Predictor-based adaptive dynamic surface control for consensus of uncertain nonlinear systems in strict-feedback form
Predictor-based adaptive dynamic surface control for consensus of uncertain nonlinear systems in strict-feedback form
复制标题
基于预测器的自适应动态表面控制，用于严格反馈形式的不确定非线性系统的一致性
DOI：
10.1002/acs.2682
复制
发表时间：
2017
影响因子：
3.1
通讯作者：
Zhouhua Peng
中科院分区：
文献类型：
--
作者：
Wei Wang;Dan Wang;Zhouhua Peng
研究了严格反馈形式的不确定非线性系统的领导-跟随一致性问题。通过对智能体的未知非线性动力学进行参数化，提出了一种基于预测器和跟踪微分器的自适应动态面控制，实现了多智能体系统的输出一致性.与现有的自适应一致性方法不同，预测器误差用于学习未知参数，可以实现快速学习，而无需控制输入中的高频信号。作为一种快速精确的信号滤波器，跟踪微分器被用于控制设计中，而不是一阶滤波器，这可以进一步提高控制性能。基于图论和李雅普诺夫稳定性理论，证明了所有跟随者的输出最终同步于领导者的输出，且跟踪误差有界。仿真结果验证了所提出的一致性算法的有效性和优越性。版权所有© 2016约翰威利父子有限公司.
This paper investigates the leader–follower consensus problem of uncertain nonlinear systems in strict‐feedback form. By parameterizations of unknown nonlinear dynamics of the agents, an adaptive dynamic surface control with the aid of predictors, tracking differentiators is proposed to realize output consensus of the multi‐agent systems. Unlike the existing adaptive consensus methods, the predictor errors are used to learn the unknown parameters, which can achieve fast learning without high‐frequency signals in control inputs. As a fast precise signal filter, the tracking differentiator is used in the control design instead of first‐order filters, which can further improve the control performance. Based on graph theory and Lyapunov stability theory, it is shown that the outputs of all followers ultimately synchronize to that of the leader with bounded tracking errors. Simulation results are provided to validate the effectiveness and advantage of the proposed consensus algorithm. Copyright © 2016 John Wiley & Sons, Ltd.