SYNERGETIC SYNTHESIS OF SLIDING MODE CONTROL FOR VEHICLE’S ACTIVE SUSPENSION SYSTEM

Abstract

This article discusses the problem of designing vehicle’s active suspension systems in which the actuator is not ideal and is a subject to the influence of hysteresis and dead zone. The main goal of this work is to synthesize a control system that reduces the influence of hysteresis and deadzone on the efficiency of the adaptive suspension system. System parameters like hysteresis require significant efforts to identify them and, moreover, can vary widely over the life cycle of the system. Thus, it is very difficult to take into account hysteresis in the synthesis of the control system, as well as the construction of observers. The solution to this problem is use of sliding control systems, which to a certain extent are robust to parametric and structural changes in the control object. Existing approaches to the synthesis of sliding control systems are based on a linear or linearized model of the control object. Thus, the effectiveness of such systems can vary significantly when the regulator operates as part of a real, non-linear control object. The proposed sliding mode control allows to reducing sensitivity of the system to disturbances due to imperfect actuator, and also takes into account the nonlinear structure of the control object. The efficiency of a closed system is investigated on a dynamic model built in Simulink package. The proposed controller is compared with an adaptive synergetic regulator. Road of class C (according to ISO 8608 classification) was selected as a disturbance. To investigate the effectiveness of the proposed control system, the following parameters are evaluated: weighted acceleration of the sprung mass; relative motion of suspension and tire reaction force. The RMS and maximum values are calculated for each parameter. The results of numerical simulations allow to conclude that the use of sliding control systems can improve the following adaptive suspension performance indicators: reduce the maximum value of the weighted acceleration of the sprung mass by more than two times and reduce the maximum load on the tire by more than 20 %.

Authors

  • A.S. Sinitsyn Joint Stock Company "Scientific Design Bureau of Computing Systems" (JSC SDB CS)

References

1. Hrovat D. Survey of advanced suspension developments and related optimal control applications,
Automatica, 1997, Vol. 33, No. 10, pp. 1781-1817.
2. Yagiz N., Hacioglu Y. Backstepping control of a vehicle with active suspensions, Contr. Eng.
Pract., 2008, Vol. 16, No. 12, pp 1457-1467.
3. Koch G., Spirk S., Pellegrini E., Pletschen N., Lohmann B. Experimental validation of a new
adaptive control approach for a hybrid suspension system, American Control Conference
2011, June 29-July 1, San Francisco, California, USA. San Francisco, 2011, pp. 4580-4585.
4. Zhao F., Ge S.S., Tu F., Qin Y., Dong M. Adaptive neural network control for active suspension
system with actuator saturation, IET Control Theory & Appl., 2016, Vol. 10, No. 14,
pp. 1696-1705.
5. Jue W., Jing Z. Model-free tracking control for vehicle active suspension systems, 34th Chinese
Control Conference (CCC), July 28-30, Hangzhou, China. Hangzhou, 2015, Vol. 10,
No. 14, pp. 1696-1705.
6. Deshpande V.S., Shendge P.D., Phadke S.B., Dual objective active suspension system based on a
novel nonlinear disturbance compensator, Veh. Syst. Dyn., 2016, Vol. 54, No. 9, pp. 1269-1290.
7. Hu C., Yao B., Wang Q. Adaptive robust precision motion control of systems with unknown
input dead-zones: a case study with comparative experiments, IEEE Trans. Ind. Electron.,
2016, Vol. 58, No. 6, pp. 2454-2464.
8. Ahmad N.J., Ebraheem H.K., Alnaser M.J., Alostath J.M. Adaptive control of a dc motor with
uncertain deadzone nonlinearity at the input, Control and Decision Conference (CCDC), Dec
12-15, Orlando, FL, USA. Orlando, 2011, pp. 4295-4299.
9. Tao G., Taware A. Control by Compensation of Nonlinearities // Control Systems, Robotics
and Automation, 2009, Vol. III, pp. 165-171.
10. Recker D., Kokotovic P., Rhode D., Winkelman J. Adaptive nonlinear control of systems containing
a deadzone, Proceedings of the 30th IEEE Conference on Decision and Control, Dec.
11-13, Brighton, England. Brighton, 1991, pp. 2111-2115.
11. Dong J., Mo B. The adaptive PID controller design for motor control system with backlash,
Fourth International Conference on Intelligent Control and Information Processing (ICICIP),
June 12-13, Beijing, China. Beijing, 2013, pp. 59-63.
12. Tao G., Kokotovic P.V. Adaptive control of plants with unknown dead-zones, IEEE Trans.
Automat. Contr., 1994, Vol. 39, No. 1, pp. 59-68.
13. Chang T., Yuan D., Hanek H. Matched feedforward/model reference control of a high precision
robot with dead-zone, IEEE Trans. Contr. Syst. Technol., 2008, Vol. 16, No. 1, pp. 94-102.
14. Danilin N.A., Shalashilin D.A. Hysteresis Modelling of Mechanical Systems at Nonstationary
Vibrations, Mathematical Problems in Engineering, 2018, Vol. 2018, pp. 1-15.
15. Solomon O. Some typical shapes of hysteretic loops using the bouc-wen model, Journal of
Information Systems & Operations Management, 2013, Vol. 7, No. 1, pp. 1-9.
16. Kolesnikov A.A. Sinergeticheskaya teoriya upravleniya [Synergetic control theory]. Moscow:
Energoatomizdat, 1994.
17. Tao G., Kokotovic P.V. Adaptive Control of Systems with Actuator and Sensor Nonlinearities.
NY.: John Wiley & Sons, Inc., 1996.
18. Pan H., Sun W., Jing X., Gao H., Yao J. Adaptive tracking control for active suspension systems
with non-ideal actuators, J. Sound Vib., 2017. Vol. 399, No. 1, pp. 2-20.
19. ISO-2631, Mechanical Vibration and Shock: Evaluation of Human Exposure to Whole-body
Vibration Part 1, General Requirements, ISO, Geneva.
20. Zuo L., Nayfeh S.A. Low order continuous-time filters for approximation of the ISO 2631-1
human vibration sensitivity weightings, J. Sound Vib., 2003, Vol. 265, No. 1, pp. 459-465.
21. Deshpande V.S., Shendge P.D., Phadke S.B. Nonlinear control for dual objective active suspension
systems, IEEE Trans. Intell. Transport. Syst., 2017, Vol. 18, No. 3, pp. 656-665.
22. Kolesnikov A.A., Veselov G.E., Popov A.N. i dr. Sinergeticheskie metody upravleniya
slozhnymi sistemami: Mekhanicheskie i elektromekhanicheskie sistemy [Synergetic control
methods of complex systems: Mechanical and Electromechanical systems], under the General
ed. of A.A. Kolesnikova. Moscow: Knizhnyy dom «LIBROKOM», 2013, 304 p.
23. Kolesnikov A.A., Veselov G.E. Sinergeticheskiy printsip ierarkhizatsii i analiticheskiy sintez
regulyatorov vzaimosvyazannykh elektromekhanicheskikh sistem [Synergetic principle of hierarchy
and analytical synthesis of regulators of interconnected Electromechanical systems], Izvestiya
YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2001, No. 5 (23), pp. 80-99.
24. ISO-8608, Mechanical Vibration-road Surface Profiles-reporting of Measured Data, ISO, Geneva.

Скачивания

Published:

2020-07-20

Issue:

Section:

SECTION II. COMPUTING AND INFORMATION AND CONTROL SYSTEMS

Keywords:

Active suspension, nonlinear control, adaptation, synergetic control theory, sliding mode control