Novel Command-Filtered Event-Triggered Control for High-Frequency Gains Nonlinear Systems Under Multiactuator Constraints

This article proposes an event-triggered command filtering adaptive fuzzy tracking control strategy for nonlinear systems with multiple unknown high-frequency gains and actuator constraints. During the design phase, a fuzzy logic system is used to approximate unknown nonlinear functions, whereas a novel equivalent transformation technique is introduced to simplify the design complexity of multiple input constraints by converting the input dead zones and saturation nonlinearities into a unified functional form. Subsequently, command filtering technology is used to address the issue of "complexity explosion" in control systems, and two additional adaptive laws are developed to assist in designing the compensation mechanism, which can both handle multiple unknown high-frequency gains and eliminate the impact of filtering errors on the control performance. Furthermore, a relative threshold event-triggered controller is developed to decrease data redundancy, and the viability of its triggering mechanism is demonstrated by excluding the Zeno phenomenon. The designed controller can ensure that the tracking error converges to a small vicinity near the origin, while all signals within the closed-loop system remain bounded. Finally, the effectiveness of the proposed solution is validated through simulation results.