基于半主动悬架的车辆抗侧倾控制研究

悬架系统可提高乘坐舒适性,用于抑制车身的侧倾。基于车辆多工况行驶下的抗侧倾控制需求,建立带有半 主动悬架系统的车辆四自由度动力学模型,以空气悬架和电机式主动稳定杆作为执行器,分别选用模糊控制和滑模控制 来设计抗侧倾控制器,通过Matlab/Simulink 与Carsim 建立联合仿真模型来验证所设计控制策略的有效性。仿真结果表 明:在双移线和鱼钩工况下,使用带有主动横向稳定杆的半主动悬架系统可有效减小车辆的侧倾角,降低车辆侧翻风险。     

矿井防尘供水智能控制及评价系统

针对矿井防尘供水系统水压不稳定、能耗大等问题,提出一种矿井防尘供水智能控制及评价系统.该系统采用参数自适应的Fuzzy-PID控制器对水压进行有效调节,仿真结果比较了常规PID和Fuzzy-PID控制效果的差别.同时,构建了供水系统可靠性评价指标体系,采用模糊层次分析法对供水系统进行可靠性评价.工程实践表明,该系统运行...     

基于改进Fuzzy-PID控制理论的无人机纵向飞控律设计

针对无人机飞行中存在大量的随机干扰和不确定误差等问题,常规的PID控制器不能满足高精度、高灵活性和强适应性的要求,提出了基于改进Fuzzy-PID控制理论的飞控律设计。该设计使用模糊规则下的切换开关来完成PID控制和Fuzzy控制输出量的加权,使控制具有两者的优点。通过调整模糊隶属度函数参数,可以得到系统的最佳控制方案。仿真结果表明:基于改进Fuzzy-PID控制理论的飞控律明显优于常规控制理论,具有较强的适应性和灵活性,在提高无人机的飞行控制系统性能上具有实际意义。     

模糊PID励磁控制器的仿真研究

针对常规PID控制器不能在线整定参数,模糊控制器对复杂的和模型无法建立的对象能够进行简单有效的控制,将常规PID与模糊控制器结合,综合其优点,构造2种模糊PID控制器。利用Matlab对两种控制器在自动励磁控制系统中进行仿真,结果表明两种模糊PID励磁控制器有很好的控制效果。     

细菌觅食优化的PID窒制器在变风量空调机组的应用

基于变风量空调机组高度非线性的特点,常规的PID控制已经不能达到满意的控制效果,本文选用细菌觅食优化的PID控制器对变风量空调机组送风温度进行控制。通过matlab仿真,并与常规的PID控制进行比较,结果表明细菌觅食优化的PID控制器比常规的PID控制器在超调量和调整时间方面有很大的改善。     

基于小波神经网络的PID控制器在高频高压电路中的应用

通过对高频高压电路结构进行分析得知,高压发生电路输出与输入存在着非线性关系。其稳定性受多种因素影响。目前工业生产中广泛使用经典PID控制器。然而经典PID参数自整定难以有效解决,文中设计了一种具有局部分据和自学习能力的小波神经网络（WNN）和经典PID相结合的控制器。实现对高频高压电路的控制。通过对WNN-PID、BP-PID和Fuzzy-PID进行仿真对比,结果表明：WWN-PID控制器具有稳态精度高、响应速度快、调节时间短和抗干扰能力强等特点。证明了该方法的有效性和优良性。     

自适应模糊PID在温度控制中的应用

温度控制具有非线性、大惯性、时变性等特点,常规PID控制和常规模糊控制还不能使温度的控制达到理想效果。设计一种自适应模糊PID控制器,该控制器在大偏差范围内采用模糊控制,根据偏差和偏差变化的需要实时调整PID参数,小偏差范围内采用PID精确控制。介绍自适应模糊PID控制器的构成和原理,并利用Matlab／Simulink和模糊逻辑工具箱对其进行仿真,仿真结果表明,这种自适应PID控制器既具有模糊控制灵活、响应快、适应性强的特点,又具有PID控制精度高的特点,改善了温度控制的效果。     

基于模糊自适应PID的炉温控制系统设计

电锅炉已成为寒冷地区供热采暖的主要设备,对于新疆地区尤为重要.电锅炉的温度控制系统由于存在非线性、滞后性以及时变性等特点,常规的PID控制器很难达到较好的控制效果.考虑到模糊控制能对复杂的非线性、时变系统进行很好的控制,但无法消除静态误差的特点,本设计将模糊控制和常规的PID控制相结合,提出一种模糊自适应PID控制器的新方法.并对电锅炉温度控制系统进行了抗扰动的仿真试验,结果表明,和常规的PID控制器及模糊PID复合控制器相比,模糊自适应PID控制改善了系统的动态性能和鲁棒性,达到了较好的控制效果.     

基于单神经元PID的并联机构稳定控制研究

并联机构由于非线性强、控制过程复杂,导致常规PID控制参数难以整定。为了实现对二自由度并联机构更精确的控制,结合神经网络,文中提出了一种基于单神经元的自适应PID控制策略,以实现PID控制参数的实时整定。通过dSPACE对被控对象进行半实物仿真,仿真结果表明,设计的单神经元PID控制器控制效果优于传统PID控制器。     

基于预测控制的Fuzzy-PID控制器算法研究

针对常规Fuzzy-PID控制器存在的问题,提出了一种基于预测控制的Fuzzy-PID控制器算法,并给出了预测部分的数学推导过程.该算法无需建立精确的数学模型,能大大改善控制器性能,使其对受控对象的适应能力加强.基于预测控制的Fuzzy-PID控制器为解决工业过程中非线性、时变、大滞后环节的控制问题提供了一个有效的方案,在热工控制领域具有较好的应用前景.     

基于转角的商用车电动助力转向回正控制研究

以改善商用车电动助力转向系统的回正特性为目标,开发了一种基于转向盘转角的回正目标电流控制器,该控制器以转角传感器LH3获取的转角信号为输入,经PID控制方式获取回正目标电流,通过控制助力电机动作,使转向盘准确快速回位。并利用Simulink仿真软件搭建了该回正控制器仿真模型,对回正特性进行分析。仿真结果表明:转向盘的回正稳定时间大大缩短,该回正控制器明显提高了EPS系统的回正性能。     

开关电源模糊PID复合控制器的研究与仿真

文中提出了一种开关电源的模糊PID复合控制器的设计方法,并以Buck拓扑结构为对象进行了Matlab仿真实验。结果表明模糊PID复合控制器结合了模糊控制与PID控制的优点,具有动态响应快、超调小、抗干扰能力强等优点。     

A fuzzy logic sliding mode controlled electronic differential for a direct wheel drive EV

In this study, a direct wheel drive electric vehicle based on an electronic differential system with a fuzzy logic sliding mode controller (FLSMC) is studied. The conventional sliding surface is modified using a fuzzy rule base to obtain fuzzy dynamic sliding surfaces by changing its slopes using the global error and its derivative in a fuzzy logic inference system. The controller is compared with proportional–integral–derivative (PID) and sliding mode controllers (SMCs), which are usually preferred to be used in industry. The proposed controller provides robustness and flexibility to direct wheel drive electric vehicles. The fuzzy logic sliding mode controller, electronic differential system and the overall electrical vehicle mechanism are modelled and digitally simulated by using the Matlab software. Simulation results show that the system with FLSMC has better efficiency and performance compared to those of PID and SMCs.     

磁阻式悬浮平台侧向气隙控研究

针对悬浮平台存在的侧向力干扰导致平台不能稳定悬浮的问题,设计了一种可以实现参数快速整定的模糊自适应PID侧向气隙控制系统。文中介绍了平台的悬浮结构和悬浮机理,采用有限元法分析了侧向位移对平台的影响,建立了控制系统静态、动态数学模型,并设计了模糊自适应PID控制器。通过MATLAB/Simulink软件对悬浮平台的侧向气隙控制系统进行建模仿真。结果表明,模糊自适应PID控制器响应速度快,且具有较强的鲁棒性。     

Normal and emergency control of a string of vehicles by fixed reference sampled-data control

A fixed reference control scheme for automated highways is proposed. Each vehicle controls itself; thus multiloop feedback is avoided. A simple proportional-integral-derivative (PID) controller is selected from many alternatives. For emergency stopping, a PI controller using a tachometer on a braked wheel can bring a vehicle with rubber tires to a controlled skid-free stop.     

The application of neural networks to fuel processors for fuel-cellvehicles

Passenger vehicles fueled by hydrocarbons or alcohols and powered by proton exchange membrane (PEM) fuel cells address world air quality and fuel supply concerns while avoiding hydrogen infrastructure and on-board storage problems. Reduction of the carbon monoxide concentration in the on-board fuel processor's hydrogen-rich gas by the preferential oxidizer (PrOx) under dynamic conditions is crucial to avoid poisoning of the PEM fuel cell's anode catalyst and thus malfunction of the fuel-cell vehicle. A dynamic control scheme is proposed for a single-stage tubular cooled PrOx that performs better than, but retains the reliability and ease of use of, conventional industrial controllers. The proposed hybrid control system contains a cerebellar model articulation controller artificial neural network in parallel with a conventional proportional-integral-derivative (PID) controller. A computer simulation of the preferential oxidation reactor was used to assess the abilities of the proposed controller and compare its performance to the performance of conventional controllers. Realistic input patterns were generated for the PrOx by using models of vehicle power demand and upstream fuel-processor components to convert the speed sequences in the Federal Urban Driving Schedule to PrOx inlet temperatures, concentrations, and flow rates. The proposed hybrid controller generalizes well to novel driving sequences after being trained on other driving sequences with similar or slower transients. Although it is similar to the PID in terms of software requirements and design effort, the hybrid controller performs significantly better than the PID in terms of hydrogen conversion setpoint regulation and PrOx outlet carbon monoxide reduction     

Vibration reduction of seat suspension using observer based terminal sliding mode control with acceleration data fusion

In this work, a disturbance observer and state observer based terminal sliding mode (TSM) controller with acceleration data fusion is proposed for the active control of a seat suspension. In practical applications, the driver's body and the friction forces are difficult to be accurately described with a mathematical model; for this reason, the proposed controller is designed based on a model simplified from a 6-degree-of-freedom (6-DOF) seat-driver model with nonlinear friction. The disturbance observer and state observer are designed together with Linear Matrix Inequality (LMI) method. For improving the observer's performance, a complementary filter is applied to fuse the estimation of the seat suspension velocity from the acceleration measurement and the state observer. The proposed controller is validated using simulations with various bump excitations applied, and the conventional state feedback TSM controller is implemented for comparison. The proposed controller is also implemented in a practical active seat suspension prototype, and a well-tuned commercial heavy duty vehicle seat suspension is applied for comparison. The power spectral density (PSD) value and ISO 2631–1 standard are used to evaluate the active seat suspension system's performance under random vibration. Both the simulation and the experimental results indicate that with the proposed controller, the vibration magnitude caused by a rough road can be greatly reduced, and the driver ride comfort is greatly improved.     

基于模糊控制纸张抗张试验机调速系统设计

纸张抗张试验机是检测纸张抗张强度和拉伸率的材料力学设备。为了能使试验机具有更加精确的调速系统,在控制策略上将模糊控制技术与PID有效结合,设计出基于模糊PID控制器的双闭环直流调速系统。通过Matlab仿真实验与常规PID控制器进行比较,模糊PID控制器的仿真结果要明显优越于常规PID控制,其响应速度、鲁棒性、稳态精度等均达到预期效果。     

Fuzzy Sliding-Mode Control of Active Suspensions

In this paper, a robust fuzzy sliding-mode controller for active suspensions of a nonlinear half-car model is introduced. First, a nonchattering sliding-mode control is presented. Then, this control method is combined with a single-input–single-output fuzzy logic controller to improve its performance. The negative value of the ratio between the derivative of error and error is the input and the slope constant of the sliding surface of the nonchattering sliding-mode controller is the output of the fuzzy logic controller. Afterwards, a four-degree-of-freedom nonlinear half-car model, which allows wheel hops and includes a suspension system with nonlinear spring and piecewise linear damper with dry friction, is presented. The designed controllers are applied to this model in order to evaluate their performances. It has been shown that the designed controller does not cause any problem in suspension working limits. The robustness of the proposed controller is also investigated for different vehicle parameters. The results indicate the success of the proposed fuzzy sliding-mode controller.      

基于虚拟仪器的模糊PID的设计研究

本文以LabVIEW为仿真平台,并利用其提供的PID和模糊逻辑工具箱,设计出一个模糊PID控制器。由于LabVIEW能快速构建实现交互控制系统的图形用户界,所以该控制器可以很容易的对3阶的线性被控对象快速进行模糊控制。实验结果表明,该控制器具有较强的抗干扰能力和鲁棒性,较好的动态特性。