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Liu Yulong,Ji Xuewu,Yang Kai-ming,He Xiangkun,Nakano Shirou 한국자동차공학회 2021 International journal of automotive technology Vol.22 No.5
Roll stability loss of heavy vehicle is a severe road safety problem and modern intelligent heavy vehicle (IHV) raises new requirement for advanced roll stability control technology. Two novel roll stability control frameworks, namely active steering-active anti-roll (AS-AAR) interactive control and worst-case optimized robust control, which have potential application to guaranteeing roll stability of IHV are proposed and investigated in this paper. The first control framework is implemented based on Nash dynamic game theory in which AS-AAR shared control is investigated as a dynamic difference game so that its two players, namely AS and AAR system, can interact with each other to provide satisfactory control performance. This interactive control scheme can be applied to vehicle automated driving scenario to improve vehicle tracking performance and roll stability. Based on zero-sum game theory, the second worst-case optimized robust control scheme is also developed to guarantee vehicle roll stability. This control method provides a suitable design framework to guarantee roll stability in scenario of vehicle-to-driver handover for IHV in which the steering input from human driver is regarded as uncertain disturbance. Simulation results show that both control frameworks can effectively improve roll stability as well as lateral stability while ensuing satisfied tracking performance.
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Tao Xu,Xuewu Ji,Xiangxin Liu,Zheng Li,Bo Feng,Fuwei Wu 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.6
Multi-axle vehicles that have important roles in transport systems require high load-carrying capacity, steering performance, and stability. Thanks to the multiple steering characteristics, the dynamic performance of multi-axle vehicles can be greatly improved, which also brings great challenges for the design of their steering controller. Therefore, this paper proposes a steering control scheme for an all-wheel-steering multi-axle vehicle with the goal of optimizing low-speed steering flexibility and high-speed vehicle stability. With the dynamic analyses, the vehicle’s steady-state gains at different speeds are reshaped, which provide the closed-loop steering control system with good tracking performance. Correspondingly, a steering controller based on the sliding mode control approach is designed to control the steering angle of each wheel at different axles. The super-twisting control algorithm is also combined with a model-based observer to deal with disturbance while eliminating chattering effects of the control system. Simulation results based on a co-simulation platform verify the efficiency and disturbance rejection of the proposed control approach.
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Yulong Liu,Tao Xu,Yahui Liu,Xuewu Ji 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.12
Modern intelligent road transportation system raises new requirements for advanced vehicle control technology of automated heavy commercial vehicle (HCV). This paper develops a novel output feedback-based linear parameter varying (LPV)/H∞ control paradigm for automated HCV to achieve multi-objective dynamic coordinated control. The proposed control paradigm aims at keeping vehicle centered with respect to the lane boundaries while achieving better roll stability by applying appropriate steering action. The main idea is to schedule tracking performance and roll stability by adjusting steering action according to HCV rollover risk evaluated by the rollover index (RI) estimator during automatic path tracking. This novel control paradigm allows a seamless multi-objective self-scheduling control to be reached and ensures robustness and stability of the closed-loop control system. Based on Simulink & TruckSim Co-Simulation as well as hardware in loop (HIL) implementation, a comparison study between the proposed LPV/H∞ control strategy and a classical linear time-invariant (LTI)/H∞ controller is conducted, which confirms the effectiveness of the proposed control scheme.
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