Variable structure controller design for steer-by-wire system of a passenger car

Mousavinejad, Eman; Kazemi, Reza

doi:10.1007/s12206-014-0740-z

Cited by 13 publications

(9 citation statements)

References 4 publications

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“…A 2DOF vehicle model is widely used as a reference model for the controller design of the vehicle steering system [30,31]. Both theory and experiment prove that the controllers based on the 2DOF vehicle model can work normally and represent the actual physical process of the vehicle steering system with great accuracy [32].…”

Section: The 2dof Vehicle Model For the Controller Designmentioning

confidence: 99%

Improving Handling Stability Performance of Four-Wheel Steering Vehicle Based on the H2/H∞ Robust Control

Liu

Chen

et al. 2019

Applied Sciences

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Considering the demand for vehicle stability control and the existence of uncertainties in the four-wheel steering (4WS) system, the mixed H2/H∞ robust control methodology of the 4WS system is proposed. Firstly, the linear 2DOF vehicle model, the nonlinear 8DOF vehicle model, the driver model, and the rear wheel electrohydraulic system model were constructed. Secondly, based on the yaw rate tracking strategy, the mixed H2/H∞ controller was designed with the optimized weighting functions to guarantee system performance, robustness, and the robust stability of the 4WS vehicle stability control system. The H∞ method was applied to minimize the effects of modeling uncertainties, sensor noise, and external disturbances on the system outputs, and the H2 method was used to ensure system performance. Finally, numerical simulations based on Matlab/Simulink and hardware-in-the-loop experiments were performed with the proposed control strategy to identify its performance. The simulation and experimental results indicate that the handling stability of the 4WS vehicle is improved by the H2/H∞ controller and that the 4WS system with the H2/H∞ controller has better handling stability and robustness than those of the H∞ controller and the proportional controller.

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Section: The 2dof Vehicle Model For the Controller Designmentioning

confidence: 99%

Improving Handling Stability Performance of Four-Wheel Steering Vehicle Based on the H2/H∞ Robust Control

Liu

Chen

et al. 2019

Applied Sciences

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“…Since the self-aligning moment has the significant effect on the handling quality and safe driving, it is recognized as an essential feedback to the driver [4]. In the present work, the two degrees of freedom bicycle model is considered for calculating the self-aligning moment of the vehicle [7]. The bicycle model of the vehicle is shown in Fig.…”

Section: Self-aligning Moment Of Vehiclementioning

confidence: 99%

“…The authors proposed a PID controller for the steering wheel and sliding mode controller for the front wheels. The complete steer by wire system was modeled using bond graph method [7].Yandong et al proposed a method for controlling the steering wheel torque by torque ratio. This method converts the torque ratio into assisting torque by analyzing the characteristic relationship.…”

Section: Introductionmentioning

confidence: 99%

Neural Network Based Approach for the Generation of Road Feel in a Steer-By-Wire System

Jayachandran

Ashok

2016

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Abstract. Steer-by-wire is an advanced steering system which connects the steering wheel with the front wheel by using motors and sensors. Generating a variable road feel to the driver in a steer by wire system is an important task as there is no mechanical connection; it requires the development of suitable feedback algorithm for producing variable torque feedback in the steering wheel. In present work, Neural Network method is proposed for estimating the current to be supplied to the feedback motor using the vehicle dynamic parameters such as vertical displacement of front axle, self-aligning moment and front wheel angle as input parameters. A simulation study has been carried out for verifying the performance of the proposed method using the vehicle dynamic models available in the literature. It was tested for dry, wet and icy road profiles using the typical model parameters. The simulated vehicle dynamic parameters and estimated motor current values for the different road surfaces using neural network are presented. From the simulation results for the sinusoidal road surface and sinusoidal steering angle driver input, it is clear that the neural network based method is able to produce the varying road feel to the driver for the different road conditions.

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“…And their simulation experimental results show that, compared with the conventional fuzzy control, particle swarm optimization fuzzy control can improve the whole dynamic response of heavy truck EPS system efficiently, also good steering portability and handling stability is obtained. Other researchers used fuzzy control [6,7], variable structure control [8], LQR control [9,10], disturbance observer [11], sliding mode control [12,13], robust and H∞ control [14][15][16], optimization algorithm [17,18], friction compensation control [19], road feeling [20], and so on for vehicle steering system control. These research results are mostly for passenger cars.…”

Section: Introductionmentioning

confidence: 99%

Electric Power Steering System Control Strategy Based on Robust H∞ Control for Electric Forklift

Jiang

Xiao

2018

Mathematical Problems in Engineering

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The dynamic model of the Electric Power Steering (EPS) system for electric forklifts and the two-degree-of-freedom (2DOF) forklift models has been established. Based on the control target of electric forklift EPS, a generalized EPS control model with model perturbation and interference is established. The standard H∞control model of the EPS system is transformed, and the EPS generalized state equation of electric forklift is derived. The principle of robust control with genetic optimization is expounded, aiming at the parameters optimization of the weighted function of H∞control model, the constraint function of the genetic algorithm (GA) is constructed, and the robust controller of genetic optimization is derived. Taking the electric forklift TFC20 as the research object, according to the actual data on the forklift, the system model is established in MATLAB, and the effects of PID control, robust control, and genetic robust control are compared, the results show that the power steering characteristic of the robust control is better than the power steering characteristic of the PID control, and the stability of the forklift under the control of robust control is better. Also, the power steering characteristic of the H∞ controller with GA optimization is better than that of an unoptimized one, and its robustness is better, under external pavement interference, the following ability is stronger for the ideal current and the steering is more stable.

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Variable structure controller design for steer-by-wire system of a passenger car

Cited by 13 publications

References 4 publications

Improving Handling Stability Performance of Four-Wheel Steering Vehicle Based on the H2/H∞ Robust Control

Improving Handling Stability Performance of Four-Wheel Steering Vehicle Based on the H2/H∞ Robust Control

Neural Network Based Approach for the Generation of Road Feel in a Steer-By-Wire System

Electric Power Steering System Control Strategy Based on Robust H∞ Control for Electric Forklift

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