Research on High-Precision Control of Hydraulic Excavator Based on Optimal Trajectory Planning

Abstract

In this article, the trajectory planning and high-precision motion control of an excavator based on the independent hydraulic system of the load port are studied. A trajectory planning algorithm based on the combination of a quintic non-uniform B-spline curve and improved sparrow algorithm and an oil inlet flow controller based on the time-varying secant barrier Lyapunov function (TSBLF) are designed. First, the traditional sparrow algorithm is innovatively improved in trajectory planning to make the generated trajectory time shorter, more stable and energy better. Then, the secant function and fixed time controller are first introduced in the design of the oil flow controller to ensure that the system error converges to the predefined boundary in finite time. At the same time, the RBF neural network is used to approximate the unmodeled error and disturbance of the system. Finally, the simulation verification is carried out with the common trenching conditions in the intelligent operation of the excavator. The results show that the generated trajectory has obvious advantages over the traditional sparrow algorithm. The trajectory tracking error can converge to the neighborhood near the equilibrium point in a fixed time while satisfying the constraints, and has high control accuracy.

Keywords

• Trajectory optimization
• load port independence
• neural network
• barrier function
• flow/pressure control