Improving the performance of adaptive PDPID control of two-link flexible robotic manipulator with ILC
Department of Mechanical Engineering, University of Ilorin, Nigeria
Flexible link manipulator systems (FLMs) have many advantages when compared to their rigid counterpart, these include: higher manipulations peed, low energy consumption, high payload to weight ratio and low overall cost. Controlling FLMs is challenging because of the highly distributed nature of the system. This paper presents a very simple and efficient control algorithm using adaptive Proportional Derivative (PD) Proportional Integral Derivative (PID) (traditional controller) and Iterative Learning Control (ILC) for two-link flexible manipulator. The adaptive control scheme constantly tunes the PD control gains, the PID controls the vibration and the ILC improves the overall performance of the system. The manipulator was modeled using Lagrange and assume mode method. The proposed control law was tested in Matlab/Simulink simulation environment. The performance and the performance index of the proposed control law were compared with those of the PDPID, PDPIDILC and adaptive PDPID controllers. The robustness of the proposed control law was further demonstrated through studying the effect of constant, repeating sequence, square wave and white noise disturbances. The result show that the proposed control law is robust to all these disturbances and has the best performance in all the cases studied.
Adaptive Control; Adaptive control schemes; Control laws; Efficient control; Flexible robotic manipulators; Flexible-link manipulators; ILC scheme; Iterative learning control; Lagrange; Low energy consumption; Matlab/Simulink simulation; Mode method; Noise disturbance; Overall costs; PD control; Performance indices; Proportional derivatives; Proportional integral derivatives; Square waves; Two-link; Weight ratios; Adaptive algorithms; Adaptive control systems; Control theory; Controllers; Energy utilization; Flexible manipulators; Three term control systems; White noise; Two term control systems