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Economical Optimization of Grid Power Factor Using Predictive Data

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 258-267页

作者： Chaojiong Huang Jason Gu Haiying Liu Yuansheng Lu Jun Luo IEEE the School of electrical engineering and automation Shanghai University the department of electrical and Computer engineering Dalhousie University

We present an electrical grid optimization method for economical benefit. After simplifying an IEEE feeder diagram, we build a compact smart grid system including a photovoltaic-inverter system, a shunt capacitor, an on-load tapchanger(OLTC) and transmission lines. The system power factor(PF) regulation and reactive power dispatching are indispensable to improve power quality. Our control method uses predictive weather and load data to decide engaging or tripping the shunt capacitor, or reactive power injection by the photovoltaic-inverter system, ultimately to keep the system PF in a good range. From the perspective of economics, the economical model is considered as a decision maker in our predictive data control method.Capacitor-only control strategy is a common photovoltaic(PV)regulation method, which is treated as a baseline case. Simulations with GridLAB-D on profiled loads and residential loads have been carried out. The comparison results with baseline control strategy and our predictive data control method show the appreciable economical benefit of our method.

关键词： Grid optimization GridLAB-D inverter power factor predictive data control shunt capacitor

Optimal output regulation for PMSM speed servo system using approximate dynamic programming

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Science China(Information Sciences) 2023年第7期66卷 75-76页

作者： Zhaowu PING Yingjie JIA Bangguo XIONG Hongwei ZHANG Jun-Guo LU School of electrical engineering and automation Hefei University of Technology School of Mechanical engineering and automation Harbin Institute of Technology department of automation Shanghai Jiao Tong University

In recent decades, the output regulation problem has received considerable attention from researchers in the control community because it simultaneously addresses reference signal tracking, disturbance rejection, and robustness [1].Furthermore, when transient performance is considered by solving an optimization problem with a prescribed cost function, this output regulation problem is called an optimal output regulation(OOR) problem.

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Stochastic process-based degradation modeling and RUL prediction: from Brownian motion to fractional Brownian motion

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Science China(Information Sciences) 2021年第7期64卷 5-24页

作者： Hanwen ZHANG Maoyin CHEN Jun SHANG Chunjie YANG Youxian SUN School of automation and electrical engineering University of Science and Technology Beijing State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang University department of automation Tsinghua University School of automation and electrical engineering Linyi University department of electrical and Computer engineering University of Alberta

Brownian motion(BM) has been widely used for degradation modeling and remaining useful life(RUL) prediction, but it is essentially Markovian. This implies that the future state in a BM-based degradation process relies only on its current state, independent of the past states. However, some practical industrial devices such as Li-ion batteries, ball bearings, turbofans, and blast furnace walls show degradations with long-range dependence(LRD), where the future degradation states depend on both the current and past degradation states. This type of degradation naturally brings two interesting problems, that is, how to model the degradations and how to predict their RULs. Recently, in contrast to the work that uses only BM, fractional Brownian motion(FBM) is introduced to model practical degradations. The most important feature of the FBM-based degradation models is the ability to characterize the non-Markovian degradations with LRD. Although FBM is an extension of BM, it is neither a Markovian process nor a semimartingale. Therefore, how to obtain the first passage time of an FBM-based degradation process has become a challenging task. In this paper, a review of the transition of RUL prediction from BM to FBM is provided. The peculiarities of FBM when addressing the LRD inherent in some practical degradations are discussed. We first review the BM-based degradation models of the past few decades and then give details regarding the evolution of FBM-based research. Interestingly, the existing BM-based models scarcely consider the effect of LRD on the prediction of RULs. Two practical cases illustrate that the newly developed FBMbased models are more generalized and suitable for predicting RULs than the BM-based models, especially for degradations with LRD. Along with the direction of FBM-based RUL prediction, we also introduce some important and interesting problems that require further study.

关键词： remaining useful life degradation model Brownian motion fractional Brownian motion long-range dependence

Remaining useful life prediction for multi-component systems with hidden dependencies

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Science China(Information Sciences) 2019年第2期62卷 57-72页

作者： Xiaopeng XI Maoyin CHEN Donghua ZHOU department of automation Tsinghua University College of electrical engineering and automation Shandong University of Science and Technology

How can we predict the remaining useful life(RUL) of a dynamic system subject to multiple dependent degradations? Is it possible to address the above problem when the degradation information is obtained indirectly? According to a new type of state space-based model, we mainly develop an online RUL prediction method for the above system. In this model, the dependencies among different degradations can be reflected in a diffusion coefficient matrix. Considering that some industrial systems like blast furnaces are usually equipped with multi-sensors, an efficient information fusion strategy also plays an important role in predicting the RUL. Based on multi-dimensional observations, the hidden degradation states are identified through the sequential Kalman filtering. Meanwhile, the unknown parameters in the model are updated iteratively by the expectation maximization(EM) algorithm. At last, the RUL distributions are simulated through the Monte Carlo method, in which three types of failure structures with regard to the degradations are considered. The effectiveness of the proposed method is fully verified by a numerical example as well as a case study about the blast furnace.

关键词： remaining useful life hidden dependencies state space model multi-source information fusion failure structure

Generic functional modelling of multi-pulse auto-transformer rectifier units for more-electric aircraft applications

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Chinese Journal of Aeronautics 2018年第5期31卷 883-891页

作者： Tao YANG Serhiy BOZHKO Patrick WHEELER Shaoping WANG Shuai WU department of electrical and Electronic engineering University of Nottingham School of automation Science and electrical engineering Beihang University

The Auto-Transformer Rectifier Unit（ATRU） is one preferred solution for high-power AC/DC power conversion in aircraft. This is mainly due to its simple structure, high reliability and reduced k VA ratings. Indeed, the ATRU has become a preferred AC/DC solution to supply power to the electric environment control system on-board future aircraft. In this paper, a general modelling method for ATRUs is introduced. The developed model is based on the fact that the DC voltage and current are strongly related to the voltage and current vectors at the AC terminals of ATRUs. In this paper, we carry on our research in modelling symmetric 18-pulse ATRUs and develop a generic modelling technique. The developed generic model can study not only symmetric but also asymmetric ATRUs. An 18-pulse asymmetric ATRU is used to demonstrate the accuracy and efficiency of the developed model by comparing with corresponding detailed switching SABER models provided by our industrial partner. The functional models also allow accelerated and accurate simulations and thus enable whole-scale more-electric aircraft electrical power system studies in the future.

关键词： Asymmetric transformer Functional modelling More-Electric Aircraft Multi-pulse rectifier Transformer rectifier unit

Fractional order modeling and control of dissimilar redundant actuating system used in large passenger aircraft

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Chinese Journal of Aeronautics 2018年第5期31卷 1141-1152页

作者： Salman IJAZ Lin YAN Mirza Tariq HAMAYUN School of automation and electrical engineering Beihang University department of electrical engineering COMSAT Institute of Information Technology

In this paper, a methodology has been developed to address the issue of force fighting and to achieve precise position tracking of control surface driven by two dissimilar actuators.The nonlinear dynamics of both actuators are first approximated as fractional order models. Based on the identified models, three fractional order controllers are proposed for the whole system. Two Fractional Order PID（FOPID） controllers are dedicated to improving transient response and are designed in a position feedback configuration. In order to synchronize the actuator dynamics, a third fractional order PI controller is designed, which feeds the force compensation signal in position feedback loop of both actuators. Nelder-Mead（N-M） optimization technique is employed in order to optimally tune controller parameters based on the proposed performance criteria. To test the proposed controllers according to real flight condition, an external disturbance of higher amplitude that acts as airload is applied directly on the control surface. In addition, a disturbance signal function of system states is applied to check the robustness of proposed controller. Simulation results on nonlinear system model validated the performance of the proposed scheme as compared to optimal PID and high gain PID controllers.

关键词： Aerospace Fractional order control Model identification Nelder-Mead optimization Robustness

A Novel PDF Shape Control Approach for Nonlinear Stochastic Systems

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1490-1498页

作者： Lingzhi Wang Guo Xie Fucai Qian Jun Liu Kun Zhang electrical engineering department School of AutomationXi’an University of Posts and TelecommunicationsXi’an 710121China School of automation and Information engineering Xi’an University of TechnologyXi’an 710048China

In this work,a novel shape control approach of the probability density function(PDF)for nonlinear stochastic systems is presented.First,we provide the formula for the PDF shape controller without devising the control law of the controller.Then,based on the exact analytical solution of the Fokker-PlanckKolmogorov(FPK)equation,the product function of the polynomial and the exponential polynomial is regarded as the stationary PDF of the state response.To validate the performance of the proposed control approach,we compared it with the exponential polynomial method and the multi-Gaussian closure method by implementing comparative simulation experiments.The results show that the novel PDF shape control approach is effective and feasible.Using an equal number of parameters,our method can achieve a similar or better control effect as the exponential polynomial method.By comparison with the multiGaussian closure method,our method has clear advantages in PDF shape control performance.For all cases,the integral of squared error and the errors of first four moments of our proposed method were very small,indicating superior performance and promising good overall control effects of our method.The approach presented in this study provides an alternative for PDF shape control in nonlinear stochastic systems.

关键词： Fokker-Planck-Kolmogorov(FPK)equation nonlinear control nonlinear stochastic systems probability density function(PDF)

A Feature Weighted Mixed Naive Bayes Model for Monitoring Anomalies in the Fan System of a Thermal Power Plant

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 719-727页

作者： Min Wang Li Sheng Donghua Zhou Maoyin Chen IEEE the department of automation Tsinghua University the College of Control Science and engineering China University of Petroleum(East China) the College of electrical engineering and automation Shandong University of Science and Technology

With the increasing intelligence and integration,a great number of two-valued variables(generally stored in the form of 0 or 1)often exist in large-scale industrial processes.However,these variables cannot be effectively handled by traditional monitoring methods such as linear discriminant analysis(LDA),principal component analysis(PCA)and partial least square(PLS)analysis.Recently,a mixed hidden naive Bayesian model(MHNBM)is developed for the first time to utilize both two-valued and continuous variables for abnormality monitoring.Although the MHNBM is effective,it still has some shortcomings that need to be improved.For the MHNBM,the variables with greater correlation to other variables have greater weights,which can not guarantee greater weights are assigned to the more discriminating variables.In addition,the conditional P(x j|x j′,y=k)probability must be computed based on historical data.When the training data is scarce,the conditional probability between continuous variables tends to be uniformly distributed,which affects the performance of MHNBM.Here a novel feature weighted mixed naive Bayes model(FWMNBM)is developed to overcome the above shortcomings.For the FWMNBM,the variables that are more correlated to the class have greater weights,which makes the more discriminating variables contribute more to the model.At the same time,FWMNBM does not have to calculate the conditional probability between variables,thus it is less restricted by the number of training data samples.Compared with the MHNBM,the FWMNBM has better performance,and its effectiveness is validated through numerical cases of a simulation example and a practical case of the Zhoushan thermal power plant(ZTPP),China.

关键词： Abnormality monitoring continuous variables feature weighted mixed naive Bayes model(FWMNBM) two-valued variables thermal power plant

Remaining useful life prediction for a nonlinear multi-degradation system with public noise

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Journal of Systems engineering and Electronics 2018年第2期29卷 429-435页

作者： ZHANG Hanwen CHEN Maoyin ZHOU Donghua department of automation Tsinghua University College of electrical engineering and automation Shandong University of Science and Technology

To predict the remaining useful life(RUL) for a class of nonlinear multi-degradation systems, a method is presented. In the real industrial processes, systems are usually composed by several parts or components, and these parts or components are working in the same environment, thus the degradations of these parts or components will be influenced by common factors. To describe such a phenomenon in degradations, a multi-degradation model with public noise is proposed. To identify the degradation states and the unknown parameters, an iterative estimation method is proposed by using the Kalman filter and the expectation maximization(EM) algorithm. Next, with known thresholds,the RUL of each degradation can be predicted by using the first hitting time(FHT). In addition, the RUL of the whole system can be obtained by a Copula function. Finally, a practical case is used to demonstrate the method proposed.

关键词： remaining useful life(RUL) multi-degradation system public noise nonlinear degradation process