基于MATLAB的发动机试验自动采集和控制系统

在MATLAB平台下开发了发动机试验台架的自动采集和控制系统。利用MATLAB中的数据采集工具箱开发了自动数据采集系统,可以实现实验数据的自动采集、处理、显示和储存等功能。另外,利用单片机开发了PID控制器系统,用来对发动机试验的进气温度和燃油温度等边界条件进行控制,成功地保证了发动机试验的一致性和可重复性。     

并联混合动力汽车发动机调速控制及试验研究

通过分析并联混合动力电动汽车的结构和工作模式的切换过程,讨论了并联混合动力汽车进行发动机调速控制的必要性。对单轴并联混合动力汽车的发动机进行了PID调速方法研究,搭建了试验台架系统,以dSPACE快速控制原型工具为控制器,进行了PID参数整定和调速试验。试验表明,在并联混合动力状态切换过程中,发动机调速系统实现了调速快、波动小和运转稳定的目标,能够满足动力系统进行快速状态切换的需求。     

基于MAILAB的发动机试验自动采集和控制系统

在MATIAB平台下开发了发动机试验台架的自动采集和控制系统，利用MATLAB中的数据采集工具箱开发了自动数据采集系统。可以实现实验数据的自动采集、处理、显示和储存等功能。另外。利用单片机开发了PID控制器系统，用来对发动机试验的进气温度和燃油温度等边界条件进行控制。成功地保证了发动机试验的一致性和可重复性。     

基于PWM控制的电涡流测功机控制器的开发

以摩托罗拉16位单片机为控制器的控制单元、以功率MOSFET为功率驱动器件、以智能PID算法为控制策略,采用嵌入式实时操作系统μC/OS-Ⅱ,进行电涡流测功机控制器的设计开发,包括控制器硬件、软件和控制算法的设计.试验结果表明,控制器的控制效果良好,完全满足发动机台架试验对控制性能的要求.     

基于磁流变阻尼器的发动机振动模糊PID控制

在对发动机激振力及动力学模型分析的基础上,提出一种模糊PID控制方法,设计出了基于磁流变阻尼器的发动机振动控制的半主动模糊PID控制器,并运用MATLAB/Simulink对隔振控制系统进行了对比仿真.仿真结果显示,与橡胶隔振垫和PID控制相比,采用模糊PID控制的磁流变阻尼器的发动机有更明显的隔振效果,表明了磁流变阻尼器在汽车发动机上运用的可行性.     

汽车发动机主动悬置模糊PID控制策略研究

应用模糊控制算法对发动机悬置主动控制系统进行了研究,为主动悬置系统设计了一种混合型模糊PID控制器。系统隔振性能仿真结果表明,采用模糊PID控制的主动悬置可以有效降低发动机振动向车身的传递。     

串联式混合动力电动汽车发动机转速新型PID控制

在混合动力电动汽车中发动机转速的优化控制是降低油耗、减少排放的关键。而发动机转速系统是一个复杂的变参数非线性系统，且很难获得其准确数学模型。本文在常规的PID控制的基础上引入单神经元自适应控制，提出了发动机转速控制的优化目标。台架试验证明控制器能够较好地实现对发动机转速控制。     

基于非线性模型的发动机非稳态工况控制

针对发动机非稳态工况,建立了非线性模型.设计了滑模控制器和PID控制器分别对节气门开度和点火时刻进行自适应调节.对发动机怠速工况进行仿真的结果表明,发动机转速波动幅值低于6 r/min,表明所建的非线性模型适合于发动机非稳态工况控制.     

考虑发动机与人椅系统的液压半主动悬架振动控制研究

在研究1/2车辆模糊控制半主动悬架的基础上,加入了发动机和人椅系统等因素,建立了"车椅人"1/4车体4自由度车辆动力学模型,设计了用于该车体的参数自整定的模糊PID控制器,并应用MATLAB/SIMULINK软件进行了仿真研究.结果表明,高频恒定的发动机激励对座椅加速度影响较小,模糊PID控制器比模糊控制器具有更强的自...     

模糊PID控制器在机油冷却器检测中的应用

通过利用参数整定PID的模糊控制器对发动机机油冷却器传热性能试验台的温度进行控制。利用模糊控制算法对PID3个参数k_p,k_i,k_d进行整定,以改善其控制性能,并根据实际系统进行仿真。结果表明,此系统能提高温度控制性能,提高了工作效率,简化了操作规程。     

基于模糊自适应PID的智能车辆路径跟踪控制

选取车辆当前位姿和参考位姿来构造车辆的动态位姿误差,建立车辆路径跟踪闭环控制系统的Simulink仿真模型,并设计了模糊自适应PID控制器,利用模糊推理的方法,对PID控制器的参数进行自动调整。利用常规PID和模糊自适应PID控制算法分别进行仿真实验。仿真结果表明,模糊自适应PID改善了控制器的动态性能且具有较好的自适应能力。     

参数自整定PID模糊控制器的设计及Simulink仿真

在传统PID控制器基础上,参数自整定PID模糊控制器应用模糊集合理论建立参数与偏差绝对值和偏差变化绝对值间的二元连续函数关系,并根据不同的偏差及其变化在线自整定PID参数。介绍了具有自整定参数功能的一类PID控制器的设计方法及在轿车行驶仿真中的应用。     

PID plus fuzzy logic method for torque control in traction control system

A Traction Control System (TCS) is used to control the driving force of an engine to prevent excessive slip when a vehicle starts suddenly or accelerates. The torque control strategy determines the driving performance of the vehicle under various drive-slip conditions. This paper presents a new torque control method for various drive-slip conditions involving abrupt changes in the road friction. This method is based on a PID plus fuzzy logic controller for driving torque regulation, which consists of a PID controller and a fuzzy logic controller. The PID controller is the fundamental component that calculates the elementary torque for traction control. In addition, the fuzzy logic controller is the compensating component that compensates for the abrupt change in the road friction. The simulation results and the experimental vehicle tests have validated that the proposed controller is effective and robust. Compared with conventional PID controllers, the driving performance under the proposed controller is greatly improved.     

基于MATLAB的ABS控制仿真研究

ABS是一种变工况、非线性的系统,且建模难度大。分别采用PID控制、模糊PID控制两种方法对单轮汽车模型进行了模拟仿真。其中模糊PID控制可以利用模糊控制规则对PID参数进行在线修改,因而具有较好的自适应能力,可以达到非常好的控制效果。     

基于模糊PID控制的汽车道路模拟系统研究与仿真

根据模糊控制理论,以汽车道路模拟系统为研究对象,将模糊控制与常规的PID控制相结合,设计出一套模糊PID控制系统。并对正弦波、方波以及随机波进行仿真再现,仿真结果表明,该模糊PID控制器比常规PID控制器具有更高的控制精度和更好的动态性能。     

基于自适应模糊PID控制的ABS仿真研究

在Matlab/Simulink中建立一种两轮的汽车动力模型,以自适应模糊PID和道路识别控制器作为控制模块,通过在高低附着路面和高低附着对接路面进行紧急制动仿真的研究。仿真结果表明道路识别控制器能够快速准确的识别路面不同附着路面最优滑移率,自适应模糊PID控制的ABS相于常规制动性能有了很大程度的提高,具有在线自整定参数的特点,具有很好的稳定性、适应性和鲁棒性。     

Application of a self-tuning fuzzy PI–PD controller in an active anti-roll bar system for a passenger car

A fuzzy proportional-integral-derivative (PID) controller has not been widely investigated for active anti-roll bar (AARB) application due to its unspecific mathematical analysis and the derivative kick problem. This paper briefly explains how the derivative kick problem arises due to the nature of the PID controller as well as the conventional fuzzy PID controller in association with an AARB. There are two types of controllers proposed in this paper: self-tuning fuzzy proportional-integral–proportional-derivative (STF PI–PD) and PI–PD-type fuzzy controller. Literature reveals that the PI–PD configuration can avoid the derivative kick, unlike the standard PID configuration used in fuzzy PID controllers. STF PI–PD is a new controller proposed and presented in this paper, while the PI–PD-type fuzzy controller was developed by other researchers for robotics and automation applications. Some modifications were made on these controllers in order to make them work with an AARB system. The performances of these controllers were evaluated through a series of handling tests using a full car model simulated in MATLAB Simulink. The simulation results were compared with the performance of a passive anti-roll bar and the conventional fuzzy PID controller in order to show improvements and practicality of the proposed controllers. Roll angle signal was used as input for all the controllers. It is found that the STF PI–PD controller is able to suppress the derivative kick problem but could not reduce the roll motion as much as the conventional fuzzy PID would. However, the PI–PD-type fuzzy controller outperforms the rest by improving ride and handling of a simulated passenger car significantly.     

基于BP-PID控制器的盾构液压推进控制系统研究

为解决盾构在复杂地层施工时推进速度和压力难以控制的问题,在压力流量控制的基础上提出BP神经网络控制策略。通过AMESim建立推进系统物理模型,并利用Simulink设计出BP神经网络控制器,最后对系统进行联合仿真,分析推进系统液压缸在变流量和变负载工况下推进速度和压力的响应特性。仿真结果表明:该控制策略与常规PID控制相比,波动幅度降低,调节时间快。采用BP神经网络PID控制能够有效地提高盾构在负载突变情况下速度和压力控制精度,稳定性好、适应能力强,为盾构控制系统设计和优化提供理论参考。     

旋转压实仪压实力控制方法研究

采用试验研究为主导,结合相应的理论分析,采取分段控制的模型对旋转压实仪的压实力进行试验仿真研究;利用模糊PID控制的方法对压实力进行控制,解决了常规PID控制方法用于非线性、时变特性的被控对象难于实现实时控制的问题。最后,采用80C196单片机,应用模糊自整定数字控制的方法,设计了旋转压实仪控制器。实际应用结果表明:该控制方法可以提高旋转压实仪的动态响应速度,其压实力的控制精度可以达到设计标准的要求。     

Model-based design of a variable nozzle turbocharger controller

Variable Nozzle Turbocharger (VNT) was invented to solve the problem of matching an ordinary turbocharger with an engine. VNT can harness exhaust energy more efficiently, enhance intake airflow response and reduce engine emissions, especially during transient operating conditions. The difficulty of VNT control lies in how to regulate the position of the nozzle at different engine working conditions. The control strategy designed in this study is a combination of a closed-loop feedback controller and an open-loop feed-forward controller. The gain-scheduled proportional-integral-derivative (PID) controller was implemented as the feedback controller to overcome the nonlinear characteristic. As it is difficult to tune the parameters of the gain-scheduled PID controller on an engine test bench, system identification was used to identify the plant model properties at different working points for a WP10 diesel engine on the test bench. The PID controller parameters were calculated based on the identified first-order-plus-dead-time (FOPDT) plant model. The joint simulation of the controller and the plant model was performed in Matlab/Simulink. The time-domain and frequency-domain performances of the entire system were evaluated. The designed VNT control system was verified with engine tests. The results indicated that the real boosting pressure traced the target boosting pressure well at different working conditions.