Emam et al. 2018. Int. J. Vehicle Structures & Systems, 10(4), 300-306 International Journal of Vehicle Structures & Systems Available online at www.maftree.org/eja ISSN: 0975-3060 (Print), 0975-3540 (Online) doi: 10.4273/ijvss.10.4.15 © 2018. MechAero Foundation for Technical Research & Education Excellence 300 Optimized Fractional-Order Proportional Integral Derivative Controller for Active Vehicle Suspension System Performance Enhancement A.S. Emam a,b , H. Metered a,c and A.M. Abdel Ghany d a Automotive & Tractors Engineering Dept., Faculty of Engg., Mataria, Helwan University, Cairo, Egypt b Corresponding Author, Email: ashrafgalab71@gmail.com c Email: hassan.metered@yahoo.com d Electrical Power & Machine Dept., Faculty of Engg., Helwan, Helwan University, Cairo, Egypt Email: ghayghany@hotmail.com ABSTRACT: In this paper, an optimal Fractional Order Proportional Integral Derivative (FOPID) controller is applied in vehicle active suspension system to improve the ride comfort and vehicle stability without consideration of the actuator. The optimal values of the five gains of FOPID controller to minimize the objective function are tuned using a Multi- Objective Genetic Algorithm (MOGA). A half vehicle suspension system is modelled mathematically as 6 degrees-of- freedom mechanical system and then simulated using Matlab/Simulink software. The performance of the active suspension with FOPID controller is compared with passive suspension system under bump road excitation to show the efficiency of the proposed controller. The simulation results show that the active suspension system using the FOPID controller can offer a significant enhancement of ride comfort and vehicle stability. KEYWORDS: Half vehicle active suspension; Fractional order PID controller; Multi-objective genetic algorithm; Ride comfort CITATION: A.S. Emam, H. Metered and A.M. Abdel Ghany. 2018. Optimized Fractional-Order Proportional Integral Derivative Controller for Active Vehicle Suspension System Performance Enhancement, Int. J. Vehicle Structures & Systems, 10(4), 300-306. doi:10.4273/ijvss.10.4.15. 1. Introduction Active and semi-active suspensions have been widely investigated during past few decades and a lot of control strategies have been applied. Suspension system is one of the most essential components of vehicle which plays a vital role related to ride comfort, vehicle stability and vehicle chassis altitude. The main purposes of suspension systems are to isolate the vehicle body from road surface irregularities to maximize passenger comfort and maintain sufficient continuous road tyre- contact to grant vehicle stability [1]. Actually, it is challenging issue for suspension system to simultaneously improve all performance criteria using a simple control technique. So that, the design of active or semi-active suspension has trade-offs between comfort and stability which the controller has to solve [2-3]. This trade-offs can be solved by the integration between simple or complicated control techniques and optimization algorithms to minimize good objective functions related to suspension performance criteria measured by few sensors to feedback the controller with appropriate inputs to compute the optimum actuator force [4-5]. There are three main categories of suspension systems; passive, semi-active, and active suspension. In passive suspension, elastic and damping characteristics of springs and dampers remain constant and have performance limitations over working frequency range. Active suspension systems are more changeable, efficient and effective in enhancing suspension performance than passive systems and semi-active as well. In active vehicle suspensions, the external road excitation is dissipated by the generation of a control force based on the vehicle response via a moveable actuator by an external energy source [6-8]. Active suspensions are usually consists of an actuator (force source), sensors, and a controller. The actuation force is calculated dynamically as a function of measured suspension performance criteria. A wide range of control strategies have been applied to active vehicle suspensions to investigate the trade-offs between comfort and stability. A full state feedback controller of active vehicle suspension was applied in [5] to study the effects of representation of the road surface as integrated or filtered white noise, cross-correlation between left and right track excitations and wheelbase time delay between front and rear inputs in deriving the control laws. Proportional-integral sliding mode controller was employed as a robust control approach to control the unwanted vibration of active suspension [9]. A simple adaptive feedback-linearization approach was applied for nonlinear vehicle suspension system which is excited by unknown road surface profiles. An extended observer was used to approximate the nonlinear effects. Based on the approximation, the effects of the nonlinear suspension are avoided [10]. Linear quadratic optimal controller and conventional acceleration dependent