Simulation comparison among three data-driven control methods for the planar manipulator

Abstract

IData-driven control (DDC) is very suitable for practical industrial processes and has attracted much attention of researchers and engineers because it does not depend on an accurate mathematical model of a controlled plant. In this paper, three typical on-line DDC methods, model free adaptive control (MFAC), model free control (MFC), and active disturbance rejection control (ADRC) are designed for the planar manipulator with 1 rotary joint (PM1R). In order to implement the proposed control methods on MATLAB platform, the discrete non-linear model of PM1R and discrete control laws for MFC and ADRC are also derived. The similarity and difference among three DDC methods are discussed briefly and the simulation comparisons among these three DDC methods are given to support the conclusions.

Mengxue Hou

Assistant Professor, Electrical Engineering

My research interests include robotic autonomy, mobile sensor networks, and human robot interaction. I aim to devise practical, computationally-efficient, and provably-correct algorithms that prepare robotic systems to be cognizant, taskable, and adaptive, and can collaborate with human operators to co-exist in a complex, ever-changing and unknown environment.