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Distributed optimal coordination control for nonlinear multi-agent systems using event-triggered adaptive dynamic

Wei Zhao¹, Huaipin Zhang²

¹School of Mathematics, Southeast University, Nanjing, 210096, PR China.

ISA Transactions

|February 6, 2019

Summary

This summary is machine-generated.

This study introduces an event-triggered adaptive dynamic programming (ETADP) method for nonlinear multi-agent systems (NMASs). This approach reduces data transmission and computation costs while ensuring system stability and optimal coordination.

Keywords:

Adaptive dynamic programming Distributed optimal coordination control Event-triggered sampling Multi-agent systems

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Area of Science:

Control Systems Engineering
Artificial Intelligence
Networked Systems

Background:

Nonlinear multi-agent systems (NMASs) require efficient coordination strategies.
Traditional time-triggered adaptive dynamic programming (TTADP) can be computationally intensive due to redundant data transmission.

Purpose of the Study:

To design a distributed optimal coordination control for NMASs using an event-triggered adaptive dynamic programming (ETADP) method.
To minimize performance functions and reduce data transmission in NMASs.

Main Methods:

Development of event-triggered conditions based on Lyapunov functional method to ensure NMAS stability.
Introduction of a novel adaptive policy iteration algorithm for online solutions of Hamilton-Jacobi-Bellman (HJB) equations.
Utilization of fuzzy hyperbolic model-based critic neural networks (NNs) for approximating value functions and control policies.

Main Results:

The event-triggered strategy significantly reduces redundant data transmission compared to TTADP.
NN weight estimations are updated aperiodically, lowering computation costs.
Uniform ultimate boundedness (UUB) is proven for weight estimation errors and local coordination errors.

Conclusions:

The proposed ETADP method effectively achieves distributed optimal coordination control for NMASs.
The method enhances efficiency by reducing data transmission and computation.
Simulation examples validate the effectiveness and stability of the ETADP approach.