Development of an Iterative Learning based Tip Position Controller of a Flexible Link Robot

Apart from industrial robots there is another class of robots which are of interest to space industry for its lightweight structure. The lightweight flexible robots are advantageous compared to rigid ones in several fronts such as higher payload-to-arm weight ratio,faster execution,and low power actuator requirements. But with these advantages, there lies an array of control complexities in Flexible Robot manipulators, as the modelling and control of a flexible robot is complex and difficult due to under actuated behaviour, non linear time varying and distributed system parameters. In the past, many control strategies have been proposed for the tip position control of flexible link robots but most of these techniques have not considered actuator dynamics in modelling and experimental validation is not carried out. The thesis proposes the use of a non linear model of a single link flexible robot manipulator obtained using Assumed Mode Method (AMM). The actuator dynamics has also been incorporated in the modelling of the single link flexible robot. The model thus obtained is experimentally validated using SIMULINK/MATLAB. The objective of the thesis is to control the tip position of a single link flexible robot. In order to achieve a successful tip trajectory tracking mechanism, the thesis proposes the use of an adaptive control mechanism called Iterative Learning Control (ILC). Iterative Learning based controller design offers significant advantages over other techniques such as it improves transient response and tracking performance of the system. It also takes care of non-linear effects such as friction, actuator dynamics etc. It requires only superficial knowledge of the system dynamics. Finally, to illustrate the effectiveness of the proposed controller, the performance of the designed controller in terms of input tracking and vibration suppression is compared with an existing PD controller by simulations