Model-Based Event-Triggered Implementation of Hybrid Controllers Using Finite-Time Convergent Observers

TL;DR

This paper presents a model-based event-triggered control approach using finite-time convergent observers, enabling stable hybrid control systems with separate sensor and controller design, validated through simulations on linear and rigid body systems.

Contribution

It introduces a novel hybrid control framework with finite-time observers and event-triggering, allowing independent sensor and controller design under mild conditions.

Findings

Stable hybrid control achieved with finite-time observers.

Effective in linear plant regulation and rigid body attitude stabilization.

Validated through numerical simulations demonstrating practical viability.

Abstract

In this paper, we explore the conditions for asymptotic stability of the hybrid closed-loop system resulting from the interconnection of a nonlinear plant, an intelligent sensor that generates finite-time convergent estimates of the plant state, and a controller node that receives opportunistic samples from the sensor node when certain model-based event-triggering conditions are met. The proposed method is endowed with a degree of separation, in the sense that the controller design is independent of the sensor design. This is achieved under mild regularity conditions imposed on the hybrid closed-loop system and the existence of persistently flowing solutions. We demonstrate the versatility of the method by implementing it on: 1) a sampled-data controller for regulation of linear plants; 2) a synergistic controller for attitude stabilization of rigid bodies. The effectiveness of these novel controllers is demonstrated through numerical simulations.