Vehicle Lateral Stability Control Based on Sliding Mode Control

Zhao, Shuen; Li, Yinong; Zheng, Ling; Lu, Shuai

doi:10.1109/ical.2007.4338642

Cited by 20 publications

(10 citation statements)

References 3 publications

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“…Some solutions for controlling the longitudinal actuators have been based on complex models of the autonomous longitudinal system [3]. However, other authors have demonstrated that fuzzy logic offers a good way to model and control complex system, like vehicle's actuators [4].…”

Section: Introduction Ruisementioning

confidence: 99%

Design and implementation of a neuro-fuzzy system for longitudinal control of autonomous vehicles

Pérez

Gajate

Milanés

et al. 2010

International Conference on Fuzzy Systems

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Abstract-The control of nonlinear systems has been putting especial attention in the use of Artificial Intelligent techniques, where fuzzy logic presents one of the best alternatives due to the exploit of human knowledge. However, several fuzzy logic real-world applications use manual tuning (human expertise) to adjust control systems. On the other hand, in the Intelligent Transport Systems (ITS) field, the longitudinal control (throttle and brake management) is an important topic because external perturbations can generate uncomfortable accelerations as well as unnecessary fuel consumption. In this work, we utilize a neuro-fuzzy system to use human driving knowledge to tune and adjust the input-output parameters of a fuzzy ifthen system. The neuro-fuzzy system considered in this work is ANFIS (Adaptive-Network-based Fuzzy Inference System). Results show several improvements in the control system adjusted by neuro-fuzzy techniques in comparison to the previous manual tuned controller, mainly in comfort and efficient use of actuators.

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Section: Introduction Ruisementioning

confidence: 99%

Design and implementation of a neuro-fuzzy system for longitudinal control of autonomous vehicles

Pérez

Gajate

Milanés

et al. 2010

International Conference on Fuzzy Systems

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“…Some researchers [1]- [8] have made studies to this problem, but many other work should still be done. So we also study this problem here and the following is just about what we do.…”

Section: Introductionmentioning

confidence: 99%

Dynamic control of an electric steering vehicle

Yan

2008

2008 IEEE International Conference on Automation and Logistics

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In the paper, a new dynamic control scheme is developed, which is uesd to control a steering system for an electric rear independent driving car. The control system consists of a feedforward control subsystem, a feedback control subsystem and a SRC subsystem, which makes the car move along some curve ways safely and reliably. To investigate the control system performance, some simulation work is done based on MATLAB/Simulink. The simulation study shows the control system can make the electric vehicle steer reliably and stably.

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“…[25] proposed a two-layer model predictive control controller to optimize the required longitudinal force and yaw moment adjustments and to achieve the minimized error of the steady state tracking objective. A combined control algorithm was designed in [26] by taking the yaw rate and the centroid slip angle error as input variables and using the braking torque as the steering angle of the control objectives. In [27], a novel fusion feed-forward neural network controller for task decomposition was proposed to realize the lateral control of autonomous vehicles.…”

Section: Introductionmentioning

confidence: 99%

Novel Design and Lateral Stability Tracking Control of a Four-Wheeled Rollator

Zhang

et al. 2019

Applied Sciences

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Design and control of smart rollators have attracted increasing research interests in the past decades. To meet the requirements of the elderly or disabled users, this paper proposes a novel design and tracking control scheme for empowering and assisting natural human mobility with a four-wheeled rollator. Firstly, by integrating the advantages of Kano Model Analysis and the Theory of Inventive Problem Solving (TRIZ), we introduce a novel Kano-TRIZ industrial design method to design and optimize its mechanical structure. The demand and quality characteristics of the clinical rollator are analyzed according to the Kano model. The Quality Function Deployment (QFD) and TRIZ are adopted to integrate industrial product innovations and optimize the function configuration. Furthermore, a lateral stability controller based on Model Predictive Control (MPC) scheme is introduced to achieve good tracking control performance with the lateral deviation and the heading angle deviation. Finally, the feasibility of the design and control method is verified with a simulation study. The simulation results indicate that the proposed algorithm keeps the lateral position error in a reasonable range. In the co-simulation of ADAMS-MATLAB, the trajectory of the rollator is smooth with constrained position error within 0.1 m, the turning angle and speed can achieve stable tracking control within 5 s and the heading angle is accurate and the speed is stable. A compared experiment with MPC and SMC show that MPC controller has faster response, higher tracking accuracy and smoother trajectory on the novel designed rollator. With the increasing demand for rollators in the global market, the methodology proposed in this paper will attract more research and industry interests.

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Vehicle Lateral Stability Control Based on Sliding Mode Control

Cited by 20 publications

References 3 publications

Design and implementation of a neuro-fuzzy system for longitudinal control of autonomous vehicles

Design and implementation of a neuro-fuzzy system for longitudinal control of autonomous vehicles

Dynamic control of an electric steering vehicle

Novel Design and Lateral Stability Tracking Control of a Four-Wheeled Rollator

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