Nonlinear Adaptive Model Predictive Controller for a Flexible Manipulator: An Experimental Study

This paper presents a new nonlinear adaptive model predictive controller (NAMPC) for tip position control of a flexible manipulator (FLM) when subjected to handle different payloads. The proposed adaptive control strategy consists of an online FLM dynamics identifier in the form of a nonlinear autoregressive moving average with exogenous input model and a control signal generator based on the above identified dynamics. The effectiveness of the proposed control algorithm is then verified by comparing its performance with that of a self-tuning controller (STC) and a nonlinear adaptive controller (NAC). The metrics of the controller performance are chosen as tip trajectory tracking accuracy and fast suppression of tip deflection. From the simulation and experimental results, it is observed that the proposed controller exhibits superior performance compared with the STC and NAC.