Zhang Meng-hua, Liu Qiang, Chen Ji-yang, et al. A Saturated PD-SMC Tracking Method for Active Suspension Systems by Employing Beneficial Nonlinearities[J]. 2022, 39(5): 29-37.
Zhang Meng-hua, Liu Qiang, Chen Ji-yang, et al. A Saturated PD-SMC Tracking Method for Active Suspension Systems by Employing Beneficial Nonlinearities[J]. 2022, 39(5): 29-37.DOI: 10.12052/gdutxb.220049.
A Saturated PD-SMC Tracking Method for Active Suspension Systems by Employing Beneficial Nonlinearities
Through purposely employing beneficial nonlinear stiffness and damping with a constructed bioinspired reference model
a novel saturated PD with sliding mode control method
(referred to as saturated PD-SMC method)
is designed for active suspension systems under saturated control input constraints. The designed control method has several distinct benefits
including the simple structure of PD control method
strong robustness of SMC method with respect to model uncertainties and external disturbances
without requirements of exact system parameters associated with traditional SMC method
as well as taking input constraints into consideration. In the designed control method
the PD part is employed to stabilize the controlled active suspension system
the SMC part is applied to provide strong robustness
and the saturation functions are introduced to prevent the violation of control input constraints. The corresponding stability analysis is provided by Lyapunov techniques. Several experimental results show that
the designed control method dramatically improves transient performance in comparison with some existing methods
including decreasing control energy by 30.65% and improving ride comfort
which can achieve a satisfactory trade-off between costs and results for suspension system control.
关键词
Keywords
references
KUMAR V, RANA K P S, KUMAR J, et al . Self-tuned robust fractional order fuzzy PD controller for uncertain and nonlinear active suspension system [J ] . Neural Computing and Applications, 2018, 30(6): 1827-1843.
SU Y, ZHENG C. Single saturated PD control for asymptotic attitude stabilization of spacecraft [J]. IET Control Theory and Applications, 2020, 14(19): 3338-3343.
ZHANG Y, KIM D G, ZHAO Y, et al . PD control of a manipulator with gravity and inertia compensation using an RBF neural network [J ] . International Journal of Control, Automation and Systems, 2020, 18(12): 3083-3092.
TENG L, GULL M A, BAI S P. PD-based fuzzy sliding mode control of a wheelchair exoskeleton robot [J]. IEEE/ASME Transactions on Mechatronics, 2020, 25(5): 2546-2555.
KOLATHAYA S. Local stability of PD controlled bipedal walking robots[J]. Automatica, 2020, 114: 108841
ZHENG C, SU Y, MERCORELLI P. A simple nonlinear PD control for faster and high-precision positioning of servomechanisms with actuator saturation [J]. Mechanical Systems and Signal Processing, 2019, 121: 215-226.
DESHPANDE V S, MOHAN B, SHENDGE P D, et al . Disturbance observer based sliding mode control of active suspension systems [J ] . Journal of Sound and Vibration, 2014, 333: 2281-2296.
CHEN H, LIU Y, LIU L, et al. Anti-saturation-based adaptive sliding-mode control for active suspension systems with time-varying vertical displacement and speed constraints[J ] . IEEE Transactions on Cybernetics, in press, doi: 10.1109/TCYB.2020.3042613 .
RAJENDIRAN S, LAKSHMI P. Performance analysis of fractional order terminal SMC for the half car model with random road input [J]. Journal of Vibration Engineering and Technologies, 2020, 8(4): 687-597.
SONG J, NIU Y, ZOU Y. A parameter-dependent sliding mode approach for finite-time bounded control of uncertain stochastic systems with randomly varying actuator faults and its application to parallel active suspension system [J]. IEEE Transactions on Industrial Electronics, 2018, 65(10): 8124-8132.
LI J, JING X, LI Z. Fuzzy adaptive control for nonlinear suspension systems based on a bioinspired reference model with deliberately designed nonlinear damping [J]. IEEE Transactions on Industrial Electronics, 2019, 66(11): 8713-8723.
ZHANG M, JING X. Switching logic-based saturated tracking control for active suspension systems based on disturbance observer and bioinspired X-dynamics [J]. Mechanical Systems and Signal Processing, 2021, 155: 107611.
ZHANG M, JING X, WANG G. Bioinspired nonlinear dynamics-based adaptive neural network control for vehicle suspension systems with uncertain/unknown dynamics and input delay[J ] . IEEE Transactions on Industrial Electronics, in press, doi: 10.1109/TIE.2020.3040667 .
SUN N, FANG Y, CHEN H. Tracking control for magnetic-suspension systems with online unknown mass identification [J]. Control Engineering Practice, 2017, 58: 242-253.
PAN H, SUN W, GAO H, et al . Nonlinear tracking control based on extended state observer for vehicle active suspensions with performance constraints [J ] . M echatronics, 2015, 30: 363-370.