交流矢量控制负载转矩智能观测器设计

从专家系统与观测器设计理论方法相结合的思想出发,研讨了一种交流矢量控制负载转矩智能观测器的设计方法,论述了设计方法的基本要求。并以重构交流矢量控制系统负载力矩为例,给出了设计过程和步骤。并用重构的负载扰动作为前馈补偿控制。仿真和实验结果表明,给出的方法不仅能很好地处理观测对象的非线性,而且对参数变化有很强的自校正能力。     

一种双滑模观测器的异步电机转矩闭环控制方法研究

为了提高异步电机的转矩控制精度,提出了一种基于双滑模观测器的异步电机转矩闭环控制方法。首先构建了一种反电动势滑模观测器的数学模型,该模型实现了反电动势的观测;同时,设计了一种磁链滑模观测器并采用数学模型表达,实现了磁链观测。然后,根据李雅普诺夫稳定性理论分析了所设计的滑模观测器的稳定性,并进一步研究了所设计的观测器的参数鲁棒性。然后对其进行仿真研究,其仿真表明,所设计的磁链观测方法和转矩闭环控制系统具有较强的参数鲁棒性,能够为异步电机的工程应用提供一定参考。     

DC-DC变换器Delta域状态观测器的设计

研究了利用Delta算子方法设计混杂动态系统观测器的方法.由BuCK DC-DC变化器的两个子线性模型推导出平均模型,并利用Delta算子方法设计观测器,并用Matlab进行了仿真.     

基于改进型全维观测器的 BLDC 无传感器控制

对基于全维观测器的无刷直流电机无传感器控制算法进行了研究,针对现有的传统全维观测器存在响应慢的问题,提出了一种改进型全维观测器,在传统全维观测器基础上,通过引入反馈增益,以提高动态响应能力和系统稳定性。为了验证提出方案的正确性,搭建相应的测试平台进行了传统和新型观测器的性能对比测试。由实验结果可知,所提出的改进型全维观测器无传感器控制算法能使系统响应更快,是实现无刷直流电机无传感器高速高响应控制的一种有效方法。     

一种感应电机参数自适应转子磁链观测器的设计

为了解决“感应电机运行过程中由电机参数变化引起的转子磁场定向不准确”的问题,根据龙贝格观测器原理提出了一种新颖的参数自适应转子磁链观测器。首先论述了观测器的设计原理,针对磁链误差无法获得这一问题提出了一种有效的解决方案,引入了新变量,然后根据Lyapunov稳定性原理设计小参数自适应律。最后分别在Matlab和DSP2812平台上对该算法的参数收敛性以及定子电阻误差对观测器的影响进行了验证。仿真和实验结果表明,该方法不但可以对转子磁链加以观测,还可以同时在线调整并辨识转子电阻以及转子时间常数,对定子电阻具有很强的鲁棒性。     

一类混合时滞系统的观测器设计

对于一类具有状态和有限自动机输出时滞的离散混合系统,给出了混合观测器的设计方法。观测器由一个位置观测器和一个离散状态观测器组成。前者应用自动机观测器来确定混合系统的当前位置,后者应用龙伯格观测器对系统离散状态的演化进行估计。对于每一个独立的观测器,系统的信息往往不完全,为了在这种情况下仍能应用混合观测器对系统进行观测,在两类独立观测器的基础上给出了一个新的信号产生器,将两类观测器有机结合起来。同时给出了信号产生器中决策函数的充分条件,进一步得到了整个混合观测器指数收敛的充分条件。保证该混合观测器能在有限步内判断出系统的当前位置,同时指数收敛于真实离散时间状态。最后,给出了仿真例子说明设计方法的可行性和有效性。     

基于自适应降阶观测器的感应电机无速度传感器矢量控制研究

针对稳定的感应电机无速度传感器转子磁链观测器和转速自适应律难以设计的问题,研究了基于转子反电动势矢量误差、位于观测转子磁链矢量定向的同步坐标系上的自适应降阶观测器。对降阶观测器和转速自适应律的结构进行了分析,通过合理设置二者的收敛速度,实现了转子磁链观测与转速估计的解耦,简化了转速自适应律的形式和降阶观测器的稳定性分析;同时结合小信号分析,提出了降阶观测器的稳定增益整定方法;在基于DSP的数字控制平台上搭建了感应电机无速度传感器矢量控制系统并进行了实验。研究结果表明:自适应降阶观测器可以在较大的速度范围内稳定运行,且具有良好的动态、稳态和抗扰性能。     

基于极小化条件数的电液伺服控制系统观测器设计

设计良好的状态观测器是电液伺服控制系统故障诊断研究的关键。本文提出一种电液伺服控制系统观测器设计的新方法。针对所构建的位置伺服系统,建立系统的离散非线性模型,绘制系统的离散观测器结构,推导极小化条件数梯度下降法的算法流程并运用该算法优化计算观测器的增益矩阵和Lipschitz常数,为系统设计一个Lipschitz非线性离散观测器。将该观测器与现有的电液伺服控制系统观测器进行比较,发现本文所采用的方法具有计算简单、设计优良等特点。     

基于多观测器的力反馈装置反向驱动补偿研究

针对力反馈主手反向驱动存在阻力的问题,提出了一种基于多观测器相结合的控制方法,即以单支链模型为研究对象,设计了两个状态观测器进行反向驱动补偿研究。一个是基于广义惯量的扰动观测器,用于对扰动力进行估计;另一个是全维速度观测器,用于对速度进行估计。在MATLAB/Simulink中搭建仿真实验环境,通过仿真实验验证了补偿方法的有效性。最后基于该方法进行了力反馈主手的反向驱动补偿实验。实验结果表明:反向驱动力减小了70%以上,力反馈主手的反向驱动性能得到了显著提高。     

光电稳定平台中高阶扰动观测器的应用

由于光电稳定平台在稳定视轴时易受到摩擦、风阻、不平衡以及载体扰动等干扰力矩的影响,本文研究了利用高阶扰动观测器抑制扰动力矩的机理和方法。该扰动观测器由控制对象的逆模型和进行了高阶设计的改进型滤波器组成。提出的方法将观测量作为电流环的输入,利用电流环超高的控制带宽抑制扰动力矩。对系统的扰动抑制能力进行了仿真,结果显示高阶扰动观测器对高阶扰动模型具有很好的抑制能力:对于阶跃扰动和斜坡扰动,三阶扰动观测器的抑制率为100%;对于抛物波扰动,三阶扰动观测器的抑制率为99.9999996%。另外,观测器对于控制对象模型的摄动具有很好的鲁棒性。提出的方法可以在提高伺服系统响应速度的同时保证系统的鲁棒性,满足光电稳定平台的应用要求。     

Disturbance observer based fault estimation and dynamic output feedback fault tolerant control for fuzzy systems with local nonlinear models

This paper addresses the problems of fault estimation (FE) and fault tolerant control (FTC) for fuzzy systems with local nonlinear models, external disturbances, sensor and actuator faults, simultaneously. Disturbance observer (DO) and FE observer are designed, simultaneously. Compared with the existing results, the proposed observer is with a wider application range. Using the estimation information, a novel fuzzy dynamic output feedback fault tolerant controller (DOFFTC) is designed. The controller can be used for the fuzzy systems with unmeasurable local nonlinear models, mismatched input disturbances, and measurement output affecting by sensor faults and disturbances. At last, the simulation shows the effectiveness of the proposed methods.     

基于扩张状态观测器的故障诊断方法研究

在分析现有基于观测器故障诊断方法的基础上,提出基于扩张状态观测器(ESO)故障诊断新方法.该方法利用ESO估计出系统的动态特性,完成对动态系统的故障检测与识别,同时,由于ESO只依赖于系统的输入参数b.和观测器的整定参数ω,因而具有很强的鲁棒性.最后,借助于三水箱非线性动态系统验证了算法的有效性.     

State and actuator fault estimation observer design integrated in a riderless bicycle stabilization system

This paper deals with an observer design for Linear Parameter Varying (LPV) systems with high-order time-varying parameter dependency. The proposed design, considered as the main contribution of this paper, corresponds to an observer for the estimation of the actuator fault and the system state, considering measurement noise at the system outputs. The observer gains are computed by considering the extension of linear systems theory to polynomial LPV systems, in such a way that the observer reaches the characteristics of LPV systems. As a result, the actuator fault estimation is ready to be used in a Fault Tolerant Control scheme, where the estimated state with reduced noise should be used to generate the control law. The effectiveness of the proposed methodology has been tested using a riderless bicycle model with dependency on the translational velocity v, where the control objective corresponds to the system stabilization towards the upright position despite the variation of v along the closed-loop system trajectories.     

一类非线性系统的执行器偏差故障检测与诊断

针对一类具有系统建模误差以及含传感器模型不确定项的非线性控制系统，本文提出了一种用于执行器故障检测与诊断的观测器方法。观测器中引入了自适应补偿项，当出现偏差后将对故障及建模不确定项进行补偿。自适应算法中采用了死区算子，增强了算法的鲁棒性。利用自适应阈值进行故障检测，同时利用自适应律进行偏差估计。仿真结果表明了该方法的有效性。     

双星编队构形保持抗干扰容错控制

为解决系统模型误差、外部干扰以及执行器故障引起的双星编队轨道控制精度低、稳定性差问题,设计一种基于观测器的抗干扰容错线性二次型调节器(LQR)控制策略。首先,根据编队双星相对运动动力学模型,设计基于双比例积分自适应律的增广观测器,同时实现对系统状态、间歇故障与快速时变故障、可建模干扰的快速精确估计,并采用H∞优化技术抑制不可建模干扰对控制系统的影响。其次,采用Lyapunov稳定性理论,保证动态误差系统渐近稳定。然后,在控制器中引入未知动态估计信息的前馈补偿项,设计闭环反馈抗干扰容错LQR控制律。最后实验结果表明,相比文献中控制方法,本文所提方法的编队卫星相对位置控制精度提高49.93%,验证了所设计的抗干扰容错LQR控制律的优越性,能够为双星编队构形保持提供精确控制策略。     

Reduced-order observer based fault estimation and fault-tolerant control for switched stochastic systems with actuator and sensor faults

This paper addresses the problems of fault estimation and fault-tolerant control for a class of switched stochastic systems with sensor and actuator faults. A reduced-order fault estimation observer is designed to estimate the system states, actuator and sensor faults, simultaneously. In the observer design process, intermediate variables are introduced such that the differential information of the measurement output is not included in the designed observer. Compared with the existing results, the dimension of the proposed observer is reduced, and the sensor fault can be completely unknown and unbounded. An observer based fault-tolerant controller is designed to stabilize the switched stochastic systems. Under arbitrary switching signal, the designed observer and controller can ensure that both the estimation error system and the closed-loop system are mean-square exponentially stable with disturbance attenuation performance. At last, both a numerical example and a switched electrical circuit example verify the proposed method.     

采用滑模观测器的机械臂故障检测与控制优化

针对复合干扰影响下机械臂的故障检测和控制精度问题,提出了一种基于滑模观测器的故障检测和控制优化方法.首先建立了带有电机故障、模型误差和机械摩擦等复合干扰的机械臂系统故障模型,然后设计了滑模观测器来实现在复合干扰下对电机故障的准确检测,最后引入滑模观测器对电机故障程度进行估计,并设计了反步容错控制方法,从而实现了对机械臂...     

Fault diagnosis for manifold absolute pressure sensor(MAP) of diesel engine based on Elman neural network observer

Intake system of diesel engine is a strong nonlinear system, and it is difficult to establish accurate model of intake system; and bias fault and precision degradation fault of MAP of diesel engine can’t be diagnosed easily using model-based methods. Thus, a fault diagnosis method based on Elman neural network observer is proposed. By comparing simulation results of intake pressure based on BP network and Elman neural network, lower sampling error magnitude is gained using Elman neural network, and the error is less volatile. Forecast accuracy is between 0.015-0.017 5 and sample error is controlled within 0-0.07. Considering the output stability and complexity of solving comprehensively, Elman neural network with a single hidden layer and with 44 nodes is presented as intake system observer. By comparing the relations of confidence intervals of the residual value between the measured and predicted values, error variance and failures in various fault types. Then four typical MAP faults of diesel engine can be diagnosed: complete failure fault, bias fault, precision degradation fault and drift fault. The simulation results show: intake pressure is observable and selection of diagnostic strategy parameter reasonably can increase the accuracy of diagnosis;the proposed fault diagnosis method only depends on data and structural parameters of observer, not depends on the nonlinear model of air intake system. A fault diagnosis method is proposed not depending system model to observe intake pressure, and bias fault and precision degradation fault of MAP of diesel engine can be diagnosed based on residuals.     

用未知输入观测器进行控制系统的故障诊断

针对在控制系统故障诊断中的不可测干扰，设计一种全新未知输入观测器进行故障诊断。通过对汽车悬架的故障诊断的仿真，证明了该方法的有效。     

Sliding mode observer based incipient sensor fault detection with application to high-speed railway traction device

This paper considers incipient sensor fault detection issue for a class of nonlinear systems with “observer unmatched” uncertainties. A particular fault detection sliding mode observer is designed for the augmented system formed by the original system and incipient sensor faults. The designed parameters are obtained using LMI and line filter techniques to guarantee that the generated residuals are robust to uncertainties and that sliding motion is not destroyed by faults. Then, three levels of novel adaptive thresholds are proposed based on the reduced order sliding mode dynamics, which effectively improve incipient sensor faults detectability. Case study of on the traction system in China Railway High-speed is presented to demonstrate the effectiveness of the proposed incipient senor faults detection schemes.