摘要
针对现有PID方法难以适用于机械臂变有效载荷工况下的控制问题,提出了一种考虑变有效载荷的机械臂自适应PID控制策略。首先,构建了变有效载荷条件下的机械臂动力学模型,探讨了经典PID在变有效载荷条件下进行机械臂控制的缺陷;然后,基于离散域中时延控制(TDC)与PID控制之间的等价性,设计了一种自适应PID控制律,确定了该自适应PID控制策略的各增益系数,分析了该方法的优势,并给出了增益系数整定方法;结合Lyapunov理论,进一步证明了该控制策略的稳定性,明确了该方法应对机械臂有效载荷变化的鲁棒性;最后,通过仿真分析与物理实验,验证了该控制策略的有效性与变有效载荷条件下的鲁棒性。研究结果表明:与经典PID控制以及现有自适应PID控制相比,该控制方法在保证控制精度相同的前提下,对于较大幅度有效载荷变化工况(致使关节惯性最多增加124.4%)下的机械臂控制,其鲁棒性更强;该控制方法并可为后续更为复杂精准的自适应控制方法的提出提供参考。
Aiming at the problem that the existing PID control methods were difficult to apply to the control of manipulator under variable payload,an adaptive PID control strategy was proposed in the present work.The dynamic model of manipulator under variable payload was firstly constructed,and the defects of classical PID control under variable payload were discussed.Based on the equivalence between time delay control(TDC)and PID control in discrete domain,the proposed adaptive PID control law was designed,the gain coefficients of the proposed adaptive PID control strategy were determined,the advantages of the proposed method were discussed,and the gain coefficient tuning method was given.Combined with Lyapunov theory,the stability of the proposed control strategy was proved,and the robustness of the method to the payload change of the manipulator was illustrated.The effectiveness and robustness of the proposed control strategy under variable payload were verified by simulation analysis and physical experiments.The results show that compared with the classical PID and existing adaptive PID control methods,the proposed control method has better control robustness for the manipulator under the condition of large payload change(resulting in the maximum increase of joint inertia by 124.4%),and can provide a reference for more complex and accurate adaptive control methods.
作者
丁荣乐
侯旋
孙文建
DING Rong-le;HOU Xuan;SUN Wen-jian(Department of Automation,Nanjing Vocational Institute of Mechatronic Technology,Nanjing 211306,China;Department of Printing Engineering,Yuncheng Vocational and Technical University,Yuncheng 044000,China;College of Mechanical and Vehicle Engineering,Taiyuan University of Technology,Taiyuan 030024,China)
出处
《机电工程》
CAS
北大核心
2022年第3期291-299,共9页
Journal of Mechanical & Electrical Engineering
基金
国家自然科学基金资助项目(51775363)。
