基于ECSOA的气动人工肌肉膝关节PID轨迹控制

PID Trajectory Control of Pneumatic Artificial Muscle Knee Joint Based on ECSOA

气动人工肌肉驱动关节存在非线性和时变性特性,传统PID控制难以取得理想的关节轨迹跟踪效果。对此提出一种基于碰撞人群搜索算法(Elastic Collision Seeker Optimization Algorithm,ECSOA)的改进PID控制策略,该策略利用ECSOA算法迭代速度快、不易陷入局部最优的特点,提升PID控制参数选取的合理性,以进一步提高气动人工肌肉的控制性能。为验证所提出策略的可行性和有效性,搭建了MATLAB/Simulink仿真模型和物理试验平台,开展气动人工肌肉膝关节轨迹跟踪控制实验。结果表明,ECSOA较SOA整定PID参数的速度更快且数据更为精准,能随着环境的变化和外界干扰自适应调节控制参数,相较于传统方法,膝关节轨迹跟踪误差降低了55.2%,系统的稳定性提高了24.6%,一定程度上解决了气动人工肌肉控制时存在的非线性和时变性问题。

The pneumatic artificial muscle drive joint has nonlinear and time-varying characteristics,and the traditional PID control is difficult to achieve ideal joint trajectory tracking.In this paper,an improved PID control strategy based on elastic collision seeker optimization algorithm(ECSOA)is proposed.The strategy uses the characteristics of the ECSOA algorithm,such as fast iteration speed and robustness against local optimum,to improve the rationality of PID control parameter selection,so as to further improve the control performance of pneumatic artificial muscle.In order to verify the feasibility and effectiveness of the proposed strategy,a MATLAB/Simulink simulation model and a physical test platform are built to carry out the trajectory tracking control experiment of the pneumatic artificial muscle knee joint.The results show that the ECSOA is faster and more accurate than the SOA in tuning the PID parameters.It can adjust the control parameters adaptively with the change of environment and external interference.Compared with the traditional method,the trajectory tracking error of the knee joint is reduced by 55.2%,and the stability of the system is improved by 24.6%.To a certain extent,the nonlinear and time-varying problems in the pneumatic artificial muscle control are solved.