Event-Triggered l2-Optimal Formation Control with State-Estimation for Agents Modeled as LPV Systems

TL;DR

This paper introduces a distributed event-triggered formation control scheme with state estimators for LPV multi-agent systems, ensuring stability and performance with reduced communication.

Contribution

It presents a novel distributed control and estimation framework for LPV multi-agent systems using event-triggered communication and LMIs, with interchangeable estimators and stability guarantees.

Findings

The proposed method guarantees stability and bounded l2-performance.

Simulation results validate effectiveness on non-holonomic unicycle agents.

Interchangeable estimators offer flexible implementation options.

Abstract

This paper proposes a distributed scheme with different estimators for the event-triggered formation control of polytopic homogeneously scheduled linear parameter-varying (LPV) multi-agent systems (MAS). Each agent consists of a time-triggered inner feedback loop and a larger event-triggered outer feedback loop to track a formation reference signal and reject input and output noise. If a local event-trigger condition is violated, the event-triggered outer feedback loop is closed through the communication network. The event-trigger condition is only based on locally available information. To design the controller, a synthesis problem is formulated as a linear matrix inequality of the size of a single agent under the assumption, that local estimators trigger intercommunication events with neighboring agents if the event-trigger condition is violated. The design procedure guarantees stability and bounded l2-performance. Furthermore, the estimators are interchangeable for a given controller. We compare in simulation zero-order hold, open-loop estimation, and closed-loop estimation strategies. Simulation trials are carried out with non-holonomic dynamic unicycles modeled as polytopic LPV systems.