Fixed-Time Adaptive Event-Triggered Guaranteed Performance Tracking Control of Nonholonomic Mobile Robots under Asymmetric State Constraints

Abstract

A fixed-time adaptive guaranteed performance tracking control is investigated for a category of nonholonomic mobile robots (NMRs) under asymmetric state constraints. For the sake of favorable transient and steady-state properties of the system, a prescribed performance function (PPF) is introduced and a transform function is further constructed. Based on the backstepping technique, an asymmetric barrier Lyapunov function is formulated to ensure the tracking errors converge within a human-specified time. On the foundation of this, the occupation of communication channel is effectively reduced by assigning an event-triggered mechanism (ETM) with relative threshold to the process of controller design. By utilizing the proposed control strategy, the NMR is capable of implementing the enemy dislodging mission while the enemy can always be caught by the NMR and the collision would never be presented. Finally, two simulation experiments are given to verify the effectiveness of the proposed scheme.

Event-Triggered Adaptive Neural Prescribed Performance Tracking Control for Nonlinear Cyber–Physical Systems against Deception Attacks

“…The use of time-triggered conventional digital control techniques may lead to a huge waste of communication resources and unnecessarily high workloads when computational and communication resources are allocated to other tasks [19]. In contrast, in systems that use an event-triggered mechanism (ETM), control inputs are updated only irregularly at certain moments, reducing the computational and communication burden [20][21][22]. A lot of research has emerged that addresses saving communication resources [23][24][25][26].…”