Adaptive soft computing strategy for ride quality improvement with anti-lock braking system

The paper analyzes vibrations effect on the ride quality of the car occupant at the driver and passenger seats along with Anti-lock Braking Sytem (ABS). Nine degrees of freedom (FoD) full-car active suspension and ABS models are used in the analysis. The vertical vibrations effect on the driver and passenger comfort is evaluated according to the set criteria defined in the ISO 2631-1 of 1997 standard for whole body vibrations. ABS analysis is based on the slip ratio control to avoid wheel lock and slip. Coordination of the active suspension and ABS is carried out. A modified adaptive NeuroFuzzy Takagi Sugeno Kang (NFTSK) control algorithm is developed for ride comfort improvement. Performance of the advanced adaptive control strategy is validated against the Gaussian random external road profile and results are compared with passive control and for further performance validation, results are compared with the indices defined by the international standard. Simulations are performed using Matlab Simulink software.

[1]  D G Wilder,et al.  The response of the seated human to sinusoidal vibration and impact. , 1987, Journal of biomechanical engineering.

[2]  Laiq Khan,et al.  Comparative Analysis of Adaptive NeuroFuzzy Control Techniques for Full Car Active Suspension System , 2014 .

[3]  Honghai Liu,et al.  State of the Art in Vehicle Active Suspension Adaptive Control Systems Based on Intelligent Methodologies , 2008, IEEE Transactions on Intelligent Transportation Systems.

[4]  D. Hrovat,et al.  Survey of Advanced Suspension Developments and Related Optimal Control Applications, , 1997, Autom..

[5]  Okyay Kaynak,et al.  A Dynamic Method to Forecast the Wheel Slip for Antilock Braking System and Its Experimental Evaluation , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[6]  Nurkan Yagiz,et al.  Fuzzy Sliding-Mode Control of Active Suspensions , 2008, IEEE Transactions on Industrial Electronics.

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

[8]  Laiq Khan,et al.  NeuroFuzzy Adaptive Control for Full-Car Nonlinear Active Suspension with Onboard Antilock Braking System , 2015 .

[9]  Karel Jelen,et al.  Mechanical reaction of the frontal abdominal wall to the impact load during gravidity. , 2003, Neuro endocrinology letters.

[10]  Sahin Yildirim,et al.  Vibration control of vehicle active suspension system using a new robust neural network control system , 2009, Simul. Model. Pract. Theory.

[11]  Hong Chen,et al.  Multiobjective output-feedback suspension control on a half-car model , 2003, Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003..

[12]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[13]  H Broman,et al.  Mounting of the transducers in measurement of segmental motion of the spine. , 1986, Journal of biomechanics.

[14]  L. Zuo,et al.  Low order continuous-time filters for approximation of the ISO 2631-1 human vibration sensitivity weightings , 2003 .

[15]  Xavier Moreau,et al.  A COOPERATIVE CONTROL FOR CAR SUSPENSION AND BRAKE SYSTEMS , 2002 .

[16]  P. E. Uys,et al.  The ride comfort vs. handling compromise for off-road vehicles , 2007 .

[17]  Rahmi Guclu.  Active Control of Seat Vibrations of a Vehicle Model Using Various Suspension Alternatives , 2003 .

[18]  Honghai Liu,et al.  Adaptive Sliding-Mode Control for Nonlinear Active Suspension Vehicle Systems Using T–S Fuzzy Approach , 2013, IEEE Transactions on Industrial Electronics.