| 引用本文: | 杨杨,刘奇东,陈笛笛,岳东,窦春霞.基于预估器的一类多智能体系统神经动态面输出一致控制[J].控制理论与应用,2021,38(8):1197~1212.[点击复制] |
| YANG Yang,LIU Qi-dong,CHEN Di-di,YUE Dong,DOU Chun-xia.Predictor-based neural dynamic surface output consensus control of a class of nonlinear multi-agent systems[J].Control Theory and Technology,2021,38(8):1197~1212.[点击复制] |
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| 基于预估器的一类多智能体系统神经动态面输出一致控制 |
| Predictor-based neural dynamic surface output consensus control of a class of nonlinear multi-agent systems |
| 摘要点击 1522 全文点击 591 投稿时间：2021-01-13 修订日期：2021-03-17 |
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| DOI编号 10.7641/CTA.2021.10047 |
| 2021,38(8):1197-1212 |
| 中文关键词 预估器 神经网络 动态面控制 扰动 多智能体系统 |
| 英文关键词 predictor neural networks dynamic surface control disturbance multi-agent system |
| 基金项目 国家自然科学基金项目(61873130, 61833008, 61833011), 江苏省自然科学基金项目(BK20202011, BK20191377), 南京邮电大学“1311人才计划”, 南京邮电大学校级科研基金项目(NY220102, NY220194, 2020XZZ11), 江苏省研究生科研与实践创新计划项目(SJCX21 0292)资助. |
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| 中文摘要 |
| 本文针对一类含未知扰动与非对称输入饱和的非线性多智能体系统, 提出基于预估器的神经动态面输出
一致控制策略. 在设计预估器的基础上构造预估误差, 驱动神经网络更新权值估计系统未知动态, 并将预估器与神
经网络应用于非线性扰动观测器来补偿广义扰动. 本文所提出的控制策略采用神经网络权值范数学习方法, 减少学
习参数数目. 对于非对称的输入饱和, 设计辅助系统, 其生成的辅助变量与反步法相结合补偿输入限制. 结合图论知
识和Lyapunov函数等技术, 证明多智能体系统的输出一致跟踪误差以及闭环系统中的所有信号最终有界. 最后通过
一组四旋翼飞行器和数值仿真验证提出控制策略的有效性. |
| 英文摘要 |
| For a class of nonlinear multi-agent systems (MASs) with unknown disturbances and nonsymmetric input
saturations, we propose a predictor-based neural dynamic surface output consensus control strategy in this paper. Based on
the design of a predictor, weights of neural networks (NNs) are updated by prediction errors, and NNs are for estimation
of unknown dynamics. A nonlinear disturbance observer is then developed by the predictor and NNs, and it is for compensation
of generalized disturbances. The number of learning parameters in the proposed strategy is reduced by the norm of
NNs’ weights. As for nonsymmetric input saturation, an auxiliary system is designed. Combined with the framework of
backstepping, this auxiliary system generates signals to compensate saturation.With the help of graph theory and Lyapunov
functions as well as other technology, it is proven that the output consensus tracking error of the MAS and all signals in
the closed-loop system are ultimately bounded. Finally, the effectiveness of the proposed control strategy is verified by an
example of a team of qurdrotor unmanned aerial vehicles (UAVs) and a numerical simulation. |
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