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检索条件"任意字段=第28届中国过程控制会议（CPCC 2017）暨纪念中国过程控制会议30周年"

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Fault Identification Method Based on KPLS Robust Reconstruction Error and Its Application in Fuel-ratio Monitoring of Blast Furnace

Fault Identification Method Based on KPLS Robust Reconstruct...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： Jiping Liu Ping Zhou Tianyou Chai State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

Nonlinear process fault identification is a difficult problem in the field of process *** this paper,a new fault identification method based on KPLS for nonlinear process is proposed,at the same time,the corresponding fault identification index and control limit are ***,the KPLS monitoring model is established utilizing the normal nonlinear process ***,the robust reconstruction error calculation method is used to estimate the normal values of the new observation process ***,the fault identification index and its control limit are calculated by utilizing residual error between estimated and actual values of process variables,and the process variables of the fault identification index beyond the control limit are considered as the fault *** proposed method was applied to a nonlinear numerical simulation processes and the blast furnace(BF) energy consumption monitoring *** simulation and test results confirm that the proposed methodology affords credible fault identification.

关键词： Fault identification KPLS Robust reconstruction Fuel-ratio monitoring Blast furnace ironmaking

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The Application Research of Self-learning Dynamic Decoupling Method in Steam Boiler

The Application Research of Self-learning Dynamic Decoupling...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： Zhu Hai-bo Zhang Yong Electronic and Information Engineering University of Science and Technology Liaoning

Aimed at the poor decoupling quality on multi-variable,nonlinear and strong coupling complex systems in industrial production based on traditional decoupling control strategy,we put forward a self-learning evolutionary cuckoo algorithm combined with neural network control strategy,it makes use of neural network training to eliminate the strong coupling effect among the coupling branches,and introduce in the cuckoo algorithm with self adjustment dynamic space strategy and a new search mechanism bind with Levy flight search mechanism based on probability selection and has the strategy combining learning and evolving method and Gauss Distribution,accelerate the optimization of neural network P,I,D parameter *** is used to complex boiler combustion system with strong *** experimental results show that this control strategy can effectively avoid the characteristics which neural network is easy to fall into local optimum,significantly improve the search accuracy and convergence speed,and has good robustness and decoupling performance,put forward an effective strategy for solving the coupling problems in actual industrial production.

关键词： Decoupling control Boiler combustion system Cuckoo search algorithm Neural network

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Quasi min-max model predictive control for Hammerstein system over networks with packet losses

Quasi min-max model predictive control for Hammerstein syste...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： Xiaoming Tang Na Liu Rui Li Key Laboratory of Industrial Internet of Things & Networked Control Ministry of EducationChongqing University of Posts and Telecommunications

In this paper,a constrained Model Predictive Control(MPC) approach is presented for the Networked Control System(NCS) containing Hammerstein nonlinearity and bounded packet *** Hammerstein nonlinearity is partially removed by establishing its pseudo inverse,and the remaining weaker nonlinearity is tackled by the polytopic *** model of NCS is constructed on the standpoint of robust control,which transforms the stabilization of the control systems with packet losses into the stabilization of a set of *** constrained networked MPC approach is given by parameterizing the infinite horizon control moves into a free control move followed by a state feedback law which the input and state constraints are explicitly *** with the networked MPC without free control move,the presented approach improves the control performance of the considered control system and is verified by a comparison simulation example.

关键词： Networked Control System Hammerstein model bounded packet losses Model Predictive Control

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Steam Pressure Control of 1000MW Ultra-supercritical Coal-fired Power Unit Based on Multi-model Predictive Control

Steam Pressure Control of 1000MW Ultra-supercritical Coal-fi...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： Guo-Liang Wang Juan Du Wei-Wu Yan School of Electric and Electronic Engineering Shanghai University of Engineering Science Department of Automation Shanghai Jiao Tong University

Coal-fired Ultra-supercritical(USC) unit is more and more popular these years for its *** the control of USC unit is a difficult issue for its characteristic of the nonlinearity,large dead time and coupling among inputs and *** this paper,model predictive control(MPC) method based on multi-model and double layered optimization is introduced for coordinated control of USC unit running in sliding pressure mode and fixed pressure *** inputs(*** opening,coal flow and feedwater flow) are employed to control three outputs(*** power,main steam temperature and main steam pressure).The step responses for the dynamic matrix control(DMC) are constructed using the three inputs by the three outputs under both pressure control *** models are built at selected operation *** simulation,the output power follows load demand quickly and main steam temperature can be controlled around the setpoint closely in load tracking *** simulation results show the effectiveness of the proposed methods.

关键词： Ultra-supercritical Coordinated Control Multi-model Model Predictive Control Steam Pressure Control

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Research on Improved LEACH Clustering Protocol in Wireless Sensor Networks

Research on Improved LEACH Clustering Protocol in Wireless S...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者：张颖毛林 College of Information Engineering Shanghai Maritime University

In wireless sensor networks,due to the limited battery power of the sensor nodes,the communication energy consumption is the main factor to affect the lifetime of the networks.A reasonable design of the communication protocol can effectively reduce the energy consumption of the network *** Improved-LEACH clustering protocol based on LEACH(Low Energy Adaptive Clustering Hierarchy) in wireless sensor networks is *** optimize the cluster head(CH) election in the cluster setup phase,the Improved-LEACH takes into account a number of factors,including energy consumption of communication between nodes,the remaining energy of the nodes,and the distance between nodes and the base station(BS).In the steady phase,one hop routing and multiple hops routing are combined to transmit data between CHs to improve energy *** forward CH is selected as relay node based on the values of path *** simulation results show that the proposed algorithm performs better in balancing network energy consumption,and it can effectively improve the data transmission efficiency and prolong the network lifetime compared with LEACH,LEACH-C and NDAPSO-C algorithms.

关键词： Wireless sensor networks LEACH Clustering Energy consumption Relay nodes

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Modeling Method of Data-driven Model Combined with A Priori Knowledge and Its Application in Average Particle Size Estimation of Composite Colloidal Sols

Modeling Method of Data-driven Model Combined with A Priori ...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： Yang Zhou Wenxi Xu Shaojun Li Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and TechnologyMinistry of Education

We present a universally applicable hybrid modeling method for nonlinear industrial processes that combine the a priori process knowledge with a data-driven *** method constructs a unified framework for the modeling process by integrating a data-driven modeling technique,sampling detection technique,constraint optimization problem,and an evolutionary *** the modeling process,a swarm intelligence algorithm is used to optimize the model parameters under the circumstances of satisfying the constraints of a priori *** adding the constraints of process a priori knowledge,we can obtain more information about the actual process and avoid the over-fitting problem to some extent,especially when modeling a system with a small quantity of *** order to show the effectiveness of the method proposed in this paper,two general data-driven models,the polynomial regression model and radial basis function network model,are used as case ***,a function simulation experiment is designed to test effectiveness,and applied to estimate average particle size of ZrO2-TiO2 composite colloidal sols.

关键词： Data-driven modeling A priori knowledge Constraint handling Intelligence algorithm Hybrid model

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Convergence Rate Estimation of Real Coded Artificial Immune Algorithm

Convergence Rate Estimation of Real Coded Artificial Immune ...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： Hong Lu Wang Jing-zhuo Zhang Jin-xue Cheng jia-li Tao zi-jun Department of Electronic Engineering Huaihai Institute of Technology Marine Resources Development Institute of Jiangsu

The stochastic process theory is utilized to replace the traditional eigenvalue estimation method of the state transition matrix so as to study the convergence rate of the real coded artificial immune *** the premise of satisfying the necessary condition for probability strong convergence of artificial immune algorithm,this method regards it as the sufficient condition for the general artificial immune algorithm and proposes a new method for estimating the exponential velocity probability strong convergence of real coded artificial immune *** method takes the final convergence of the optimum antibody in the population and avoids the deficiency of the conservative property of traditional estimation *** can estimate the convergence property and convergence rate of a class of artificial immune *** the practical application of artificial immune algorithm,it has a certain theoretical reference value in optimizing the convergence rate.

关键词： Artificial immune algorithm convergence rate estimation probability strong convergence Markov chain

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Reliability and Numerical Analysis of A Robot Safety System

Reliability and Numerical Analysis of A Robot Safety System

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： Qiao Xing Yao Xuliang Ma Dan Guo Shuang College of Automation Harbin Engineering University Department of Mathematics Daqing Normal University

This paper introduces a model for a repairable robot safety system consisting of a safety component and two redundant robots according to a semigroup *** proposed model is applied to the following:(I) The use of pure analysis to prove the uniqueness of a classic solution to this model.(II) The verification of this uniqueness by providing a non-negative solution to the model.(III) The formulation of reliability indices for the model,along with numerical examples to explain the *** existence,uniqueness,and exponential stability of the solution of the repairable robot safety system were studied using Volterratype Integro-Differential Equation theory and discussion the spectral distribution of the ACP ***,we proposed a method to investigate stable-mode targets of the robot safety system with the safety parts working,and with or without the parts revolving,to make use of the eigenvector correspondence to the eigenvalue *** showed that the robot safety parts with or without safety parts revolving and with fractional motion is superior than that with the safety parts *** novelty of this approach lies in its examination of a unique solution to the system and its exponential stability based on the C0-semigroup theory and functional analysis.

关键词： Stability Robot safety system Reliability index Numerical analysis

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Discriminative Dictionary Learning for Automatic Fault Diagnosis of Solar Modules in Electroluminescence Images

Discriminative Dictionary Learning for Automatic Fault Diagn...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： Xuan Li Qingyu Yang Wei Zhou System Engineering Center Space Star Technology Co.Ltd.

As a basic unit of solar module used in photovoltaic power generating system,solar cell is *** appear during manufacturing,transporting,and *** assembled into solar modules many faults cannot be visually observed with the conventional CCD imaging *** some algorithms have been developed,the accurate diagnosis of solar modules is still challenging *** this paper,we propose a novel method for automatic fault diagnosis of solar modules in electroluminescence(EL) images,which is based on Fisher Discrimination Dictionary Learning(FDDL) with Sparse Representation Classifier(SRC).The whole EL image is firstly divided into several image blocks representing the solar ***,discriminative dictionaries(i.e.,the dictionary atoms have correspondences to the class labels) are learned based on these image *** the test step,a query EL image is divided into a series of image blocks,the class label of each image block can be identified by computing the reconstruction error and representation coefficients for each *** evaluate our proposed method with the EL images collected on the experiment *** results show that the proposed method performs effectively for detecting and diagnosing the four common faults on solar modules.

关键词： Diagnosis Electroluminescence Fault detection Discrimination dictionary learning Sparse representation

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A Fractional Order PIλDμ Control Method for Microbial Fuel Cell

A Fractional Order PIλDμ Control Method for Microbial Fuel...

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第28届中国过程控制会议（cpcc 2017）暨纪念中国过程控制会议30周年

作者： AN Ai'min LIU Yun'li ZHANG Hao'chen ZHU Lu HAN Kejian College of Electrical and Information Engineering Lanzhou University of Technology Key Laboratory of Gansu Advanced Control for Industrial Processes National Experimental Teaching Center of Electrical and Control Engineering

Aiming at the problem that the traditional integer order PID control strategy of microbial fuel cell(MFC) system is slow respond to rapid dynamics and the overshoot is large in the manipulation *** this paper,a fractional order PID control strategy for MFC is put forward and implemented based on the advantage of fractional PID *** anode and cathode models are modeled respectively,then apply the models to analyze the performance of the microbial fuel cell system.A fractional PID controller is designed for controlling the MFC according to the dynamic analysis results.A MFC case is used to demonstrate the effectiveness of proposed fractional PID *** simulation results show that the designed fractional PID controller has the advantages of smaller overshoot and faster response speed compared to integer PID controller.

关键词： microbial fuel cell neural network performance analysis predictive control

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