轮式移动机器人预定时间领导跟随一致性控制OA北大核心CSTPCD
Predefined-time Leader-following Consensus Control for Wheeled Mobile Robots
研究了轮式移动机器人的领导跟随一致性问题,提出了预定时间一致性控制算法.首先,在有向图下,为每个跟随者提出一个分布式观测器,使其在预定时间内估计领导者状态.其次,基于观测器和构造的双幂次趋近律、非线性流形,设计了一种新的控制器,使得估计的领导者状态在预定时间内被跟踪.再次,引用了一个切换协议和一个线性流形,以确保在不引起奇异性问题的情况下,控制器在任何初始条件下均能实现预定时间的领导跟随一致性.然后,通过代数图论和李雅普诺夫理论证明系统的预定时间稳定性.最后,通过仿真对比实验验证了所提算法的有效性和优越性.相较于有限时间控制器,所提控制器收敛时间不依赖于初始状态,且收敛效果更好;相较于固定时间控制器,本文控制器收敛时间设定简单,可直接通过单一参数预先设定系统收敛时间.
A predefined-time consensus control approach is investigated for the leader-following consen-sus problem of wheeled mobile robot(WMR).First,under the directed graph,a distributed ob-server is proposed for each follower to estimate the leader's state in a predefined time.Second,on the basis of the observer and a constructed double power reaching law and a nonlinear manifold,a new controller is designed to track the estimated leader state in a predefined time.Moreover,a switching protocol and a linear manifold are referenced to ensure that the controller can achieve leader-following consensus for a predefined time under any initial condition without causing singu-larity problems.The predefined time stability of the system is then proved by algebraic graph theo-ry and Lyapunov theory.Finally,simulation comparison experiments verify the proposed algorithm's effectiveness and superiority.Compared with that of the finite-time controller,the convergence time of the proposed controller is independent of the initial conditions,and the convergence effect is better.Compared with that of the fixed-time controller,the convergence time setting of the pro-posed controller is simpler,and a single parameter can directly preset the system convergence time.
马小陆;谭毅波;梅宏;张睿;吴明
安徽工业大学电气与信息工程学院,安徽马鞍山 243002南京航空航天大学航天学院,江苏南京 210000
计算机与自动化
轮式移动机器人领导跟随一致性预定时间控制一致性控制有向图
wheeled mobile robot(WMR)leader-following consensuspredefined-time controlconsensus controldirected graph
《信息与控制》 2024 (001)
58-70 / 13
国家自然科学基金项目(61472282、62172004、62072002);安徽省科技重大专项(202003a05020028);安徽高校自然科学研究重点项目(KJ2019A0065);安徽省重点研究开发计划项目(202004a0502001);特种重载机器人安徽省重点实验室开放课题(TZJQR004-2020)
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