共查询到18条相似文献,搜索用时 969 毫秒
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基于LMS自适应滤波的模糊控制主动悬架研究 总被引:1,自引:0,他引:1
以车辆操纵稳定性及行驶平顺性为控制目标,根据路面一车辆系统的特点,提出一种在线可调整的模糊控制算法,利用LMS自适应模块调整模糊控制器的自调整因子,改善单一模糊控制算法对专家先期经验的依赖。针对简化的车辆模型,以路面信号作为激励源,进行悬架系统的振动控制研究,结果表明提出的算法对车辆悬架系统的振动控制具有较好的适应性。 相似文献
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规则自调整模糊控制及其在主动悬架系统中的应用 总被引:1,自引:1,他引:1
根据路面 车辆系统的非线性特点,本文提出一种在线可调整的模糊控制算法,其模糊控制规则表可以用解析的方法进行计算。该方法不仅体现了模糊控制算法对非线性系统具有的明显优势,而且利用LMS自适应算法在线调整模糊控制器的修正因子。针对简化的车辆模型,以路面信号作为激励源进行了仿真研究,证明该算法对悬架系统的振动控制具有较好的效果,簧上质量加速度功率谱密度得到明显降低。 相似文献
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主要提出基于可调整因子的模糊控制策略,详细分析了自调整因子模糊控制器的原理。以MATLAB/SIMULINK为平台,应用此控制策略对某高级客车的空气悬架刚度进行控制,根据车辆振动响应的结果来判断车体的振动情况,实时调节空气悬架刚度,使车辆对路面的变化具有适应能力,从而改善汽车行驶平顺性。 相似文献
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应用模糊控制和神经网络控制理论,构建了1/2车辆的半主动悬架模型,设计了基于轴距预瞄的半主动悬架模糊神经网络控制系统.对前轮半主动悬架采用以对应处车身垂向加速度为目标的模糊控制,对后轮半主动悬架采用轴距预瞄模糊控制,并利用神经网络来调整模糊控制器的控制规则和隶属度函数.在不同车速下对所建的控制系统分别进行了白噪声和路面脉冲输入的仿真.结果表明,与传统的被动系统相比,轴距预瞄模糊神经网络控制的半主动悬架系统能有效降低车辆振动;与模糊控制的半主动悬架系统相比,质心垂向加速度和后轮对应处车身加速度均有显著减小,较好地改善了车辆的行驶平顺性. 相似文献
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基于频率分析的半主动悬架模糊控制方法研究 总被引:1,自引:0,他引:1
对悬架的频响特性进行的分析发现,悬架的特性与振动频率有关.因此提出了一种基于频率分析的半主动悬架的模糊控制方法.利用Matlab分别对被动悬架、采用skyhook控制的半主动悬架和基于频率分析的模糊控制的半主动悬架进行了仿真.对比仿真的结果验证了文中提出的模糊控制方法的有效性. 相似文献
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《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(5):407-423
A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results. 相似文献
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Wun-Tong Sie Ruey-Jing Lian Bai-Fu Lin 《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2006,44(5):407-423
A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results. 相似文献
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《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(12):1123-1139
This study proposed a self-organising fuzzy controller (SOFC) for controlling an active suspension system to evaluate its control performance. During the control process, the SOFC continually updated the learning strategy in the form of fuzzy rules. The fuzzy rule table of this SOFC could be initially set to zero. This not only overcame the difficulty in finding appropriate membership functions and control rules for designing a fuzzy controller, but also solved the database problem where the fuzzy rules of a fuzzy controller, once determined, remained fixed and could not suitably regulate them in real time to optimise the dynamic response of the system required to gain the desired control performance. To demonstrate the applicability of the proposed SOFC for active suspension systems, a quarter-car hydraulic-servo suspension system was designed and constructed to evaluate the feasibility of active suspension control. Additionally, to conform to real-time application requirements in the vehicular industry, the SOFC was implemented with a digital signal processor to control the hydraulic-servo suspension system so that the control performance could be determined. The SOFC has shown a better control performance in suppressing the vibration amplitude of the vehicle body for enhancing the structural safety of the vehicle and increasing the life of the suspension system. It also effectively suppressed the amplitude of the vehicle body acceleration and reduced the tire deflection for improving the ride and the handling quality of a vehicle better than a passive control, as verified in experimental results. 相似文献
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This study designs a fuzzy logic controller (FLC) for an active automobile suspension system in which the membership functions
and control rules are optimized using a genetic algorithm (GA). The objective of the FLC is to strike an optimal balance between
the ride comfort and the vehicle stability. The values of the crossover and mutation parameters in the GA are adapted dynamically
during the convergence procedure using a fuzzy control scheme. The convergence state of the GA is determined by using a support
vector machine (SVM) method to identify the variation in each of the genes of the best-fit GA chromosome following each iteration
loop. The feasibility of the proposed GA-assisted FLC scheme is verified by performing a series of numerical simulations in
which the characteristics of the controlled plant are compared with those observed in a passive suspension system and obtained
under an optimal linear feedback controller. The results demonstrate that the GA-assisted FLC results in a lower suspension
deflection, a reduced sprung mass acceleration and a lower bouncing distance between the tire and the ground. 相似文献
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Hongbin Ren Sizhong Chen Gang Liu Lin Yang 《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2016,54(2):168-190
This paper proposes an improved virtual reference model for semi-active suspension to coordinate the vehicle ride comfort and handling stability. The reference model combines the virtues of sky-hook with ground-hook control logic, and the hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high-speed condition. Suspension state observer based on unscented Kalman filter is designed. A sliding mode controller (SMC) is developed to track the states of the reference model. The stability of the SMC strategy is proven by means of Lyapunov function taking into account the nonlinear damper characteristics and sprung mass variation of the vehicle. Finally, the performance of the controller is demonstrated under three typical working conditions: the random road excitation, speed bump road and sharp acceleration and braking. The simulation results indicated that, compared with the traditional passive suspension, the proposed control algorithm can offer a better coordination between vehicle ride comfort and handling stability. This approach provides a viable alternative to costlier active suspension control systems for commercial vehicles. 相似文献
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Optimal Preview Control of a Two-dof Vehicle Model Using Stochastic Optimal Control Theory 总被引:2,自引:0,他引:2
S. Senthil S. Narayanan 《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》1996,25(6):413-430
An optimal preview control algorithm is applied to a two degree of freedom(dof) vehicle model travelling with constant velocity on a randomly profiled road. The road roughness is modelled as a homogeneous random process being the output of a linear first order filter to white noise. The input from the road irregularity is assumed to be measured at some distance in front of the vehicle and this measured infonnation is utilized by the active controller to prepare the system for the ensuing input. The preview control algorithm is obtained by minimizing a quadratic performance index and by describing the average behaviour of the system by the covariance matrix of the vehicle response state vector. Results are presented for full state feedback and significant improvements in sprung mass acceleration, suspension working space and road holding are observed. 相似文献
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《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(12):1923-1948
Both ride quality and roadholding of actively suspended vehicles can be improved by sensing the road ahead of the vehicle and using this information in a preview controller. Previous applications have used look-ahead sensors mounted on the front bumper to measure terrain beneath. Such sensors are vulnerable, potentially confused by water, snow, or other soft obstacles and offer a fixed preview time. For convoy vehicle applications, this paper proposes using the overall response of the preceding vehicle(s) to generate preview controller information for follower vehicles. A robust observer is used to estimate the states of a quarter-car vehicle model, from which road profile is estimated and passed on to the follower vehicle(s) to generate a preview function. The preview-active suspension, implemented in discrete time using a shift register approach to improve simulation time, reduces sprung mass acceleration and dynamic tyre deflection peaks by more than 50% and 40%, respectively. Terrain can change from one vehicle to the next if a loose obstacle is dislodged, or if the vehicle paths are sufficiently different so that one vehicle misses a discrete road event. The resulting spurious preview information can give suspension performance worse than that of a passive or conventional active system. In this paper, each vehicle can effectively estimate the road profile based on its own state trajectory. By comparing its own road estimate with the preview information, preview errors can be detected and suspension control quickly switched from preview to conventional active control to preserve performance improvements compared to passive suspensions. 相似文献
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H. Du N. Zhang 《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2008,46(5):385-412
This paper presents an approach to design the H∞/GH 2 static-output feedback controller for vehicle suspensions by using linear matrix inequalities (LMIs) and genetic algorithms (GAs). Three main performance requirements for an advanced vehicle suspension are considered in this paper. Among these requirements, the ride-comfort performance is optimized by minimizing the H∞ norm of the transfer function from the road disturbance to the sprung mass acceleration, while the road-holding performance and the suspension deflection limitation are guaranteed by constraining the generalized H2 (GH 2) norms of the transfer functions from the road disturbance to the dynamic tyre load and the suspension deflection to be less than their hard limits, respectively. At the same time, the controller saturation problem is considered by constraining its peak response output to be less than a given limit using the GH 2 norm as well. A four-degree-of-freedom half-car model with active suspension system is applied in this paper. Several kinds of H∞/GH 2 static-output feedback controllers, which use the available sprung mass velocities or the suspension deflections as feedback signals, are obtained by using the GAs to search for the possible control gain matrices and then resolving the LMIs together with the minimization optimization problem. These designed H∞/GH 2 static-output feedback controllers are validated by numerical simulations on both the bump and the random road responses which show that the designed H∞/GH 2 static-output feedback controllers can achieve similar or even better active suspension performances compared with the state-feedback control case in spite of their simplicities. 相似文献