking error with guaranteed performance is pursued. In this work, by integrating filtered variables into the design process, we develop a neuroadaptive proportional-integral (PI) control with the following salient features: 1) the resultant control scheme is of the simple PI structure with analytical algorithms for auto-tuning its PI gains; 2) under a less conservative controllability condition, the proposed control is able to achieve asymptotic tracking with adjustable rate of convergence and bounded performance index collectively; 3) with simple modification, the strategy is applicable to square or nonsquare affine and nonaffine MIMO systems in the presence of unknown and time-varying control gain matrix; and 4) the proposed control is robust against nonvanishing uncertainties/disturbances, adaptive to unknown parameters and tolerant to actuation faults, with only one online updating parameter. The benefits and feasibility of the proposed control method are also confirmed by simulations.