摘要
针对含有不确定项和随机噪声的分数阶Lorenz-Stenflo混沌系统控制问题,提出了一种结合神经网络和鲁棒微分控制器技术的滑模控制方法。为了应对系统中的不确定性和随机噪声,采用神经网络对不确定项进行逼近处理,采用鲁棒微分控制器消除随机噪声的影响。通过滑模控制策略,确保系统达到收敛状态。使用李雅普诺夫稳定性定理验证了系统的稳定性。Matlab数值仿真结果证实了该方案的可行性和显著效果。
A sliding mode control method combining neural network and robust differential controller techniques is proposed in response to the control problem of fractional order Lorenz-Stenflo chaotic system containing uncertain terms and random noise.In order to cope with the uncertainty and random noise in the system,a neural network method is used to approximate the uncertainty terms,and a robust differentiator is used to eliminate the effect of random noise.The sliding mode control strategy is implemented to ensure that the system reaches a converged state.The stability of the system is verified using the Lyapunov stability theorem.Matlab numerical simulation results confirm the feasibility and significant effect of the scheme.
作者
崔晋伟
赵小山
CUI Jinwei;ZHAO Xiaoshan(School of Sciences,Tianjin University of Technology and Education,Tianjin 300222,China)
出处
《天津职业技术师范大学学报》
2024年第2期38-43,共6页
Journal of Tianjin University of Technology and Education
基金
国家自然科学基金资助项目(12301428)。
关键词
混沌控制
神经网络控制
鲁棒微分控制器
滑模控制
分数阶
chaotic control
neural network control
robust differentiator
sliding mode control
fractional-order
