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arXiv 2025年

作者： Tondji, Lionel Lorenz, Dirk A. Necoara, Ion Institute of Analysis and Algebra TU Braunschweig Braunschweig38092 Germany Automatic Control and Systems Engineering Department University Politehnica Bucharest Bucharest060042 Romania Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics The Romanian Academy Bucharest050711 Romania

In this paper, we propose a randomized accelerated method for the minimization of a strongly convex function under linear constraints. The method is of Kaczmarz-type, i.e. it only uses a single linear equation in each iteration. To obtain acceleration we build on the fact that the Kaczmarz method is dual to a coordinate descent method. We use a recently proposed acceleration method for the randomized coordinate descent and transfer it to the primal space. This method inherits many of the attractive features of the accelerated coordinate descent method, including its worst-case convergence rates. A theoretical analysis of the convergence of the proposed method is given. Numerical experiments show that the proposed method is more efficient and faster than the existing methods for solving the same *** Codes 65F10, 68W20, 90C25 © 2025, CC BY.

关键词： Convex optimization

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Basic Principles of MPC for Power Converters

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IEEE INDUSTRIAL ELECTRONICS MAGAZINE 2015年第3期9卷 31-43页

作者： Bordons, Carlos Montero, Carlos Department of Systems Engineering and Automatic Control University of Seville Spain

This article presents the basic principles of operation for model predictive control (MPC), a control methodology that opens a new world of opportunities. MPC is a powerful technique that can fulfill the increased performance and higher efficiency demands of power converters today. The main features of this technique are presented as well as the MPC strategy and basic elements. The two main MPC methods for power converters [continuous-control-set MPC (CCS-MPC) and finite-control-set MPC (FCS-MPC)] are described, and their application to a voltage-source inverter (VSI) is shown to illustrate their capabilities. This article tries to bridge the gap between the powerful but sometimes abstract techniques developed by researchers in the control community and the empirical approach of power electronics practitioners.

关键词： Converters Model predictive control Predictive control control systems Inverters Bridge circuits

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RADIAL BASIS FUNCTION NETWORK CONFIGURATION USING GENETIC ALGORITHMS

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NEURAL NETWORKS 1995年第6期8卷 877-890页

作者： BILLINGS, SA ZHENG, GL Department of Automatic Control and Systems Engineering University of Sheffield UK

Most training algorithms for radial basis function (RBF) neural networks start with a predetermined network structure which is chosen either by using a priori knowledge or based on previous experience. The resulting network is often insufficient or unnecessarily complicated and an appropriate network structure can only be obtained by trial and error. Training algorithms which incorporate structure selection mechanisms are usually based on local search methods and often suffer from a high probability of being trapped at a structural local minima. In the present study, genetic algorithms are proposed to automatically configure RBF networks. The network configuration is formed as a subset selection problem. The task is then to find an optimal subset of n(c) terms from the N-t training data samples. Each network is coded as a variable length string with distinct integers and genetic operators are proposed to evolve a population of individuals. Criteria including single objective and multiobjective functions me proposed to evaluate the fitness of individual networks. Training based on a practical data set is used to demonstrate the performance of the new algorithms.

关键词： RADIAL BASIS FUNCTION GENETIC ALGORITHMS NETWORK STRUCTURE SYSTEM IDENTIFICATION PATTERN RECOGNITION

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H observer-based control for fuzzy Hadamard fractional-order systems

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Computational and Applied Mathematics 2025年第4期44卷 1-14页

作者： Rhaima, Mohamed Gassara, Hamdi Mchiri, Lassaad El Hajjaji, Ahmed Ben Makhlouf, Abdellatif Department of Statistics and Operations Research College of Science King Saud University Riyadh Saudi Arabia Laboratory of Sciences Techniques of Automatic Control and Computer Engineering National School of Engineering of Sfax University of Sfax Sfax Tunisia Panthéon-Assas University Paris II Paris France Modeling Information and Systems Laboratory University of Picardie Jules Verne UFR of Sciences Amiens France Department of Mathematics Faculty of Sciences Sfax University Sfax Tunisia

While the $$H_\infty $$ observer-based control has found widespread application in the literature for integer-order systems, researchers have shown less interest in addressing the same issue within the fractional-order framework. In this context, this study delves into the application of $$H_\infty $$ observer-based control for the Hadamard fractional-order system (HFOS) described by the Takagi–Sugeno fuzzy models (TSFM). Using Lyapunov approach and by employing a matrix decoupling technique, LMI based conditions ensuring the existence of an observer and controller, are proposed. To minimize the impact of disturbances on the controlled output, $$H_\infty $$ optimization technique is used. The validity of our approach is substantiated through an example, underscoring the robustness and reliability of our proposed findings.

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A nonparametric polynomial identification algorithm for the Hammerstein system

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IEEE TRANSACTIONS ON automatic control 1997年第10期42卷 1435-1441页

作者： Lang, ZQ Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

Almost all existing Hammerstein system nonparametric identification algorithms can recover the unknown system nonlinear element up to an additive constant, and one functional value of the nonlinearity is usually assumed to be known to make the constant solvable. To overcome this defect, in this paper, a new nonparametric polynomial identification algorithm for the Hammerstein system is proposed which extends the idea in the author's previous work on the Hammerstein system identification to a more general and practical case, where no functional value of the system nonlinearity is known a priori. Convergence and convergence rates in both uniform and global senses are established, and simulation studies demonstrate the effectiveness and advantage of the new algorithm.

关键词： convergence convergence rates Hammerstein model nonlinear systems nonparametric identification

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SELF-ADAPTIVE AND SELF-ORGANIZING control APPLIED TO NONLINEAR MULTIVARIABLE ANESTHESIA - A COMPARATIVE MODEL-BASED STUDY

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IEE PROCEEDINGS-D control THEORY AND APPLICATIONS 1992年第4期139卷 381-394页

作者： LINKENS, DA MAHFOUF, M ABBOD, M Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

Various SISO feedback control techniques have been applied successfully to muscle relaxant anaesthesia in simulations and clinical trials. SISO generalised predictive control (GPC) altogether with self-organising control using fuzzy logic theory (SOFLC) are among these techniques. A multivariable model combining muscle relaxation (paralysis) and anaesthesia (unconsciousness) has been identified. The multivariable version of GPC in its basic form as well as its different extensions to include model following and observer filter polynomials is outlined in addition to the multivariable version of SOFLC. Both of these strategies are applied to the previous model whose parameters were chosen according to a Monte-Carlo method. The robustness of both control strategies is investigated and the results presented and discussed, enabling a comparison to be made between self-adaptive and self-organising techniques. It is concluded that, when a detailed mathematical model structure is available, GPC provides better control than SOFLC.

关键词： ADAPTIVE control SELF-TUNING GENERALIZED PREDICTIVE control SELF-ORGANIZING control ANESTHESIA FUZZY SETS UNCONSCIOUSNESS MUSCLE RELAXATION

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Digital phenotyping from heart rate dynamics: Identification of zero-poles models with data-driven evolutionary learning

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Computers in Biology and Medicine 2025年 186卷 109596-109596页

作者： Patrascu, Adrian Ion, Andreea Vislapuu, Maarja Husebo, Bettina S. Tache, Irina Andra Reithe, Haakon Patrascu, Monica Centre for Interdisciplinary Research in Physical Education and Sport Babes-Bolyai University Cluj-Napoca Romania Complex Systems Laboratory University Politehnica of Bucharest Bucharest Romania Centre for Elderly and Nursing Home Medicine University of Bergen Bergen Norway Department of Nursing VID Specialized University Bergen Norway Neuro-SysMed Center University of Bergen Bergen Norway Department of Automatic Control and Systems Engineering University Politehnica of Bucharest Bucharest Romania Department of Image Fusion and Analytics Siemens SRL Brasov Romania

Heart rate response to physical activity is widely investigated in clinical and training practice, as it provides information on a person's physical state. For emerging digital phenotyping approaches, there is a need for individualized model estimation. In this study, we propose a zero-poles model and a data-driven evolutionary learning method for identification. We also perform a comparison with existing first and second order models and gradient descent identification methods. The proposed model is based on a five-phase description of heart rate dynamics. Data was collected from 30 healthy participants using a treadmill and a thoracic sensor in two protocols (static and dynamic), for increasing and decreasing activity. Results show that the zero-poles model is a good fit for heart rate response to exercise (Pearson's coefficient ρ>.95), while first and second order models are also suitable (ρ>.92). The evolutionary learning method shows excellent results for fast model identification, in comparison with least-squares methods (p © 2024 The Author(s)

关键词： Contrastive Learning

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Payoff-based accumulative effect promotes cooperation in spatial prisoner’s dilemma

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Chinese Physics B 2010年第9期19卷 53-58页

作者：刘永奎李智陈小杰王龙 Center for Complex Systems Department of Automatic Control EngineeringXidian University State Key Laboratory for Turbulence and Complex Systems Center for Systems and ControlCollege of EngineeringPeking University

We study the effect of accumulative payoff on the evolution of cooperation in the evolutionary prisoner＇s dilemma on a square lattice. We introduce a decaying factor for the accumulative payoff, which characterizes the extent that the historical payoff is accumulated. It is shown that for fixed values of the temptation to defect, the density of cooperators increases with the value of the decaying factor. This indicates that the more the historical payoff is involved, the more favourable cooperators become. In the critical region where the cooperator density converges to zero, cooperators vanish according to a power-law-like behaviour. The associated exponents agree approximately with the two-dimensional directed percolation and depend weakly on the value of the decaying factor.

关键词： payoff accumulative effect prisoner's dilemma cooperation

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Evolutionary prisoner's dilemma game on highly clustered community networks

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Chinese Physics B 2009年第7期18卷 2623-2628页

作者：刘永奎李智陈小杰王龙 Center for Complex Systems Department of Automatic Control Engineering Xidian University State Key Laboratory for Turbulence and Complex Systems Center for Systems and Control College of Engineering Peking University

This paper studies the evolutionary prisoner＇s dilemma game on a highly clustered community network in which the clustering coefficient and the community size can be tuned. It finds that the clustering coefficient in such a degree-homogeneous network inhibits the emergence of cooperation for the entire range of the payoff parameter. Moreover, it finds that the community size can also have a marked influence on the evolution of cooperation, with a larger community size leading to not only a lower cooperation level but also a smaller threshold of the payoff parameter above which cooperators become extinct.

关键词： prisoner's dilemma cooperation clustering coefficient community structure

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Complexity of Linearized Perturbed Augmented Lagrangian Methods for Nonsmooth Nonconvex Optimization with Nonlinear Equality Constraints

arXiv

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arXiv 2025年

作者： Bourkhissi, Lahcen El Necoara, Ion Patrinos, Panagiotis Tran-Dinh, Quoc Automatic Control and Systems Engineering Department Politehnica Bucharest Bucharest060042 Romania Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics The Romanian Academy Bucharest050711 Romania Department of Electrical Engineering K.U. Leuven LeuvenB-3001 Belgium Department of Statistics and Operations Research University of North Carolina at Chapel Hill Chapel HillNC27599 United States

This paper addresses a class of general nonsmooth and nonconvex composite optimization problems subject to nonlinear equality constraints. We assume that a part of the objective function and the functional constraints exhibit local smoothness. To tackle this challenging class of problems, we propose a novel linearized perturbed augmented Lagrangian method. This method incorporates a perturbation in the augmented Lagrangian function by scaling the dual variable with a sub-unitary parameter. Furthermore, we linearize the smooth components of the objective and the constraints within the perturbed Lagrangian function at the current iterate, while preserving the nonsmooth components. This approach, inspired by prox-linear (or Gauss-Newton) methods, results in a convex subproblem that is typically easy to solve. The solution of this subproblem then serves as the next primal iterate, followed by a perturbed ascent step to update the dual variables. Under a newly introduced constraint qualification condition, we establish the boundedness of the dual iterates. We derive convergence guarantees for the primal iterates, proving convergence to an ϵ-first-order optimal solution within O(ϵ−3) evaluations of the problem’s functions and their first derivatives. Moreover, when the problem exhibits for example a semialgebraic property, we derive improved local convergence results. Finally, we validate the theoretical findings and assess the practical performance of our proposed algorithm through numerical comparisons with existing state-of-the-art methods. © 2025, CC BY.

关键词： Lagrange multipliers

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