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In this paper, a nonlinear semi-active vehicle suspension system using MR fluid dampers is investigated to enhance ride comfort and vehicle stability. Fuzzy logic and fuzzy self-tuning PID control techniques are applied as system controllers to compute desired front and rear damping forces in conjunction with a Signum function method damper controller to assess force track-ability of system controllers. The suggested fuzzy self-tuning PID operates fuzzy system as a PID gains tuner to mitigate the vehicle vibration levels and achieve excellent performance related to ride comfort and vehicle stability. The equations of motion of four-degrees-of-freedom semi-active half-vehicle suspension system incorporating MR dampers are derived and simulated using Matlab/Simulink software.

The number of speed humps (sleeping policemen) has seen a global increase in the last decade. This paper addresses the geometric requirements of these humps using Genetic Algorithms optimization techniques to control the speed, stability, and ride feel of the traversing vehicles. The interaction between road hump profile and the modeled vehicles (passenger and a two-axle truck) are studied with a dynamic model. The shape of the proposed profile is described by numbers of amplitudes of harmonic functions. The extreme acceleration of the drivers’ seats of the vehicles traversing the hump is set as multiobjective function for the optimization process, taking into consideration the road-holding ability represented by the tire lift-off speed. The results show that hump geometry can be improved while fulfilling the requirements of speed control and vehicle dynamic responses.

This paper is concerned with the analysis of the performance of actively suspended vehicles when the effects of the aerodynamics are considered. The investigation is wholly theoretical and treats a half vehicle model, active suspension, through simulation of running at different speeds on a random-profile road. Using classical control laws, which do not account for aerodynamic effects, it is shown that starting from a vehicle speed of 35 m/s, ride comfort and road holding parameters significantly deteriorate. A method is introduced to modify the control strategy so that these effects can be taken into consideration. Various forms of control laws are presented, and conclusions are drawn to specify the benefits that could be achieved from this modified control strategy.

A full vehicle of a preview control semi-active suspension system based on an interval type-2 fuzzy controller design using a magnetorheological (MR) damper to improve ride comfort is investigated in this paper. It is integrated with the force distribution system to obtain the optimal rate of road adhesion during braking and handling. The nonlinear suspension model is derived by considering vertical, pitch, and roll motions. The preview interval type-2 fuzzy technique is designed as a system controller, and it is attached with a Signum function method as a damper controller to turn on the voltage for the MR damper. This voltage is adjusted for each wheel based on the external excitation generated by road roughness in order to enhance ride comfort. To describe the effectiveness and adaptable responses of the preview controlled semi-active system, the performance is compared with both the passive and MR passive suspension systems during time and frequency domains.

This research aims to model and assess autonomous vehicle controller while including a four-wheel steering and longitudinal speed control. Such a modeling process simulates human driver behavior with consideration of real vehicle dynamics’ characteristics during standard maneuvers. However, a four-wheel steering control improves vehicle stability and maneuverability as well. A three-degree of freedom bicycle model, lateral deviation, yaw angle, and longitudinal speed is constructed to describe vehicle dynamics’ behavior. Moreover, a comprehensive traction model is implemented which includes an engine, automatic transmission, and non-linear magic formula tire model for simulation of vehicle longitudinal dynamics. A combination of proportional integral derivative (PID) longitudinal controller and fuzzy lateral controller are implemented simultaneously to track the desired vehicle path while minimizing lateral deviation and yaw angle errors.

Vehicle suspension is considered a vital system of modern automotive and necessary to offer an adequate level of ride comfort and roadholding. In the present paper, a fuzzy-based sliding surface (FBSS) controller is designed, as a system controller for the first time, for a semi-active vehicle suspension using a magnetorheological (MR) damper in order to minimize the transmitted unwanted vibrations to the passengers. Therefore, an ideal reference skyhook model is employed to construct the sliding surface, which is the input of fuzzy logic. MR damper is a semi-active device and is controlled indirectly using an external voltage source. So a neural-based damper controller is used to compute the applied voltage to the magnet coil of the MR damper in series with the FBSS system controller. The proposed semi-active controlled quarter-vehicle suspension using an MR damper is solved numerically by Matlab.

In this paper, a fuzzy-PID controller is applied in a half vehicle active suspension system to enhance vibration levels of vehicle chassis and passenger seat. The fuzzy-PID controller consists of fuzzy and PID connecting in a series manner, the fuzzy output is considered as the PID input. Genetic Algorithm (GA) is selected to tune controller parameters to obtain optimal values that minimize the objective function. The equations of motion of five-degrees-of-freedom active half-vehicle suspension system are derived and simulated using Matlab/Simulink software. Double bumps and random road excitations are used to study the performance of suspension systems including bounce and pitch motion. The performance of the active suspension system using optimized fuzzy-PID controller is compared with conventional passive to show the efficiency of the proposed active suspension system.

In order to achieve the high capability of the ride comfort and regulating the tire slip ratio, a preview of a nonlinear semi-active vibration control suspension system using a magnetorheological (MR) fluid damper is integrated with traction control in this paper. A controlled semi-active suspension system, which consists of the system controller and damper controller, was used to develop ride comfort, while the traction controller is utilized to reduce a generated slip between the vehicle speed and rotational rate of the tire. Both Fractional-Order Filtered Proportional-Integral-Derivative (P¯IλDμ) and Fuzzy Logic connected either series or parallel with P¯IλDμ are designed as various methodologies of a system controller to generate optimal tracking of the desired damping force. The signum function method is modified as a damper controller to calculate an applied input voltage to the MR damper coil based on both preview signals and the desired damping force tracking.

1 Rear wheel drive vehicles have a long driveline using a propeller shaft with two universal joints. Consequently, in this design usage of universal joints within vehicle driveline is inevitable. However, the angularity of the driveshaft resulting from vertical oscillations of the rear axle causes many torsional and bending fluctuations of the driveline. Unfortunately, most of the previously published research work in this area assume the propeller inclination angle is constant under all operating conditions. As a matter of fact, this assumption is not accurate due to the vehicle body attitudes either in pitch or bounce motions. Where the vehicle vibration due to the suspension flexibility, either passive or active type, exists.

Proportional-integral-derivative (PID) controller is effective, popular and cost effective for a lot of scientific and engineering applications. In this paper, PID and fuzzy-self-tuning PID (FSTPID) controllers are applied to improve the performance of an active seat suspension system to enhance the pregnant woman comfort. The equations of motion of thirteen-degrees-of-freedom (13-DOF) active seat suspension system incorporating pregnant woman body model are derived and simulated. PID gains are tuned and estimated using genetic algorithm (GA) to formulate GA PID controller. In FSTPID, fuzzy logic technique is used to tune PID controller gains by selecting appropriate fuzzy rules using Matlab/Simulink software. Both controlled active seat suspension systems are compared with a passive seat suspension. Suspension performance is evaluated under bump and random road excitations in order to verify the success of the proposed controllers.

In this paper, semi-active MR main suspension system based on system controller design to minimize pitch motion linked with MR-controlled seat suspension by considering driver’s biodynamics is investigated. According to a fixed footprint tire model, the transmitted tire force is determined. The linear-quadratic Gaussian (LQG) system controller is able to enhance ride comfort by adjusting damping forces based on an evaluation of body vibration from the dynamic responses. The controlled damping forces are tracked by the signum function controllers to evaluate the supply voltages for the front and rear MR dampers. Based on the sprung mass acceleration level and its derivative as the inputs, the optimal type-2 (T-2) fuzzy seat system controller is designed to regulate the controlled seat MR damper force.

The purpose of this paper is to investigate the efficiency of a quarter car semi-active suspension system with the state-derivative feedback controller using the Bouc-Wen model for magneto-rheological fluids. The magnetorheological (MR) dampers are classified as adaptive devices because of their characteristics can be easily modified by applying a controlled voltage signal. Semi-active suspension with MR dampers combines the benefits of active and passive suspension systems. The dynamic system captures the basic performance of the suspension, including seat travel distance, body acceleration, passenger acceleration, suspension travel distance, dynamic tire deflection and damping force. With minimal reliance on the use of sensors, the investigation aims to improve ride comfort and vehicle stability. In this study, the state derivative feedback controller and Genetic algorithm (GA) is utilized to improve the performance of semi-active suspension system.

Proportional integral derivative (PID) control technique is a famous and cost-effective control strategy, in real implementation, applied in various engineering applications. Also, the ant colony optimization (ACO) algorithm is extensively applied in various industrial problems. This paper addresses the usage of the ACO algorithm to tune the PID controller gains for a semi-active heavy vehicle suspension system integrated with cabin and seat. The magnetorheological (MR) damper is used in main suspension as a semi-active device to enhance the ride comfort and vehicle stability. The proposed semi-active suspension consists of a system controller that calculate the desired damping force using a PID controller tuned using ACO, and a continuous state damper controller that predict the input voltage that is required to track the desired damping force.

The study investigates the ride comfort of a rail vehicle with semi-active suspension control and its effect on train vertical dynamics. The Harmony Search algorithm optimizes the gains of a proportional integral derivative (PID) controller using the self-adaptive global best harmony search method (SGHS) due to its effectiveness in reducing the tuning time and offering the least objective function value. Magnetorheological (MR) dampers are highly valuable semi-active devices for vibration control applications rather than active actuators in terms of reliability and implementation cost. A quarter-rail vehicle model consisting of six degrees of freedom (6-DOF) is simulated using MATLAB/Simulink software to evaluate the proposed controller's effectiveness. The simulated results show that the optimized PID significantly improves ride comfort compared to passive.