Due to fast variation of desired variables in vehicle handling problem, design of an accurate applicable economic and considerably quick responsible controller for steering control of such systems has attracted much attention in the literature. The problem becomes more complicated, if the variation of road condition comes into play also. In this study, by combination of a simple PID and an optimized adaptive neural network controller, an arrangement for active front steering control of vehicles in different road frictions is proposed. A general PID controller is picked up and then optimized using the particle swarm optimization algorithm. After that, a neural network is added consecutively and trained by the outputs of PID controller and neural network toolbox of MATLAB software. The proposed controller fulfills both the applicability and efficiency due to dual use of PID and neural network controllers. Simulation results confirm the rightness of suggested controller in active steering control of vehicles even for unpredictable road friction.

Combination of particle swarm optimization algorithm and artificial neural network to propose an efficient controller for vehicle handling in uncertain road conditions

In this study, two adaptive neural network and neurofuzzy identification models are proposed to identify vehicle handling under uncertainties. These models are used to identify vehicle handling in ...

Comparison of neural network and neurofuzzy identification of vehicle handling under uncertainties

Vehicle stability control system has evolved significantly over the past three decades. Several control strategies have been implemented to enhance the vehicle stability control performance. However, most of these control strategies have not been focused on improving the transient response for vehicle yaw rate and sideslip angle tracking controller in the presence of uncertainties and disturbance. This paper is aimed at reviewing the proposed control algorithms based on their control objectives, different types of actuators required for the vehicle stability control system, advantages and disadvantages. According to this review, we derive that the advanced type of sliding mode control with non-singular fast terminal sliding surface has an ideal capacity to provide a fast transient response of yaw rate and sideslip tracking controllers under the presence of disturbances.

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Control strategies for improving ground vehicle stability: State-of-the-art review

Vehicle stability control (VSC) is one of important topics in vehicle dynamics and active automotive control. This research is focusing on vehicle stability control by active steering system that utilizes steering control method to improve stability of the vehicle. This stability control system is solely based on kinematic and dynamics motion of vehicle. The development of mathematical model of vehicle dynamic that includes body and tyre dynamics is one of the most important steps to make sure the result obtain is close as possible to actual system. In the other hand, an analysis of transient state is very crucial in control system performance where one of the objectives is to track reference signal as fast as possible with minimum overshoot, fast settling time, and without exceed nature of actuator saturation limit. Hence, in order to achieve this target, a robust and high performance of control algorithm is essential for vehicle stability control. In this research project report, a Composite Nonlinear Feedback (CNF) strategy is used to control yaw rate of vehicle through active steering. 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.

An active front steering control based on composite nonlinear feedback for vehicle yaw stability system

This paper studies and applied the composite nonlinear feedback (CNF) control technique for improving the transient performances of vehicle yaw rate response. In the active front steering control design and analysis, the linear bicycle model is used for controller design while the 7DOF nonlinear vehicle model is used as vehicle plant for simulation and controller evaluations. The vehicle handling test of the J-turn and single lane change maneuvers are implemented in computer simulations in order to evaluate the designed yaw rate tracking controller. The simulation results show that the CNF technique could improve the transient performances of yaw rate response and enhance the vehicle maneuverability.

Improving transient performances of vehicle yaw rate response using composite nonlinear feedback

In this paper, an Active Front Steering controller is designed to improve vehicle yaw stability based on fuzzy logic. The yaw rate error and its rate of change are applied to the controller as inputs, where the steering angle correction of the front wheels is the output. The performance of the proposed control system has been verified using a nonlinear eight degrees of freedom nonlinear vehicle model, and the simulation results illustrate considerable improvements in vehicle yaw stability is achieved for several maneuvers, especially in the tire linear region.

Jian Ma

Papers

An AFS control based on fuzzy logic for vehicle yaw stability