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Adaptive fuzzy iterative learning control with initial-state learning for coordination control of leader-following multi-agent systems

機(jī)譯：具有初始狀態(tài)學(xué)習(xí)的自適應(yīng)模糊迭代學(xué)習(xí)控制，用于領(lǐng)導(dǎo)者跟隨多主體系統(tǒng)的協(xié)調(diào)控制

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摘要

We propose a distributed adaptive fuzzy iterative learning control (ILC) algorithm to deal with coordination control problems in leader-following multi-agent systems in which each follower agent has unknown dynamics and a non-repeatable input disturbance. The ILC protocols are designed with distributed initial-state learning and it is not necessary to fix the initial value at the beginning of each iteration. A fuzzy logical system is used to approximate the nonlinearity of each follower agent. A fuzzy learning component is an important learning tool in the protocol, and combined time-domain and iteration-domain adaptive laws are used to tune the controller parameters. The protocol guarantees that the follower agents track the leader for the consensus problem and keep at a desired distance from the leader for the formation problem on [0, T]. Simulation examples illustrate the effectiveness of the proposed scheme.
機(jī)譯：我們提出了一種分布式自適應(yīng)模糊迭代學(xué)習(xí)控制（ILC）算法來(lái)解決領(lǐng)導(dǎo)者跟隨多主體系統(tǒng)中的協(xié)調(diào)控制問題，其中每個(gè)跟隨者主體具有未知的動(dòng)力學(xué)特性并且具有不可重復(fù)的輸入干擾。 ILC協(xié)議設(shè)計(jì)為具有分布式初始狀態(tài)學(xué)習(xí)，因此不必在每次迭代的開始時(shí)就固定初始值。模糊邏輯系統(tǒng)用于近似每個(gè)跟隨者代理的非線性。模糊學(xué)習(xí)組件是該協(xié)議中的重要學(xué)習(xí)工具，并且結(jié)合時(shí)域和迭代域自適應(yīng)律來(lái)調(diào)整控制器參數(shù)。該協(xié)議保證追隨者代理跟蹤領(lǐng)導(dǎo)者的共識(shí)問題，并在[0，T]上與領(lǐng)導(dǎo)者保持理想距離，以應(yīng)對(duì)編隊(duì)問題。仿真算例說(shuō)明了該方案的有效性。

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  • 來(lái)源
    《Fuzzy sets and systems》 |2014年第1期|122-137|共16頁(yè)
  • 作者

    Junmin Li; Jinsha Li;

  • 作者單位

    Department of Applied Mathematics, Xidian University, Xi'an 710071, PR China;

    Department of Applied Mathematics, Xidian University, Xi'an 710071, PR China;

  • 收錄信息 美國(guó)《科學(xué)引文索引》(SCI);美國(guó)《工程索引》(EI);
  • 原文格式 PDF
  • 正文語(yǔ)種 eng
  • 中圖分類
  • 關(guān)鍵詞

    Multi-agent system; Fuzzy system; Adaptive iterative learning control; Nonlinear system;

    機(jī)譯：多代理系統(tǒng);模糊系統(tǒng);自適應(yīng)迭代學(xué)習(xí)控制;非線性系統(tǒng);

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