基于模型控制的液压机械臂高精度轨迹跟踪

Model-based Control of the Hydraulic Manipulator for the High-precision Trajectory Tracking

  • 摘要: 液压机械臂具有高度非线动力学特性,末端轨迹跟踪误差大。为此,提出一种辨识动力学参数的基于模型的控制算法(Model-based control, MBC)。该控制算法由外环的液压缸位置反馈控制器、内环的力控制器以及前馈流量补偿控制器三部分输出叠加组成。力控制器充分考虑液压机械臂动力学模型,动态补偿惯性力、重力和摩擦力等干扰力对控制精度的影响;位置控制器用以消除液压执行器造成的力偏差;前馈流量补偿器根据液压执行器动力学模型计算流量补偿量,提高系统响应与精度。针对动力学模型中存在的参数不准确问题,采用了最小二乘参数辨识的方法,在激励轨迹下获取液压机械臂动力学参数精确值。试验结果表明,所提出的辨识动力学参数的MBC控制算法相比3D模型参数的MBC控制在自由空间运动位置跟踪精度提升了39.24%,相比与传统PID控制提升了93%,显著提高了轨迹跟踪精度。

     

    Abstract: The hydraulic manipulator has high non-linear dynamic characteristics, causing large errors of end-effector trajectory tracking. A model-based control algorithm (Model-based control, MBC) with dynamic parameters identification was proposed for high-precision end-effector trajectory tracking of the hydraulic manipulator. The control algorithm was composed of three output parts: the hydraulic cylinder position feedback controller of the outer loop, the force controller of the inner loop and the feedforward flow compensation controller. The force controller fully considered the dynamics model of the hydraulic manipulator and compensated for the influence of inertial force, gravity force, and friction force on the control accuracy. The position controller is used to eliminate the force deviation caused by hydraulic actuators. The feedforward flow compensator calculates the flow compensation amount according to the dynamic model of the hydraulic actuator to improve the control response and accuracy. The least-square parameter identification method was adopted to solve the problem of inaccurate parameters in the dynamics model, and the accurate dynamic parameters of the hydraulic manipulator were captured under the excitation trajectory. The experimental results show that the proposed MBC control algorithm for identifying dynamic parameters improves the tracking accuracy of motion position in free space by 39.24% compared with the MBC control with 3D model parameters, and increases the tracking accuracy by 93% compared with the traditional PID control, which significantly improves the trajectory tracking accuracy.

     

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