摘要
双边控制系统常处于恶劣的工作环境中,设备磨损、老化等因素不可避免,当系统物理参数发生变化时,原先所设计的控制器将不能有效地对系统进行控制.本文以二连杆双边控制系统为对象开展数据驱动动力学建模和自适应控制研究.首先利用系统输入输出数据和拉格朗日神经网络(LNN)分别建立主、从端系统数据驱动动力学模型,然后考虑数据驱动模型与系统真实结构之间不可避免的误差,基于数据驱动动力学模型设计了四通道自适应控制器,并利用Lyapunov稳定性理论证明了该闭环控制系统的稳定性.最后考虑主端受到不同操纵力和从端受到不同环境力的情况进行仿真研究,仿真结果表明所提出的控制器具有稳定性和透明性,能够保证从端系统稳定地跟踪主端系统的运动,并能够在主端反映从端机械臂与外界环境间的作用力.
Bilateral control systems often operate in harsh working environments,where equipment wear and aging factors are unavoidable.When the physical parameters of the system change,the originally designed controller may no longer effectively control the system.This paper focuses on the two-link bilateral control system to conduct research on data-driven dynamic modeling and adaptive control.First,the input-output data of the system is used to establish the data-driven dynamic models for both the master and slave systems using Lagrangian neural networks(LNN).Then,considering the inevitable errors between the data-driven model and the actual system structure,a four-channel robust adaptive controller is designed based on the data-driven dynamic model,and the stability of the closed-loop control system is proven using Lyapunov stability theory.Finally,simulations are conducted to investigate scenarios where the master side is subjected to different manipulation forces and the slave side experiences various environmental forces.The simulation results indicate the stability and transparency of the proposed controller,ensuring that the slave system can stably track the motion of the master system and effectively reflect the interaction forces between the slave manipulator and the external environment.
作者
赵财银
陈龙祥
Zhao Caiyin;Chen Longxiang(School of Ocean and Civil Engineering,Shanghai Jiao Tong University,shanghai 200240,China)
出处
《动力学与控制学报》
2025年第4期45-56,共12页
Journal of Dynamics and Control
基金
国家自然科学基金资助项目(11972223)。
