Fixed-time event-triggered fuzzy adaptive control for uncertain nonlinear systems with full-state constraints

This research investigates the fixed-time event-triggered fuzzy adaptive control for uncertain nonlinear systems with full-state constraints. Due to the difficulty of modeling and the inherent characteristics of mechanical structures, uncertainties and state constraints often arise in engineering applications, and the system may suffer from network congestion. Ignoring the effects of these constraints can affect the performance of the system. In addition, the system often requires high convergence speeds to increase productivity. To cope with these problems, this study investigates the fixed-time event-triggered fuzzy adaptive control method. First, special barrier Lyapunov functions (BLFs) are constructed to ensure that the full-state constraints are not violated. Furthermore, considering that the communication resources of practical systems are limited, a fuzzy based event-triggered mechanism (ETM) is designed. On this basis, a fixed-time fuzzy adaptive controller is constructed to achieve the fast convergence of the system. Finally, simulation results verify the feasibility.

Automated summary

This research investigates the fixed-time event-triggered fuzzy adaptive control for uncertain nonlinear systems with full-state constraints. Due to the difficulty of modeling and the inherent characteristics of mechanical structures, uncertainties and state constraints often arise in engineering applications, and the system may suffer from network congestion. Ignoring the effects of these constraints can affect the performance of the system. In addition, the system often requires high convergence speeds to increase productivity. To cope with these problems, this study investigates the fixed-time event-triggered fuzzy adaptive control method, which uses special barrier Lyapunov functions (BLFs) to ensure that the full-state constraints are not violated. A fuzzy based event-triggered mechanism (ETM) is also designed to manage limited communication resources. Simulation results verify the feasibility of the proposed method.