Path Tracking and Direct Yaw Moment Coordinated Control Based on Robust MPC With the Finite Time Horizon for Autonomous Independent-Drive Vehicles

It is a striking fact that the characteristics of parametric uncertainties, external disturbance, time-varying and nonlinearities are available in the constructed model of autonomous independent-drive vehicles; therefore, in this paper, the robust model predictive control (MPC) with the finite time...

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Vydané v:	IEEE transactions on vehicular technology Ročník 69; číslo 6; s. 6053 - 6066
Hlavní autori:	Peng, Haonan, Wang, Weida, An, Quan, Xiang, Changle, Li, Liang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.06.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Autonomous independent-drive vehicles Computer simulation Cornering Degrees of freedom direct yaw moment control Dynamic characteristics Electric vehicles finite time horizon Linear matrix inequalities linear parameter varying model Mathematical model Optimization Path tracking path tracking control Predictive control Predictive models Real-time systems Robust control robust model predictive control Stiffness Tires Uncertainty Vehicle dynamics Vehicles Wheels Yawing moments
ISSN:	0018-9545, 1939-9359
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Abstract	It is a striking fact that the characteristics of parametric uncertainties, external disturbance, time-varying and nonlinearities are available in the constructed model of autonomous independent-drive vehicles; therefore, in this paper, the robust model predictive control (MPC) with the finite time horizon is proposed to realize the coordinated path tracking and direct yaw moment control (DYC) for autonomous four in-wheel motor independent-drive electric vehicles (AMIDEV). Firstly, considering the time-varying and uncertain feature of the tire cornering stiffness and the vehicle velocity in the state space equation constructed by 2 degrees of freedom (DoF) vehicle model and the path tracking preview model, the linear parameter varying (LPV) discrete model with four polytypic vertexes is constructed. Then, based on the linear matrix inequality (LMI) method, the novel robust MPC theory with the finite time horizon is put forward to solve the min-max optimization problem after updating four polytypic vertexes in real time, which could deal with the inevitable model mismatch problem caused by the time-varying, uncertain vehicle dynamic characteristics and external disturbance. Finally, the simulation and experimental results have verified that the proposed novel robust MPC theory could emerge from the stranglehold exercised by the conservativeness of the traditional robust MPC theory with the infinite time horizon, which strengthens the robustness of this control system as well as achieves better path tracking accuracy and handling ability of AMIDEV.
AbstractList	It is a striking fact that the characteristics of parametric uncertainties, external disturbance, time-varying and nonlinearities are available in the constructed model of autonomous independent-drive vehicles; therefore, in this paper, the robust model predictive control (MPC) with the finite time horizon is proposed to realize the coordinated path tracking and direct yaw moment control (DYC) for autonomous four in-wheel motor independent-drive electric vehicles (AMIDEV). Firstly, considering the time-varying and uncertain feature of the tire cornering stiffness and the vehicle velocity in the state space equation constructed by 2 degrees of freedom (DoF) vehicle model and the path tracking preview model, the linear parameter varying (LPV) discrete model with four polytypic vertexes is constructed. Then, based on the linear matrix inequality (LMI) method, the novel robust MPC theory with the finite time horizon is put forward to solve the min-max optimization problem after updating four polytypic vertexes in real time, which could deal with the inevitable model mismatch problem caused by the time-varying, uncertain vehicle dynamic characteristics and external disturbance. Finally, the simulation and experimental results have verified that the proposed novel robust MPC theory could emerge from the stranglehold exercised by the conservativeness of the traditional robust MPC theory with the infinite time horizon, which strengthens the robustness of this control system as well as achieves better path tracking accuracy and handling ability of AMIDEV.
Author	Xiang, Changle An, Quan Wang, Weida Li, Liang Peng, Haonan
Author_xml	– sequence: 1 givenname: Haonan orcidid: 0000-0003-2987-2411 surname: Peng fullname: Peng, Haonan email: penghaonanteddy@126.com organization: National Key Lab of Vehicular Transmission, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China – sequence: 2 givenname: Weida orcidid: 0000-0001-6420-5898 surname: Wang fullname: Wang, Weida email: wangwd0430@163.com organization: National Key Lab of Vehicular Transmission, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China – sequence: 3 givenname: Quan orcidid: 0000-0001-7004-4103 surname: An fullname: An, Quan email: 1520005763@qq.com organization: School of Vehicle and Mobility, Tsinghua University, Beijing, China – sequence: 4 givenname: Changle surname: Xiang fullname: Xiang, Changle email: xiangcl@bit.edu.cn organization: National Key Lab of Vehicular Transmission, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China – sequence: 5 givenname: Liang orcidid: 0000-0002-1577-408X surname: Li fullname: Li, Liang email: liangl@tsinghua.edu.cn organization: School of Vehicle and Mobility, Tsinghua University, Beijing, China
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SubjectTerms	Autonomous independent-drive vehicles Computer simulation Cornering Degrees of freedom direct yaw moment control Dynamic characteristics Electric vehicles finite time horizon Linear matrix inequalities linear parameter varying model Mathematical model Optimization Path tracking path tracking control Predictive control Predictive models Real-time systems Robust control robust model predictive control Stiffness Tires Uncertainty Vehicle dynamics Vehicles Wheels Yawing moments
Title	Path Tracking and Direct Yaw Moment Coordinated Control Based on Robust MPC With the Finite Time Horizon for Autonomous Independent-Drive Vehicles
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