Liu Wei, Huang Jie
IEEE Trans Neural Netw Learn Syst. 2018 Nov;29(11):5486-5498. doi: 10.1109/TNNLS.2018.2803142. Epub 2018 Mar 6.
In this paper, we study the cooperative global robust practical output regulation problem for a class of second-order uncertain nonlinear multiagent systems via a distributed event-triggered state feedback control strategy. Compared with the existing work, one of the main challenges is that we need to design two distributed internal models to learn both the desired steady-state state and steady-state input for each agent. Moreover, to obtain a directly implementable digital control law, the two distributed internal models of each agent only depend on the sampled states of the neighboring agents and itself. As a result, the resulting augmented system is more complicated, and the control law needs to be recursively designed. To overcome the difficulty, we propose a novel distributed event-triggered control law and a novel distributed event-triggered mechanism to deal with our problem. By adjusting a design parameter in the proposed event-triggered mechanism, we show that the Zeno behavior does not happen and the ultimate bound of the tracking error can be made arbitrarily small. Our design will be illustrated by two examples.
在本文中,我们通过一种分布式事件触发状态反馈控制策略,研究了一类二阶不确定非线性多智能体系统的协同全局鲁棒实际输出调节问题。与现有工作相比,主要挑战之一在于我们需要设计两个分布式内部模型,来学习每个智能体的期望稳态状态和稳态输入。此外,为了获得可直接实现的数字控制律,每个智能体的两个分布式内部模型仅依赖于相邻智能体及其自身的采样状态。结果,所得的增广系统更加复杂,并且控制律需要递归设计。为克服这一困难,我们提出了一种新颖的分布式事件触发控制律和一种新颖的分布式事件触发机制来处理我们的问题。通过在所提出的事件触发机制中调整一个设计参数,我们表明芝诺行为不会发生,并且跟踪误差的最终界可以任意小。我们的设计将通过两个例子来说明。