轻轨线路曲线半径对车轮磨耗的影响

为分析线路曲线半径对轻轨列车车轮磨耗的影响,以长春市轻轨3号线70％低地板轻轨列车车轮为研究对象,建立独立旋转轮对的轻轨车辆-轨道耦合动力学计算模型、轮轨接触模型和Archard材料磨耗模型,对轻轨列车车轮磨耗进行仿真分析.计算结果表明:轻轨列车通过半径为50 m的曲线时,圆曲线上的车轮磨耗比缓和曲线更严重,整体轮对比独立轮对磨耗更严重;曲线半径大于150 m时,内、外侧车轮磨耗随着曲线半径增大而减小,并且在曲线半径相同的条件下,独立轮对各车轮磨耗量均比整体轮对各车轮磨耗量约大2 ～3 mm;随着列车行驶里程的增加,车轮磨耗率有先增大后减小的变化趋势,即可以将车轮磨耗分为快速磨耗和稳定磨耗2个阶段.轻轨车辆外侧车轮的磨耗率大于内侧车轮,说明车轮磨耗主要发生在外侧车轮.     

空气弹簧在100%低地板轻轨车上应用可行性分析*

基于多体动力学仿真软件SIMPACK,对某型采用纵向耦合边驱电机转向架的100%低地板轻轨车三模块编组建模,在MATLAB/Simulink中对其中央悬挂部件空气弹簧的主气室、节流孔、附加气室建模.对100%低地板轻轨车运行工况进行设定,通过联合仿真的方式对空气弹簧在100%低地板轻轨车上应用可行性进行分析,得到:1)空气弹簧应用到100%低地板车上后,车辆蛇行失稳临界速度为149km/h,大于设计时速,车辆有较好的运行稳定性.2)车辆运行时,平稳性及最大加速度指标均小于2.5,车辆有较好的运行平稳性.3)车辆通过小半径曲线时,轮重减载率、脱轨系数、轮轴横向力、轮轨横向力指标均小于评判标准限值,车辆有较好的曲线通过能力.4)空气弹簧在通过工况设定的小半径曲线时,各项性能指标均符合该型空气弹簧技术标准,空气弹簧在100%低地板轻轨车上应用可行.     

基于主从交互式萤火虫群优化算法的船舶航向分数阶PID控制

为了改善船舶航向控制的效果,文章首次运用了分数阶PID控制方法,并提出一种新的主从交互式萤火虫优化算法,以优化控制器参数,使得达到控制性能指标最优的目标;根据船舶动力学模型,以船舶实际参数作实验,实验结果表明经过FA优化的分数阶PID控制器,比PSO算法具有更好的控制性能;通过敏感性分析验证了算法求出的FOPID参数具有鲁棒性,当系统参数大幅度变化时不需要重新设置;证明了经萤火虫算法优化的分数阶PID控制器能够更好地满足船舶航向控制的需求。      

分数阶PID模型预测控制算法改进研究

在分析FOPID(分数阶PID)算法和MAC(模型算法控制)算法的基础上,结合两种算法的优点,推导了基于FOPID性能指标的改进的MAC控制算法FOPID-MAC算法.这种算法既具有FOND算法的优点,稳定性较好,又具有预测功能.通过仿真研究的对比,在时域内分析了FOPID-MAC控制器的参数选择对系统控制性能的影响,...     

基于分数阶PID控制器的智能车控制

针对智能车高速行驶下对目标轨迹的快速跟踪要求,结合预瞄跟随理论设计了分数阶PID控制器(FOPID).分数阶PID比传统PID控制器多两个参数自由度,所以在设计过程中有更大的灵活性.利用改进Oustaloup数字实现算法,框图化实现分数阶PID控制器,通过遗传算法对IAE性能指标寻优整定FOC参数并应用于智能车被控系统...     

用改进的人工蜂群算法设计AVR系统最优分数阶PID控制器

分数阶PID控制器（FOPID）是标准PID控制器的一般形式.与PID控制器相比,FOPID有更多的参数,其参数整定也更复杂.本文提出一种基于环交换邻域和混沌的人工蜂群算法（CNC-ABC）,用于FOPID控制器的参数整定.CNC-ABC算法由于应用了环交换邻域,增加了解的搜索范围,从而能加快人工蜂群算法的收敛速度;同时利用混沌的遍历性使算法跳出局部最优解.用CNC-ABC算法优化AVR系统的FOPID控制器的参数.仿真结果表明,CNC-ABC算法整定的FOPID控制器比其它FOPID及PID控制器有较好的性能.     

轴箱内置与外置直线电机地铁车辆曲线通过性能对比

为比较轴箱内置与外置直线电机地铁车辆的曲线通过性能,建立直线电机地铁车辆-无砟轨道耦合动力学模型.模型将直线电机定子和转子考虑为Euler梁,将定子与转子之间的垂向电磁力作为气隙的函数,将轨道系统简化为梁-三维实体有限元模型.详细比较轴箱内置与外置直线电机车辆曲线通过时的轮对冲角、轮轨横向力、脱轨因数、运行平稳性和车轮磨耗指数.结果表明:在不同的曲线半径和行车速度以及车轮踏面周向存在非均匀磨耗的状态下,轴箱内置直线电机车辆的曲线通过性能均优于轴箱外置车辆;随着曲线半径增加,轴箱外置直线电机车辆动力学性能迅速减小,而轴箱内置式车辆缓慢减小.     

基于整车动力学模型的EPS预测控制策略仿真研究

为了提高车辆的转向性能,基于整车动力学模型,研究电动助力转向系统(EPS)控制策略;针对PID控制参数固定不变,无法实时控制EPS动态响应的问题,提出了一种滚动优化的预测控制策略,并运用CarSim整车模型与Matlab软件相结合,实现了EPS控制仿真;通过对比仿真结果中横摆角速度和质心侧偏角等转向性能参数表明:用预测控制算法对EPS实施控制,比传统控制方法更精确,可有效提高车辆的转向性能和操纵稳定性,使EPS操控更加精准和轻捷。     

长春轻轨3号线钢轨轨底坡对列车车轮磨耗的影响

摘要： 为探究小半径曲线钢轨轨底坡对车轮磨耗的影响规律,建立长春市轻轨3号线70%低地板轻轨列车车轮磨耗预测分析模型,包括独立旋转轮对的车辆 轨道耦合动力学计算模型、轮轨接触模型和Archard材料磨耗模型,并采用这些模型分析轻轨列车通过小半径曲线轨道时轨底坡对车轮磨耗的影响。分析结果表明：轻轨列车通过小半径曲线轨道时,动车轮对的磨耗程度比拖车轮对更严重,动车轮对总磨耗量为拖车轮对总磨耗量的159%;从轮对自身来看,内侧车轮的磨耗均比外侧车轮的磨耗严重,内侧车轮总磨耗量为外侧车轮总磨耗量的165%;钢轨轨底坡对车轮磨耗的影响显著,车轮踏面最大磨耗量出现位置随轨底坡变化的规律较为复杂,车轮轮缘磨耗量在轨底坡为1/20时最小。     

一种改进型动态矩阵控制在水箱液位系统中的应用

针对三容水箱液位控制的多变量、强耦合、非线性、难以建立精确数学模型等特点,提出了在一种在状态空间方程形式下的多变量动态矩阵控制(dynamic matrix control,DMC)和分数阶PID (FOPID)控制相结合的新型模型预测控算法(MFOPID-DMC),以改善控制品质;用李雅普诺夫第二方法证明该算法的稳定性;将该算法应用在三容水箱液位控制系统,并与FOPID和DMC控制效果进行对比;仿真结果表明,该算法克服了FOPID超调大和DMC动态响应慢的不足,是一种鲁棒性较强、控制精度高的控制策略,较好地解决了三容水箱液位控制系统的耦合性、难以建立数学模型等问题.     

Multi‐objective robust fuzzy fractional order proportional–integral–derivative controller design for nonlinear hydraulic turbine governing system using evolutionary computation techniques

The present paper proposes a novel multi‐objective robust fuzzy fractional order proportional–integral–derivative (PID) controller design for nonlinear hydraulic turbine governing system (HTGS) by using evolutionary computation techniques. The fuzzy fractional order PID (FOPID) controller takes closed loop error and its fractional derivative as inputs and performs fuzzy logic operations. Then, it produces the output through the fractional order integrator. The predominant advantages of the proposed controller are its capability to handle complex nonlinear processes like HTGS in heuristic manner, due to fuzzy incorporation and extending an additional flexibility in tuning the order of fractional derivative/integral terms to enhance the closed loop performance. The present work formulates the optimal tuning problem of fuzzy FOPID controller for HTGS as a multi‐objective one instead of a traditional single‐objective one towards satisfying the conflicting criteria such as less settling time and minimum damped oscillations simultaneously to ensure the improved dynamic performance of HTGS. The multi‐objective evolutionary computation techniques such as non‐dominated sorting genetic algorithm‐II (NSGA‐II) and modified NSGA‐II have been utilized to find the optimal input/output scaling factors of the proposed controller along with the order of fractional derivative/integral terms for HTGS system under no load and load turbulence conditions. The performance of the proposed fuzzy FOPID controller is compared with PID and FOPID controllers. The simulations have been conducted to test the tracking capability and robust performance of HTGS during dynamic set point changes for a wide range of operating conditions and model parameter variations, respectively. The proposed robust fuzzy FOPID controller has ensured better fitness value and better time domain specifications than the PID and FOPID controllers, during optimization towards satisfying the conflicting objectives such as less settling time and minimum damped oscillations simultaneously, due to its special inheritance of fuzzy and FOPID properties.     

Robust FOPID controller design for fractional‐order delay systems using positive stability region analysis

In this paper, a robust fractional‐order PID (FOPID) controller design method for fractional‐order delay systems is proposed based on positive stability region (PSR) analysis. Firstly, the PSR is presented to improve the existing stability region (SR) in D‐decomposition method. Then, the optimal fractional orders λ and μ of FOPID controller are achieved at the biggest three‐dimensional PSR, which means the best robustness. Given the optimal λ and μ, the other FOPID controller parameters k_p, k_i, k_d can be solved under the control specifications, including gain crossover frequency, phase margin, and an extended flat phase constraint. In addition, the steps of the proposed robust FOPID controller design process are listed at length, and an example is given to illustrate the corresponding steps. At last, the control performances of the obtained robust FOPID controller are compared with some other controllers (PID and FOPI). The simulation results illustrate the superior robustness as well as the transient performance of the proposed control algorithm.     

Design of a fractional order PID controller for an AVR using particle swarm optimization

Application of fractional order PID (FOPID) controller to an automatic voltage regulator (AVR) is presented and studied in this paper. An FOPID is a PID whose derivative and integral orders are fractional numbers rather than integers. Design stage of such a controller consists of determining five parameters. This paper employs particle swarm optimization (PSO) algorithm to carry out the aforementioned design procedure. PSO is an advanced search procedure that has proved to have very high efficiency. A novel cost function is defined to facilitate the control strategy over both the time-domain and the frequency-domain specifications. Comparisons are made with a PID controller and it is shown that the proposed FOPID controller can highly improve the system robustness with respect to model uncertainties.     

Modeling and Trajectory Tracking Control for Flapping-Wing Micro Aerial Vehicles

This paper studies the trajectory tracking problem of flapping-wing micro aerial vehicles(FWMAVs)in the longitudinal plane.First of all,the kinematics and dynamics of the FWMAV are established,wherein the aerodynamic force and torque generated by flapping wings and the tail wing are explicitly formulated with respect to the flapping frequency of the wings and the degree of tail wing inclination.To achieve autonomous tracking,an adaptive control scheme is proposed under the hierarchical framework.Specifically,a bounded position controller with hyperbolic tangent functions is designed to produce the desired aerodynamic force,and a pitch command is extracted from the designed position controller.Next,an adaptive attitude controller is designed to track the extracted pitch command,where a radial basis function neural network is introduced to approximate the unknown aerodynamic perturbation torque.Finally,the flapping frequency of the wings and the degree of tail wing inclination are calculated from the designed position and attitude controllers,respectively.In terms of Lyapunov's direct method,it is shown that the tracking errors are bounded and ultimately converge to a small neighborhood around the origin.Simulations are carried out to verify the effectiveness of the proposed control scheme.     

改进的粒子群优化算法优化分数阶PID控制器参数

为了提高分数阶比例积分微分（FOPID）控制器的控制效果,针对FOPID控制器参数整定的范围广、复杂性高等特点,提出改进的粒子群优化（PSO）算法优化FOPID控制器参数的方法。该算法对PSO中惯权重系数的上下限设定范围并随迭代次数以伽玛函数方式非线性下降,同时粒子的惯性权重系数和学习因子根据粒子的适应度值大小动态调整,使粒子保持合理运动惯性和学习能力,提高粒子的自适应能力。仿真实验表明,改进的PSO算法优化FOPID控制器的参数较标准PSO算法具有收敛速度快和收敛精度高等优点,使FOPID控制器得到较优的综合性能。     

Robust adaptive control of a bio-inspired robot manipulator using bat algorithm

This paper proposes a novel adaptive fractional order PID sliding mode controller (AFOPIDSMC) using a Bat algorithm to control of a Caterpillar robot manipulator. A fractional order PID (FOPID) control is applied to improve both trajectory tracking and robustness. Sliding mode controller (SMC) is one of the control methods which provides high robustness and low tracking error. Using hybridization, a new combined control law is proposed for chattering reduction by means of FOPID controller and high trajectory tracking through using SMC. Then, an adaptive controller design motivated from the SMC is applied for updating FOPID parameters. A metaheuristic approach, the Bat search algorithm based on the echolocation behavior of bats is applied for optimal design of the Caterpillar robot in order to tune the parameter AFOPIDSMC controllers (BA-AFOPIDSMC). To study the effectiveness of Bat algorithm, its performance is compared with five other controllers such as PID, FOPID, SMC, AFOPIDSMC and PSO-AFOPIDSMC. The stability of the AFOPIDSMC controller is proved by Lyapunov theory. Numerical simulation results completely indicate the advantage of BA-AFOPIDSMC for trajectory tracking and chattering reduction.     

Optimum design of fractional order PID controller for AVR system using chaotic ant swarm

Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared to PID controller, the tuning of FOPID is more complex and remains a challenge problem. This paper focuses on the design of FOPID controller using chaotic ant swarm (CAS) optimization method. The tuning of FOPID controller is formulated as a nonlinear optimization problem, in which the objective function is composed of overshoot, steady-state error, raising time and settling time. CAS algorithm, a newly developed evolutionary algorithm inspired by the chaotic behavior of individual ant and the self-organization of ant swarm, is used as the optimizer to search the best parameters of FOPID controller. The designed CAS-FOPID controller is applied to an automatic regulator voltage (AVR) system. Numerous numerical simulations and comparisons with other FOPID/PID controllers show that the CAS-FOPID controller can not only ensure good control performance with respect to reference input but also improve the system robustness with respect to model uncertainties.     

车辆线控转向系统的分数阶鲁棒控制研究

线控转向系统有别于普通车辆的机械转向机构,它是由转向电机、转向机构、转角和力矩传感器以及控制单元构成的复杂转向系统．系统性能受到参数的不确定性、未建模动态以及前轮回正力矩的影响．本文基于分数微积分理论,根据转向系统鲁棒性的设计要求,提出一种新的PI^λD^μ控制策略,保证线控转向系统在所要求的频域范围具有鲁棒性．文中通过优化方法得到PI^λD^μ控制器的五个设计参数,并用Oustaloup算法对分数阶控制器进行仿真验证,结果表明该控制方法对提高转向系统性能的鲁棒性是有效的．