Advanced Robot control Algorithms based on model-based nonlinear velocity-observers and adaptive friction compensation

Abstract

Filtered velocity has two limitations: first, the introduction of a low-pass filter will cause tracking delay; second, even with the help of a low-pass filter, the noise in filtered velocity cannot be completely removed. The objective of the Ph.D research is to design a velocity observer without use of a low-pass filter, and at the same time, to minimize the noise level in observed velocity.Based on this objective, two observer-controllers have been developed. Experimental results indicate that, the noise level in observed velocity is lower than the filtered velocity. Under parametric uncertainty and payload variations, the proposed observer-controllers can achieve higher position tracking accuracy than the controller employing filtered velocity.Encouraged by the performance of the observer-controllers, two adaptive observer-controllers have been designed to perform friction identification and compensation function. Experimental results indicate that both the proposed adaptive observer-controllers are able to achieve much higher tracking accuracy than the observer-controller without friction compensation.Velocity observers can also help in force control applications. Two parallel force and motion controllers using observed velocity have been developed. Experimental results also show their better control performance in both force and motion subspace as compared with the controller using filtered velocity.