汽车悬架系统的有限频域控制与采样控制
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摘要
由于和汽车的整体性能密切相关,汽车主动悬架系统一直是近年来的研究热点。本文针对汽车主动悬架系统控制中的两个热点问题――有限频域控制问题和数字采样控制问题进行了研究,提出了相应的控制器设计方法。
在有限频域H∞控制中,有别于现有的汽车悬架系统H∞控制方法在全频域下进行扰动衰减,本文的控制器设计方法可以实现在有限频域下的扰动抑制,使振动在人体所敏感的频率范围内被最大程度衰减。通过使用广义Kalman-Yakubovich-Popov引理,从扰动到控制输出的H∞范数在关心的频域范围内被最小化,进而改善驾驶舒适度。同全频方法相比较,有限频域方法在特定的频域内可以更加有效的进行控制,与此同时,悬架设计中的一些必要的时域约束也都可以得到保证。
状态反馈控制可以很好的对系统实现控制,结合广义KYP引理,本文首先给出了有限频域下的状态反馈控制器设计方法,针对汽车悬架系统的有限频域特性进行了H∞控制。状态反馈控制是以所有的状态变量均是可测量为前提的,这在实际中往往不容易达到,为了适应实际情况,本文针对状态的不完全可测量情况又提出了有限频域下的动态输出反馈控制器设计方法,并借用四分之一主动悬架系统模型,分别了对状态反馈闭环系统和输出反馈闭环系统进行时域和频域的仿真验证,仿真结果验证了控制器设计的有效性。
数字采样控制问题是汽车悬架系统控制中的另外一个难点问题,它的控制难点在于系统中同时包含连续时间信号和离散时间信号,传统的控制方法往往十分受限。本文通过使用一种输入时滞的方法,将采样悬架系统转化为带有时滞的连续时间系统,这种转化包含有不可导的时变时滞,最后,控制器设计被转化为一个带有线性矩阵不等式(LMI)约束的凸优化问题进行求解,为了满足车辆行驶中的参量变化,我们进一步设计了鲁棒控制器。仿真结果验证了控制器设计的有效性。
Vehicle active suspensions have been a hot research topic for many years due totheir important role in vehicle performance. In this paper, two hot issues of vehicleactive suspension system are considered, that is, finite frequency control and sampled-data control, and the corresponding controller design method is given, respectively.
Different from the existing H∞control methods, which conduct disturbance at-tenuation within the entire frequency domain, this paper addresses the problem of H∞control for active vehicle suspension systems in finite frequency domain. By usingthe generalized Kalman-Yakubovich-Popov (KYP) lemma, the H∞norm from the dis-turbance to the controlled output is decreased in specific frequency band to improvethe ride comfort. Compared with the entire frequency approach, the finite frequencyapproach suppresses the vibration more effectively for the concerned frequency range.In addition, the time-domain constraints are guaranteed in the controller design.
State feedback control is a useful control strategy in modern control system.Combined with the generalized KYP lemma, a state feedback H∞controller is de-signed firstly, in order to meet the finite frequency characteristic of the vehicle sus-pension system. State feedback control is based on that all the state variables aremeasurable, which is often not easy to achieve in practice. In order to meet the actualsituation, in this paper, an dynamic output feedback controller is also designed, and aquarter-car model with active suspension system is considered to illustrate the effec-tiveness of the designed controllers (state feedback and dynamic output feedback) inboth frequency domain and time domain.
Sampled-data control is a difficult problem in the area of vehicle suspension sys-tem, since both continuous-time signal and discrete-time signal are contained in thecontrol system, which leads to the limitation of traditional control methods. By usingan input delay approach, the active vehicle suspension system with sampling mea-surements is transformed into a continuous-time system with a delay in the state. Thetransformed system contains possibly non-differentiable time-varying delay. Finally,the controller design is cast into a convex optimization problem with LMI constraints,and the controller designed is robust in order to meet the actual system with uncertain parameters. The effectiveness of the proposed approach is illustrated by a realisticdesign example.
在有限频域H∞控制中,有别于现有的汽车悬架系统H∞控制方法在全频域下进行扰动衰减,本文的控制器设计方法可以实现在有限频域下的扰动抑制,使振动在人体所敏感的频率范围内被最大程度衰减。通过使用广义Kalman-Yakubovich-Popov引理,从扰动到控制输出的H∞范数在关心的频域范围内被最小化,进而改善驾驶舒适度。同全频方法相比较,有限频域方法在特定的频域内可以更加有效的进行控制,与此同时,悬架设计中的一些必要的时域约束也都可以得到保证。
状态反馈控制可以很好的对系统实现控制,结合广义KYP引理,本文首先给出了有限频域下的状态反馈控制器设计方法,针对汽车悬架系统的有限频域特性进行了H∞控制。状态反馈控制是以所有的状态变量均是可测量为前提的,这在实际中往往不容易达到,为了适应实际情况,本文针对状态的不完全可测量情况又提出了有限频域下的动态输出反馈控制器设计方法,并借用四分之一主动悬架系统模型,分别了对状态反馈闭环系统和输出反馈闭环系统进行时域和频域的仿真验证,仿真结果验证了控制器设计的有效性。
数字采样控制问题是汽车悬架系统控制中的另外一个难点问题,它的控制难点在于系统中同时包含连续时间信号和离散时间信号,传统的控制方法往往十分受限。本文通过使用一种输入时滞的方法,将采样悬架系统转化为带有时滞的连续时间系统,这种转化包含有不可导的时变时滞,最后,控制器设计被转化为一个带有线性矩阵不等式(LMI)约束的凸优化问题进行求解,为了满足车辆行驶中的参量变化,我们进一步设计了鲁棒控制器。仿真结果验证了控制器设计的有效性。
Vehicle active suspensions have been a hot research topic for many years due totheir important role in vehicle performance. In this paper, two hot issues of vehicleactive suspension system are considered, that is, finite frequency control and sampled-data control, and the corresponding controller design method is given, respectively.
Different from the existing H∞control methods, which conduct disturbance at-tenuation within the entire frequency domain, this paper addresses the problem of H∞control for active vehicle suspension systems in finite frequency domain. By usingthe generalized Kalman-Yakubovich-Popov (KYP) lemma, the H∞norm from the dis-turbance to the controlled output is decreased in specific frequency band to improvethe ride comfort. Compared with the entire frequency approach, the finite frequencyapproach suppresses the vibration more effectively for the concerned frequency range.In addition, the time-domain constraints are guaranteed in the controller design.
State feedback control is a useful control strategy in modern control system.Combined with the generalized KYP lemma, a state feedback H∞controller is de-signed firstly, in order to meet the finite frequency characteristic of the vehicle sus-pension system. State feedback control is based on that all the state variables aremeasurable, which is often not easy to achieve in practice. In order to meet the actualsituation, in this paper, an dynamic output feedback controller is also designed, and aquarter-car model with active suspension system is considered to illustrate the effec-tiveness of the designed controllers (state feedback and dynamic output feedback) inboth frequency domain and time domain.
Sampled-data control is a difficult problem in the area of vehicle suspension sys-tem, since both continuous-time signal and discrete-time signal are contained in thecontrol system, which leads to the limitation of traditional control methods. By usingan input delay approach, the active vehicle suspension system with sampling mea-surements is transformed into a continuous-time system with a delay in the state. Thetransformed system contains possibly non-differentiable time-varying delay. Finally,the controller design is cast into a convex optimization problem with LMI constraints,and the controller designed is robust in order to meet the actual system with uncertain parameters. The effectiveness of the proposed approach is illustrated by a realisticdesign example.
引文
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3 J. Swevers, C. Lauwerys, B. Vandersmissen, et al. A Model-free Control Struc-ture for the On-line Tuning of the Semi-active Suspension of a Passenger Car .Mechanical Systems and Signal Processing. 2007, 21:1422–1436
4 J. J. H. Paulides, L. Encica, E. A. Lomonova, et al. Design Considerations for aSemi-active Electromagnetic Suspension System. IEEE Trans. Magnetics. 2006,42(10):3446–3448
5 M. Ieluzzi, P. Turco, M. Montiglio. Development of a Heavy Truck Semi-activeSuspension Control. Control Engineering Practice. 2006, 14:305–312
6 H. P. Willumeit, F. Bohm. Wheel Vibrations and Transient Tire Forces. VehicleSystem Dynamics. 1995, 24(6-7):525–550
7 C. C. Liang, C. F. Chiang, T. G. Nguyen. Biodynamic Responses of SeatedPregnant Subjects Exposed to Vertical Vibrations in Driving Conditions. VehicleSystem Dynamics. 2007, 45(11):1017–1049
8 M. Gobbi, J. C. Botero, G. Mastinu. Improving the Active Safety of Road Vehi-cles by Sensing Forces and Moments at the Wheels. Vehicle System Dynamics.2008, 46:957–968
9 T. T. Fu, D. Cebon. Economic Evaluation and the Design of Vehicle Suspensions
10 H. P. Du, N. Zhang. Fuzzy Control for Nonlinear Uncertain ElectrohydraulicActive Suspensions with Input Constraint. IEEE Trans. Fuzzy Systems. 2009,17(2):343–356
11 S. J. Huang, W. C. Lin. Adaptive Fuzzy Controller with Sliding Surface forVehicle Suspension Control . IEEE Trans. Fuzzy Systems. 2003, 11(4):550–559
12 A. Barr, J. Ray. Control of an Active Suspension Using Fuzzy Logic . Pro-ceedings of the Fifth IEEE International Conference on Fuzzy Systems. 1996,1:42–48
13 P. Guarneri, M. Rocca, G.and Gobbi. A Neural-network-based Model for theDynamic Simulation of the Tire/suspension System While Traversing Road Ir-regularities . IEEE Trans. Neural Networks. 2008, 19(9):1549–1563
14 M. Yu, S. B. Choi, D. X. M. et al. Fuzzy Neural Network Control for Vehicle Sta-bility Utilizing Magnetorheological Suspension System . Journal of InternationalMaterial Systems and Strucctures. 2009, 20(4):457–466
15 L. Zuo, J.-J. E. Slotine, S. Nayfeh. Model Reaching Adaptive Control for Vibra-tion Isolation . IEEE Trans. Control Systems Technology. 2005, 13(4):611–617
16 I. Fialhm, G. J. Balas. Road Adaptive Active Suspension Design Using LinearParameter-varying Gain-scheduling . IEEE Trans. Control Systems Technology.2002, 10(1):43–54
17 G. Priyandoko, M. Mailah, H. Jamaluddin. Vehicle Active Suspension SystemUsing Skyhook Adaptive Neuro Active Force Control . Mechanical Systems andSignal Processing. 2009, 23(3):855–868
18 S. Chantranuwathana, H. Peng. Adaptive Robust Force Control for VehicleActive Suspensions. Int. J. Adaptive Control and Signal Processing. 2009,23(3):855–868
19 N. Yagiz, Y. Hacioglu, Y. Taskin. Fuzzy Sliding-mode Control of Active Sus-pensions . IEEE Trans. Industrial Electronics. 2004, 18:83–102
20 H. Liu, K. Nonami, T. Hagiwara. Active Following Fuzzy Output FeedbackSliding Mode Control of Real-vehicle Semi-active Suspensions . J. of sound andvibration. 2008, 314(1–2):39–52
21 H. Chen, Z. Y. Liu, P. Y. Sun. Application of Constrained H∞Control to Ac-tive Suspension System on Half-car Models . J. Dyn. Syst. Meas. Contr. 2005,127:345–354
22 H. Du, J. Lam, K. Y. Sze. Non-fragile Output Feedback H∞Vehicle Suspen-sion Control Using Genetic Algorithm. Engineering Applications of ArtificialIntelligence. 2003, 16(7–8):667–680
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