Fuzzy adaptive dynamic programming-based optimal leader-following consensus for heterogeneous nonlinear multi-agent systems

Cooperative Differential Game-Based Distributed Optimal Synchronization Control of Heterogeneous Nonlinear Multiagent Systems

This article presents an online off-policy policy iteration (PI) algorithm using reinforcement learning (RL) to optimize the distributed synchronization problem for nonlinear multiagent systems (MASs). First, considering that not every follower can directly obtain the leader's information, a novel adaptive model-free observer based on neural networks (NNs) is designed. Moreover the feasibility of the observer is strictly proved. Subsequently, combined with the observer and follower dynamics, an augmented system and a distributed cooperative performance index with discount factors are established. On this basis, the optimal distributed cooperative synchronization problem changes into solving the numerical solution of the Hamilton-Jacobian-Bellman (HJB) equation. Finally, an online off-policy algorithm is proposed, which can be used to optimize the distributed synchronization problem of the MASs in real time based on measured data. In order to prove the stability and convergence of the online off-policy algorithm more conveniently, an offline on-policy algorithm whose stability and convergence are proved is given before the online off-policy algorithm is proposed. We give a novel mathematical analysis method for establishing the stability of the algorithm. The effectiveness of the theory is verified by simulation results.

Distributed bipartite leader-following consensus of linear multi-agent systems with input time delay based on event-triggered transmission mechanism

This study focuses on the distributed bipartite consensus tracking for linear multi-agent systems with input time delay based upon event-triggered transmission mechanism. Both cooperative interaction and antagonistic interaction between neighbor agents are considered. A novel distributed bipartite control technique with event-triggered mechanism is raised to address this consensus issue. Different from the existing methods, our control technique does not need continuous communication among agents, is capable of addressing the case of input delay, and is applicable for the signed communication topology. Moreover, to avoid continuous monitoring of one's own state, a self-triggered control strategy is further proposed. And when the system states cannot be measured, the observer-based bipartite control technique with event-triggered mechanism is thus put forward. Furthermore, the results in leader-following consensus are extended to containment control. It is proven that the proposed controllers fulfill the exclusion of Zeno behavior in two consensus problems. Finally, simulation experiments are used to test the practicability of the theoretical analysis.

Distributed cooperative output regulation of heterogeneous linear multi-agent systems based on event- and self-triggered control with undirected topology

In this note, the cooperative output regulation problem is considered for a kind of heterogeneous linear multi-agent systems under undirected communication topological graphs. Our approach consists of two techniques, the design of distributed dynamic observer for exosystem under the event-triggered and self-triggered control mechanisms. Firstly, a distributed event-triggered control protocol is designed, which proves that multi-agent system can achieve stability and Zeno behavior is excluded under this protocol. Secondly, a self-triggered control protocol is designed to achieve the cooperative output regulation problem of heterogeneous multi-agent system. Moreover, by designing parameter in the self-triggered mechanism, the Zeno behavior does not exist. Finally, the theoretical results are verified by a simulation of output regulation problem under two triggered mechanisms.