Abstract:The variable universe fuzzy proportionalintegraldifferential(PID) control method based on genetic algorithm (GA) was proposed for the quartercar active suspension system. Based on the establishment of the active suspension system model, the fuzzy PID controller was designed by introducing the idea of variable universe. To further improve the vibration attenuation effect of the controller, GA was employed to optimize the parameters in description functions of the expansion factor for variable universe. The simulation results show that compared with PID, fuzzy PID and unoptimized variable universe fuzzy PID control methods, the GAbased variable universe fuzzy PID method has superiority for reducing the vertical acceleration of the vehicle body and improving the ride comfort. The proposed control method has strong robustness against uncertainties of sprung mass and vehicle speed.
孙维超.汽车悬架系统的主动振动控制[D].哈尔滨:哈尔滨工业大学,2013. [2]XUE W P, LI K J, CHEN Q, et al. Mixed FTS/H∞ control of vehicle active suspensions with shock road disturbance[J]. Vehicle System Dynamics, 2019, 57(6): 841-854.
[3]
MAJDOUB K E, GIRI F, CHAOUI F Z. Adaptive backstepping control design for semi-active suspension of half- vehicle with magnetorheological damper[J]. IEEE/CAA Journal of Automatica Sinica, 2021, 8(3): 582-596. [4]FAZELI S, JAHED-MOTLAGH M R,MOAREFIANPUR A. An adaptive approach for vehicle suspension system control in presence of uncertainty and unknown actuator time delay[J]. Systems Science and Control Engineering, 2021, 9(1): 117-126. [5]CHEN H, GUO K H. Constrained H∞ control of active suspensions: an LMI approach[J]. IEEE Transactions on Control Systems Technology, 2005, 13(3): 412-421.
[6]
GUAN Y P, HAN Q L, YAO H J, et al. Robust event-triggered H∞controller design for vehicle active suspension systems[J]. Nonlinear Dynamics, 2018, 94(1): 627-638.
[7]
WEN S P, CHEN M Z Q, ZENG Z G, et al. Fuzzy control for uncertain vehicle active suspension systems via dynamic sliding-mode approach[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(1): 24-32.
[8]
LI H Y, LIU H H, GAO H J, et al. Reliable fuzzy control for active suspension systems with actuator delay and fault[J]. IEEE Transactions on Fuzzy Systems, 2012, 20(2): 342-357.
[9]
MIN X, LI Y M, TONG S C. Adaptive fuzzy output feedback inverse optimal control for vehicle active suspension systems[J]. Neurocomputing, 2020, 403: 257-267. [10]MUSTAFA G I Y, WANG H P, TIAN Y. Vibration control of an active vehicle suspension systems using optimized model-free fuzzy logic controller based on time delay estimation[J]. Advances in Engineering Software, 2019, 127: 141-149.
[11]
GHAFOURI M, DANESHMAND S. Design and evaluation of an optimal fuzzy PID controller for an active vehicle suspension system[J]. Transactions of Famena, 2017, 41(2): 29-44.
[12]
李洪兴.变论域自适应模糊控制器[J].中国科学 (E辑),1999,29(1):32-42. LI H X. Variable universe adaptive fuzzy controller[J]. Science in China (Series E), 1999, 29(1): 32-42. (in Chinese)
[13]
庞辉,刘凡,王延.某越野汽车磁流变半主动悬架变论域模糊控制[J].振动、测试与诊断,2019,39(2):311-319. PANG H, LIU F, WANG Y. Variable universe fuzzy control stratategy for magneto-rheological semi-active supension of cross country car[J]. Journal of Vibration, Measurement & Diagnosis, 2019, 39(2): 311-319. (in Chinese)
[14]
姚建峰,卢军,郑一力,等.基于变论域模糊控制算法的树木年轮测量仪直流电机转速控制[J].农业工程学报,2019,35(14):57-63. YAO J F, LU J, ZHENG Y L, et al. DC motor speed control of annual-ring measuring instrument based on variable universe fuzzy control algorithm[J]. Transactions of the Chinese Society of Agricultural Engineering, 2019, 35(14): 57-63. (in Chinese)
[15]
LI M X, YANG G L, LI X Q, et al. Variable universe fuzzy control of adjustable hydraulic torque converter based on multi-population genetic algorithm[J]. IEEE Access, 2019, 7: 29236-29244.