基于无传感器的PMSM电流控制策略的研究

提出一种新型的滑模观测器,并分别研究在4种不同的电流控制策略下,基于该新型滑模观测器的PMSM伺服系统的控制问题。该新型滑模观测器引进了Sigmoid函数作为控制函数用来抑制抖振,并根据PMSM的反电动势模型构建了反电势观测器来提取所需的连续信号,因此取消了传统的一阶低通滤波器和相角补偿环节。为了对电机的转子位置和转速进行更加精确的估算,引入了转子位置锁相环结构。在Matlab/Simulink平台基础上建立了4种不同的电流控制策略,基于新型滑模观测器PMSM无位置传感器三闭环控制系统仿真模型,分别对反电动势估算、速度估算、位置估算和突加负载扰动进行了仿真分析。仿真结果表明,该新型滑模观测器在4种不同的电流控制策略下,对电机转子位置和转速的估算、电磁转矩以及定子三相电流有着不同的影响,验证了该新型滑模观测器算法的可行性。     

基于多项式混沌理论的感应电机自愈控制系统

针对感应电机控制系统中速度传感器故障提出了一种自愈控制方法.考虑转子电阻不确定性,基于多项式混沌理论(PCT),对定子电流模型进行扩展,再利用扩展Kalman滤波法,设计定子电流观测器,并在此基础上设计速度自适应估计器.当传感器正常时,利用电流观测器观测值进行状态监测;传感器发生故障后,系统利用估计转速代替传感器信号作为新的反馈,保证系统的连续运行,实现了对系统的自愈控制.仿真结果验证了该方法的有效性.     

载重轮胎硫化过程的故障诊断

硫化过程是载重轮胎生产工艺中非常重要的一步,硫化质量的好坏对轮胎的质量起举足轻重的作用。在实际生产过程中,高温蒸汽有可能损伤阀门,使阀门泄漏而产生故障。因此,建立载重轮胎硫化生产过程的故障诊断,以便能及时、正确地对异常状态和故障状态做出诊断和预防,提高设备运行的可靠性、安全性和有效性,把故障损失降低到最低水平。首先,对轮胎硫化生产过程进行了分析,利用橡胶轮胎硫化实时监控系统所采集到的相关数据,采用参数估计法建立了硫化过程的数学模型。在此模型的基础上设计状态观测器,比较无故障和有故障的残差信号以判断有无故障发生,从而实现了轮胎硫化生产过程的故障诊断。最后仿真结果表明,当轮胎硫化过程中出现故障时,该方法可以有效地实现对故障的诊断。     

基于滑模观测器和神经网络的传感器故障诊断方法比较研究

针对航空发动机传感器故障诊断中各种方法的优势和劣势,选择滑模观测器和神经网络这两种故障诊断方法分别对航空发动机转速传感器进行故障诊断研究,采用实验室搭建的发动机实验台DGEN380的实验数据,选择对航空发动机控制系统影响较大的偏置故障、漂移故障、脉冲故障、周期性干扰故障这四类传感器故障进行诊断。研究结果表明,滑模观测器和IPSO-BP神经网络都能实现航空发动机传感器的故障诊断;滑模观测器方法可以诊断出偏置故障、脉冲故障和周期性干扰故障,但不能诊断出传感器发生的漂移故障;IPSO-BP神经网络方法可以诊断出偏置故障、漂移故障、脉冲故障和周期性干扰故障。因此,滑模观测器在故障诊断中可能会出现漏诊的现象,IPSO-BP神经网络相对滑模观测器而言不会出现漏诊的现象。     

一种新型的轮胎力级联估计方法

为了增强车辆主动安全性和底盘的集成控制,根据干扰输入观测器理论,基于简化的车轮动力学模型设计估计器,对每个轮胎纵向力进行估计.此外,基于"自行车"模型,利用车辆动力学,在纵向轮胎力估计值的基础上估计轮胎侧向力.涉及到的车载传感器测量值包括发动机扭矩和转速、轮缸压力、车轮角速度、方向盘转角、侧向加速度和横摆角速度.为验证轮胎力级联估计方法的有效性,应用高保真的车辆动力学软件ve DYNA进行了仿真研究,并与扩展卡尔曼滤波(extended Kalman filter,EKF)方法作对比分析.实验结果表明,轮胎力级联估计方法能够获得车辆轮胎力的估计效果.     

具有积分测量和时延的离散线性变参数系统故障与状态估计

故障检测与诊断(FDD)技术可以有效地提高系统的安全性和可靠性,因此受到越来越多的关注.目前,关于离散系统的状态和故障估计问题的研究还不够充分.本文针对具有积分测量和时延的线性变参数(LPV)系统,提出了一种同时估计执行器/传感器故障和状态的方法.首先,系统当前状态、系统延迟状态和传感器故障构造一个扩维状态,得到广义离散LPV系统.其次,给出了该观测器存在的充分条件并证明观测器是H∞稳定的.然后,将系统状态、执行器和传感器故障的同时估计转化为矩阵不等式的求解问题,给出了观测器待设计矩阵的计算过程.最后,通过仿真验证了该方法的有效性.     

基于滑模观测器的电流传感器故障监测系统设计

为了保证电流传感器的工作效率,为设备维护提供有效参考,利用滑模观测器优化设计了电流传感器故障监测系统。加设滑模观测器,改装数据采集器、信号处理器等设备,调整系统的电路连接方式,在抗干扰约束下,完成硬件系统的优化设计。根据电流传感器的工作原理和故障特征,构建电流传感器故障数学模型。利用滑模观测器及其逻辑原理,实时收集电流传感器的运行信号。根据传感器故障特征,选择并计算电流传感器的故障监测指标,通过与设置故障标准的比对,输出可视化的电流传感器故障监测结果。通过系统测试实验得出,基于滑模观测器的电流传感器故障监测系统的指标监测误差、故障类型误检率和漏检率均低于预设值,由此证明优化设计系统具有良好的故障监测功能。     

基于高增益鲁棒滑模观测器的故障检测和隔离

针对一类同时具有执行器和传感器故障的不确定线性系统,讨论了基于观测器的故障检测和隔离方法.首先,通过引入增维向量,使得在构造的增维系统中,故障向量包含了原系统的执行器故障和传感器故障.通过构造辅助输出使增维系统的观测器匹配条件得以满足,同时设计高增益滑模观测器对辅助输出进行估计.然后,对增维系统构造鲁棒滑模观测器并用作故障检测观测器,通过滑模控制项来抑制干扰,使观测器具有鲁棒性.在此基础上,结合多观测器故障隔离思想,提出了可以同时对执行器故障和传感器故障进行检测和隔离的方法. 最后,通过对一个五阶飞行器模型进行仿真,证明了所提方法的有效性.     

液位传感器容错控制方法研究

传统的PID(比例-积分-微分)控制法在液位过程控制中占据主要地位,但由于液位控制系统,特别是其系统传感器容易发生故障,使得PID控制法具有抗故障能力不足的缺陷,对生产生活造成重大损失,因此需采用容错控制方法使得液位传感器发生故障时仍能较为正常运行,提出状态观测器估计传感器液位故障值的容错控制方法,使状态观测器对故障状态产生观测跟踪,将故障状态作用于原控制器,并使原控制器弃置已经存在故障的传感器信号,使得故障值被抵消。     

风力机系统基于H_/H∞未知输入观测器的故障诊断

针对实际工程中风力机传动系统未知输入难以完全解耦的问题,提出基于H_-/H_∞未知输入观测器(unknown input observer, UIO)故障诊断方法.首先,利用未知输入观测器的等式条件将未知输入分解为可解耦与不可解耦两部分,且将可解耦部分从估计误差中消除.其次,利用H_-/H_∞性能指标设计未知输入观测器的残差产生器,使残差对未知输入中不可解耦部分具有鲁棒性并对故障信号具有敏感性,并通过引入松弛矩阵解决观测器参数设计过程中的保守问题.考虑残差信号的随机特性,采用统计理论确定故障检测阈值.经仿真验证,该方法可对风力机传动系统传感器加性故障和乘性故障进行有效诊断.     

Estimation of road frictional force and wheel slip for effective antilock braking system (ABS) control

The introduction of electric braking via brake‐by‐wire systems in electric vehicles) has reduced the high transportation delays usually involved in conventional friction braking systems. This has facilitated the design of more efficient and advanced control schemes for antilock braking systems (ABSs). However, accurate estimation of the tire‐road friction coefficient, which cannot be measured directly, is required. This paper presents a review of existing estimation methods, focusing on sliding‐mode techniques, followed by the development of a novel friction estimation technique, which is used to design an efficient ABS control system. This is a novel slip‐based estimation method, which accommodates the coupling between the vehicle dynamics, wheel dynamics, and suspension dynamics in a cascaded structure. A higher‐order sliding‐mode observer–based scheme is designed, considering the nonlinear relationship between friction and slip. A first‐order sliding‐mode observer is also designed based on a purely linear relationship. A key feature of the proposed estimation schemes is the inclusion of road slope and the effective radius of the tire as an estimated state. These parameters impact significantly on the accuracy of slip and friction estimation. The performance of the proposed estimation schemes are validated and benchmarked against a Kalman filter (KF) by a series of simulation tests. It is demonstrated that the sliding‐mode observer paradigm is an important tool in developing the next generation ABS systems for electric vehicles.     

Vehicle state estimation for anti-lock control with nonlinear observer

Vehicle state estimation during anti-lock braking is considered. A novel nonlinear observer based on a vehicle dynamics model and a simplified Pacejka tire model is introduced in order to provide estimates of longitudinal and lateral vehicle velocities and the tire-road friction coefficient for vehicle safety control systems, specifically anti-lock braking control. The approach differs from previous work on vehicle state estimation in two main respects. The first is the introduction of a switched nonlinear observer in order to deal with the fact that in some driving situations the information provided by the sensor is not sufficient to carry out state estimation (i.e., not all states are observable). This is shown through an observability analysis. The second contribution is the introduction of tire-road friction estimation depending on vehicle longitudinal motion. Stability properties of the observer are analyzed using a Lyapunov function based method. Practical applicability of the proposed nonlinear observer is shown by means of experimental results.     

防抱制动系统滑模状态观测和控制系统仿真

该文在考虑不平路面随机激励作用下车辆垂向振动的基础上 ,首先建立了四分之一车辆制动模型 ,而后充分运用滑移模式变结构的分析和设计方法 ,提出了车轮最佳滑移率的滑模实时在线辨识滑模优化算法 ,在对系统可观测性论证的基础上 ,设计了非线性滑模状态观测器 ,给出了单通道防抱制动系统基于滑移率的滑模控制算法 ,通过计算机仿真 ,验证了该控制算法的可行性和有效性 ,为设计具有高鲁棒性的防抱制动系统做了一定的理论探索和仿真工作     

Adaptive neuro-fuzzy wheel slip control

Due to complex and nonlinear dynamics of a braking process and complexity in the tire–road interaction, the control of automotive braking systems performance simultaneously with the wheel slip represents a challenging problem. The non-optimal wheel slip level during braking, causing inability to achieve the desired tire–road friction force strongly influences the braking distance. In addition, steerability and maneuverability of the vehicle could be disturbed. In this paper, an active neuro-fuzzy approach has been developed for improving the wheel slip control in the longitudinal direction of the commercial vehicle. The dynamic neural network has been used for prediction and an adaptive control of the brake actuation pressure, during each braking cycle, according to the identified maximum adhesion coefficient between the wheel and road surface. The brake actuation pressure was dynamically adjusted on the level that provides the optimal level of the longitudinal wheel slip vs. the brake pressure selected by driver, the current vehicle speed, the brake interface temperature, vehicle load conditions, and the current value of longitudinal wheel slip. Thus the dynamic neural network model operates (learn, generalize and predict) on-line during each braking cycle, fuzzy logic has been integrated with the neural model as a support to the neural controller control actions in the case when prediction error of the dynamic neural model reached the predefined value. The hybrid control approach presented here provided intelligent dynamic model – based control of the brake actuation pressure in order to keep the longitudinal wheel slip on the optimum level during a braking cycle.     

高速AWID车辆车轮独立制动控制研究

全部车轮均独立驱动/制动(AWID)的车辆比非独立驱动/制动的车辆在高速工况下具有更优越的动力、机动和操纵性能,论文对车轮独立制动控制问题进行研究;首先建立车轮独立制动的数学模型,简单介绍轮胎LuGre动态模型;然后分析制动控制的目标,设计控制系统结构和自抗扰控制器;最后对动态期望滑移率下的车轮制动控制进行仿真;结果表明,所设计的自抗扰控制器可以实现强鲁棒和高精度的车轮独立制动控制。     

Tire lateral force estimation and grip potential identification using Neural Networks,Extended Kalman Filter,and Recursive Least Squares

This paper presents a novel hybrid observer structure to estimate the lateral tire forces and road grip potential without using any tire–road friction model. The observer consists of an Extended Kalman Filter structure, which incorporates the available prior knowledge about the vehicle dynamics, a feedforward Neural Network structure, which is used to estimate the highly nonlinear tire behavior, and a Recursive Least Squares block, which predicts the road grip potential. The proposed observer was evaluated under a wide range of aggressive maneuvers and different road grip conditions using a validated vehicle model, validated tire model, and sensor models in the simulation environment IPG CarMaker ^®. The results confirm its good and robust performance.

     

Observer based estimation of parameter variations and its application to tyre pressure diagnosis

This paper deals with an estimation method of parameter variations of dynamic systems based on the disturbance observer. The disturbance observer is designed to estimate the parameter variations as disturbances. The simple least squares method can extract the parameter variations from the estimated disturbances which include external disturbances and noise. The proposed method is applied to the tyre pressure diagnosis system which can detect underinflated tyres in every situation such as a puncture and natural leaks using wheel speed sensors already provided for anti-lock brake system. Several experimental results are shown to confirm the effectiveness of the method.     

Estimation of vehicle sideslip, tire force and wheel cornering stiffness

This paper presents a process for the estimation of tire–road forces, vehicle sideslip angle and wheel cornering stiffness. The method uses measurements (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities) only from sensors which can be integrated or have already been integrated in modern cars. The estimation process is based on two blocks in series: the first block contains a sliding-mode observer whose principal role is to calculate tire–road forces, while in the second block an extended Kalman filter estimates sideslip angle and cornering stiffness. More specifically, this study proposes an adaptive tire-force model that takes variations in road friction into account. The paper also presents a study of convergence for the sliding-mode observer. The estimation process was applied and compared to real experimental data, in particular wheel force measurements. The vehicle mass is assumed to be known. Experimental results show the accuracy and potential of the estimation process.     

基于UIO的EPS系统状态反馈最优控制

准确地获知电动助力转向（Electric powering steering,EPS）系统阻力矩是提高行车安全的一个重要因素.针对车辆转向过程中,由不同附着路面上EPS 系统所需辅助力矩与转向路感之间的差别而可能导致的误操纵问题,本文基于2自由度整车动力学的EPS系统模型,结合轮胎特性,以轮胎侧偏角和理想路面附着系数为输入,通过设计非线性观测器估计当前路面的附着系数,以获取EPS系统阻力矩;进而,根据EPS 系统模型,运用未知输入观测器（Unknown input observer,UIO）估算方向盘输入转矩,并基于EPS系统状态反馈以实现对EPS系统的无传感器最优控制.最后,对基于永磁同步电机（Permanent magnet synchronous motor,PMSM）的EPS系统进行仿真实验分析.结果表明: 在以电机q轴电流闭环误差最小为指标函数情形下,本设计的方向盘回正残留角从25°降到0°,能有效抑制系统外界干扰,提高了转向时人-车系统的鲁棒性.     

基于模糊控制的汽车防抱制动系统仿真

汽车防抱制动系统(ABS)通过在制动过程中自动控制车轮的制动力矩从而防止了车轮抱死。这对于提高汽车制动时的方向稳定性和转向操纵性，改善汽车的制动效能，保证驾驶员和乘客的安全是十分重要的。文中通过对某轻型客车的防抱制动过程进行动力学分析，建立了该轻型客车ABS模糊控制系统的数学模型，并且在Matlab／simullnk仿真软件下进行了计算机仿真。仿真结果表明，模糊控制的防抱制动系统能取得较好的控制效果，具有一定的自适应能力。