Fault detection for a class of nonlinear networked control systems

In this paper, an observer‐based fault detection (FD) method is presented for a class of nonlinear networked control systems (NCSs) with Markov transfer delays. Firstly, based on Euler approximate method, a nonlinear NCS model with uncertainty is proposed using the Takagi‐Sugeno (T‐S) fuzzy model. Some geometric conditions are given to transfer the NCS model into an output‐feedback form. Then, the H_∞ FD observer is designed such that the estimation error (residual) converges to zero, if there exist no fault and uncertainty in the system, or the residual is minimized in the sense of H_∞ norm, when system contains fault and uncertainties. Furthermore, to simplify the model, the approximate model without uncertainty is considered. Then, sufficient conditions for the existence of FD observer gain and the sampling time of NCSs are given to achieve the semiglobal practical property. An inverted pendulum example is used to illustrate the efficiency of the developed techniques. Copyright © 2009 John Wiley & Sons, Ltd.     

长延时网络控制系统动态矩阵控制研究

在实际工程系统中,采样频率的选择取决于系统中信号的最高频率,网络传输延时取决于网络本身的传输特性。由此可见,网络传输延时不一定小于一个采样周期,但在网络控制有关的论文中往往假定网络延时小于一个采样周期。本文针对这种不合理的设定,提出了一种新型的长延时预测控制算法。首先对一类长延时网络控制系统进行了建模;接着利用动态矩阵控制原理导出了长延时网络控制系统的预测控制律。最后给出了仿真实验,结果表明在对一类长延时网络系统的控制中,提出算法的合理性和有效性。     

Determination of the optimal DR capacity for a commercial building with chiller system and energy storage system

Demand response (DR ), which is used to shave the peak demand for securing supply reliability in a power system, is one of the promising constitutions for the end users. In a commercial building (COB ), the most popular adjustable DR resource (DRR ) is the chiller system. More specifically, its power consumption can be reduced by thermal mass control (precooling) in a specified DR duration. On the other hand, installation of energy storage systems (ESSs ) is going on at an accelerated pace because of its high economic efficiency. ESSs have been used for peak‐shift operation under the time‐of‐use (TOU ) tariff. However, ESS can be also used as an attractive DRR because it can reduce the net load by discharging the ESS for a specified DR duration. Based on this background, this paper presents a method for determining the optimal DR capacity in a COB with a chiller system and ESS . In the proposed scheme, the optimal DR capacity (kW ) can be determined so that the total expected cost of a COB becomes minimum by using the chiller system and ESS while avoiding the DR penalty threat adopted in the Korean DR market. Uncertainty in the ambient temperature, the amount of reduction, and DR durations are considered as the scenarios. The estimation and economic evaluation of the proposed scheme is ascertained through case studies. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

网络环境下控制理论在区域电网控制中的应用探讨

介绍了一种基于广域测量系统(WAMS)的区间阻尼闭环控制方案,指出存在的问题及目前网络化控制理论的主要研究进展情况,分析了二者的结合,提出了新的研究方向,即用网络化控制理论解决基于广域测量系统技术的阻尼闭环控制问题.     

电厂网控系统AGC的实现方案

介绍了在网控系统中配合调度中心实现自动发电控制(AGC)的几种方案;包括传统的硬接线方案及在综合自动化系统中的通信方案。分析了这些方案的优缺点,并提出了今后的发展前景,即通信方式必将替代硬接线方式,厂站端系统的功能越来越强,扮演着越来越重要的角色。     

Adaptive estimation of hidden nearly completely decomposable Markov chains with applications in blind equalization

This paper proposes maximum likelihood (ML) estimation schemes for nearly completely decomposable Markov chains (NCDMCs) in white Gaussian Noise. Aggregation techniques based on stochastic complementation are applied to significantly reduce the dimension of the resulting hidden Markov model (HMM) and hence substantially reduce the computational requirements of the estimation algorithms. Stochastic complementation results in exact aggregation in that no approximations are involved in the steady state probability distribution of the Markov chain. We then present an off-line estimation algorithm for the parameters and states of the HMM based on the estimation of the aggregated HMM. This off-line algorithm is an ML estimation scheme and is based on the expectation maximization (EM) algorithm. It has a significantly reduced computational complexity compared with the standard (full-order) EM-based HMM estimation scheme. Finally we present an application of our techniques. We show that hidden NCDMCs can be used to formulate the blind equalization problem for noisy FIR channels with Markov inputs, e.g. phase-shiftkeyed (PSK) signals. We then propose recursive EM and gradient estimation techniques for the aggregated HMM resulting in on-line estimates of the channel coefficients and signal estimate. For an N_a-state Markov chain our aggregate-based estimation scheme has a computational complexity O(N^?2_a), whereas standard algorithms have a complexity O(N_a^{?L + 1}) at each time instant, where L is the length of the FIR channel.     

An indirect adaptive pole‐placement control for MIMO discrete‐time stochastic systems

In this paper, an indirect adaptive pole‐placement control scheme for multi‐input multi‐output (MIMO) discrete‐time stochastic systems is developed. This control scheme combines a recursive least squares (RLS) estimation algorithm with pole‐placement control design to produce a control law with self‐tuning capability. A parametric model with a priori prediction outputs is adopted for modelling the controlled system. Then, a RLS estimation algorithm which applies the a posteriori prediction errors is employed to identify the parameters of the model. It is shown that the implementation of the estimation algorithm including a time‐varying inverse logarithm step size mechanism has an almost sure convergence. Further, an equivalent stochastic closed‐loop system is used here for constructing near supermartingales, allowing that the proposed control scheme facilitates the establishment of the adaptive pole‐placement control and prevents the closed‐loop control system from occurring unstable pole‐zero cancellation. An analysis is provided that this control scheme guarantees parameter estimation convergence and system stability in the mean squares sense almost surely. Simulation studies are also presented to validate the theoretical findings. Copyright © 2005 John Wiley & Sons, Ltd.     

Parameter estimation for MIMO system based on MUSIC and ML methods

The frequency offset and channel gain estimation problem for multiple-input multiple-output (MIMO) systems in the case of flat-fading channels is addressed. Based on the multiple signal classification (MUSIC) and the maximum likelihood (ML) methods, a new joint estimation algorithm of frequency offsets and channel gains is proposed. The new algorithm has three steps. A subset of frequency offsets is first estimated with the MUSIC algorithm. All frequency offsets in the subset are then identified with the ML method. Finally, channel gains are calculated with the ML estimator. The algorithm is a one-dimensional search scheme and therefore greatly decreases the complexity of joint ML estimation, which is essentially a multi-dimensional search scheme. __________ Translated from Journal of Electronics and Information Technology, 2008, 30(7): 1552–1556 [译自: 电子与信息学报]     

基于Stackelberg模型的主动配电网动态电价需求响应设计

传统价格型需求响应(DR)可能造成负荷弹性不大的用户用电成本的增加,为此提出了一种基于Stackelberg模型的主动配电网(ADN)动态电价DR方案,确保用户参与DR的收益。将负荷分为代理负荷和非代理负荷两类,通过DR代理调控代理负荷,利用动态博弈理论下的Stackelberg模型分析DR代理与ADN的互动过程,求解Stackelberg均衡得到DR代理与ADN的均衡策略,即动态电价与负荷安排。最后,采用IEEE 6节点的算例证明了所提出的DR设计在限制用户电费支出方面的有效性。     

Retracted: State estimation of Takagi-Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

This article concerns the event-triggered fuzzy filter design for Takagi-Sugeno (T-S) fuzzy systems subject to deception attacks under the stochastic multiple time-varying delays. A sequence of random variables, which are mutually independent but obey the Bernoulli distribution, is introduced to account for the randomly occurring communication delays. In order to efficiently utilize limited network communication bandwidth resources, the event-triggering scheme is adopted. A fuzzy filter with the attacked input signal is presented. Moreover, due to communication delays caused by event-triggering schemes and transmission, the filter adopts non-synchronous premise variables with the system. Then, by utilizing a model transformation technique, the fuzzy systems are developed. Furthermore, using the piecewise Lyapunov functional method technique, the resulting criterion provides sufficient conditions to ensure that fuzzy systems under deception attacks are stochastically stable with an H_∞ performance. Accordingly, the conditions for the co-design of the fuzzy filter and event-triggering schemes are given. Finally, numerical simulation with the industrial process provided to verify the proposed event-triggered design.