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      Sliding mode-based active disturbance rejection control for vehicle steer-by-wire systems

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          Abstract

          This study presents a sliding mode-based active disturbance rejection control (SMADRC) scheme for a steer-by-wire (SbW) system in road vehicles. First, a plant model that describes the mechanical dynamics of the SbW system is elaborated, where the viscous friction and the self-aligning torque are regarded as external disturbances. Second, the design of SMADRC is exposited, in which a non-linear extended state observer is utilised to estimate the non-linearities existing in the plant model, and a sliding mode control component is used to cope with the effect of the non-linearities and guarantee the control robustness against system uncertainties and varying road conditions. Finally, experimental results are shown to demonstrate the superiority of the designed SMADRC in comparison with a conventional sliding mode controller and a PD-based active disturbance rejection controller (PDADRC).

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          Most cited references 21

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          Modification of vehicle handling characteristics via steer-by-wire

           J.C. Gerdes,  P. Yih (2005)
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            Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

            This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.
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              An Analytical Redundancy-Based Fault Detection and Isolation Algorithm for a Road-Wheel Control Subsystem in a Steer-By-Wire System

               Sohel Anwar,  Lei Chen (2007)
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                Author and article information

                Contributors
                Journal
                IET-CPS
                IET Cyber-Physical Systems: Theory & Applications
                IET Cyber-Phys. Syst., Theory Appl.
                The Institution of Engineering and Technology
                2398-3396
                2398-3396
                24 July 2017
                14 November 2017
                March 2018
                : 3
                : 1
                : 1-10
                Affiliations
                [1 ] School of Software and Electrical Engineering, Swinburne University of Technology , Melbourne, VIC 3122, Australia
                [2 ] School of Electrical Engineering and Automation, Hefei University of Technology , Hefei, Anhui 230009, People's Republic of China
                [3 ] School of Automation and Guangdong Key Laboratory of IoT Information Technology, Guangdong University of Technology , Guangzhou 510006, People's Republic of China
                Article
                IET-CPS.2016.0013 CPS.2016.0013.R1
                10.1049/iet-cps.2016.0013

                This is an open access article published by the IET under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                Page count
                Pages: 0
                Product
                Funding
                Funded by: Swinburne University of Technology
                Categories
                Research Article

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