LQR Tuning by Particle Swarm Optimization of Full Car Suspension System

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    This paper attempts to examine the potential value in showing the performance of Particle Swarm Optimization (PSO) in order to produce diagonal components of matrix Q, R. The linear model was used in this system, because it has ability to describe all basic performance that exist in full car vehicle suspension system such as roll, pitch, body sprung and each wheel vertical movement. Performance of suspension system measured by range of acceleration arise in automobile body. Drive handling and comfort is an opposite condition. Balancing condition of both define quality of control strategy of suspension system. The disturbances are applied to all tires in testing scenario of applied control algorithm. The simulation result shown better performance of LQR tuning by PSO than passive and LQR without tuning system.


  • Keywords


    Car, Suspension System, Optimization, Modeling

  • References


      [1] Aly, A.A. and F.A. Salem, Vehicle suspension systems control: A review. International journal of control, automation and systems, 2013. 2(2): p. 46-54.

      [2] Zulkarnain, N., H. Zamzuri, and S. Mazlan, Ride and handling analysis for an active anti-roll bar: case study on composite nonlinear control strategy. International Journal of Automotive and Mechanical Engineering, 2014. 10: p. 2122.

      [3] Ismail, M.F., et al. A control performance of linear model and the MacPherson model for active suspension system using composite nonlinear feedback. in 2012 IEEE International Conference on Control System, Computing and Engineering. 2012.

      [4] Ismail, M.F., et al. A reduce chattering problem using composite nonlinear feedback and proportional integral sliding mode control. in 2015 10th Asian Control Conference (ASCC). 2015.

      [5] Fallah, M., R. Bhat, and W. Xie, New model and simulation of Macpherson suspension system for ride control applications. Vehicle System Dynamics, 2009. 47(2): p. 195-220.

      [6] Kruczek, A. and A. Stribrsky. A full-car model for active suspension - some practical aspects. in Mechatronics, 2004. ICM '04. Proceedings of the IEEE International Conference on. 2004.

      [7] Esmailzadeh, E. and F. Fahimi, Optimal adaptive active suspensions for a full car model. Vehicle System Dynamics, 1997. 27(2): p. 89-107.

      [8] Choi, S., Y.T. Choi, and D. Park, A sliding mode control of a full-car electrorheological suspension system via hardware in-the-loop simulation. Journal of Dynamic Systems, Measurement, and Control, 2000. 122(1): p. 114-121.

      [9] Du, H. and N. Zhang, Fuzzy Control for Nonlinear Uncertain Electrohydraulic Active Suspensions With Input Constraint. IEEE Transactions on Fuzzy Systems, 2009. 17(2): p. 343-356.

      [10] Darus, R. and Y.M. Sam. Modeling and control active suspension system for a full car model. in 2009 5th International Colloquium on Signal Processing & Its Applications. 2009.

      [11] Sandhu, F., H. Selamat, and Y.M.D. Sam. Linear quadratic regulator and skyhook application in semiactive MR damper full car model. in 2015 10th Asian Control Conference (ASCC). 2015.

      [12] Koch, G. and T. Kloiber, Driving state adaptive control of an active vehicle suspension system. IEEE Transactions on Control Systems Technology, 2014. 22(1): p. 44-57.

      [13] Kumar, E.V., G.S. Raaja, and J. Jerome, Adaptive PSO for optimal LQR tracking control of 2 DoF laboratory helicopter. Applied Soft Computing, 2016. 41: p. 77-90.

      [14] Hassan, R., et al. A comparison of particle swarm optimization and the genetic algorithm. in 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. 2005.

      [15] Valle, Y.d., et al., Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems. IEEE Transactions on Evolutionary Computation, 2008. 12(2): p. 171-195.


 

View

Download

Article ID: 13479
 
DOI: 10.14419/ijet.v7i2.13.13479




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.