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Yang W.,Key Laboratory of Advanced Control and Optimization for Chemical Processes | Chen G.,City University of Hong Kong | Wang X.,Shanghai JiaoTong University | Shi L.,Hong Kong University of Science and Technology
Automatica | Year: 2014

We consider distributed state estimation over a resource-limited wireless sensor network. A stochastic sensor activation scheme is introduced to reduce the sensor energy consumption in communications, under which each sensor is activated with a certain probability. When the sensor is activated, it observes the target state and exchanges its estimate of the target state with its neighbors; otherwise, it only receives the estimates from its neighbors. An optimal estimator is designed for each sensor by minimizing its mean-squared estimation error. An upper and a lower bound of the limiting estimation error covariance are obtained. A method of selecting the consensus gain and a lower bound of the activating probability is also provided. Source


Xu Y.,Shanghai Maritime University | Xu Y.,Key Laboratory of Advanced Control and Optimization for Chemical Processes | Zhang Y.,Shanghai Maritime University | Wang J.,Shanghai JiaoTong University | Yuan J.,Shanghai JiaoTong University
Computers and Chemical Engineering | Year: 2013

Selective catalytic reduction (SCR) with ammonia or urea is regarded as one of the most important technologies to reduce the NOx emissions from coal-fired power plants. However, the design and development of SCR-DeNOx systems are a complicated process involving the optimization of several parameters such as the ammonia/urea injection strategy, the installment of the gate leaf and the hybrid grid, as well as the thickness of straightener. These parameters determine the velocity and concentration distributions at the entrance of catalyst layers, which are key factors to affect the efficiency of flue gas denitrification and ammonia slip. In this work, CFD simulations are carried out to portray the performance of the SCR-DeNOx facility in a 300MW coal-fired power plant. The influences of the gate leaf, hybrid grid and straightener on the distributions of the velocity and concentration are investigated. And then the corresponding experiments are performed to qualitatively confirm the simulation results. © 2012 Elsevier Ltd. Source


Zhou L.,Zhejiang University | Liao Z.,Zhejiang University | Wang J.,Zhejiang University | Jiang B.,Zhejiang University | And 2 more authors.
Applied Energy | Year: 2015

The production of regular clean fuels is faced with a problem of declining profit under more strict and costly environmental regulations. To satisfy the desire for higher profit and the firm requirements of environmental protection, it is imperative to improve the efficiency of energy systems within refineries. Over the past decade numerous attempts were made to enhance the energy system, addressing the steam power system and hydrogen system in particular. However, the fuel gas system, which serves as the dominant energy source of refineries, has drawn little attention in the research community. Industrial practices indicate that the energy efficiency of the fuel gas systems can be improved remarkably by optimizing the operation schedules. This paper presents a multi-period optimizing model for the scheduling of fuel gas system within refineries. Modeling of the pipeline system is considered important, which was usually ignored in the former studies. Flow reversal and flow transition in the pipe segments are taken into consideration. Pipelines with branching structure and loop structure can be easily modeled and solved with rational computation effort. Complementarity formulations are utilized in modeling of discrete decisions instead of the commonly used binary variables. Application of this method is illustrated with a case study. © 2014 Elsevier Ltd. Source


Yang W.,Key Laboratory of Advanced Control and Optimization for Chemical Processes | Wang X.,Shanghai JiaoTong University | Shi H.,Key Laboratory of Advanced Control and Optimization for Chemical Processes
Systems and Control Letters | Year: 2013

This paper considers the problem of finding the optimal network topology and consensus gain for the fastest second-order consensus with time delay. By using the root locus method in the frequency domain, the problem can be decomposed into two convex optimization problems. In the case that the network topology is fixed, a multi-hop relay scheme is introduced for fast consensus seeking. Each agent can receive information from its multi-hop neighbors with a certain delay. The optimal number of hops for the fastest convergence speed can be derived from the largest generalized eigenvalue of a pair of extension matrices. Finally, some examples are supplied to verify the theoretical results. © 2012 Elsevier B.V. All rights reserved. Source


Yang W.,Key Laboratory of Advanced Control and Optimization for Chemical Processes | Shi H.,Key Laboratory of Advanced Control and Optimization for Chemical Processes
International Journal of Control, Automation and Systems | Year: 2012

Motivated by navigation and tracking applications within sensor networks, we consider the distributed estimation problem over wireless sensor network. We propose a consensus based Kalman filtering algorithm based on optimal Linear Quadratic Gaussian control, in which each sensor can observe the dynamical system state, process the information data individually and communicate with each other within a sensing range. We provide a sufficient condition for the convergence of the proposed algorithm, and also give an upper bound for the estimation error covariance. Further, we find an optimal consensus gain for minimizing the network estimation error. Considering the occasional sensor fault and limited sensor energy, we investigate the proposed algorithm using only a subset of sensors to observe the dynamical system. With the assistance of the simulations, we verify the effectiveness of the proposed algorithms and present some interesting examples. © 2012 Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg. Source

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