Command-Filtered Adaptive Fuzzy Control for Switched MIMO Nonlinear Systems with Unknown Dead Zones and Full State Constraints

This paper studies the problem of adaptive fuzzy control for switched multi-input and multi-output (MIMO) nonlinear systems with full state constraints and unknown dead zones. First, fuzzy logic systems (FLSs) serve as approximate instruments of unknown nonlinear functions, which are used to tackle the issue of parameter uncertainties. The unmeasured states are estimated by designing a switched MIMO state observer. Then, an adaptive fuzzy control strategy based on the command filter technique and average dwell time (ADT) method is proposed, which tackles the issue of explosion of complexity in the conventional backstepping recursive procedure, and also overcomes the drawback of dynamic surface control by designing compensating signals. Furthermore, the dead zone nonlinearities are handled using the information for dead zone slopes. In particular, barrier Lyapunov functions are employed to testify the stability of the system under our proposed control signals while preventing the constraint violations. Finally, two simulation examples demonstrate the availability and effectiveness of the presented adaptive controller.

Automated summary

This paper studies the problem of adaptive fuzzy control for switched multi-input and multi-output (MIMO) nonlinear systems with full state constraints and unknown dead zones. The proposed method utilizes fuzzy logic systems to approximate unknown nonlinear functions and estimate unmeasured states. An adaptive fuzzy control strategy is then proposed to handle the complexity explosion and overcome the drawbacks of dynamic surface control. The effectiveness of the presented adaptive controller is demonstrated through simulation examples.