A New Nonlinear Dynamic Speed Controller for a Differential Drive Mobile Robot

Abstract

A disturbance/uncertainty estimation and disturbance rejection technique are proposed in this work and verified on a ground two-wheel differential drive mobile robot (DDMR) in the presence of a mismatched disturbance. The offered scheme is the an improved active disturbance rejection control (IADRC) approach-based enhanced dynamic speed controller. To efficiently eliminate the effect produced by the system uncertainties and external torque disturbance on both wheels, the IADRC is adopted, whereby all the torque disturbances and DDMR parameter uncertainties are conglomerated altogether and considered a generalized disturbance. This generalized disturbance is observed and cancelled by a novel nonlinear sliding mode extended state observer (NSMESO) in real-time. Through numerical simulations, various performance indices are measured, with a reduction of 86% and 97% in the ITAE index for the right and left wheels, respectively. Finally, these indices validate the efficacy of the proposed dynamic speed controller by almost damping the chattering phenomena and supplying a high insusceptibility in the closed-loop system against torque disturbance.

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“…Robustness is commonly characterised as the bare minimum that a control system must meet in order to be usable in a real situation. Once created, the controller's settings do not alter, and control performance is assured (Ahmed et al, 2023a(Ahmed et al, ,b, 2022aSergiyenko et al, 2023 ;Kengne et al, 2023a,b ;Hashim et al, 2023 ;Hameed et al, 2023 ;Fekik et al, 2023a,b ;Zhang et al, 2023 ;Wang et al, 2023 ;Dendani et al, 2023 ;Toumi et al, 2022 ;Mahdi et al 2022 ;Ali el al., 2022a,b ;Abdul-Kareem et al, 2022;Abed et al, 2022;Sekhar et al, 2022 ;Saidi et al, 2022;Al Mhdawi et al, 2022 ;Lajouad et al, 2021;El Kafazi et al, 2021 ;Sundaram et al, 2021 ;Tolba et al, 2017a,b ;Soliman et al, 2017Soliman et al, , 2020Wang et al, 2017;Humaidi et al 2022Humaidi et al , 2021Humaidi et al , 2020Djeddi et al, 2019;Shukla et al, 2018;Khettab et al, 2018;Vaidyanathan et al, 2021aVaidyanathan et al, ,b,c,d,e, 2019Vaidyanathan et al, , 2018aVaidyanathan et al, ,b,c,d, 2017aVaidyanathan et al, ,b,c, 2015aVaidyanathan and Azar, 2021, 2016a,b,c,d,e,f, 2015aSantoro et al, 2013).…”

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“…Artificial Intelligence (AI) stands as the overarching field that encompasses computational intelligence, metaheuristic algorithms, control and robotics, forming a dynamic and interconnected landscape of technological advancement (Ahmed et al, 2023a(Ahmed et al, ,b,c, 2022aSayed et al, 2023;Sergiyenko et al, 2023;Vaidyanathan et al, 2023Vaidyanathan et al, , 2019Vaidyanathan et al, , 2018aVaidyanathan et al, ,b, 2017aVaidyanathan et al, ,b, 2015Kengne et al, 2023a,b;Azar et al, ,d, 2022aAzar et al, ,b, 2020aHashim et al, 2023;Hameed et al, 2023;Fekik et al, 2023aFekik et al, ,b,c, 2022aFekik et al, ,b,c, 2021aZhang et al, 2023;Wang et al, 2023;Dendani et al, 2023;Bousbaine et al, 2023;Hasan et al, 2023;Hamida et al, 2023Hamida et al, , 2022bNaoui et al, 2023). Artificial intelligence (AI) is rapidly transforming the field of robotics, enabling robots to perform more complex tasks and operate in more challenging environments.…”