الفهرس 
Acknowledgment
General IntroductionOnly 14 pages are availabe for public view
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Abstract
The main task of vehicle suspension is to provide passenger ride comfort, safe road handling together with an acceptable load capacity for a variety of road conditions and vehicle maneuvers. The majority of early vehicles up to now utilize passive suspension systems. These systems suffer a compromise between ride comfort, road handling and load capacity. Several studies have shown that this conflict can be eased by using active suspension systems instead of passive ones. In active suspension, the damper and spring system is interceded by an actuator force which adds energy to the system in order to suppress sprung mass oscillation. The actuator force can be controlled by various types of controllers to achieve the desired performance. The correct control strategy should reduce the displacement and acceleration of the sprung mass and provide adequate suspension deflection to maintain tires in contact with road and maximize load capacity. Thus, the improvement of vehicle active suspension systems via controller design has attracted more interest and become a promising subject of research and development in the last decade. In the present work, the performance of a vehicle active suspension system using different control strategies is investigated under different road disturbances. The tested control strategies are proportional integral derivative (PID), linear quadratic regulator (LQR), fuzzy logic control (FLC), genetic algorithm (GA) tuned PD, GA tuned FLC and supervised neural network controllers. A quarter vehicle model has been used to model suspension system of a passenger car. For PID, LQR and FLC, Different road profiles have been input to the modeled active suspension system. These road profiles are single rectangular pothole, single cosine bump, sine wave road profile, and an ISO class “A” road profile. Proposed system performance has been tested and evaluated at a vehicle speed of 60km/hr (16.66 m/s). However, for the ISO road profile, performance of proposed controllers is evaluated at three different vehicle speeds, namely 60, 90& 120 Km/hr (16.6, 25 & 33.3 m/s). Also, vehicle ride comfort, according to ISO 2631-1, road handling and suspension travel root mean square (RMS) are evaluated for each of these control strategies. For GA tuned PD, GA tuned FLC and supervised NN controllers, Their performance is evaluated and compared at different vehicle speeds from 20 to 130 km/hr (5.56 to 36.1 m/s) in steps of 10 km/hr (2.78 m/s). Also, their performance is evaluated under different classes of ISO road profiles. These are A, B, C &D class. Simulation results show that, active suspension systems perform better compared to passive ones. Also, active suspension implementing FLC control surpassed both PID and LQR controllers. And also, its performance is slightly affected by change of vehicle speed or road profile disturbance. Moreover, A supervised NN controller achieved better ride comfort, rattle space utilization and road handling. Also, it requires the lowest actuator force when implemented compared to GA tuned PD and GA tuned FLC. It showed the best performance at different vehicle speeds and different road profile classes.