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作者： Li, Jun Zhou, Mengchu Guo, Tao Gan, Yahui Dai, Xianzhong Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China School of Automation Southeast University Nanjing 210096 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

Supervisory control reconfiguration can handle the uncertainties including resource failures and task changes in discrete event systems. It was not addressed to exploit the robustness of closed-loop systems to accommodate some uncertainties in the prior studies. Such exploitation can cost-efficiently achieve reconfigurability and flexibility for real systems. This paper presents a robust reconfiguration method based on Petri nets (PNs) and integer programming for supervisory control of resource allocation systems (RASs) subject to varying resource allocation relationships. An allocation relationship is seen as a control specification while the execution processes requiring resources as an uncontrolled plant. First, a robust reconfiguration mechanism is proposed. It includes updating the P-invariant-based supervisor and evolving the state of the closed-loop system. The latter adapts to the control specification changes by the self-regulation of the closed-loop system's state. Next, two novel integer programming models for control reconfiguration are proposed, called a reconfiguration model with acceptability and reconfiguration one with specification correction. Since both models integrate the firability condition of transitions, no additional efforts are required for the state reachability analysis. Finally, a hospital emergency service system is used as an example to illustrate them. © 2014 Elsevier Ltd. All rights reserved.

关键词： Integer programming

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A new hybrid optimization algorithm for solving economic load dispatch problem with valve-point effect

A new hybrid optimization algorithm for solving economic loa...

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2014 North American Power Symposium, NAPS 2014

作者： Elyas, Seyyed H. Mandal, Paras Haque, Ashraf U. Giani, Annarita Tseng, Tzu-Liang Bill Department of Electrical and Computer Engineering University of Texas El PasoTX79968 United States Power Study Group Teshmont Consultants LP CalgaryAB Canada Energy and Infrastructure Decision Group Los Alamos National Laboratory Los AlamosNM87545 United States Department of Industrial Manufacturing and Systems Engineering University of Texas El PasoTX79968 United States

ISBN: (纸本)9781479959044

This paper presents an efficient approach for solving the economic load dispatch (ELD) problem with valve-point effect using a new hybrid optimization algorithm. The main aim for solving ELD problem is to schedule the output of the committed generating units in order to meet the system load under various operating constraints. Since ELD is a non-linear and non-convex problem, stochastic search algorithms are considered as appropriate solutions. In this paper, the proposed new hybrid optimization algorithm is based on Clonal Selection Algorithm (CSA) that uses the positive features of two other optimization techniques, Gases Brownian Motion Optimization (GBMO) and Particle Swarm Optimization (PSO), for local search and improving the quality of initial population, respectively. To validate the efficiency of the proposed hybrid method, termed as PG-Clonal in this paper, we tested it on two systems considering different constraints, and the obtained results are compared with the results of existing stochastic search algorithms available in the literature. The test results demonstrate the effectiveness of the proposed new hybrid PG-Clonal method in solving the ELD problem efficiently. © 2014 IEEE.

关键词： Brownian movement

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Positive Stabilization with Maximum Stability Radius for Linear Time-Delay systems

Positive Stabilization with Maximum Stability Radius for Lin...

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IEEE Annual Conference on decision and control

作者： B. Shafai A. Oghbaee T. Tanaka department of Electrical and computer Engineering Northeastern University Boston MA 02115 USA LIDS (Laboratory for Information and Decision Systems) Massachusetts Institute of Technology Cambridge MA 02139 USA

ISBN: (纸本)9781467360890

This paper considers the problem of positive stabilization of uncertain linear time-delay systems by state feedback such that the resulting closed-loop system attains maximum stability radius with positivity constraint. First, we focus on the class of linear continuous-time positive delay systems (Metzlerian delay systems) and outline its interesting properties. Using the stability properties associated with this class, we formulate a constrained stabilization problem for the linear time delay system and provide conditions for the existence of controllers satisfying the stability and Metzlerian constraints. The Metzlerian stabilization is solved using Linear Matrix Inequality (LMI) or Linear Programming (LP). Next, we characterize the uncertainties associated with the positive delay systems and define the stability radius associated with this class which can be expressed in a closed form. Finally, we combine Metzlerian stabilization with maximum stability radius with the aid of bounded real lemma (BRL) and provide a complete solution using LMI. Examples are included for the purpose of illustration.

关键词： Delay systems linear time-delay system uncertain linear time-delay systems State feedback Induction loop systems

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ANN-based DTC scheme to improve the dynamic performance of an IM drive

ANN-based DTC scheme to improve the dynamic performance of a...

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7th IET International Conference on Power Electronics, Machines and Drives, PEMD 2014

作者： Bouhoune, K. Yazid, K. Boucherit, M.S. Power and Industrial Systems Laboratory Faculty of Electronics and Computer Science University of Science and Technology Houari Boumediene PO Box 32 El Alia Bab Ezzouar 16111 Algiers Algeria Process Control Laboratory Department of Electrical Engineering Polytechnic National School PO Box 182 10 Hassan Badi El-Harrach 16200 Algiers Algeria

ISBN: (纸本)9781849198158

In addition to simplicity, the DTC of the IM allows a good torque control in steady-state and transient operating conditions. However, high torque ripple is produced, which is reflected in speed estimation responses. It also increases acoustical noise and makes the voltage source inverter operated in high and variable switching frequency, requiring a high sampling frequency. In this paper, a simple effective ANN-based DTC of the induction machine is proposed. Neural networks with a simple architecture are designed and implemented in influential points of the direct torque control block of the three phase induction machine in order to improve its dynamic performance while preserving the DTC structure simplicity as much as possible. In particular, this paper proposes to reduce, on the one hand, the torque ripple and commutation frequency. Neural comparators are used to select the appropriate bandwidth for the torque and flux hysteresis controllers. Their aim is to optimize the ripple level in the developed torque and flux. On the other hand, a neural speed controller is designed in order to improve the system ability to respond rapidly to changes in process variables and mitigate the effects of external perturbations. The performance of the proposed control are tested in simulation and highlighted by comparing to the conventional DTC control based on conventional hysteresis comparators and conventional PI speed controller. The obtained results show the feasibility and good performances of the proposed control.

关键词： Neural networks

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Experimental Design for System Identification of Boolean control Networks in Biology

Experimental Design for System Identification of Boolean Con...

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IEEE Annual Conference on decision and control

作者： Alberto Giovanni Busetto John Lygeros Intelligent and Predictive Systems Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara California USA Automatic Control Laboratory ETH Zurich Zurich Switzlerand

ISBN: (纸本)9781467360890

This study is primarily motivated by biological applications and focuses on the identification of Boolean networks from scarce and noisy data. We consider two Bayesian experimental design scenarios: selection of the observations under a budget, and input design. The goal is to maximize the mutual information between models and data, that is the ultimate statistical upper bound on the identifiability of a system from empirical data. First, we introduce a method to select which components of the state variable to measure under a budget constraint, and at which time points. Our greedy approach takes advantage of the submodularity of the mutual information, and hence requires only a polynomial number of evaluations of the objective to achieve near-optimal designs. Second, we consider the computationally harder task of designing sequences of input interventions, and propose a likelihood-free approximation method. Exact and approximate design solutions are verified with predictive models of genetic regulatory interaction networks in embryonic development.

关键词： System identification State variable Biological Science Disciplines biology Budgets Boolean algebra Mathematic Identifiability noisy data Approximation method Prediction models Embryonic Development Input design

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Erratum to: The whole genome sequence of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), reveals insights into the biology and adaptive evolution of a highly invasive pest species

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Genome biology 2017年第1期18卷 11页

作者： Alexie Papanicolaou Marc F Schetelig Peter Arensburger Peter W Atkinson Joshua B Benoit Kostas Bourtzis Pedro Castañera John P Cavanaugh Hsu Chao Christopher Childers Ingrid Curril Huyen Dinh HarshaVardhan Doddapaneni Amanda Dolan Shannon Dugan Markus Friedrich Giuliano Gasperi Scott Geib Georgios Georgakilas Richard A Gibbs Sarah D Giers Ludvik M Gomulski Miguel González-Guzmán Ana Guillem-Amat Yi Han Artemis G Hatzigeorgiou Pedro Hernández-Crespo Daniel S T Hughes Jeffery W Jones Dimitra Karagkouni Panagiota Koskinioti Sandra L Lee Anna R Malacrida Mosè Manni Kostas Mathiopoulos Angela Meccariello Monica Munoz-Torres Shwetha C Murali Terence D Murphy Donna M Muzny Georg Oberhofer Félix Ortego Maria D Paraskevopoulou Monica Poelchau Jiaxin Qu Martin Reczko Hugh M Robertson Andrew J Rosendale Andrew E Rosselot Giuseppe Saccone Marco Salvemini Grazia Savini Patrick Schreiner Francesca Scolari Paolo Siciliano Sheina B Sim George Tsiamis Enric Ureña Ioannis S Vlachos John H Werren Ernst A Wimmer Kim C Worley Antigone Zacharopoulou Stephen Richards Alfred M Handler Hawkesbury Institute for the Environment Western Sydney University Sydney Australia. Justus-Liebig-University Giessen Institute for Insect Biotechnology 35394 Giessen Germany. Department of Biological Sciences Cal Poly Pomona Pomona CA 91768 USA. Department of Entomology and Center for Disease Vector Research University of California Riverside Riverside CA 92521 USA. Interdepartmental Graduate Program in Genetics Genomics & Bioinformatics University of California Riverside Riverside CA 92521 USA. Department of Biological Sciences University of Cincinnati Cincinnati OH 45221 USA. Insect Pest Control Laboratory Joint FAO/IAEA Programme of Nuclear Techniques in Food and Agriculture Seibersdorf Vienna Austria. Department of Environmental and Natural Resources Management University of Patras Agrinio Greece. Department of Environmental Biology Centro de Investigaciones Biológicas CSIC 28040 Madrid Spain. Human Genome Sequencing Center Department of Human and Molecular Genetics Baylor College of Medicine 77030 Houston TX USA. National Agricultural Library USDA 20705 Beltsville MD USA. Georg-August-Universität Göttingen Johann-Friedrich-Blumenbach-Institut für Zoologie und Anthropologie 37077 Göttingen Germany. Department of Biology University of Rochester 14627 Rochester NY USA. Department of Biological Sciences Wayne State University 48202 Detroit MI USA. Department of Biology and Biotechnology University of Pavia 27100 Pavia Italy. USDA-ARS Pacific Basin Agricultural Research Center 96720 Hilo HI USA. DIANA-Lab Department of Electrical & Computer Engineering University of Thessaly 382 21 Volos Greece and Hellenic Pasteur Institute 11521 Athens Greece. Department of Entomology University of Illinois at Urbana-Champaign 61801 Urbana IL USA. Department of Biological Sciences Oakland University 48309 Rochester MI USA. Department of Biochemistry and Biotechnology University of Thessaly Larissa Greece. Department of Biology Univer

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On the Cooperative Observability of a Continuous-Time Linear System on an Undirected Network

On the Cooperative Observability of a Continuous-Time Linear...

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International Joint Conference on Neural Networks

作者： Henghui Zhu Kexin Liu Jinhu Lu Zongli Lin Yao Chen Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Charles L. Brown Department of Electrical and Computer Engineering University of Virginia School of Electronic and Information Engineering Beijing Jiaotong University

ISBN: (纸本)9781479914821

In traditional control theory, a single observer has access all the measured outputs of the plant to estimates its asymptotically. In many real world engineering systems, it may be difficult to build a single observer that has access to all the measured outputs. One way around this difficulty is to build a network of cooperative observers, each of which obtains a portion of the measurement outputs, that collectively produce an asymptotic estimate of the plant state. In this paper, we construct a network of such observers for a continuous-time linear system. Assuming that these observers are connected through an undirected connected network, we establish a necessary and sufficient condition on the plant parameters under which the network of observers will achieve asymptotic omniscience. A network of cooperative observers is said to achieve asymptotic omniscience if their states all converge to the plant state asymptotically. Numerical simulation results are presented to validate theoretical results. The design of cooperative observers sheds some light on the solution of some other real-world problems, such as the design of networked location-based services and sensor networks.

关键词： Observers Eigenvalues and eigenfunctions Laplace equations Couplings Symmetric matrices Linear systems Kalman filters

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Maximum work extraction and implementation costs for nonequilibrium Maxwell's demons

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Physical Review E 2014年第4期90卷 042119-042119页

作者： Henrik Sandberg Jean-Charles Delvenne Nigel J. Newton Sanjoy K. Mitter Department of Automatic Control KTH Royal Institute of Technology Stockholm Sweden ICTEAM and CORE Université catholique de Louvain Louvain-la-Neuve Belgium School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom Laboratory for Information and Decision Systems MIT Cambridge Massachusetts USA

We determine the maximum amount of work extractable in finite time by a demon performing continuous measurements on a quadratic Hamiltonian system subjected to thermal fluctuations, in terms of the information extracted from the system. The maximum work demon is found to apply a high-gain continuous feedback involving a Kalman-Bucy estimate of the system state and operates in nonequilibrium. A simple and concrete electrical implementation of the feedback protocol is proposed, which allows for analytic expressions of the flows of energy, entropy, and information inside the demon. This let us show that any implementation of the demon must necessarily include an external power source, which we prove both from classical thermodynamics arguments and from a version of Landauer's memory erasure argument extended to nonequilibrium linear systems.

关键词： MAXWELL'S demon NONEQUILIBRIUM thermodynamics FLUCTUATIONS (Physics) FEEDBACK control systems ENTROPY

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An high-efficient online reinforcement learning algorithm for continuous-state systems

An high-efficient online reinforcement learning algorithm fo...

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World Congress on Intelligent control and Automation (WCICA)

作者： Yuanheng Zhu Dongbin Zhao Haibo He The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI USA

In this paper, we consider continuous-state systems and pursue a near-optimal policy through online learning. A new online reinforcement learning algorithm-MSEC (Multi-Samples in Each Cell) is proposed. The proposed algorithm combines state aggregation technique and efficient exploration principle, making high utilization of samples observed online. More concretely, we apply a grid over the continuous state space and partition it into different cells. Then, a near-upper Q iteration operator is defined to use samples in each cell and produce a near-upper Q function, whose corresponding greedy policy is efficient for exploration. MSEC is a totally model-free algorithm, which means no system dynamics is required during the implementation. It collects the system knowledge during the online learning. Based on PAC (Probability Approximately Correct) principle, MSCE can find a near-optimal policy in finite time bound online. To test the performance, an inverted pendulum is simulated and the results show the new algorithm is qualified for solving online optimal control problems.

关键词： Algorithm design and analysis Heuristic algorithms Partitioning algorithms Learning (artificial intelligence) Approximation algorithms Polynomials Upper bound

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ANN-based DTC scheme to improve the dynamic performance of an IM drive

ANN-based DTC scheme to improve the dynamic performance of a...

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7th IET International Conference on Power Electronics, Machines and Drives (PEMD 2014)

作者： K Bouhoune K Yazid M S Boucherit Power and Industrial Systems Laboratory Faculty of Electronics and Computer Science University of Science Algeria Process Control Laboratory Department of Electrical Engineering Polytechnic National School PO Box 182 10 Hassan Badi El-Harrach 16200 Algiers Algeria

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