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Improving Performance for Multi-Agent Systems using Fuzzy-Logic Tuning and Mixed Feedback Controller

机译:使用模糊逻辑调整和混合反馈控制器提高多智能体系统的性能

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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.
机译:本文提出了一种采用模糊逻辑控制(FLC)的自适应混合反馈控制器,以提高具有未知时变通信时延的一组领导者代理的同步性能。为了提高整体系统性能,同时确保延迟下的稳定性,基于Lyapunov的方法和线性矩阵不等式(LMI)技术被用于设计一种分布式控制策略,该策略使用具有和不具有估计的自我延迟的座席状态信息。 FLC用于对控制器中自延迟状态的控制增益和权重进行在线调整,以作为总一致性误差的非线性函数。进行了由五个和七个直流电动机组成的跟随跟随器组的数值仿真,以证明所提出的控制器的有效性和整体性能的改善。

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