Scaled consensus of second‐order multiagent systems via distributed adaptive control

2021 ◽  
Author(s):  
Wangli He ◽  
Hualiang Guo ◽  
Feng Qian
Keyword(s):  
Adaptive Control ◽  
Multiagent Systems ◽  
Second Order ◽  
Distributed Adaptive Control

Resilient Control of Linear Time-Invariant Networked Multiagent Systems

2017 ◽  
Author(s):  
J. Daniel Peterson ◽  
Gerardo De La Torre ◽  
Tansel Yucelen ◽  
Dzung Tran ◽  
K. Merve Dogan ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Multiagent Systems ◽  
Linear Time ◽  
Relevant Literature ◽  
System Level ◽  
Linear Time Invariant ◽  
Distributed Adaptive Control ◽  
Exogenous Disturbances ◽  
Network Topologies ◽  
Time Invariant

A local state emulator-based adaptive control law is proposed for multiagent systems with agents having linear time-invariant dynamics. Specifically, we present and analyze a distributed adaptive control architecture, where agents achieve system-level goals in the presence of exogenous disturbances. Apart from existing relevant literature that makes specific assumptions on network topologies, agent dynamics, and/or the fraction of agents subjected to disturbances, the proposed approach allows agents to achieve system-level goals — even when all agents are subject to exogenous disturbances. Several numerical examples are provided to demonstrate the efficacy of our approach.

Robust distributed adaptive consensus for linear multiagent systems with uncertain topologies

2021 ◽  
pp. 014233122110605
Author(s):  
Wenchao Huang ◽  
Chengrong Lin ◽  
Bo Hu ◽  
Tao Niu
Keyword(s):  
Adaptive Control ◽  
Multiagent Systems ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Homogeneous Markov Chain ◽  
Consensus Control ◽  
Distributed Adaptive Control ◽  
Communication Topology ◽  
Parameter Dependent ◽  
Partly Unknown Transition Rates

This paper focuses on the robust mean-square consensus control problem for linear multiagent systems over randomly switching signed interaction topologies. The stochastic process is governed by a time-homogeneous Markov chain with partly unknown transition rates. Sufficient conditions for a consensus in the form of linear matrix inequalities are given via distributed adaptive control based on parameter-dependent Lyapunov functions. The adaptive control protocols require only the neighbor information of the agents, and the algorithm that designs the protocols reduces the influence of the communication topology on the consensus, which can prevent undesirable interaction impacts. Moreover, the disturbance rejection problem is addressed as an extension. Finally, two simulations are utilized to illustrate the effectiveness of the algorithms.

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