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Adaptive robust tracking control for uncertain nonlinear fractional-order multi-agent systems with directed topologies

机译:具有定向拓扑的不确定非线性分数多算机系统的自适应鲁棒跟踪控制

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This paper addresses the robust consensus tracking problem for a class of uncertain nonlinear fractional order multi-agent systems (FOMASs) under general directed topologies. More specifically, FOMASs in the presence of heterogeneous unknown nonlinearities and external disturbances are considered in this paper, which include the second-order MASs as its special cases. First, we design two distributed saturated observers to overcome the deficiency of the traditional tracking control strategies. Second, when there exists a dynamics leader with unknown and bounded state trajectory, a discontinuous observer-based distributed controller with a-modification adaptive schemes is presented to guarantee the tracking error converges to zero asymptotically. Next, a continuous observer-based distributed controller is further proposed, under which the consensus tracking error is uniformly ultimately bounded (UUB) and can be reduced as small as desired. A neural network (NN), whose weights are tuned online, is used in the designed controllers to approximate the unknown nonlinearities. Motivated by the a-modification adaptive method, all the proposed adaptation algorithms require only local information and allow for robust even in the presence of heterogeneous unknown disturbances and fractional-order dynamics. Finally, the simulation results validate the efficacy of our proposed method. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文根据一般定向拓扑结构,解决了一类不确定的非线性分数阶多代理系统(FOMASS)的强大共识跟踪问题。更具体地,在本文中考虑了非均相未知非线性和外部干扰存在的污物,其包括二阶质量作为其特殊情况。首先,我们设计两个分布式饱和的观察者,以克服传统跟踪控制策略的缺陷。其次,当存在具有未知和有界状态轨迹的动态领导者时,提出了一种具有修改自适应方案的不连续观察者的分布式控制器,以确保跟踪误差会聚到零渐近零。接下来,进一步提出了一种连续观察者的分布式控制器,在该基于同观察者的分布式控制器,在该概念上是均匀的最终界限(UB)的共识跟踪误差,并且可以根据需要减小。在线调谐的神经网络(NN),用于设计的控制器,以近似未知的非线性。通过A-Demification自适应方法的动机,即使在存在异质未知干扰和分数级动态的情况下,所有所提出的适应算法也需要局部信息并允许稳健。最后,仿真结果验证了我们所提出的方法的功效。 (c)2018年elestvier有限公司保留所有权利。

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