DG出力不确定性对交直流混合系统潮流影响的量化分析方法

交直流混合系统可以有效接纳多种分布式电源（distributed generation,DG）,为研究DG出力不确定性对交直流混合潮流的影响,提出了基于齐诺多面体和线性化潮流的量化分析方法。首先采用齐诺多面体建立DG功率注入的不确定集合,随后通过线性化交直流统一潮流模型,得到了状态量的不确定集合,其包含电压、相角等状态量所有可能的取值,从而分析系统在不确定条件下的运行安全性。文章将所提方法运用在含不同控制方式的交直流混合电网算例中,验证了所提方法的有效性和实用性。     

基于集员未知输入观测器的风力机桨距执行器故障诊断

风力机一般放置在恶劣的环境中,其桨距执行器极易出现故障。文中针对一类含有未知但有界干扰和噪声的风力机系统的桨距执行器故障问题,设计了集员未知输入观测器对桨距的执行器故障进行检测并分离。采用气动机理和现代辨识原理建立风力机系统模型,通过优化未知输入观测器设计对系统中的干扰解耦,基于中心对称多胞体估计不考虑故障时残差的区间包络,并将其作为残差估计的上下动态阈值,实现状态估计。在上述基础上提出了利用一组集员未知输入观测器进行故障诊断的策略。仿真结果表明,在实验过程中,文中所设计的集员未知输入观测器准确地诊断出了风力机桨距执行器的3阶和5阶线性系统在发生突变故障和缓慢时变故障的时间和位置,证明了所提故障诊断策略的有效性。     

Zonotopic reachable set estimation for linear discrete‐time systems with time delay

This article studies reachable set estimation for linear discrete‐time systems with time delay, which are influenced by unknown but bounded disturbances. We propose a novel reachable set estimation method based on zonotopes for the considered systems. The proposed method can estimate real‐time reachable set under nonzero initial conditions. In order to increase estimation accuracy, we propose an iterative method to reduce the conservatism caused by the couplings between reachable sets at different instants. The effectiveness of the proposed method is illustrated by three numerical simulations.     

考虑灵活性收益的需求侧资源可行域聚合方法

为实现需求侧灵活性资源的高效协同调控,一般将其以聚合体的形式参与电力市场。灵活性资源聚合问题的数学本质是求取若干资源运行可行域的闵科沃夫斯基和,该问题的计算负担随聚合对象的维度和数量增加呈指数增长趋势。考虑灵活性在不同时段的收益差异,利用奇诺多面体表征参数的特殊性质实现可行域快速聚合。首先,建立灵活性资源可行域在奇诺多面体表征形式下的近似模型,相较现有模型保留爬坡特性对可行域边界特征的影响;然后,引入随机搜索方法,提升可行域近似模型的求解效率;最后,考虑灵活性资源出力在不同时段的收益差异,提出可行域近似模型的优化目标权重修正策略。基于真实电价数据及储能模型验证了所提方法的有效性。     

Active fault detection based on set‐membership approach for uncertain discrete‐time systems

Active fault detection facilitates determination of the fault characteristics by injecting proper auxiliary input signals into the system. This article proposes an observer‐based on‐line active fault detection method for discrete‐time systems with bounded uncertainties. First, the output including disturbances, measurement noise and interval uncertainties at each sample time is enclosed in a zonotope. In order to reduce the conservativeness in the fault detection process, a zonotopic observer is designed to estimate the system states allowing to generate the output zonotopes. Then, a proper auxiliary input signal is designed to separate the output zonotopes of the faulty model from the healthy model that is injected into the system to facilitate the detection of small fault . Since the auxiliary input signal generation leads to a nonconvex optimization problem, it is transformed into a mixed integer quadratic programming problem. Finally, a case study based on a DC motor is used to show the effectiveness of the proposed method.     

基于多胞体双重滤波的系统状态估计方法

针对未知但有界噪声离散时间状态空间系统,提出一种基于多胞体双重滤波的系统状态估计方法.首先,采用有界误差方法对测量噪声和状态预测过程进行分析,利用正多胞体预测状态集包裹后离散成初始约束条件;然后,根据更新最小边,全对称多胞体经过正多胞体紧致包裹后离散成约束条件,与测量方程约束条件组成3重约束;最后,通过求解线性规划问题得到全部状态的上下界,并获得包裹状态可行集的最紧致正多胞体.仿真示例验证了该方法估计离散状态空间系统状态的有效性和准确性.     

Interval estimation and fault detection for switched nonlinear systems based on zonotope method

This paper investigates the state interval estimation and fault detection (FD) problems for a Lipschitz nonlinear switched system based on the combination of the $H_{\infty }$ observer and the zonotope method. To begin with, an $H_{\infty }$ observer that is robust to the disturbance is designed, and the stability of the observer error dynamic system is analyzed under the average dwell time (ADT) concept. After this, the zonotope theory is applied on the $H_{\infty }$ observer error dynamic system such that the interval state estimation can be calculated iteratively when the system suffers from no fault. Furthermore, for FD purpose, a residual is constructed based on the $H_{\infty }$ observer. Because the constructed residual contains disturbance, it cannot be used for FD directly. To overcome this drawback, the interval estimation method of the residual is proposed by using the zonotope method, and a residual-based FD scheme is developed. Finally, a simulation example is given to verify the effectiveness of the proposed method.     

集员卡尔曼滤波器在电机故障诊断中的应用

本文针对伺服电机提出了一种基于集员卡尔曼滤波器的故障诊断方法并进行了实际应用. 首先, 基于运动学关系和数据驱动技术构建了伺服电机的综合系统动态. 之后, 针对电机的位置–速度模型设计了一个中心对称多面体卡尔曼滤波器来检测位置传感器和速度传感器是否发生故障. 同时, 针对电机的力矩–速度模型设计了一个中心对称多面体卡尔曼滤波器来检测力矩执行器故障和速度传感器故障. 然后, 基于上述的两个中心对称多面体卡尔曼滤波器提出了一种故障隔离律, 可以定位出伺服电机故障部件的位置. 最后, 通过一个实际的伺服电机实验平台对所提出方法进行了应用, 并验证了其可行性与有效性