Modelling and Feed-Forward Control of Robot Arms with Flexible Joints and Flexible Links

摘要

Reducing the weight of robotic manipulators has been identified as one of the important factors that can reduce the production and installation cost and allow for safe physical human-robot interaction but it results to flexible robotic manipulators.Motion control of flexible manipulators is a challenging task, particularly when the flexibility is arising not only because of flexible joints but also due to flexible links.To address this problem, more advanced real-time control strategies that effectively use more accurate mathematical models are required.This thesis deals with the various aspects of modelling, design, simulation and control of robotic manipulators that have both flexible joints and flexible links.For a manipulator with long-reach elastic arms (links), the simulations show that a lumped mass-spring-damper model with enough number of elements can adequately capture the critical modes of the distributed link flexibility of a robot arm.The main contributions of this work is the use of lumped inverse dynamic models to generate the required actuator references in addition to feedforward computed torque for high performance end-effector's trajectory tracking.To pursue this target, the dynamic differences between lumped models and elastic links are compensated both in the frequency-and time-domain.The compensation in frequency-domain relies on frequency response matching of zeros and poles between lumped models and models of the manipulator arms and joints.By using lumped model in the inverse dynamic models for feedforward control, real-time implementation will be possible in robot controllers used today.The compensation in the time-domain is based on feed-forward compensation of estimated link position errors obtained from measurements or FEM model simulations.Trajectory tracking results using different model implementations are presented and analysed and they show that the performance of the proposed modelling and control methodologies is promising.