Xu Jing, Niu Yugang, Zou Yuanyuan
IEEE Trans Cybern. 2022 Sep;52(9):8692-8702. doi: 10.1109/TCYB.2021.3051366. Epub 2022 Aug 18.
In some practical systems, it often remains difficult to directly measure all state variables. This article investigates the memory output sliding-mode control (SMC) for the finite-time consensus of singularly perturbed multiagent systems (SPMASs). First, the virtual state-feedback sliding surface (SFSS) is constructed to ensure the consensus of all agent states. Then, the unknown output derivatives in SFSS are approximated by a moving finite difference method with error estimation and refinement, which gives rise to a new delay-dependent sliding surface. On this basis, the memory output switching control law is designed to stabilize the consensus errors in finite time, even in the presence of estimation biases, singular perturbations, and input noises. Different from the observer-based SMC, the proposed memory output SMC is of simple static form without introducing extra dynamical structures for state estimation. The effectiveness and superiority of the design method are verified in an SPMAS with double-integrator dynamics.
在一些实际系统中,直接测量所有状态变量往往仍然很困难。本文研究了奇异摄动多智能体系统(SPMASs)有限时间一致性的记忆输出滑模控制(SMC)。首先,构造虚拟状态反馈滑模面(SFSS)以确保所有智能体状态的一致性。然后,采用具有误差估计和细化的移动有限差分法对SFSS中未知的输出导数进行近似,从而产生一个新的时滞相关滑模面。在此基础上,设计记忆输出切换控制律,即使在存在估计偏差、奇异摄动和输入噪声的情况下,也能在有限时间内稳定一致性误差。与基于观测器的SMC不同,所提出的记忆输出SMC具有简单的静态形式,无需引入额外的动态结构进行状态估计。在具有双积分器动力学的SPMAS中验证了该设计方法的有效性和优越性。