Robust fault detection and adaptive parameter identification for DC-DC converters via switched systems

In this paper, the problem of fault detection and identification for DC-DC converters is presented. First, switched systems model and fault model are analyzed based the switched characteristics of the DC-DC converters, taking the DC-DC buck converter as an example. According to the switched Lyapunov function technique, a fault detection observer and a bank of linear switched fault identification observers are designed for the switched systems. Next, the fault detection observer detects the fault based on the residual produced by the observer output and actual output. After the fault is detected, fault identification observers are activated. The location of fault is identified by comparing the residual evaluation functions. Meanwhile, the adaptive parameter identification is achieved by choosing an appropriate adaptive law. Finally, in order to show the feasibility of the fault detection and identification, the simulation results are given in this article.     

Robust failure detection for linear distributed parameter systems

This paper discusses the robust failure detection methods in general separable Hilbert space using an operator approximation approach. It is simple and provides an intuitive geometric interpretation. The computational procedure required is the Schmit expansion of an operator. An example arising from the sensor failure detection design for space structures is given to illustrate the methodology suggested. This paper was recommended for publication by editor A. Benveniste     

发电机励磁系统参数辨识综述

综述了发电机励磁系统参数辨识的方法及其在国内外的应用和发展,将辨识方法分为时域法、频域法和人工智能法3种。时域法原理简单,计算方便,对激励信号没有特别要求,容易实现,但是该方法没有滤波功能;频域法利用快速傅里叶变换,将时域上的卷积转化为频域上的简单乘积,计算方便,但它需要伪随机信号作为激励信号,对伪随机码的参数选取要视具体情况而定,对低阶系统的参数辨识准确度高;人工智能方法原理简单,对激励信号没有特殊要求,能辨识非线性系统,可以直接得到实际参数,但它也没有滤波功能,而且对系统的先验知识要求较高,这些先验知识制约着用遗传算法辨识系统参数的精度。3种辨识方法没有绝对的最优,可根据不同情况选用不同方法,必要时3种方法可结合使用。     

Position and speed sensorless control system of permanent magnet synchronous motor with parameter identification

The model parameters of a permanent magnet synchronous motor (PMSM) are required for high‐performance control and a model‐based sensorless control. This paper proposes a sensorless control system of PMSM that does not need parametric information beforehand. The parameters of a PMSM drive system, including the inverter, are identified at standstill and under operating conditions. At first, the initial rotor position is estimated by a signal injection sensorless scheme in which the machine parameters are not required. After the initial position has been estimated, the resistance, including the on resistance of the IGBT, the voltage error caused by dead time in the inverter, and d‐axis and q‐axis inductances, are identified at standstill. After the motor starts by the signal injection sensorless control, the sensorless scheme changes to an extended EMF estimation scheme. The estimated parameters for the resistance, and daxis and q‐axis inductances are used in such sensorless control. The magnet flux‐linkage, which cannot be estimated at standstill, is identified under the sensorless operation at medium and high speeds. The effectiveness of the proposed method is verified by several experimental results. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 160(2): 68–76, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/ eej.20548     

柔性多状态开关参数辨识无差拍控制

柔性多状态开关(SOP)作为一种多功能性的新型电力电子装置,既能够优化配电网中的潮流,又能够优化电压分布。文中先推导了SOP的数学模型,针对多端口SOP传统PI双环控制的PI参数较多,且整定比较困难的缺点,利用无差拍控制设计电流内环,从而减少PI控制器的数量,简化控制电路的设计。针对无差拍控制对滤波电感较为敏感,抗电感参数摄动能力差的缺点,加入参数辨识环节,对系统参数进行跟踪估计,提高无差拍控制的鲁棒性。然后就基于参数辨识的无差拍控制对各端口的U_dcQ、PQ以及U_acf控制模式进行算法实现。通过在MATLAB/Simulink中进行仿真实验,验证了所提控制算法的可行性。     

基于增广状态估计的混合不良数据诊断与参数辨识

电网同时存在遥测坏数据和参数错误时,由于坏数据会影响参数辨识结果,全网参数辨识和估计方法很难保证结果的准确性。文中提出一种基于增广状态估计的混合不良数据诊断与参数辨识方法,先通过残差平衡度判断不良数据是遥测坏数据还是错误参数,将遥测坏数据直接剔除;然后,通过分区方法将多个潜在的不良参数尽可能分开在不同的局部区域,以减弱不良数据之间的相互影响;最后,采用分区增广状态估计方法修正不良参数。算例结果表明,该方法能有效区分坏数据和错误参数,且分区参数辨识能避免不良数据之间相互影响,从而提高了可疑参数辨识的精度。     

Robust fuzzy control and evolutionary fuzzy identification of singularly perturbed nonlinear systems with parameter uncertainty

This paper presents an H _∞ robust fuzzy control strategy which stabilizes singularly perturbed (SP) nonlinear systems with bounded uncertainties and guarantees disturbance attenuation bounds for all admissible uncertainties. The modified Takagi–Sugeno (T–S) fuzzy linear models are used to describe the SP nonlinear systems. By the proposed fuzzy control strategy, the number and type of membership functions in the fuzzy control rules are not necessarily the same as those in the fuzzy models. A sufficient condition for the existence of the H _∞ robust fuzzy controllers is then presented in terms of a novel linear matrix inequalities (LMIs) form which takes full consideration of modeling error and uncertainties in system parameters. This condition provides extra design parameters with more flexibility in control gain selection. Furthermore, we propose a compound search strategy composed of island genetic algorithms concatenated with the simplex method to identify the uncertain SP nonlinear systems for the fuzzy control design, and to solve the LMI problem. Finally, design example of the proposed H _∞ robust fuzzy controller for an uncertain SP nonlinear system is presented.     

高速短初级直线感应电动机等效电路模型及时变参数辨识

由于受到动态纵向边端效应和铁心饱和的影响,直线感应电机传统等效电路模型电磁参数时变.针对此,本文提出了多因素耦合影响下高速短初级直线感应电机等效电路模型及其时变参数辨识方法.首先,分析不同工况下电机推力变化规律;其次,分析电机电磁参数与运行工况之间的规律,提出激磁电感和次级电阻修正系数,构建直线感应电机改进等效电路模型,并通过响应面分析法计算两个修正系数;最后,开展样机静态堵驻实验和动态实验.计算和实测结果表明:推力计算值与实测值误差不超过4.1％,端口基波正序阻抗的实部、虚部计算值与实测值误差不超过4.7％,验证了时变参数辨识的准确性.     

改进遗传算法在发电机励磁系统参数辨识中的应用

提出了一种基于改进遗传算法的将发电机励磁系统原模型转换为仿真软件下标准模型的参数辨识方法,以原模型和标准模型的输出误差最小作为辨识目标,利用改进遗传算法不断优化调整标准模型中的参数,最终得到满足要求的励磁系统标准模型参数。与传统的励磁系统参数辨识方法相比较,该方法很好地解决了励磁系统非线性环节难以有效辨识的问题,方便可靠,精度高。实际发电机励磁系统参数辨识结果表明,该方法具有很好的效果。     

改进遗传算法在发电机励磁系统参数辨识中的应用

提出了一种基于改进遗传算法的将发电机励磁系统原模型转换为仿真软件下标准模型的参数辨识方法,以原模型和标准模型的输出误差最小作为辨识目标,利用改进遗传算法不断优化调整标准模型中的参数,最终得到满足要求的励磁系统标准模型参数.与传统的励磁系统参数辨识方法相比较,该方法很好地解决了励磁系统非线性环节难以有效辨识的问题,方便可靠,精度高.实际发电机励磁系统参数辨识结果表明,该方法具有很好的效果.     

基于DFT的瞬时谐波检测方法

提出了一种用离散傅里叶变换DFT（Discrete Fourier Transform)实现特殊滤波器的瞬时谐波电流的检测方法。该滤波器在基频处的值无衰减，相位无延时，能将2次以上的谐波全部滤掉。根据滤波器冲激响应的特点得到了滤波算法的递推关系，大大地节约了计算量。基于此滤波器设计的数字谐波检测方法可用于任何一种电力系统的谐波补偿装置中，理论推导和仿真实验表明，该数字谐波检测系统既保留了数字滤波器的准确性，又克服了长期以来数字滤波器跟随性差的问题，算法易于实现，具有较高的实用价值。     

溪洛渡拱坝模态参数识别

随着一系列高拱坝在西南地区兴建,坝体的健康状况及其真实的抗震性能成为近年来研究的热点。模态参数反映坝体结构的动态特性,可用于评估坝体的健康状况及更新坝体抗震分析有限元模型。本文基于永善县两次地震记录和环境激励数据,分别采用带外源输入的自回归（ARX）模型、随机子空间法（SSI）和频域分解法（FDD）,识别溪洛渡拱坝的模态参数。结果显示,在相同工况下,不同算法识别结果的差异较小;当水位一致时,基于环境激励数据识别结果与基于地震记录识别结果基本一致,当库水水位从566 m变化到598 m时,坝体第一阶自振频率从1.63 Hz减小到1.51 Hz;地震前后识别结果基本一致,表明溪洛渡拱坝在经历两次地震作用后,坝体振动特性不变,坝体处于正常运行状态。     

Consistent parameter estimation for deterministic mimo systems with overparametrized models

In this paper the parameter estimation problem for deterministic MIMO systems with overparametrized models will be addressed. In SISO systems overparametrized signal models might arise if the order of the plant model is set too high. For MIMO systems this problem will arise whenever its observability indices are different or, as in SISO systems, the order of the system is set too high. With a proper definition of persistent excitation it is shown that the estimated parameters will converge to a set of parameters. Each point of this set will result in the same transfer function as that of the system under consideration. A very efficient correction algorithm will be used to remove the greatest left common divisor of the estimated system parameters. Hence adaptive control algorithms, which may not be suitable if the estimated system parameters are not left coprime, can then be implemented.     

基于综合算法的汽轮机及其调节系统参数智能辨识

基于Matlab/Simulink,开发了综合多项式拟合、最小二乘法、单纯形法、遗传算法、模拟退火算法的汽轮机及其调节系统参数智能辨识软件。软件能自动完成原始数据的预处理、执行机构参数辨识样本的提取、负载试验数据边界条件的处理等,继而采用多种算法分别对参数进行辨识,并根据预设的逻辑选出最终的参数辨识结果。仿真校核的结果表明,所得到的参数辨识结果能够反映实际汽轮机及其调节系统的综合特性。最后,指出了影响汽轮机及其调节系统参数辨识准确性的关键因素。     

Fault detection and identification for a class of continuous piecewise affine systems with unknown subsystems and partitions

This paper establishes a novel online fault detection and identification strategy for a class of continuous piecewise affine (PWA) systems, namely, bimodal and trimodal PWA systems. The main contributions with respect to the state‐of‐the‐art are the recursive nature of the proposed scheme and the consideration of parametric uncertainties in both partitions and in subsystems parameters. In order to handle this situation, we recast the continuous PWA into its max‐form representation and we exploit the recursive Newton‐Gauss algorithm on a suitable cost function to derive the adaptive laws to estimate online the unknown subsystem parameters, the partitions, and the loss in control authority for the PWA model. The effectiveness of the proposed methodology is verified via simulations applied to the benchmark example of a wheeled mobile robot.     

汽轮发电机组的调速系统参数辨识

调速系统是汽轮发电机组的重要组成部分,对其进行准确建模,有利于提高汽轮发电机组的运行和控制水平。分析汽轮发电机组典型的调速系统,确定其模型结构和需要辨识的具体参数,进行调速系统参数可辨识性理论研究。得出在该模型下,通过设置合适的观测点,可唯一辨识调速系统量测环节的放大倍数、伺服机构时间常数、蒸汽容积效应的时间常数等参数。算例表明,利用可控量电磁转矩作为输入、可观量转子转速和汽门开度作为输出,以误差平方和倒数为目标函数,采用进化策略法进行参数辨识,能有效地辨识出调速系统的参数,并且具有唯一性。     

Iterative parameter and order identification for fractional-order nonlinear finite impulse response systems using the key term separation

This article considers the parameter estimation for a fractional-order nonlinear finite impulse response system with colored noise. For the fractional-order systems, the challenge and difficulty are to identify the order and parameters of the systems simultaneously under colored noise disturbances. In order to reduce the problem of redundant parameter estimation, the output form of the system can be expressed by a linear combination of unknown parameters through the separation of the key term separation. A key term separation auxiliary model gradient-based iterative algorithm is derived by using the negative gradient search. Meanwhile, to achieve the higher estimation accuracy, we propose a key term separation auxiliary model multiinnovation gradient-based iterative algorithm by utilizing the multiinnovation theory. Finally, the simulation results test the effectiveness of the proposed algorithms.     

感应电机双滑模面变结构MRAS转速辨识

为了研究感应电机无速度传感器磁场定向控制系统,基于变结构控制和自适应控制理论,提出一种双滑模面变结构模型参考自适应观测器,用于感应电机的转速辨识.该方法将变结构和模型参考自适应系统进行有机的整合,选择转子磁链电压模型和电流模型分别作为参考模型和可调模型,采用两模型输出的偏差构造了两个滑模面,利用代数计算方法获得转子估计速度.理论分析和仿真结果表明:所提出的感应电机转速辨识方法具有较高的转子磁链观测准确度,改善了转速估计的动静态性能;对于参数变化具有很强的自适应能力,同时算法简单,适用于实时应用.     

Robust adaptive control for unmatched systems with guaranteed parameter estimation convergence

This paper provides a modified model reference adaptive control (MRAC) scheme to achieve better transient control performance for systems with unknown unmatched dynamics, where an adaptive law with guaranteed convergence is introduced. We first revisit the standard MRAC system and analyze the tracking error bound by using L₂‐norm and Cauchy‐Schwartz inequality. Based on this analysis, we suggest a feasible way to compensate the undesired transient dynamics induced by the gradient descent–based adaptive laws subject to sluggish convergence or even parameter drift. Then, a modified adaptive law with an alternative leakage term containing the parameter estimation error is developed. With this adaptive law, the convergence of both the estimation error and tracking error can be proved simultaneously. This enhanced convergence property can contribute to deriving smoother control signal and improved control response. Moreover, this paper provides a simple and numerically feasible approach to online verify the well‐known persistent excitation condition by testing the positive definiteness of an introduced auxiliary matrix. Comparative simulations based on a benchmark 3‐DOF helicopter model are given to validate the effectiveness of the proposed MRAC approach and show the improved performance over several other MRAC schemes.