Command Filter-Based Adaptive Fuzzy Self-Triggered Control for MIMO Nonlinear Systems with Time-Varying Full-State Constraints

This paper focuses on the adaptive fuzzy self-triggered tracking controller design for full-state constrained multiple-input and multiple-output nonlinear systems. The implementation of the control scheme is categorized into three steps: (1) restricting the states to satisfy the corresponding constraints; (2) handling the explosion of complexity; and (3) achieving a better compromise between system performances and communication loads. First, tangent barrier Lyapunov functions are applied to constrain the outputs and system states within time-varying boundaries. Then, the explosion of complexity is addressed via the command filtering method. Furthermore, an adaptive self-triggered control mechanism is developed to reduce resource consumption for each subsystem. In addition to solving the problem of monitoring the triggering threshold continuously, the designed adaptive self-triggered mechanism allows the triggering intervals to be dynamically adjusted according to the tracking errors, which makes the proposed control protocol possible to coordinate the system performances and communication resources. By using the Lyapunov stability criterion, it is demonstrated that all signals of the closed-loop systems are semi-globally uniformly ultimately bounded. Finally, two simulation examples are presented to confirm the effectiveness of the proposed control approach.