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UBC Theses and Dissertations

Real-time implementation of adaptive control of industrial robots Zhou, Yuchen

Abstract

A robot working in an industrial environment has some uncertainties in its dynamics and is subject to some external disturbances. Application of adaptive control to the robot is intended to tolerate these uncertainties and disturbances by letting the robot system learn and improve its performance as it operates. Usually, adaptive control algorithms assume that the control torque can be generated as desired. Since most of industrial robots are actuated by electrical DC motors, this assumption neglects actuator dynamics. In fact, the behavior of the actuators (DC motors) is governed by a third order differential equation, and sometimes the actuator dynamics will dominate the robot dynamics. Very few experiments have been reported on the adaptive control of robots incorporating actuator dynamics. Development, stability analysis and implementation of an adaptive control scheme that incorporates actuator dynamics is the core of this thesis research. To evaluate adaptive control and to compare its performance with other control schemes through real-time implementation, a robot testbed is developed by retrofitting an industrial robot with a custom-built controller. The testbed features an open hardware architecture, high computational capacity and good software programmability. The development of the testbed is also an essential part of the thesis research. The adaptive control scheme incorporating actuator dynamics is implemented on this testbed. The effects of the actuator dynamics are studied. Experiments show that the performance of the robot, with the adaptive control scheme, is significantly improved when compensated for the actuator dynamics. The comparison between the proposed control scheme and the conven tional joint PD controller shows that application of adaptive control to an industrial robot can significantly improve the performance of the robot with minimal extra cost.

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