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Optimized Proportional Integral Derivative Controller of Vehicle Active Suspension System Using Genetic Algorithm
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 3, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Proportional integral derivative (PID) control method is an effective, easy in implementation and famous control technique applied in several engineering systems. Also, Genetic Algorithm (GA) is a suitable approach for optimum searching problems in science, industrial and engineering applications. This paper presents the usage of GA for determining the optimal PID controller gains and their implementation in the active quarter-vehicle suspension system to achieve good ride comfort and vehicle stability levels. The GA is applied to solve a combined multi-objective (CMO) problem to tune PID controller gains of vehicle active suspension system for the first time. The active vehicle suspension system is modeled mathematically as a two degree-of-freedom mechanical system and simulated using Matlab/Simulink software. The performance of the proposed suspension system controlled using the optimized PID GA is compared to both controlled system using the classical PID (C PID) controller and the passive suspension systems. Systems performance criteria are evaluated in both time and frequency domains, in order to quantify the success of the proposed suspension system. The theoretical results reveal that the proposed optimized PID GA controller of the active vehicle suspension provides a vital enhancement of ride comfort and vehicle stability levels.
CitationMetered, H., Abbas, W., and Emam, A., "Optimized Proportional Integral Derivative Controller of Vehicle Active Suspension System Using Genetic Algorithm," SAE Technical Paper 2018-01-1399, 2018, https://doi.org/10.4271/2018-01-1399.
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- Gad, J., Metered, H., Bassuiny, A., andAbdel Ghany, A.M., “Multi-objective genetic algorithm fractional-order PID controller for semi-active magnetorheologically damped seat suspension,” Journal of Vibration and Control, 23(8):1248-1266, 2017.
- Gad, S., Metered, H., Bassuiny, A., and Abdel Ghany, A.M., “Ride Comfort Enhancement of Heavy Vehicles using Magnetorheological Seat Suspension,” Int. J. of Heavy Vehicle Systems, 22(2):93-113, 2015.
- Yin, F., Wang, J., andGuo, C., “Design of PID Controllers Using Genetic Algorithms Approach for Low Damping Slow Response Plants,” In: L.N.i.C. Science, editor. Advances in Neural Networks. (Springer-Verlag, Berlin Heidelberg, 2004), 219-220.
- Metered, H., Elsawaf, A., Vampola, T., and Sika, Z., “Vibration Control of MR-Damped Vehicle Suspension System Using PID Controller Tuned by Particle Swarm Optimization,” SAE Int. J. Passeng. Cars - Mech. Syst., 8(2):426-435, 2015, doi:10.4271/2015-01-0622.
- Gillespie, T.D., “Fundamentals of Vehicle Dynamics,” SAE International, 1993, ISBN: 978-1-56091-199-9.
- Cao, J., Liu, H., Li, P., and Brown, D., “State of the Art in Vehicle Active Suspension Adaptive Control Systems Based on Intelligent Methodologies,” IEEE Transactions on Intelligent Transportation Systems, 9(3):392-405, 2008.
- Cao, J., Li, P., and Liu, H., “An Interval Fuzzy Controller for Vehicle Active Suspension Systems,” IEEE Transactions on Intelligent Transportation Systems, 11(4):885-895, 2010.
- Gao, H., Lam, J., and Wang, C., “Multi-Objective Control of Vehicle Active Suspension Systems via Load-Dependent Controllers,” Journal of Sound and Vibration, 290(3-5):654-675, 2006.
- Hrovat, D., “Survey of Advanced Suspension Developments and Related Optimal Control Applications,” Automatica, 33(10):1781-1817, 1997.
- Mohan, B., Modak, J.P., andPhadke, S.B., “Vibration Control of Vehicles Using Model Reference Adaptive Variable Structure Control,” Advances in Vibration Engineering, 2(4):343-361, 2003.
- Fialho, I. and Balas, J., “Road Adaptive Active Suspension Design Using Linear Parameter-Varying Gain-Scheduling,” IEEE Transactions on Control Systems Technology, 10(1):43-54, 2002.
- Rajamani, R. andHedrick, J., “Adaptive Observers for Active Automotive Suspensions: Theory and Experiment,” IEEE Transactions on Control Systems Technology, 3(1):86-93, 1995.
- Gao, H., Sun, W., andShi, P., “Robust sampled-data H∞ control for vehicle active suspension systems,” IEEE Transactions on Control Systems Technology, 18(1):238-245, 2010.
- Metered, H., “Application of Nonparametric Magnetorheological Damper Model in Vehicle Semi-active Suspension System,” SAE Int. J. Passeng. Cars - Mech. Syst., 5(1):715-726, 2012, doi:10.4271/2012-01-0977.
- Metered, H. andŠika, Z., “Vibration Control of Vehicle Active Suspension Using Sliding Mode Under Parameters Uncertainty,” Journal of Traffic and Logistics Engineering, 3(2):136-142, 2015.
- Vaijayanti, S.D., Mohan, B., Shendge, P.D., andPhadke, S.B., “Disturbance Observer Based Sliding Mode Control of Active Suspension Systems,” Journal of Sound and Vibration, 333(11):2281-2296, 2014.
- Emam, A.S., “Active Vibration Control of Automotive Suspension System using Fuzzy Logic Algorithm,” Int. J. of Vehicle Structures & Systems, 9(2):77-82, 2017.
- Emam, A.S., “Fuzzy Self Tuning of PID Controller for Active Suspension System,” Advances in Powertrains and Automotive, 1(1):34-41, 2015.
- Choi, S.B., Choi, Y.T., andPark, D.W., “A Sliding Mode Control of a Full-Car Electrorheological Suspension System via Hardware in-the-Loop Simulation,” Dynamic Systems, Measurement, and Control, 122:114-121, 2000.
- Michael, A.J. andMohammad, H.M., “PID Control: New Identification and Design Methods,” (London Limited, Springer-Verlag, 2005).
- Deb, K., “Genetic Algorithm-Based Optimum Vehicle Suspension Design Using Minimum Dynamic Pavement Load as a Design Criterion,” Sadhana, 24:293-315, 1999.
- Kumarl, A. andGupta, R., “Compare the Results of Tuning of PID Controller by Using PSO and GA Technique for AVR System,” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 2:2130-2138, 2013.
- Abbas, W., Abouelatta, O. B., El-Azab, M., andMegahed, A. A., “Application of genetic algorithms to the optimal design of vehicle’s driver-seat suspension model,” Proceedings of the World Congress on Engineering, Vol. II, June 30 - July 2, London, UK, 2010.
- Abbas, W., Abouelatta, O., El-Azab, M., Elsaidy, M. et al., “Optimization of Biodynamic Seated Human Models Using Genetic Algorithms,” SCIRP Journal of Engineering, 2:710-719, 2010.
- Abbas, W., Abouelatta, O., El-Azab, M., Elsaidy, M. et al., “Optimal Seat Suspension Design Using Genetic Algorithms,” Journal of Mechanics Engineering and Automation, 1:44-52, 2011.
- Abbas, W., Emam, A.S., Badran, S., Shebl, M., andAbouelatta, O.B., “Optimal Seat and Suspension Design for a Half-Car with Driver Model Using Genetic Algorithm,” Intelligent Control and Automation, 4:199-205, 2013.
- Lakshmi, T.P., Narayanan, K.R.S., Jayanthi, T., and SatyaMurty, S.A.V., “Simulation and Tuning of PID Controllers using Evolutionary Algorithms,” Int J of Information Technology and Computer Science, 11:50-57, 2012.
- Rajamani, R., “Vehicle Dynamics and Control,” (New York, Springer Science and Business Media, 2006).
- Choi, S.B. andKim, W.K., “Vibration Control of a Semi-active Suspension Featuring Electrorheological Fluid Dampers,” Journal of Sound and Vibration, 234:537-546, 2000.
- Fischer, D. andIsermann, R., “Mechatronic Semi-active and Active Vehicle Suspensions,” Control Engineering Practice, 12(11):1353-1367, 2004.
- Metered, H., “Modelling and Control of Magnetorheological Dampers for Vehicle Suspension Systems,” PhD Thesis, School of Mechanical, Aerospace and Civil Engineering, The University of Manchester: Manchester, UK, 2010.