【作者】 李广军；

【导师】 金炜东；

【作者基本信息】 西南交通大学 ， 电力系统及其自动化， 2013， 博士

【摘要】 列车在高速运行时,由于轨道不平顺输入影响,使得列车产生横移、侧滚和摇头振动,并在车体上合成横向加速度,影响了列车横向平稳性。为了减少横向振动,提高列车的运行平稳性和舒适性,采用车辆悬挂系统来减少振动。半主动悬挂在减振效果上既好于被动悬挂,又比主动悬挂节约能源,故其将成为未来车辆减振研究的一个重点和难点。由于列车横向运动模型是复杂的动力学系统,具有非线性、时变,多变量等特点,很多横向半主动悬挂控制算法都有其局限性。其中,模糊控制不依赖精确的数学模型,具有人工智能的特点,在列车横向半主动悬挂控制中显示出很强的优势。因此,本文在建立17个自由度的列车横向运动模型基础上,分别设计了普通、变论域、满意优化的模糊控制器和混合模糊控制器,并通过仿真证明各算法的有效性。论文的主要工作如下：(1)分析了列车横向半主动悬挂振动结构。列车横移、侧滚和摇头三种振动的加速度最大值和均方根值分析表明,横移和摇头振动是影响列车横向振动的重要因素；互相关函数和小波变换分析表明,列车横向振动的主频为1Hz以下的低频段,水平不平顺对列车横移和摇头振动影响较大,方向不平顺对侧滚振动影响较大,水平不平顺是影响列车横向合成加速度的重要因素。(2)设计了列车横向半主动悬挂模糊控制器。以列车横向速度和加速度为模糊控制器的输入变量,模糊控制器的输出变量为可变阻尼器的输入电流,根据经验设计模糊控制器的控制规则,从而调整可变阻尼器的阻尼,减少列车横向振动。仿真结果表明,列车横向半主动悬挂模糊控制在加速度最大值、均方根值和功率谱密度最大值上都好于被动悬挂。(3)实现了列车横向半主动悬挂变论域模糊控制策略。首先,推广了变论域模糊控制收敛条件,并将其应用于列车横向半主动悬挂系统。在建立的17个自由度的列车横向运动模型基础上,设计了变论域模糊控制器。仿真结果表明,变论域模糊控制在列车横移、侧滚和摇头振动、前端、中间和后端加速度最大值、均方根值和功率谱密度最大值上均好于普通的模糊控制。(4)利用满意优化原理优化了列车横向半主动悬挂模糊控制器。依据满意优化原理,利用生物地理优化算法优化了列车横向半主动悬挂模糊控制器。为了提高优化效果,采用了基于复形法的生物地理优化算法。仿真结果表明,该方法优化的模糊控制可以有效降低列车横向加速度的最大值、均方根和功率谱密度最大值。(5)设计了列车横向半主动悬挂混合模糊控制器。在变论域模糊和进化算法优化的模糊控制基础上,把两种控制策略结合起来,设计混合模糊控制器。研究结果表明,在控制因子为0.5时,控制器混合效果最佳,并在控制因子为0.5的情况下,利用改进的生物地理优化算法优化了混合控制器。仿真结果显示，优化后的混合模糊控制效果好于变论域模模糊控制,并与其他列车横向半主动悬挂控制策略做了对比,证明了混合模糊控制策略的有效性。更多还原

【Abstract】 As the train is running at high speed, the body of train has lateral.rolling and yawing vibration due to track irregularity input.And three kinds of vibration constitudes train lateral synthetic acceleration,the lateral stability of train is affected. So,the suspension system is used to reduce the lateral vibration and improve the vehicle running stability and comfort. Semi-active suspension not only is better than passive suspension in the damping effect but also achieves more energy conservation than active suspension, which can become the focus and difficulty in the futural research. Because the train lateral motion system is a dynamic one with complex, nonlinear, time-varying and multi-variable characters, many control algorithms of semi-active suspension have their limitations. Fuzzy control does not depend on the accurate mathematical model among those control algorithms, and has also characteristics of artificial intelligence, thus shows strong superiority in the semi-active suspension system. After train lateral system model with 17 degrees of freedom is built by Simulink software, the general,variable universe,optimized by evolutionary algorithm and hybrid fuzzy control are respectively designed, and then the validity of the algorithm is proved through simulation. The main work is as follows:(1) Vibration structure of train semi-active suspension is analyzed. In three kinds of vibration, lateral and yawing vibration is important factor of affecting the lateral synthetic acceleration of train. The cross correlation function and wavelet transform analysis show that the main frequency of lateral vibration mainly is concentrated in the low frequency band below 1Hz, horizontal irregularity is an important eause of train lateral and yawing vibration, and alignment irregularity is an important factor of train rolling vibration, horizontal irregularity is an important factor for the train lateral synthetic acceleration at the same time.(2) Fuzzy controller is designed for semi-active suspension of train. To improve the ride quality and reduce lateral vibration, the fuzzy controller is designed to adjust damping parameter by taking the the body’s acceleration and velocity as the controller’s input variables and the dampmer’s current as the controller’s output variables. Simulation result by the means of root mean square shows that lateral acceleration of the body significantly decreases by the ordinary fuzzy control, and it is proved that semi-active suspension is better than passive suspension at the same time.(3) The variable universe fuzzy control strategy is completed. The more widely convergence conditions of variable universe fuzzy control is given, and it is suitable for semi-active suspension system. After lateral motion model of 17 degree-of-freedom train is established, the variable universe fuzzy controller is designed. The simulation results show that the variable universe fuzzy control is better than the ordinary fuzzy control in the maximum amplitude, mean square root and power spectral density maximum value of the lateral, rolling and yawing, front, middle and rear acceleration.(4) Satisfactory optimization mothed is used to optimize the fuzzy controller by an improved biogeography-based optimization algorithm. To improve satisfactory optimization effect, the semi-active suspension fuzzy controller is optimized by the improved biogeography-based optimization algorithm based on complex method. The simulation results show that fuzzy control optimized by this method can effectively reduce the maximum amplitude, mean square root and power spectral density maximum value of lateral vibration.(5) A hybrid fuzzy controller is designed. The variable universe fuzzy controller and the fuzzy cotroller optimized by evolutionary algorithm is organically combined, and the hybrid fuzzy controller is designed. Research results show that control effect is the best while control factor is 0.5. So, modified biogeography-based optimization algorithm is also used to optimize the hybrid control when control factor is 0.5.Simulation results show that the control effect of hybrid fuzzy controller is better than that of the variable universe fuzzy controllor.更多还原