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Output tracking of Markovian jumping systems via error feedback regulation

IFAC Proceedings Volumes 2011年第1期44卷 2424-2429页

作者： Shuping He Zhengtao Ding Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi 214122 P. R.China Control Systems Centre School of Electrical and Electronic Engineering University of Manchester Manchester M60 1QD UK

Abstract This paper studies the output tracking problem of continuous-time Markovian jumping systems (MJSs) via error feedback scheme. With the extension of output regulation to MJSs, sufficient conditions are obtained based on stochastic Lyapunov-Krasovskii functional. The resulting closed-loop system is guaranteed to be stochastically stable and the output tracking is achieved almost asymptotically. Moreover, the output regulation error almost asymptotically converges to zero. In order to ensure the relaxed solutions of the regulation equations, we described the problem as a semi-definite optimization approach via disciplined convex programming. Simulation result is also given to illustrate the performance and effectiveness of the proposed approach.

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Novel variance-constrained filtering for uncertain systems subject to randomly varying sensor delay

Novel variance-constrained filtering for uncertain systems s...

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Chinese control and Decision Conference, CCDC

作者： Yijing Wang Zhiqiang Zuo Daniel W. C. Ho Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University TJU Tianjin China Department of Mathematics City University of Hong Kong Kowloon Hong Kong China

In this paper, the problem of robust filtering for a class of uncertain discrete-time stochastic systems under randomly varying distributed sensor delay is reconsidered. A new and efficient method for robust filter design is introduced to achieve some performance requirements, that is, the error state of filtering process is mean square bounded and the steady-state variance of the estimation error for each state is less than the individual prescribed upper bound. Different from the previous method which involves a two-step design procedure with algebraic Riccati-like inequalities and linear constraint, it is shown that this problem can be directly converted to the feasibility of some linear matrix inequalities. Furthermore, the inequality used for handling the parameter uncertainty in the previous literature is no required which reduces the conservatism of the obtained results. An example is carried out to illustrate the effectiveness of the method and the improvement over the existing result in the literature.

关键词： Delay Steady-state Robustness Uncertain systems Linear matrix inequalities Symmetric matrices Mathematical model

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Experiment design for Pauli channel estimation

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IFAC Proceedings Volumes 2011年第1期44卷 4344-4349页

作者： Gábor Balló Katalin M. Hangos Department of Electrical Engineering and Information Systems University of Pannonia Egyetem u. 10 H-8200 Veszprém Hungary Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences P.O. Box 63 H-1518 Budapest Hungary

Abstract Experiment design for quantum channel parameter estimation includes the design of the quantum input to the channel and the observables to be applied on the resulting quantum output system, called the experiment configuration. An experiment design procedure based on maximizing the Fisher information of the qubit Pauli channel parameters is presented in this paper. It can be shown that the Fisher information is a convex function in both the input and the experiment configuration parameters. This leads to an optimal setting that includes pure input states and projective measurements directed towards the channel directions. An iterative method of estimating the channel directions is also proposed.

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Active Disturbance Rejection control simulation toolbox in open-source software Scilab/Xcos

Active Disturbance Rejection Control simulation toolbox in o...

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

作者： Lijun Wang Qing Li Chaonan Tong Yixin Yin Jiangyun Li Siyang Song School of Automation & Electrical Engineering Key Laboratory of Advanced Control of Iron and Steel Process Ministry of Education University of Science and Technology Beijing(USTB) Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781612844923

To satisfy high accuracy and speed requirement, a kind of Active Disturbance Rejection control (ADRC) solution is proposed according to the complexity of Monitor Finishing Automatic Width control (FAWC) system with large time-delay for hot strip mill. In order to improve the versatility of ADRC parameters, a unit gain was added in the loop. Based on the simplified model, the presented ADRC consists of linear functions which make it easier to realize. For applying ADRC algorithms conveniently and widely, the control system is implemented in Scilab/Xcos, which is one of an Open-source Software for Scientific Computation (OSSC) and is free of charge. According to the program of data exchanging between Xocs and Scilab, Xcos simulation can be carried out in batch processing in Scilab. The disturbances rejection and robustness of the proposed control method is verified by ADRC simulation toolbox in Scilab/Xcos.

关键词： Strips Monitoring Educational institutions Uncertainty Steel control systems Temperature measurement

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A multiscale slice model for continuous casting of steel

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IOP Conference Series: Materials Science and engineering 2012年第1期33卷

作者： B Šarler R Vertnik A Z Lorbiecka I Vušanović B Senčič Laboratory for Multiphase Processes University of Nova Gorica Vipavska 13 SI-5000 Nova Gorica Slovenia Centre of Excellence for Biosensorics Automation and Process Control Velika pot 22 Solkan Slovenia Štore Steel d.o.o Technical Developement Železarska 3 SI-3220 Štore Slovenia Faculty of Mechanical Engineering University of Montenegro George Washington st. 81000 Podgorica Montenegro

A simple Lagrange-an traveling slice model has been applied for the prediction of the relations between process parameters, macrosegregation and solidification grain structure formation (equiaxed to columnar and columnar to equiaxed transition) during the continuous casting process of steel billets. The main advantage of the slice model is its very fast calculation time in comparison with the complete 3D heat and fluid flow model which might need calculation time, measured in days. The slice models thus allows for fast optimisation and even for on-line simulation. The heat and species transfer models are based on the mixture continuum assumptions with Lever solidification rule and enhanced thermal and solutal diffusivities for heuristic accounting of fluid flow effects. The grain structure evolution model is based on the Gaussian nucleation rule, and KGT growth model, coupled to the macroscopic heat and species transfer models. The heat and species transfer models are solved by the meshless technique by using local collocation with radial basis functions. The grain structure evolution model is solved by the point automata technique, a novel meshless variant of the cellular automata method. A comparison of the results with the experimental data for steel grade 51CrV4 is shown in terms of macrosegregation and grain structure across the billet. Simulations and comparisons have been carried out for nominal casting conditions, reduced casting temperature, and reduced casting speed. The model predicts surprisingly well the qualitative features of the macrosegregation and grain structure patterns. Possible refinements of the model with respect to other physical mechanisms are discussed.

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Stochastic gradient parameter estimation of input nonlinear systems using the filtering technique

Stochastic gradient parameter estimation of input nonlinear ...

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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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