Robust control of low-cost actuator for automotive active front steering application

Namuduri, Chandra; Gopalakrishnan, S.; Murty, B.V.; Bolio, R.; Feller, Ross

doi:10.1109/ecce.2009.5316063

Cited by 3 publications

(4 citation statements)

References 9 publications

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“…Besides, it also can reduce the disturbances happened on the curvature which increases linearly respect to time [12]. This conventional PID control also can overcome precision when the angle error too large [13]. Rather than using PID controller, there also have many methods for controlling the steering [14].…”

Section: Introductionmentioning

confidence: 99%

Improving steering convergence in autonomous vehicle steering control

Mohamad¹,

Zaman²,

Ruslan³

2019

IJEECS

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<p>Steering control is a critical design element in autonomous vehicle development since it will determine whether the vehicle can navigate safely or not. For the prototype of UiTM Autonomous Vehicle 0 (UiTM AV0), Vexta motor is used to control the steering whereas Pulse Width Modulation (PWM) signal is responsible to drive the motor. However, by using PWM signal it is difficult to converge to the desired steering angle and furthermore time taken for steering angle to converge is much longer. Thus, Proportional Integral Derivative (PID) has been introduced in this autonomous vehicle steering controller to improve the convergence of the steering. Meanwhile a microcontroller was used to control the Vexta Motor direction and perform the calculation of the desired steering angle. Simulation results showed PID controller showed better time taken and preicison of successful convergence of the desired steering angle compared to the PWM controller. Analysis results showed that PID controller significantly reduce the overshooting of steering angle and significantly improve the time taken for convergence by up to 37 seconds faster than PWM controller in UiTM AV0.</p>

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Section: Introductionmentioning

confidence: 99%

Improving steering convergence in autonomous vehicle steering control

Mohamad¹,

Zaman²,

Ruslan³

2019

IJEECS

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“…Vehicle stability implementation by active steering control can be seen in many research papers, mostly by Active Front Steering (AFS) ) [1][2][3][4][5]. This is an effective way to ensuring stable cornering at moderate levels by driver commanded steering.…”

Section: Introductionmentioning

confidence: 99%

“…There are many control method proposed in designing of active front steering for vehicle stability such as by Quantitative Feedback Theory (QFT) [1], Adaptive Nonlinear Control [2], Mu Control Theory [3], PID [4], Fuzzy Logic [5], and Predictive Control (MPC) [8]. However, so far there are no research works for Composite Nonlinear Feedback (CNF) technique applied in vehicle stability.…”

Section: Introductionmentioning

confidence: 99%

Composite Nonlinear Feedback for Vehicle Active Front Steering

Hasan

Sam

Peng

et al. 2014

AMM

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In this paper, Composite Nonlinear Feedback (CNF) is applied on Active Front Steering (AFS) system for vehicle yaw stability control in order to have an excellent transient response performance. The control method, which has linear and nonlinear parts that work concurrently capable to track reference signal very fast with minimum overshoot, fast settling time, and without exceed nature of actuator saturation limit. Beside, modelling of 7 degree of freedom for typical passenger car with magic formula to represent tyre nonlinearity behaviour is also presented to simulate controlled vehicle as close as possible with a real situation. An extensive computer simulation is performed with considering a various profile of cornering manoeuvres with external disturbance to evaluate its performance in different scenarios. The performance of the proposed controller is compared to conventional Proportional Integration and Derivative (PID) for effectiveness analysis.

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“…It controls the steer angle of front inner and outer wheels independently to equalize the tire workload of two wheels. Namuduri et al proposed a control methodology developed to make a low-cost brushless permanent magnet motor drive (BLDC) suitable for the AFS application [6]. They designed a simulation model and used a conventional PID controller to achieve smooth operation of the AFS actuator and to prevent unwanted vibration at the steering wheel.…”

Section: Introductionmentioning

confidence: 99%

Design and Comparison of AFS Controllers with PID, Fuzzy-Logic, and Sliding-Mode Controllers

Song

2013

Advances in Mechanical Engineering

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Three active front-steering (AFS) controllers were developed to enhance the lateral stability of a vehicle. They were designed using proportional-integral-derivative (PID), fuzzy-logic, and sliding-mode control methods. The controllers were compared under several driving and road conditions with and without the application of braking force. A 14-degree-of-freedom vehicle model, a sliding-mode antilock brake system (ABS) controller, and a driver model were also employed to test the controllers. The results show that the three AFS controllers allowed the yaw rate to follow the reference yaw rate very well, and consequently the lateral stability improved. On a split-road, the controllers forced the vehicle to proceed straight ahead. The results also verify that the driver model can sufficiently control the vehicle to allow it to follow a desired path.

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Robust control of low-cost actuator for automotive active front steering application

Cited by 3 publications

References 9 publications

Improving steering convergence in autonomous vehicle steering control

Improving steering convergence in autonomous vehicle steering control

Composite Nonlinear Feedback for Vehicle Active Front Steering

Design and Comparison of AFS Controllers with PID, Fuzzy-Logic, and Sliding-Mode Controllers

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