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International Symposium on Advanced control of Industrial processes (ADCONIP)

作者： Dongqing Wang Feng Ding Shouqing Sun College of Automation Engineering Qingdao University of China Qingdao China Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of Internet of Things Engineering Jiangnan University Wuxi China Qingdao Hismile College Qingdao China

For input nonlinear output error moving average systems with a two-segment piecewise nonlinearity, a data filtering based stochastic gradient algorithm is developed to estimate the parameters of this nonlinear system based on the data filtering. The basic idea is to combine the key-term separation principle and the data filtering technique, and to decompose the identification model into two models. The simulation results indicate that the proposed algorithm can give more accurate parameter estimates than existing extended stochastic gradient algorithm.

关键词： Stochastic processes Signal processing algorithms Mathematical model Computational modeling Nonlinear systems Parameter estimation Digital signal processing

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Realization of intelligent-PI algorithm in water level control system

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Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) 2011年第SUPPL. 1期42卷 930-934页

作者： Bi, Shu-Jiao Dong, Feng Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin 300072 China

Through analyzing the processes and different parameter conditions of wheat malting in beer brew, the liquid-level control system was designed from the perspectives of system and algorithm to get good control results. In the hierarchical structure, PLC was responsible for collecting and processing signals from the field and the real-time control of executive components, the computer was a platform to set parameters and program. The liquid-level control system was controlled by PID method, and the improvement of PID control algorithm was realized to adjust multivariable coupled or more complex system. That was intelligent PI control algorithm which can adjust PID parameters on line. The experiment results prove conveniences and universality of PID controller and the intelligent PI control algorithm can significantly reduce the overshoot and control the process time.

关键词： Real time control

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A novel type of trigonometric neural network trained by Extended Kalman Filter

A novel type of trigonometric neural network trained by Exte...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： M. Norouzi M. Mansouri M. Teshnehlab M. Aliyari Shoorehdeli Faculty of Engineering Department of Computer Engineering Science and Research Branch Islamic Azad University Iran Intelligent System Laboratory (ISLAB) Faculty of Electrical Engineering Control Department K.N. Toosi University of Technology Tehran Iran Faculty of Electrical Engineering Department of Mechatronics Engineering Advanced Process Automation &Control Laboratory (APAC) K.N. Toosi University of Technology Tehran Iran

In this study, a new type of trigonometric neural network is presented by adding frequency and phase to trigonometric activation functions. The proposed trigonometric neural network has more flexibility in comparison with conventional trigonometric neural networks and even other types of neural networks. Due to the low convergence rate and high posibility of trapping in a local minimum of backpropagation algorithm, Extended Kalman Filter algorithm is used to train the neural network's parameters which they appear in a nonlinear form. The Simulation of the suggested neural network based on the prediction of Mackey-Glass time series and identification of a nonlinear dynamic ystem reveals the efficiency of the proposed network. To show the efficiency of this method, the results are compared with the results of the others.

关键词： Biological neural networks Kalman filters Equations Neurons Vectors Covariance matrix Mathematical model

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Two-Stage Method and Application for Molten Iron Scheduling Problem between Iron-Making Plants and Steel-Making Plants

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IFAC Proceedings Volumes 2011年第1期44卷 9476-9481页

作者： Hui Huang Tianyou Chai Xiaochuan Luo Binglin Zheng Hong Wang State Key Laboratory of Integrated Automation for Process Industry (Northeastern University) Shenyang China 110819 (Tel: +86-24-83678332) National Metallurgical Automation Engineering Technology Research Center Northeastern University Shenyang China 110819 Control Systems Centre School of Electrical and Electronic Engineering the University of Manchester P O Box 88Manchester M60 1QD UK

Abstract In this paper, a two-stage method is proposed to solve the molten iron scheduling problem (MISP). Firstly, a 0-1 mixed-integer nonlinear programming model is established for special type of molten iron scheduling problem (STMISP). A method to solve mathematical model of STMISP is presented, which include assigning machine strategy of STMISP and determining mathematical model of eliminating machine conflicts. Secondly, on the basis of results of STMISP, a heuristic algorithm based on the rule of first come first serve (FCFS) principle is established to solve normal type of molten iron scheduling problem (NTMISP). The molten iron scheduling system with the two-stage method has been successfully applied to Shanghai Baosteel Company to realize quickly optimal molten iron scheduling. Application results show that the two-stage method is both effective and feasible.

关键词： Molten iron scheduling problem Two-stage method Hybrid flow shop Mixed-integer nonlinear programming model Heuristic algorithm

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Training ANFIS system with DE algorithm

Training ANFIS system with DE algorithm

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Allahyar Z. Zangeneh Mohammad Mansouri Mohammad Teshnehlab Ali K. Sedigh Computer Engineering Department Science and Research Branch Islamic Azad university of Tehran Iran Intelligent System laboratory (ISLAB) Control Department K. N. Toosi University of Technology Tehran Iran Advanced Process Automation & Control laboratory (APAC) Control Department K. N. Toosi University of Technology Tehran Iran

In this study, a new type of training the adaptive network-based fuzzy inference system (ANFIS) is presented by applying different types of the Differential Evolution branches. The TSK-type consequent part is a linear model of exogenous inputs. The consequent part parameters are learned by a gradient descent algorithm. The antecedent fuzzy sets are learned by basic differential evolution (DE/rand/1/bin) and then with some modifications in it. This method is applied to identification of the nonlinear dynamic system, prediction of the chaotic signal under both noise-free and noisy conditions and simulation of the two-dimensional function. Instead of DE/rand/1/bin, this paper suggests the complex type (DE/current-to-best/1+1/bin & DE/rand/1/bin) on predicting of Mackey-glass time series and identification of a nonlinear dynamic system revealing the efficiency of proposed structure. Finally, the method is compared with pure ANFIS to show the efficiency of this method.

关键词： Vectors Adaptive systems Input variables Training Mathematical model Equations Firing

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New method about how to construct decision tree based on association rule

New method about how to construct decision tree based on ass...

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IEEE International Workshop on Open-source Software for Scientific Computation (OSSC)

作者： Jing Gao Baoyong Zhao Information College Capital University of Economics and Business Beijing China School of Automation & Electrical Engineering University of Science and Technology Beijing Beijing China Key Laboratory of Advanced Control for Iron and Steel Process Ministry of Education China

ISBN: (纸本)9781612844923

Nowadays, decision tree is widely used as one of the most powerful tools in data mining. However, to construct an optimization decision tree is a complete NP problem. So a new method about how to construct decision tree, which is based on association rule mining, is proposed in this paper. Firstly, approximate exact rule with high reliability is defined. Secondly new attributes are generated from the approximate exact rule. And then its evaluation method is discussed in detail. Thirdly, the decision tree is constructed with both the new generated attributes and its original data. Finally, after comprehensive analysis, experimental results show that this new method has higher accuracy than any other old method.

关键词： Association rules Decision trees Approximation algorithms Classification algorithms Itemsets Accuracy

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Dynamic Optimal Scheduling Method and Its Application for Converter Fault in Steelmaking and Continuous Casting Production process

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IFAC Proceedings Volumes 2011年第1期44卷 9506-9511页

作者： Shengping Yu Tianyou Chai Hong Wang Xinfu Pang Binglin Zheng State Key Laboratory of Integrated Automation for Process Industry (Northeastern University) Shenyang China 110004 (Tel: +86-24-83689665-8013) National Metallurgical Automation Engineering Technology Research Center Northeastern University Shenyang China 110004 Control Systems Centre School of Electrical and Electronic Engineering the University of Manchester P O Box 88 Manchester M60 1QD UK

Abstract In steelmaking and continuous casting (SMCC) production process, converter fault can lead to unexpected changes to the pre-specified converter-continuous caster production mode so that the original scheduling plan becomes unrealizable. In this paper, the dynamic scheduling problem in response to converter fault is firstly analyzed. This is then followed by the establishment of a novel multi-objective nonlinear programming model (MONPM) by introducing the production mode parameter α, production schedule parameter β and χ. The proposed method considers changes in production mode, production schedule of charge, the interval characteristics of processing time. In specific, a two-stage dynamic optimal scheduling method is proposed including the production path planning of charges (PPP) and the production time scheduling (PTS). As a result, a dynamic optimal scheduling software system (DOSSS) is developed and is successfully applied to the scheduling of the largest iron and steel company (BaoSteel) in China. The real-time application shows that the proposed method can efficiently reduce scheduling time, significantly increase the outputs of converters and dramatically shorten the redundant waiting time for molten steel.

关键词： steelmaking and continuous casting dynamic optimization production mode nonlinear programming scheduling system

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Optimization research of genetic neural network based on Scilab

Optimization research of genetic neural network based on Sci...

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IEEE International Workshop on Open-source Software for Scientific Computation (OSSC)

作者： Baoyong Zhao Yingjian Qi Xing Tao School of Automation & Electrical Engineering University of Science and Technology Beijing Beijing China Key Laboratory of Advanced Control for Iron and Steel Process Ministry of Education China Science School Communication University of China Beijing China Beijing Research Center of Urban System Engineering Beijing China

ISBN: (纸本)9781612844923

Radial basis function (RBF) network is one of the significant neural networks. It has been used successfully in various fields. But in RBF network approximation algorithm, the initial value of the network weights, Gauss function center vector and broad-based vector is not easy to determine, and when these parameter choice is undeserved, RBF network approximation precision will decline and even the serious consequences of network spread will be produced. By using genetic algorithm in this paper, which can better realize RBF network parameter optimization, thereby increasing the accuracy of approximation. Scilab is open source software and has good simulation capabilities. Experiments using Scilab shows that the optimization method of genetic neural network is feasible and results are satisfied.

关键词： Genetic algorithms Radial basis function networks Optimization Approximation methods Vectors Biological cells Genetics

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A new double frequency exciting mode for the electromagnetic flowmeter

A new double frequency exciting mode for the electromagnetic...

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International Conference on Electric Information and control engineering (ICEICE)

作者： Shizhong Tang Feng Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University TJU Tianjin China

ISBN: (纸本)9781424480364

A new double frequency and rectangular waveform exciting mode is proposed, as to overcome the disadvantage of the current mode. The designed waveform is made up of two kinds of frequencies, the high frequency of 75Hz and the low frequency of 6.25Hz. The high frequency is used to reduce the interference from flow noise. The low frequency is introduced to keep the stabilization of zero. The design is established by using the FPGA and DDS technology. A 10-bit D/A converter and WCS circuit are adopted to change the voltage signal from FPGA for a current one. The design consists of a power amplification circuit as well, which has a function of magnifying the output current and boosting the ability of load. The characteristics of the new exciting mode are analyzed in details, and the design of the hardware and software is introduces. The experimental result indicates that once the new exciting mode is established, the error of differential inference and orthogonal inference can be reduced greatly. Besides, the measurement accuracy is improved at the same time.

关键词： Field programmable gate arrays Electromagnetics Patents Instruments Frequency measurement Automatic frequency control Electromagnetic scattering

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Generating Li-Yorke chaos in a stable continuous-time T-S fuzzy model via time-delay feedback control

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Chinese Physics B 2010年第7期19卷 141-149页

作者：孙秋野张化光赵琰 College of Information Science and Engineering Northeastern University Key Laboratory of Integrated Automation of Process Industry Ministry of EducationNortheastern University Department of Automatic Control Engineering Shenyang Institute of Engineering

This paper investigates the chaotification problem of a stable continuous-time T S fuzzy system. A simple nonlinear state time-delay feedback controller is designed by parallel distributed compensation technique. Then, the asymptotically approximate relationship between the controlled continuous-time T-S fuzzy system with time-delay and a discrete-time T-S fuzzy system is established. Based on the discrete-time T-S fuzzy system, it proves that the chaos in the discrete- time T-S fuzzy system satisfies the Li-Yorke definition by choosing appropriate controller parameters via the revised Marotto theorem. Finally, the effectiveness of the proposed chaotic anticontrol method is verified by a practical example.

关键词： chaotification T-S fuzzy model time-delay feedback Li Yorke chaos 1

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