Simultaneous Optimal Distribution of Lateral and Longitudinal Tire Forces for the Model Following Control

Mokhiamar, Ossama; Abé, Masato

doi:10.1115/1.1850533

Cited by 222 publications

(105 citation statements)

References 6 publications

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“…Using linearization of the model τ = Gϕ(u, x, θ ), where θ are time-varying parameters, the constrained least-squares problem of allocation error minimization can be solved using numerical online quadratic programming (Andreasson & Bünte 2006, Tagesson, Sundström, Laine & Dela 2009). The effect of vehicle handling performance of weighting matrix coefficients on the control allocation performance is studied in (Mokhiamar & Abe 2004, Mokhiamar & Abe 2006, when using a control allocation method that assumes unconstrained optimization. Nonlinearities and uncertainty is with these approaches handled within low-level actuator/effector controllers that can also provide time-varying constraint limits (such as estimated maximum tire/road friction coefficient) to the control allocation.…”

Section: Yaw Stability Controlmentioning

confidence: 99%

Control allocation—A survey

2013

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The control algorithm hierarchy of motion control for over-actuated mechanical systems with a redundant set of effectors and actuators commonly includes three levels. First, a high-level motion control algorithm commands a vector of virtual control efforts (i.e. forces and moments) in order to meet the overall motion control objectives. Second, a control allocation algorithm coordinates the different effectors such that they together produce the desired virtual control efforts, if possible. Third, low-level control algorithms may be used to control each individual effector via its actuators. Control allocation offers the advantage of a modular design where the high-level motion control algorithm can be designed without detailed knowledge about the effectors and actuators. Important issues such as input saturation and rate constraints, actuator and effector fault tolerance, and meeting secondary objectives such as power efficiency and tear-and-wear minimization are handled within the control allocation algorithm. The objective of the present paper is to survey control allocation algorithms, motivated by the rapidly growing range of applications that have expanded from the aerospace and maritime industries, where control allocation has its roots, to automotive, mechatronics, and other industries. The survey classifies the different algorithms according to two main classes based on the use of linear or nonlinear models, respectively. The presence of physical constraints (e.g input saturation and rate constraints), operational constraints and secondary objectives makes optimization-based design a powerful approach. The simplest formulations allow explicit solutions to be computed using numerical linear algebra in combination with some logic and engineering solutions, while the more challenging formulations with nonlinear models or complex constraints and objectives call for iterative numerical optimization procedures. Experiences using the different methods in aerospace, maritime, automotive and other application areas are discussed. The paper ends with some perspectives on new applications and theoretical challenges.

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Section: Yaw Stability Controlmentioning

confidence: 99%

Control allocation—A survey

2013

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“…ESC와 함께 ARS와 같은 다른 장치들이 차량에 장착되는 경우 이 장치들을 협력하여 제어하는 것이 새로운 문제로 대 두되었고 이 문제를 풀기 위해 다양한 방법들이 제안되었다 [7][8][9]. 일반적으로, 차량 안정성 제어기 또는 요 모멘트 제어 Fig.…”

Section: 기호unclassified

Optimum Yaw Moment Distribution with Electronic Stability Control and Active Rear Steering

Yim¹

2014

Journal of Institute of Control, Robotics and Systems

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This article presents an optimum yaw moment distribution scheme for a vehicle with electronic stability control (ESC) and active rear steering (ARS). After computing the control yaw moment in the yaw moment controller, it should be distributed into tire forces, generated by ESC and ARS. In this paper, yaw moment distribution is formulated as an optimization problem. New objective function is proposed to tune the relative magnitudes of the tire forces. Weighed pseudo-inverse control allocation (WPCA) is adopted to solve the problem. To check the effectiveness of the proposed scheme, simulation is performed on a vehicle simulation package, CarSim. From the simulation, the proposed optimum yaw moment distribution scheme is shown to effective for vehicle stability control.

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“…독립조향의 경우 기존의 기계적인 시스템에서 조향 휠과 조향 기구부를 연결하는 조향 column을 제거하고 좌/우륜을 독립적으로 제어가 가능한 SBW (Steer-by-Wire) 시스템 연구 가 활발히 진행되고 있다 [2]. M. Abe 등은 횡방향 및 종방향 타이어 힘을 최적 배분하는 연구를 4륜 차량에 적용하여 차 량의 안정성을 향상시키는 연구를 진행하였다 [4]. 그림 2.…”

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Improvement of the Yaw Motion for Electric Vehicle Using Independent Front Wheel Steering and Four Wheel Driving

장재호¹,

김창준²,

김상호³

et al. 2013

Journal of Institute of Control, Robotics and Systems

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With the recent advancement of control method and battery technology, the electric vehicle have been researched to replace the conventional vehicle with electric vehicle with the view point of the environmental concerns and energy conservation. An electric vehicle which is equipped with the independent front steering system and in-wheel motors has advantage in terms of control. For example, the different torque which generated by left and right wheels directly can make yaw moment and the independent steering using outer wheel control is able to reduce the sideslip angle. Using of independent steering and driving system, the 4 wheel electric vehicle can improve a performance better than conventional vehicle. In this paper, we consider the method for improving the cornering performance of independent front steering system and in-wheel motor used electric vehicle with the compensated outer wheel angle and direct yaw moment control. Simulation results show that the method can improve the cornering performance of 4 wheel electric vehicle. We also apply the steering motor failure to steer the vehicle turned by the torque difference without steering. This paper describes an independent front steering and driving, consist of three parts; Vehicle Model, Control Algorithm for independent steering and driving and simulation. First, vehicle model is application of TruckSim software for independent front steering and 4 wheel driving. Second, control algorithm describes the reduced sideslip and direct yaw moment method in view of cornering performance. Last is simulation and verification.Keywords: 4X4 Vehicle, independent steering, independent driving, TruckSim, virtual steering angle, optimum tire force distribution method

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Simultaneous Optimal Distribution of Lateral and Longitudinal Tire Forces for the Model Following Control

Cited by 222 publications

References 6 publications

Control allocation—A survey

Control allocation—A survey

Optimum Yaw Moment Distribution with Electronic Stability Control and Active Rear Steering

Improvement of the Yaw Motion for Electric Vehicle Using Independent Front Wheel Steering and Four Wheel Driving

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