| Current industrial and space manipulators are required to achieve higher speeds in a lighter structure without sacrificing payload capabilities. Consequently, undesirable vibration occurs during the motion. By suitable modelling of the manipulator flexibility, advanced control strategies can be formulated to improve the joint tracking performance and reduce the residual vibration of the end-point in the presence of payload uncertainties.;Toward this goal, an experimental two-link, 3D, anthropomorphic manipulator with flexible links was designed and built to be used as a test bed for the verification and refinement of the proposed modelling and control strategies.;The nonlinear equations of motion for the robot were derived using Lagrangian dynamics. The model was verified using experimental modal analysis techniques. Based on experimental results, a simplified nonlinear model, that contains the relevant modes of the system, was derived and subsequently used in controller designs and state estimation.;A conventional Proportional-plus-Derivative (PD) controller that implements joint angles feedback was designed to be used as a baseline controller due to its wide applicability on industrial manipulators.;By measuring the links tip vibration using accelerometers, several adaptive controllers and state observers were designed and implemented successfully on the manipulator, namely, a gain-scheduling linear quadratic regulator, a model reference adaptive controller, an adaptive inverse dynamics controller, a least-squares nonlinear state estimator and a robust sliding observer. The controllers performance and robustness were tested and experimentally verified against the change of the payload.;The control strategies and identification techniques, developed in this thesis, are applicable to a wide range of robot manipulators including industrial manipulators. |
