Modelling and long-term simulation of a heat recovery steam generator

Developing accurate non-linear dynamical models for heat recovery steam generator (HRSG) units is presented in this article. The common non-linear autoregressive with exogenous input (NARX) system topology was employed to develop the neuro-fuzzy models based on the experimental data taken during field experiments. In this structure, the non-linear behaviours of the HRSG unit can be characterized through interpolation of local linear models associated with different operating regions via fuzzy inference mechanism. The operating regimes were recognized by applying a genetic algorithm-based fuzzy clustering technique to the prepared data sets. The structures of the fuzzy models are defined with respect to the obtained optimal cluster centres and the corresponding membership functions. The parameters of fuzzy rules were adjusted by recursive least-squares estimation method to fit the model responses to real data. The performances of developed models were evaluated by performing a comparison between the model responses and the responses of the real plant. In addition, the stability of the developed models was assessed by perturbing the model inputs from the nominal values. This guarantees the long-term simulation capabilities of the developed models. A comparison between the responses of the corresponding models and the models obtained from some recent modelling approaches was performed to show the advantages of the developed models. The results show the accuracy and reliability of the developed models at transient and steady-state conditions.     

The fault detection problem in nonlinear systems using residual generators

In this work we study the fault detection problem using residualgenerators based upon high gain nonlinear observers in a differentialalgebraic framework. We analyse the stability of the residualgenerator when a fault occurs. We also consider two faults types:constant and time-varying faults. It is shown that under somemild conditions over the aforementioned faults the residualis different from zero.     

Hybrid modeling based double-granularity fault detection and diagnosis for quadrotor helicopter

Fault detection and diagnosis (FDD) is an effective technology to assure the safety and reliability of quadrotor helicopters. However, there are still some unsolved problems in the existing FDD methods, such as the trade-offs between the accuracy and complexity of system models used for FDD, and the rarely explored structure faults in quadrotor helicopters. In this paper, a double-granularity FDD method is proposed based on the hybrid modeling of a quadrotor helicopter which has been developed in authors’ previous work. The hybrid model consists of a prior model and a set of non-parametric models. The coarse-granularity-level FDD is built on the prior model which can isolate the faulty channel(s); while the fine-granularity-level FDD is built on the nonparametric models which can isolate the faulty components in the faulty channel. In both coarse and fine granularity FDD procedures, principal component analysis (PCA) is adopted for online fault detection. Using such a double-granularity scheme, the proposed FDD method has inherent ability in detecting and diagnosing structure faults or failures in quadrotor helicopters. Experimental results conducted on a 3-DOF hover platform can demonstrate the feasibility and effectiveness of the proposed hybrid modeling technique and the hybrid model based FDD method.     

Vertical and oblique fault detection in explicit surfaces

The purpose of this paper is to study the problem of detection of vertical and oblique faults in explicit surfaces. First, we characterize the finite jump discontinuities of a univariate function in terms of the divergence of sequences related to the slopes of least-squares polynomial approximations of the function. Then, we propose an algorithm to locate the finite jump discontinuities of a univariate function and its first derivative from a finite set of scattered data values of the function. As a consequence, we derive a method to detect vertical and oblique faults in explicit surfaces when the data sets are distributed along lines. We finally present some numerical and graphical examples.     

Derivation of a nine variable model of a U-tube steam generator coupled with a three-element controller

In this work a U-Tube Steam Generator – UTSG model derivation is presented. This model was developed as test bed to build a complete power plant simulator. The UTSG is an ordinary component of most of the Pressurized Water Reactor – PWR. A proportional-integral three-element controller was also coupled with the UTSG model. This model is part of a library called SIMODIS – SImulation MODeling Integrated System (“SIstema MODular Integrado de Simulação”). A few transient results are presented as well. The developed simulation program was implemented in MATLAB.     

Filtering-based robust fault detection of fuzzy jump systems

This paper studies the robust fault detection filter (RFDF) design problems for uncertain nonlinear Markov jump systems with state delays and parameter uncertainties. By means of Takagi-Sugeno fuzzy models, the dynamics of filtering error generator and the fuzzy RFDF system are constructed. With the aid of the selected weighting matrix function, the design objective is to find an optimal RFDF which results in a minimal difference between the reference model (ideal solution) and the RFDF (real solution) to be designed. A sufficient condition is firstly established on the stochastic stability by using stochastic Lyapunov-Krasovskii functional approach. Then in terms of linear matrix inequalities techniques, sufficient conditions on the existence of fuzzy RFDF are presented and proved. Finally, the design problem is formulated as an optimization algorithm. Simulation results illustrate that the proposed RFDF can detect the faults shortly after the occurrences.     

Robust fault detection of Markovian jump systems with different system modes

This paper deals with the robust fault detection filter (RFDF) design problems for uncertain nonlinear Markovian jump systems with unknown input. By using a observer-based fault detection filter as residual generator, the RFDF design is formulated as an _H∞$H_{\infty }$-filtering problem. Particularly, two different Markov processes are considered for modeling the randomness of system matrix and the state delay. With the aid of the weighting matrix function, the design objective is to find an optimal RFDF, which results in a minimal difference between the reference model and the RFDF to be designed. By using a new convex polyhedron technique and two mode-dependent Lyapunov functional, some new sufficient conditions are established in terms of delay-dependent linear matrix inequalities (LMIs) to synthesize the residual generation scheme. Finally, a numerical example is given to illustrate the effectiveness of the proposed techniques.     

枪弹头痕迹自动比对数学模型的研究及统计分析

对于题目中的几个问题,首先给出了一个计算并消除两组划痕数据之间平移误差和转动误差的精确算法,然后利用中值滤波+低通滤波+高斯滤波的方案来消除噪声和误差,最后对过滤后的数据进行分析,提取了一维特征向量并提出了比对特征相关系数作为检验弹头相似程度的标准.     

Vibration testing for anomaly detection

In this paper we propose an efficient method to reconstruct a small inclusion buried inside a body using the perturbation of modal parameters measured on the boundary of the body. We design a reconstruction algorithm based on the asymptotic expansions of the eigenvalue perturbations obtained by Ammari and Moskow (Math. Meth. Appl. Sci. 2003; 26 :67–75). We then implement this algorithm and demonstrate its viability and limitations. Copyright © 2008 John Wiley & Sons, Ltd.     

A model of a homogenized cavity corresponding to a multinozzle droplet generator for continuous ink-jet printers

We modelize the behavior of a vibrating fluid cavity. Small nozzles are uniformly distributed in one direction on a side of the cavity. By means of asymptotic expansion in powers of the smallest dimension of the cavity, including boundary layer terms, we get the convergence of the solution of the three-dimensional problem, as well as the convergence of the solution of the “homogenized” three-dimensional problem towards the solution of the same two-dimensional problem. Numerical experiments have been carried out in order to illustrate the previous theoretical results. © 1998 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 14: 821–842, 1998     

The serial test for a nonlinear pseudorandom number generator

Let and A sequence is obtained by the formula The sequence is a sequence of pseudorandom numbers of the maximal period length if and only if (mod 4), (mod 4). In this note, the uniformity is investigated by the 2-dimensional serial test for the sequence. We follow closely the method of papers by Eichenauer-Herrmann and Niederreiter.

     

Design of a robust nonlinear controller for a synchronous generator connected to an infinite bus

This article presents a new design of robust finite‐time controller which replaces the traditional automatic voltage regulator for excitation control of the third‐order model synchronous generator connected to an infinite bus. The effects of system uncertainties and external noises are fully taken into account. Then a single input robust controller is proposed to regulate the system states to reach the origin in a given finite time. The designed robust finite‐time excitation controller can refine the system behaviors in convergence and robustness against model uncertainties and external disturbances. The robustness and finite‐time stability of the closed‐loop system are analytically proved using the finite‐time control idea and Lyapunov stability theorem. The suitability and robustness of the designed controller are shown in contrast with two other strong nonlinear control strategies. The main advantages of the proposed controller are as follows: a) robustness against system uncertainties and external noises; b) convergence to the equilibrium point in a given finite time; and c) the use of a single control input. © 2015 Wiley Periodicals, Inc. Complexity 21: 203–213, 2016     

Design of an active fault tolerant control system for a simulated industrial steam turbine

An active fault tolerant control (FTC) scheme is proposed in this paper to accommodate for an industrial steam turbine faults based on integration of a data-driven fault detection and diagnosis (FDD) module and an adaptive generalized predictive control (GPC) approach. The FDD module uses a fusion-based methodology to incorporate a multi-attribute feature via a support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) classifiers. In the GPC formulation, an adaptive configuration of its internal model has been devised to capture the faulty model for the set of internal steam turbine faults. To handle the most challenging faults, however, the GPC control configuration is modified via its weighting factors to demand for satisfactory control recovery with less vigorous control actions. The proposed FTC scheme is hence able to systematically maintain early FDD with efficient fault accommodation against faults jeopardizing the steam turbine availability. Extensive simulation tests are conducted to explore the effectiveness of the proposed FTC performances in response to different categories of steam turbine fault scenarios.     

A GENERATOR AND A SIMPLEX SOLVER FOR NETWORK PIECEWISE LINEAR PROGRAMS

ＡＧＥＮＥＲＡＴＯＲＡＮＤＡＳＩＭＰＬＥＸＳＯＬＶＥＲＦＯＲＮＥＴＷＯＲＫＰＩＥＣＥＷＩＳＥＬＩＮＥＡＲＰＲＯＧＲＡＭＳＳＵＮＪＩＥ（孙捷）（ＩｎｓｔｉｔｕｔｅｏｆＡｐｐｌｉｅｄＭａｔｈｅｍｅｍａｔｉｃｓ，ｔｈｅＣｈｉｎｅｓｅＡｃａｄｅｍｙｏｆＳｃｉ...     

Observer-based fault detection for networked control systems with network Quality of Services

This paper addresses the problem of the fault detection for linear time-invariant systems over data networks with limited network Quality of Services (QoS). An integrated index _ηk${\eta }_k$, which related with data dropout, network-induced delay and error sequence, is presented to described the non-ideal QoS, the probabilistic switching between different _ηk${\eta }_k$ is assumed to obey a homogeneous Markovian chain. Then by view of the augmented matrices approach, the fault detection error dynamic systems are transferred to Markov jumping systems (MJSs). With the developed model and using the bounded real lemma (BRL) for MJSs, an _H∞$H_{\infty }$ observer-based fault detection filter is established in terms of linear matrix inequalities (LMIs) to guarantee that the error between the residual and the weighted faults is made as small as possible. A simulation example is provided to show the effectiveness of the present methods.     

A characterization of generator for multiresolution analysis with composite dilations

In this paper, we will introduce multiresolution analysis with composite dilations and give a characterization of generator for multiresolution analysis with composite dilations.     

Mathematical modeling of a pressurizer in a pressurized water reactor for control design

A pressurizer is a key equipment to ensure the safe operation of a pressurized water reactor by maintaining the reactor coolant system pressure within allowed tolerances. In this paper, a nonequilibrium three-region pressurizer model for the pressurized water reactor was developed first base on the basic conservation laws of mass and energy for the steam and water in the pressurizer. Then the nonlinear model was linearized to introduce the transfer function models of the pressurizer during insurge and outsurge transients for the controller design of a small pressurized water reactor pressurizer. Based on the developed transfer function models, the closed-loop pressurizer pressure and water level control systems including conventional proportional-integral-derivative controllers were designed employing the control strategy that uses a spray valve and two electric heaters for pressure control and regulates the charging flow rate with the letdown flow rate keeping constant for water level control. Finally, a simulation platform for the small pressurized water reactor pressurizer was developed in MATLAB/Simulink with implementation of the proposed nonlinear and nonequilibrium three-region pressurizer model, a widely-used nonlinear and nonequilibrium three-region pressurizer model and the designed pressure and water level controllers. Two typical load change transients, including the 100% to 90% of full power step load decrease and load rejection from 100% to 25% of full power, were simulated based on the platform. Dynamic responses of the pressure and water level obtained using the two nonlinear pressurizer models were analyzed, and the controller performances were assessed. The analysis and assessment results have shown satisfactory control performance and good robustness of the designed controllers regardless of the pressurizer simulation model adopted, demonstrating the feasibility, effectiveness and accuracy of the developed nonlinear and transfer function models of the pressurizer for dynamic simulation and controller design.     

Observer-based fault detection for networked discrete-time infinite-distributed delay systems with packet dropouts

This paper addresses the problem of fault detection for networked discrete-time infinite-distributed delay systems with packet dropouts. Both sensor-to-controller and controller-to-actuator packet dropouts are described by two different Bernoulli distributed white sequences, respectively. The problem addressed is to design an observer-based fault detection filter (FDF) such that the error between the residual and the fault is made as small as possible. Unlike most of the existing literature, we have noted that the control input of the observer is different from that of the plant because of packet dropouts in the controller-to-actuator link. Sufficient condition for the existence of the FDF is derived in terms of some linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterized. A numerical example is exploited to show the effectiveness of the obtained results.     

Bond graph model-based system mode identification and mode-dependent fault thresholds for hybrid systems

Hybrid system models exploit the modelling abstraction that fast state transitions take place instantaneously so that they encompass discrete events and the continuous time behaviour for the while of a system mode. If a system is in a certain mode, e.g. two rigid bodies stick together, then residuals of analytical redundancy relations (ARRs) within certain small bounds indicate that the system is healthy. An unobserved mode change, however, invalidates the current model for the dynamic behaviour. As a result, ARR residuals may exceed current thresholds indicating faults in system components that have not happened. The paper shows that ARR residuals derived from a bond graph cannot only serve as fault indicators but may also be used for bond graph model-based system mode identification. ARR residuals are numerically computed in an off-line simulation by coupling a bond graph of the faulty system to a non-faulty system bond graph through residual sinks. In real-time simulation, the faulty system model is to be replaced by measurements from the real system. As parameter values are uncertain, it is important to determine adaptive ARR thresholds that, given uncertain parameters, allow to decide whether the dynamic behaviour in a current system mode is the one of the healthy system so that false alarms or overlooking of true faults can be avoided. The paper shows how incremental bond graphs can be used to determine adaptive mode-dependent ARR thresholds for switched linear time-invariant systems with uncertain parameters in order to support robust fault detection. Bond graph-based hybrid system mode identification as well as the determination of adaptive fault thresholds is illustrated by application to a power electronic system easy to survey. Some simulation results have been analytically validated.