天然气发动机氧传感器驱动及故障诊断策略设计

氧传感器温度控制是空燃比精确反馈的重要条件,是发动机提高燃料利用率的重要手段。本文在常规温度 PID 驱动控制的基础上,设计了氧传感器诊断控制策略,包括信号处理模块、模式选择模块及故障检测模块。同时基于开放式控制器,在快速原型测试试验台上对PID控制参数进行整定。最后在一台大功率气体发动机上进行台架实验,实验结果表明本文所设计的控制和诊断策略能快速准确地控制氧传感器温度,使其更准确地反应稳态和瞬态空燃比,并得出了不同的温度控制精度对空燃比数值的影响。     

煤层气发动机空燃比 PID 迭代学习控制

煤层气发动机优化控制问题,对预混合双阀控制,煤层气发动机空燃比前馈控制查询表需要稳态标定试验得到,传统的方法是进行反复的测试和离线修正来获得最优控制数据.为了降低试验工作量及其耗费,提出了反馈信息在线校正前馈控制脉谱的方法,采用迭代学习控制技术,分别设计了 PID 和模糊自适应整定控制器.利用辨识的发动机稳态模型,研究了不同初始状态下两种学习控制器的收敛性能和稳态空燃比校正效果.仿真结果表明,模糊自适应整定 PID 学习控制算法具有较快的收敛速度和较小的学习误差,更适合煤层气发动机位置控制参数的在线应用.     

基于H_∞理论的LPG发动机空燃比控制系统研究与开发

针对燃气发动机实际运行工况,采用开环与闭环相结合的控制策略,建立燃气发动机空燃比系统模型,研究H∞混合灵敏度空燃比闭环控制系统的设计方法,开发了基于嵌入式操作系统的电控单元软件与硬件,将发动机的空燃比精确控制在理论值,在NJG415P发动机上进行台架试验,试验结果表明,燃油消耗率满足要求,控制系统工作稳定可靠,当发动机工作环境变化和长期使用情况下,仍能够保证空燃比控制系统具有良好的性能。     

天然气发动机空燃比智能控制策略的研究

该文详细介绍了基于神经网络的控制器在天然气发动机空燃比中的控制实现，并用Matlab进行了仿真，仿真结果表明，其控制效果优于基于PID的控制器，所研究的基于单神经元控制器的学习算法在工程上易于实现，在发动机空燃比控制的工程应用中有很好的前景。     

基于dSPACE的宽带型废气氧传感器控制器设计

宽带型废气氧(UEGO)传感器在稀燃发动机混合气空燃比控制中起着极其重要的作用,它在工作过程中的电流和温度等信号需要进行控制.研究了基于dSPACE的UEGO传感器控制器的设计,详细介绍了加热驱动、温度检测及泵电流测量等硬件电路,并利用数字PID实现泵电流的反馈控制.通过在发动机台架上实验,结果表明:设计的控制器能在较宽范围内较好地检测混合气空燃比变化.     

汽油机非线性卡尔曼滤波暂态进气量估计及空燃比控制

暂态工况下缸进气量的准确估计是提高发动机空燃比控制精度的有效措施之一,为此本文提出一种基于无迹卡尔曼滤波的暂态缸进气量估计算法,并利用估计的缸进气量设计了一种前馈-反馈空燃比控制器.MATLAB环境下的仿真实验给出了所提出的算法与现有进气量估计算法的比较,同时基于暂态气量估计的空燃比控制仿真实验验证了估计的有效性.论文与现有成果的区别在于:一是暂态进气量估计模型不仅包含了歧管压力动态还考虑了曲轴角速度动态,并采用了基于非线性辨识的均值模型;二是考虑了泵气波动的影响,采用了移动平均值法的数字滤波器对泵气波动进行滤波;三是采用无迹卡尔曼滤波算法对歧管压力和曲轴角速度进行估计.     

某特种动力发动机控制器设计

以某特种固体火箭发动机研制为工程应用背景,基于DSP+ FPGA主协处理器方案设计了发动机控制器,安全可靠地完成了发动机转级控制,基于PID控制方案实现燃气发生器压强闭环控制.该发动机控制器完成了大量发动机地面试车试验.试验结果表明系统具有使用方便、稳定性高等特点,为该发动机的探索研究建立起了工程实用的压强控制实验装置.     

基于二阶滑模的汽油机瞬态空燃比控制

为克服瞬态工况下油膜动态特性对空燃比控制精度的影响,提出了一种二阶滑模空燃比控制策略。通过对发动机平均值模型的分析,确定其作为单输入单输出(SISO)系统的非线性形式,设计了基于Super-twisting算法的二阶滑模空燃比控制器并运用Matlab建模仿真。仿真结果表明,基于Super-twisting算法的二阶滑模控制器鲁棒性强;与PID控制器和一阶滑膜控制器相比较,控制精度和速度明显提高。     

基于IMC-PID的超临界火电机组AGC性能优化北大核心CSCD

自动发电控制(AGC)功能要求火电机组的负荷响应具有较快的速度和较高的控制精度。常规的AGC采用基于PID的前馈-反馈控制策略,当电网AGC模式改变时,常规AGC策略的性能可能发生恶化乃至引起考核。为了全面优化火电机组的AGC性能,设计了一种基于内模控制PID(IMC-PID)的前馈-反馈功率控制回路,通过构建调节级压力-负荷的传递函数引入内模,在考虑分散控制系统离散控制特性和发电机响应特性的基础上实现控制回路参数整定。最后,将该策略应用在某660 MW超临界机组,结果表明机组AGC性能得到显著提升。     

超燃冲压发动机PID解耦控制设计

针对超燃冲压发动机控制通道间的强耦合性及其控制过程的快速性要求,研究设计了超燃冲压发动机分路式PID解耦控制器;该方法采用零极点配置技术,设计了稳定的前馈补偿解耦器,并利用此解耦器对超燃冲压发动机模型进行解耦;对解耦后的控制对象设计了每个控制回路的PID控制器,实现分路式控制;仿真结果表明,所设计的解耦器比静态解耦器更能有效地解决发动机耦合问题,控制器控制效果满足控制精度和快速性要求;该方法简单实用对超燃冲压发动机的控制器设计有借鉴意义。     

A parameter-varying filtered PID strategy for air–fuel ratio control of spark ignition engines

In this paper, a new synthesis method is presented to control air–fuel ratio (AFR) in spark ignition engines to maximize the fuel economy while minimizing exhaust emissions. The major challenge in the control of AFR is the time-varying delay in the control loop which restricts the application of conventional control techniques. In this paper, the time-varying delay in the system dynamics is first approximated by Padé approximation to render the system dynamics into non-minimum phase characteristics with time-varying parameters. Application of parameter-varying dynamic compensators is invoked to retrieve unstable internal dynamics. The associated error dynamics is then utilized to construct a filtered PID controller combined with a parameter-varying dynamic compensator to track the desired AFR command using the feedback from the universal exhaust gas oxygen sensor. The proposed method achieves desired dynamic properties independent of the matched disturbances. It also accommodates the unmatched perturbations due to the dynamic compensator features. The results of applying the proposed method to experimental numerical data demonstrate the closed-loop system stability and performance against time-varying delay, canister purge disturbances and measurement noise for both port fuel injection engines and lean-burn engines.     

网络控制系统PI预测控制及稳定性分析

将PID反馈原理引入广义预测控制（GPC）思想,把GPC目标性能函数改造成具有PI的结构形式,根据反馈时延导出多步控制序列,通过时延补偿器对前向时延进行补偿,使控制性能在网络环境下得到极大改善。控制器结合了PID控制和预测控制的优点,具有较强的鲁棒性和工程意义。构造Lyapunov函数对闭环系统的稳定性进行分析,并通过仿真验证了该算法的有效性。     

网络控制系统的自整定PID 控制器设计

结合广义预测控制（GPC）方法和PID反馈结构,设计了一种具有预测功能的PID控制器,PID参数根据未来时刻的预计输出误差进行整定.控制器导出多步控制序列,置于执行器端的延迟补偿器根据网络时延从控制序列中选择控制信息并作用于控制对象,从而对时延进行补偿,使控制性能得到极大改善.控制器结合了PID控制和预测控制的优点,具有较强的鲁棒性和工程意义.最后通过构造Lyapunov函数对闭环系统的稳定性进行了分析,并通过仿真验证了该算法的有效性.     

Online linearization-based neural predictive control of air–fuel ratio in SI engines with PID feedback correction scheme

Model predictive control (MPC) frequently uses online identification to overcome model mismatch. However, repeated online identification does not suit the real-time controller, due to its heavy computational burden. This work presents a computationally efficient constrained MPC scheme using nonlinear prediction and online linearization based on neural models for controlling air–fuel ratio of spark ignition engine to its stoichiometric value. The neural model for AFR identification has been trained offline. The model mismatch is taken care of by incorporating a PID feedback correction scheme. Quadratic programming using active set method has been applied for nonlinear optimization. The control scheme has been tested on mean value engine model simulations. It has been shown that neural predictive control with online linearization using PID feedback correction gives satisfactory performance and also adapts to the change in engine systems very quickly.     

Reconstruction of cylinder pressure for SI engine using recurrent neural network

Model predictive control (MPC) frequently uses online identification to overcome model mismatch. However, repeated online identification does not suit the real-time controller, due to its heavy computational burden. This work presents a computationally efficient constrained MPC scheme using nonlinear prediction and online linearization based on neural models for controlling air–fuel ratio of spark ignition engine to its stoichiometric value. The neural model for AFR identification has been trained offline. The model mismatch is taken care of by incorporating a PID feedback correction scheme. Quadratic programming using active set method has been applied for nonlinear optimization. The control scheme has been tested on mean value engine model simulations. It has been shown that neural predictive control with online linearization using PID feedback correction gives satisfactory performance and also adapts to the change in engine systems very quickly.     

Closed-loop individual cylinder air–fuel ratio control via UEGO signal spectral analysis

The paper presents the development and real time application of an original closed-loop individual cylinder AFR control system, based on a spectral analysis of the lambda sensor signal. The observation that any type of AFR disparity between the various cylinders is reflected in a specific harmonic content of the AFR signal spectrum, represents the starting point of the project. The results observed on a 4 cylinder Spark Ignition engine are encouraging, since in the investigated engine operating conditions the controller is able to reduce AFR inequality below 0.01 lambda. The paper also shows how the proposed controller can be applied to other engine configurations.     

鲁棒PID算法在船舶柴油机控制中应用

基于闭环增益成形算法给出鲁棒PID算法,并将之应用于船舶柴油机的控制中。从仿真结果可知,该算法的控制性能和鲁棒稳定性良好,算法简单、实用。     

Simple adaptive air-fuel ratio control of a port injection SI engine with a cylinder pressure sensor

The problem of air-fuel ratio(AFR) control of the port injection spark ignition(SI) engine is still of considerable importance because of stringent demands on emission control. In this paper, the static AFR calculation model based on in-cylinder pressure data and on the adaptive AFR control strategy is presented. The model utilises the intake manifold pressure, engine speed, total heat release, and the rapid burn angle, as input variables for the AFR computation. The combustion parameters, total heat release,and rapid burn angle, are calculated from in-cylinder pressure data. This proposed AFR model can be applied to the virtual lambda sensor for the feedback control system. In practical applications, simple adaptive control(SAC) is applied in conjunction with the AFR model for port-injected fuel control. The experimental results show that the proposed model can estimate the AFR, and the accuracy of the estimated value is applicable to the feedback control system. Additionally, the adaptive controller with the AFR model can be applied to regulate the AFR of the port injection SI engine.     

航空发动机MIMO系统的闭环辨识与故障诊断算法

针对航空发动机结构复杂、易发生故障的特点以及机理分析建模方法存在过程繁琐、运算效率低下等问题,提出了一种基于数据的航空发动机燃油机构MIMO(multiple-input multiple-output)闭环系统的参数辨识和故障诊断算法.算法先通过估计辅助模型系统的阶次间接求得时延参数,再通过多阶段最小二乘算法辨识得到前向通道和反馈通道的参数.以某型双轴涡扇航空发动机为例进行验证.结果表明,在应用中辨识结果与系统真值基本吻合,当遗忘因子取值随辨识结果的收敛程度变化时,算法可以有效地应用于气路故障的诊断当中,及时辨识出故障参数值.最后,对算法的两方面特点进行了说明:一是遗忘因子选取的重要性及选取的原则,二是算法可以有效排除噪声对辨识结果带来的干扰.