Abstract
This paper studies the decentralized adaptive tracking control problem for a class of discrete-time multi-agent systems with unknown parameters and high-frequency gains using multi-model method. Each agent is strong coupling with its neighbors by the historical outputs. All agents are interacted either directly or indirectly. In the face of uncertainties, the projection algorithm as a normal adaptive method is adopted. In order to improve quality of identification, the multi-model method is taken to identify unknown parameters and high-frequency gains using switching sets of the multiple parameters' and high-frequency gains' estimates, and the index switching functions. Using the certainty equivalence principle, the control law for the hidden leader agent is designed by the desired reference signal; the control law for each follower agent is devised by neighbors' historical outputs. Moreover, the proposed decentralized adaptive control laws can guarantee the following performances of the system: (1) the leader agent tracks the reference trajectory and each follower agent follows the average value of its neighborhood historical outputs; (2) the synchronization of all the follower agents to the leader agent is achieved; (3) all the agents track the reference trajectory, and the closed-loop system eventually achieves strong synchronization. Finally, simulations validate the effectiveness on improving control performance of multi-model adaptive algorithm by comparing with the projection algorithm.
Highlights
During the past decades, the control of multi-agent systems (MASs) has attracted extensive attention due to its potential applications in many fields, such as unmanned ground/air vehicles [1], multiple spacecrafts [2], sensor networks [3] and so on
Motivated by the above observations, this paper addresses the decentralized adaptive tracking control problem for a class of discrete-time multi-agent systems with unknown parameters and high-frequency gains
This paper is to study the tracking control of the multi-agent system using involves the projection-type algorithm and uses multi-model method to identify unknown parameters and high-frequency gains
Summary
The control of multi-agent systems (MASs) has attracted extensive attention due to its potential applications in many fields, such as unmanned ground/air vehicles [1], multiple spacecrafts [2], sensor networks [3] and so on. This paper is to study the tracking control of the multi-agent system using involves the projection-type algorithm and uses multi-model method to identify unknown parameters and high-frequency gains. The minimal value theorem, convergence criterion of the positive series, limit and set knowledge and so on To address such challenges, in this paper, a discretetime MAS with unknown parameters and high-frequency gains is investigated and the contributions are highlighted as follows: (1) for the discrete-time MAS with the parameter uncertainties and completely unknown high-frequency gains, the unknown internal parameters and unknown high-frequency gains are dealt with by the projection-type parameter estimation algorithm and multi-model method; (2) the leader’s output tracks the desired reference trajectory as time goes on, and each follower’s output asymptotically tracks the mean value of its neighbors’ outputs; (3) each follower’s output tends to the hidden leader’s output as time goes by; (4) the MAS eventually achieves synchronization in the presence of strong couplings. Definition 2 [13]: The agent in one multi-agent system is called one hidden leader if the agent knows the given signal, while other agents are aware of neither given signal nor the existence of the leader
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