ROBUST NONLINEAR CONTROL AND ESTIMATION OF AN PRRR ROBOT SYSTEM

Mohammad AlShabi, Khaled S. Hatamleh, S. Andrew Gadsden, Bassel Soudan, and Amr El-Nady

Keywords

Sliding Mode Controller; Estimation; Control; Unscented Kalman Filter; Smooth Variable Structure Filter

Abstract

In this paper, a newly proposed implementation of an unscented smooth variable structure filter (UK-SVSF) is introduced. The method is combined with a sliding mode controller (SMC) to compensate for modeling uncertainties. The robustness and tracking accuracy of the proposed controller and estimation strategy are demonstrated on a four degree-of-freedom (DOF) robotic system with one prismatic and three rotary joints (PRRR). The effectiveness of the proposed combination is proven through comparisons with three different nonlinear estimation algorithms: the standard unscented Kalman filter (UKF), smooth variable structure filter (SVSF), and a previously published UK-SVSF. The robot’s trajectory following accuracy and efficiency are used as the performance parameters to study and compare the different strategies. Modeling uncertainties are added to the system to provide a more thorough evaluation of the robustness of the different nonlinear control and estimation strategies.

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