Mechanical arm trajectory tracking control method based on high-order sliding-mode observer

Abstract

The invention discloses a mechanical arm trajectory tracking control method based on a high-order sliding-mode observer. The method comprises the following steps of 1, establishing a dynamical model of an n-degree-of-freedom rotary joint rigid mechanical arm system; 2, acquiring measurement information of joint angles q of a mechanical arm by utilizing a photoelectric encoder, and calculating a mechanical arm trajectory tracking error e = q - qd according to a set expected joint angle qd; 3, establishing a global integral fast terminal sliding mode surface according to e; 4, determining control torque tau of joint driving motors of the mechanical arm according to the sliding mode surface and establishing a control gain self-adaptive rate capable of being dynamically adjusted; and 5, establishing the output feedback high-order sliding mode observer according to the control torque tau and the joint angles q of the mechanical arm, and estimating current angular velocity of joints and lumped disturbance. According to the method, under the situation that nonlinear uncertain items such as system parameter perturbation, external torque interference and damping friction exist in the mechanical arm system, the trajectory tracking control of the mechanical arm is realized only based on the measurement information of all the joint angles, and robustness of whole control process is ensured.

Description

technical field [0001] The invention belongs to the technical field of industrial control, in particular to a trajectory tracking control method of a manipulator based on a high-order sliding mode observer. Background technique [0002] In recent years, the robot industry has developed rapidly in the world, and its application range covers all fields of production and life. As a typical nonlinear system, the control of industrial manipulators has become a research hotspot in the field of automation. Considering that the industrial manipulator system has nonlinear uncertainties such as system parameter perturbation, external disturbance, and time-varying friction, it is difficult to obtain an accurate dynamic model of the manipulator. However, if these uncertain factors are ignored in the modeling process, it will lead to the deterioration of control performance and even cause system instability. Therefore, how to design a robust, self-adaptive, and simple-structure controll...

AI Technical Summary

Problems solved by technology

Considering that the actual manipulator can only directly obtain the angle information of each joint through high-precision position sensors, such as photoelectric encoders, and if the speed sensor is equipped, it will be easily disturbed by high-frequency noise on the one hand, and will also Increase the size and cost of the entire robotic arm control system

Images