Improving Performance for Multi-Agent Systems using Fuzzy-Logic Tuning and Mixed Feedback Controller
Lucas Wan, Ya‐Jun Pan · IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society · 2020
In this paper, an adaptive mixed feedback controller using fuzzy logic control (FLC) is proposed to improve the performance of the synchronization of a group of leader-follower agents with unknown time-varying communication delays. With the aim to improve the overall system performance while ensuring the stability under delays, Lyapunov-based methods and linear matrix inequality (LMI) techniques are applied to design a distributed control policy that uses agent state information with and without estimated self-delays. FLC is applied to online tune the control gains and weight of the self-delayed state in the controller as a nonlinear function of the total consensus error. Numerical simulations of a leader-follower group of five and seven DC motors are carried out to demonstrate the effectiveness and improvement in overall performance of the proposed controller.