Research on adaptive control of six-degree-of-freedom manipulator based on fuzzy PID

In enhancing the precision of cooperative control among multiple manipulators, the traditional PID control method faces challenges in managing coupling interference and escalating chaos in the control parameters. An adaptive control strategy leveraging fuzzy logic-integrated PID technology is being investigated to attain the accurate manipulation of a six-degrees-of-freedom (DOF) robotic arm. Utilizing the D-H convention, a motion model for a six-degree-of-freedom manipulator was constructed. After assessing the manipulator's reachable workspace, an adaptive control model informed by fuzzy PID was employed to track changes in the manipulator's position and orientation. This model adjusts the rotation angle and speed of the joint motor to align with the desired state. Given the manipulators’ variable working environments and tasks, an adaptive neural network was integrated to continually optimize and refine the joint motor's rotation angle and speed. This enhances the control performance and stability of the manipulator, thereby facilitating the adaptive control. In the experiment, after the proposed method controlled the manipulator with six degrees of freedom, the joint position and angle of the manipulator were consistent with the expected state, which could achieve accurate adaptive control of the 6-DOF manipulator.