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International Conference on Electrical engineering and Software Applications (ICEESA)

作者： Assil Ayadi Amine Trabelsi Mohamed Chaabane Driss Mehdi National Engineering School of Sfax (ENIS) Laboratory of Sciences and Techniques of Automatic control & computer engineering (Lab-STA) University of Sfax Sfax Tunisia Laboratoire dInformatique et dautomatique pour les systèmes (LIAS) Université de Poitiers Poitiers France

ISBN: (纸本)9781467363020

This paper deals with the H ∞ control of nonlinear fuzzy descriptor system described by Takagi-Sugeno fuzzy models. In the first step, we present a stability analysis of nonlinear fuzzy descriptor system. The stability conditions are given in LMI form. In the second step, we have developed H ∞ PDC control law in order to reject the effects of external disturbances submitted to the system. Finally, a simulation example is presented to illustrate the mains results.

关键词： Symmetric matrices Xenon Stability analysis Mathematical model Vectors PD control Matrix decomposition

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Comparison between a backstepping mode control and a sliding mode control for a boost DC-DC converter of a photovoltaic panel

Comparison between a backstepping mode control and a sliding...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Yosra Massaoudi Tarak Damak Mariem Ghamgui Driss Mehdi National Engineering School of Sfax (ENIS) Laboratory of Sciences and Techniques of Automatic control & computer engineering (Lab-STA) University of Sfax Sfax Tunisia Laboratoire dInformatique et dAutomatique pour les systèmes (LIAS-ENSIP) Université de Poitiers Poitiers France

ISBN: (纸本)9781467364591

This paper focuses on the development of renewable energy systems. The main goal is the optimal exploitation from photovoltaic panels. Therefore, two robust control laws will be applied on the DC-DC boost converter in order to maintain a robust output voltage regulation. The first part of this communication is devoted to the backstepping mode control. In the second part, we will present the sliding mode control. Finally, we will present simulations to illustrate the validity of the proposed approaches and to compare their performances.

关键词： Backstepping Voltage control Mathematical model Sliding mode control Resistance Stability analysis Equations

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Fuzzy c-regression models based on the BELS method for nonlinear system identification

Fuzzy c-regression models based on the BELS method for nonli...

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International Conference on Electrical engineering and Software Applications (ICEESA)

作者： Borhen Aissaoui Moêz Soltani Dorsaf Elleuch Abdelkader Chaari Universite de Tunis Ecole Superieure des Sciences et Techniques de Tunis Tunis TN Laboratory of Sciences and Techniques of Automatic control & computer engineering (Lab-STA) National Engineering School of Sfax Sfax Tunisia Research Unit on Control Monitoring and Safety of Systems (C3S) (ESSTT) Tunisia

ISBN: (纸本)9781467363020

A fuzzy c-regression model clustering algorithm based on Bias-Eliminated Least Squares method (BELS) is presented. This method is designed to develop an identification procedure for noisy nonlinear systems. The BELS method is used to identify consequent parameters and eliminate the bias. The proposed approach has been applied to benchmark modeling problem which proved a good performance.

关键词： Mathematical model Clustering algorithms Equations Noise Vectors Nonlinear systems Computational modeling

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H_∞ filtering with Diagonal Interacting Multiple Model Algorithm for Maneuvering Target Tracking

H_∞ filtering with Diagonal Interacting Multiple Model Algo...

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American control Conference

作者： X. Fu Y. Jia J. Du J. Zhang W. Li X. Liu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunication school of Electronic and Information Engineering Beihang University (BUAA) Department of Automatic Beijing Information and Science of University

ISBN: (纸本)9781479901777

This paper is devoted to the problem of state estimate of discrete-time stochastic systems with Markov jump parameters. A robust algorithm-diagonal interacting multiple model algorithm based on H_∞ filtering (DIMMH) is presented for maneuvering target tracking when measurement noise is of unknown statistics. Extensive Monte Carlo simulations show the effectiveness and superiority of the proposed algorithm.

关键词： Maneuvering Target Tracking Markov jump parameters effectiveness Target tracking maneuvering target State estimation Filtration tracking Noise measurement Diagonal Monte Carlo technique

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Distributed event-triggered control with network delays and packet losses

Distributed event-triggered control with network delays and ...

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51st IEEE Annual Conference on Decision and control (CDC)

作者： Guinaldo, M. Lehmann, D. Sanchez, J. Dormido, S. Johansson, K. H. Department of Computer Science and Automatic Control at UNED Spain School of Electrical Engineering Royal Institute of Technology (KTH) Sweden

ISBN: (纸本)9781467320665

This paper presents a distributed event-based control approach to cope with communication delays and packet losses affecting a networked dynamical system consisting of N linear time-invariant coupled systems. Two communication protocols are proposed to deal with these communication effects. It is shown that both protocols preserve the system stability in the sense that the state of every subsystem converges to a small region around the origin if the delay and the number of packet losses are bounded. Analytical expressions for the delay bound and the maximum number of consecutive packet losses are derived. Simulations illustrate the results.

关键词： delays distributed parameter systems linear systems networked control systems protocols stability

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Genetic algorithm assisted fuzzy iterative learning optimizer for automatic optimization of oil well placement under production constraints

Genetic algorithm assisted fuzzy iterative learning optimize...

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15th IFAC Workshop on control Applications of Optimization, CAO 2012

作者： Ebadat, A. Karimaghaee, P. Automatic Control Lab. School of Electrical and Computer Engineering KTH Stockholm Sweden School of Electrical and Computer Engineering Shiraz University Shiraz Iran

ISBN: (纸本)9783902823144

In this paper a new optimization approach based on fuzzy systems and iterative learning is proposed where Genetic Algorithm (GA) employed to optimally determine fuzzy parameters. The method is appropriate for highly nonlinear and uncertain large scale systems such as optimal oil well placement. Well-placement is a crucial step in field development. However, the major difficulties of the problem are highly nonlinear dynamics of reservoir, well locations constraints and large number of decision variables. Therefore, in this paper, a new optimization method is proposed and employed to solve the problem. Fuzzy rule generation is done employing GA to avoid being stuck in local optima. Since fuzzy coefficients are considered as decision variables instead of well locations, number of optimization parameters reduces significantly. Simulation results show superior performance such as lower computational load and less number of simulator runs compared with ones obtained by previous methods. © 2012 IFAC.

关键词： Genetic algorithms

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state estimation with fading measurements, randomly varying nonlinearities and probabilistic distributed delays

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International Journal of Robust and Nonlinear control 2014年第13期25卷

作者： Derui Ding Zidong Wang Bo Shen Hongli Dong School of Information Science and Technology Donghua University Shanghai 200051 China Department of Computer Science Brunel University Uxbridge Middlesex UB8 3PH UK NAAM Research Group Department of Mathematics King Abdulaziz University Jeddah 21589 Saudi Arabia Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg 47057 Germany College of Electrical and Information Engineering Northeast Petroleum University Daqing 163318 China

In this paper, the state estimation problem is investigated for a class of discrete-time stochastic systems in simultaneous presence of three network-induced phenomena, namely, fading measurements, randomly varying nonlinearities and probabilistic distributed delays. The channel fading is characterized by the ℓ th-order Rice fading model whose coefficients are mutually independent random variables with given probability density functions. Two sequences of random variables obeying the Bernoulli distribution are utilized to govern the randomly varying nonlinearities and probabilistic distributed delays. The purpose of the problem addressed is to design an state estimator such that the dynamics of the estimation errors is stochastically stable and the prespecified disturbance rejection attenuation level is guaranteed. Through intensive stochastic analysis, sufficient conditions are established under which the addressed state estimation problem is recast as a convex optimization one that can be solved via the semi-definite program method. Finally, a simulation example is provided to show the usefulness of the proposed state estimation scheme. Copyright © 2014 John Wiley & Sons, Ltd.

关键词： state estimation fading measurements randomly varying nonlinearities probabilistic distributed delays

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Identification of box-jenkins models using structured ARX models and nuclear norm relaxation

Identification of box-jenkins models using structured ARX mo...

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Universite Libre de Bruxelles

作者： Hjalmarsson, Hakan Welsh, James S. Rojas, Cristian R. Automatic Control Lab. ACCESS Linnaeus Centre KTH Royal Institute of Technology Sweden School of Electrical Engineering and Computer Science University of Newcastle Australia

ISBN: (纸本)9783902823069

In this contribution we present a method to estimate structured high order ARX models. By this we mean that the estimated model, despite its high order is close to a low order model. This is achieved by adding two terms to the least-squares cost function. These two terms correspond to nuclear norms of two Hankel matrices. These Hankel matrices are constructed from the impulse response coefficients of the inverse noise model, and the numerator polynomial of the model dynamics, respectively. In a simulation study the method is shown to be competitive as compared to the prediction error method. In particular, in the study the performance degrades more gracefully than for the Prediction Error Method when the signal to noise ratio decreases. © 2012 IFAC.

关键词： Impulse response

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Genetic Algorithm Assisted Fuzzy Iterative Learning Optimizer for automatic Optimization of Oil well Placement under Production Constraints

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IFAC Proceedings Volumes 2012年第25期45卷 223-228页

作者： A. Ebadat P. Karimaghaee Automatic Control Lab School of Electrical and Computer Engineering KTH Stockholm Sweden School of Electrical and Computer Engineering Shiraz University Shiraz Iran

关键词： Optimization Method Evolutionary algorithm stochastic optimization Multi-objective Optimization Oil well Placement

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Synchronization of FitzHugh-Nagumo systems: An adaptive approach

Synchronization of FitzHugh-Nagumo systems: An adaptive appr...

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2012 8th International Conference on Natural Computation, ICNC 2012

作者： Wei, Wei Zuo, Min Liu, Zaiwen Wang, Jing Department of Automatic Control Computer and Information Engineering School Beijing Technology and Business University Beijing China National Engineering Research Center of Advanced Rolling University of Science and Technology Beijing China

ISBN: (纸本)9781457721311

In this article, synchronization of FitzHugh-Nagumo (FHN) neurons is considered. Adaptive controller based on active compensation is adopted to drive the slave neuron to track the master neuron. Sufficient condition for asymptotic stability of the close-loop system is derived. Numerical simulation results are given to confirm the adaptive controller is valid. © 2012 IEEE.

关键词： Neurons

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