Periodic Event-Triggered Prescribed Time Control of Euler-Lagrange Systems under State and Input Constraints

2025-10-03

AI Summary

This paper addresses trajectory tracking control for Euler–Lagrange systems subject to external disturbances and simultaneous state, input, and time constraints. We propose a periodic event-triggered adaptive barrier control method. The approach constructs an exact (i.e., approximation-free) adaptive barrier function to rigorously enforce all constraints; introduces a time-varying triggering threshold combined with periodic sampling to eliminate Zeno behavior while substantially reducing communication and computational overhead; and integrates filtered error analysis to achieve robust disturbance rejection. Rigorous stability analysis proves that the tracking error converges within a prescribed finite time to a user-defined residual set. Comparative simulations and hardware experiments validate the method’s integrated superiority in constraint satisfaction, transient performance, and resource efficiency.

Technology Category

• Intelligent Robots: State Estimation
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Tracking, profiling, and countermeasures against them
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

This article proposes a periodic event-triggered adaptive barrier control policy for the trajectory tracking problem of perturbed Euler-Lagrangian systems with state, input, and temporal (SIT) constraints. In particular, an approximation-free adaptive-barrier control architecture is designed to ensure prescribed-time convergence of the tracking error to a prescribed bound while rejecting exogenous disturbances. In contrast to existing approaches that necessitate continuous real-time control action, the proposed controller generates event-based updates through periodic evaluation of the triggering condition. Additionally, we derive an upper bound on the monitoring period by analysing the performance degradation of the filtered tracking error to facilitate periodic evaluation of the event-triggered strategy. To this end, a time-varying threshold function is considered in the triggering mechanism to reduce the number of triggers during the transient phase of system behaviour. Notably, the proposed design avoids Zeno behaviour and precludes the need for continuous monitoring of the triggering condition. A simulation and experimental study is undertaken to demonstrate the efficacy of the proposed control scheme.

Problem

• Achieving prescribed-time trajectory tracking for perturbed Euler-Lagrange systems
• Ensuring state and input constraints while rejecting exogenous disturbances
• Developing periodic event-triggered control to avoid continuous monitoring

Innovation

• Periodic event-triggered control with adaptive barrier architecture
• Approximation-free prescribed-time convergence under constraints
• Time-varying threshold prevents Zeno behavior in triggering