Hybrid Learning Control Schemes With Input Shaping Of A Flexible Manipulator System

Input shaping is a simple method for reducing the residual vibration in positioning lightly damped systems. Although several input shaping techniques have been derived to control a flexible manipulator system without payload, theoretical results are hard to be traced for their application to control a flexible manipulator system in real time. This project attempts to describe a practical approach to investigate and develop a hybrid iterative learning control scheme with input shaping. An experimental flexible manipulator rig and corresponding simulation environment are used to demonstrate the effectiveness of the proposed control strategy. In this work, a single link flexible robot manipulator that moves in horizontal plane is considered. A collocated proportional-integral-derivative (PID) controller utilizing hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to control the system with acceleration feedback for optimization of the learning parameters and a feed forward controller based for nonlinear model closed loop system on input shaping technique for control of vibration (flexible motion) of the system. The system performance with the controllers is presented and analysed in simulation using MATLAB and SIMULINK. The performance of the PID controller with input shaping is assessed in terms of level of vibration reduction. The effectiveness of the control schemes in handling various speed of flexible link is also analyzed. The performance of the system in term of with and without input shaping method also been compared. From the simulation results, satisfactory vibration reduction of a flexible manipulator has been achieved using the proposed method.