摘要
针对一类存在输入饱和和输出死区现象的非严格反馈非线性随机多智能体系统,提出一种自适应神经网络一致性饱和控制算法.首先,为了解决非对称输入饱和问题,构造一类与所考虑智能体相同阶次的辅助系统;然后,以反步法和辅助系统作为框架,利用神经网络处理系统中的未知非线性函数,并结合Nussbaum函数解决输出死区问题;接着,利用动态面控制技术避免“计算爆炸”问题;然后,基于李雅普诺夫稳定性理论验证所提出的控制算法能够保证闭环系统全部信号依概率半全局一致最终有界;最后,通过数值仿真和实例仿真的结果验证所提出控制算法的有效性.
An adaptive neural network consensus control algorithm is proposed for a class of non-strict feedback stochastic multi-agent systems with unknown input saturations and output dead zones.To solve the problem of asymmetric input saturations,an auxiliary system with the same order as the considered agent is constructed.Based on the framework of the backstepping method and the auxiliary system,neural networks are utilized to approximate the unknown nonlinear functions of multi-agent systems,and the Nussbaum function is introduced to compensate the negative effect of output dead zones.Moreover,the dynamic surface control technique is employed to avoid the problem of“explosion of complexity”.According to the Lyapunov stability theory,it is strictly proved that all signals in the closed-loop system are semi-globally uniformly ultimately bounded in probability.Finally,simulation results are provided to verify the effectiveness of the proposed control algorithm.
作者
于跃飞
林国怀
马慧
周琪
鲁仁全
YU Yue-fei;LIN Guo-huai;MA Hui;ZHOU Qi;LU Ren-quan(School of Automation,Guangdong University of Technology,Guangzhou 510006,China;School of Mathematics and Statistics,Guangdong University of Technology,Guangzhou 510006,China;Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control,Guangzhou 510006,China)
出处
《控制与决策》
EI
CSCD
北大核心
2023年第5期1249-1257,共9页
Control and Decision
基金
国家自然科学基金项目(62121004,62141606)
广东省研究生教育创新计划项目(2019JGXM40)
广东特支计划本土创新创业团队项目(2019BT02X353)
中国博士后科学基金项目(BX20220095,2022M710826)。
关键词
随机多智能体系统
一致性控制
输入饱和
输出死区
stochastic multi-agent systems
consensus control
input saturations
output dead zones
