Abstract
A tracking control algorithm of nonlinear multiple agents with undirected communication is studied for each multiagent system affected by external interference and input saturation. A control design scheme combining iterative learning and adaptive control is proposed to perform parameter adaptive time-varying adjustment and prove the effectiveness of the control protocol by designing Lyapunov functions. Simulation results show that the high-precision tracking control problem of the nonlinear multiagent system based on adaptive iterative learning control can be well realized even when the input is saturated. Finally, the validity of the proposed algorithm is verified by numerical analysis.
Highlights
A multiagent control system is formed by multiple agents with independent action capabilities to complete a complex task through local cooperation and interaction [1,2,3,4]
Another work [20] evaluated the consistency problem of the Lupin clustering of nonlinear agents through adaptive sliding mode variable control based on [21,22,23] which considered the control problem of switched nonlinear multiagent systems and Complexity achieved the consensus tracking under the presented control strategies
Compared with the event-triggered control problem of multiagent systems and the finite-time control problem of multiagent systems, our results are only studied from the consensus control problem. e main reason is that the consensus control problem is the basic problem of the multiagent systems
Summary
A multiagent control system is formed by multiple agents with independent action capabilities to complete a complex task through local cooperation and interaction [1,2,3,4]. E study in [31] used Lyapunov theory to design an adaptive iterative learning algorithm with time-varying coupled-gain full-saturation parameter update to solve the problem of multiagent coordinated learning control with input saturation. We use adaptive iterative control to solve the high-precision tracking problem of nonlinear multiple agents in undirected communication. Inspired by the above analysis, we discuss the iterative learning control approach for tracking control of leader-following nonlinear multiagent systems with input saturation. E tracking problem of leader-following nonlinear multiagent systems with input saturation can be comprehensively solved using the presented iterative learning control protocol.
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