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20th International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Malinski, Lukasz Figwer, Jaroslaw Silesian Tech Univ Inst Automat Control Akad 16 PL-44100 Gliwice Poland

ISBN: (纸本)9781479987016

In the paper a unified approach to parametric nonlinear input-output dynamic system identification based on a memetic optimisation algorithm is presented. Efficiency of the presented approach is illustrated by a simulated identification of block-oriented nonlinear input-output dynamic systems. A focus on model identification for the case of very small as well as large number of input-output measurements is given.

关键词： System identification INPUT-OUTPUT model identification optimization algorithms Dynamic systems Nonlinear systems block-oriented Authentication

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Design Methodology and Run-time Management for Predictable Many-Core Systems 18

Design Methodology and Run-time Management for Predictable M...

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IEEE 18th International Symposium on Real-Time Distributed Computing Workshops

作者： Wildermann, Stefan Weichslgartner, Andreas Teich, Juergen Univ Erlangen Nurnberg Hardware Software Codesign Erlangen Germany

ISBN: (纸本)9781467377096

Many-core systems provide a feasible means to build high-performance multi-application systems. They are increasingly exposed to dynamic changes due to varying and online modified application mixes, as well as unavailability of hardware resources due to thermal and power management or faults. Particularly, when applications with real-time requirements are executed, these constraints may become a problem. Here, self-adaptive mechanisms are a means to optimally and feasibly manage such a system at run-time. This paper gives an overview of a design flow for hybrid application mapping for predictable many-core systems. The idea behind this concept is to perform a complex timing analysis and verification of an application during design time and then exploit this information for run-time management (RM) of the system. We propose a novel optimization algorithm to perform RM, which statically calculates a set of application mappings that are guaranteed to fulfill real-time requirements while heuristically optimizing the system objectives. Here, minimization of the energy consumption is exemplary chosen. The algorithm achieves significantly better results than a state-of-the-art approach, especially for systems with a high resource congestion.

关键词： Many-core systems design space exploration run-time management timing predictability Runtime Redmouth disease Design flow optimization algorithms hardware resource design year time series analysis Space Exploration Time Management energy consumption MAPPING(MATHEMATICAL)

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Extraction of Equivalent Sources from Near-Field Scanning Data with a Restart Differential Evolution Method

Extraction of Equivalent Sources from Near-Field Scanning Da...

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USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Proceedings

作者： Zhao, W. J. Inst High Performance Comp Singapore 138632 Singapore

ISBN: (纸本)9781479978175

Complex electronic circuitry is seen in many devices, which results in a vast interference potential. To predict the electromagnetic interference, source reconstruction techniques that extract equivalent sources of current or dipole from scanned near-field (NF) data are developed. Some source reconstruction techniques need the knowledge of NF phase and they employ the least-square method to solve inverse problems (Z. Yu, et al., IEEE Trans. EMC, 1, 2013, 97?08). Due to the ill-posted nature of the problem, regularization techniques are often needed along with the least-square method to eliminate potential false solutions. However, accurate measurement of NF phase is usually difficult in practical applications, especially as the operating frequency is very high. Some other source reconstruction techniques which do not need the NF phase are also developed. They employ global optimization algorithms such as the genetic algorithm to solve inverse problems (X. Tong, et al., IEEE Trans. EMC, 2, 2010, 462?70). These techniques are generally associated with high computational complexity, and they need several hours to obtain the equivalent dipoles of a simple printed circuit board (PCB). An effective source reconstruction technique is proposed in this abstract for the prediction of radio-frequency interference (RFI). The proposed technique does not need to know the NF phase. Equivalent magnetic dipoles are used to model the radiated emission sources of devices, and they are determined by solving an inverse problem with a proposed restart differential evolution (DE) algorithm. Compared to previous methods, the present method has much lower computational complexity. It only needs around 10 minutes on normal desktop PC to extract the equivalent dipole sources of a PCB.

关键词： Least squares method Inverse method complexity classes Printed Circuit Board Device Component image reconstruction technique dipoles Restarting Equivalent optimization algorithms Polychlorinated Biphenyls Radiofrequency interference near-field operating frequency Reconstructive Surgical Procedures Current sources

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A comparative study of Improved Bat Algorithm and Bat Algorithm on numerical benchmarks 4

A comparative study of Improved Bat Algorithm and Bat Algori...

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4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT)

作者： Beskirli, Mehmet Koc, Ismail Selcuk Univ Engn Fac Dept Comp Engn Konya Turkey

ISBN: (纸本)9781509004249

optimization is employed in solutions of many problems today. optimization is described as finding the most suitable alternative among many others under the given constraints. Meta-heuristic algorithms used in solutions of the problems are developed upon the behaviors of living creatures in the nature. One of these is Bat Algorithm (BA), an optimization method based on swarm intelligence. BA is a numerical optimization technique developed in recent times. In this paper, it is aimed at improving Bat Algorithm (IBA) by using Differential Evolution Algorithm population strategy instead of population generation method of BA. IBA was tested on 17 benchmark functions with different characteristics. Suggested method has been seen to exhibit better results compared to the original BA.

关键词： Bat Algorithm Benchmark Functions Improved Bat Algorithm Swarm Intelligence optimization algorithms

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Extended Support for Limited Preemption Fixed Priority Scheduling for OSEK/AUTOSAR-Compliant Operating Systems 10

Extended Support for Limited Preemption Fixed Priority Sched...

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IEEE International Symposium on Industrial Embedded Systems (SIES)

作者： Becker, Matthias Khalilzad, Nima Bril, Reinder J. Nolte, Thomas Malardalen Univ MRTC Vasteras Sweden Tech Univ Eindhoven Eindhoven Netherlands

ISBN: (纸本)9781467377119

Fixed Priority Scheduling (FPS) is the de facto standard in industry and it is the scheduling algorithm used in OSEK/AUTOSAR. Applications in such systems are compositions of so-called runnables, the functional entities of the system. Runnables are mapped to operating system tasks during system synthesis. In order to improve system performance it is proposed to execute runnables non-preemptively while varying the tasks threshold between runnables. This allows simpler resource access, which can reduce the stack usage of the system and improve the schedulability of the task sets. FPDS center dot, as a special case of fixed-priority scheduling with deferred preemptions, executes subjobs non-preemptively and preemption points have preemption thresholds, providing exactly the proposed behavior. However OSEK/AUTOSAR- conform systems cannot execute such schedules. In this paper we present an approach allowing the execution of FPDS center dot schedules. In our approach we exploit pseudo resources in order to implement FPDS center dot. It is further shown that our optimal algorithm produces a minimum number of resource accesses. In addition, a simulation-based evaluation is presented in which the number of resource accesses as well as the number of required pseudo-resources by the proposed algorithms are investigated. Finally, we report the overhead of resource access primitives using our measurements performed on an AUTOSAR-compliant operating system.

关键词： Fixed Priority Priority scheduling Operating systems plate detector optimization algorithms

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Distributed quadratic programming under Asynchronous and Lossy Communications via Newton-Raphson Consensus

Distributed quadratic programming under Asynchronous and Los...

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European Control Conference (ECC)

作者： Carli, Ruggero Notarstefano, Giuseppe Schenato, Luca Varagnolo, Damiano Univ Padua Dept Informat Engn Via Gradenigo 6-a I-35131 Padua Italy Univ Salento Dept Engn I-73100 Lecce Italy Lulea Univ Technol Dept Comp Sci Elect & Space Engn S-97187 Lulea Sweden

ISBN: (纸本)9783952426937

Quadratic optimization problems appear in several interesting estimation, learning and control tasks. To solve these problems in peer-to-peer networks it is necessary to design distributed optimization algorithms supporting directed, asynchronous and unreliable communication. This paper addresses this requirement by extending a promising distributed convex optimization algorithm, known as Newton-Raphson consensus, and originally designed for static and undirected communication. Specifically, we modify this algorithm so that it can cope with asynchronous, broadcast and unreliable lossy links, and prove that the optimization strategy correctly converge to the global optimum when the local cost functions are quadratic. We then support the intuition that this robustified algorithm converges to the true optimum also for general convex problems with dedicated numerical simulations.

关键词： Newton-Raphson method convex programming distributed algorithms distributed programming peer-to-peer computing quadratic programming telecommunication control Newton-Raphson consensus asynchronous communication distributed convex optimization algorithm distributed optimization algorithm distributed quadratic programming lossy communication numerical simulation optimization strategy peer-to-peer network quadratic optimization static communication undirected communication unreliable communication Algorithm design and analysis Convergence Gold optimization Packet loss Robustness quadratic programming Algorithm design and analysis Asynchronous communication Peer to peer computing optimization algorithms Communication and control Distributed software Packet loss Newton-Raphson method convex programming distributed algorithms Peer-to-peer network numerical simulation Asynchronous Converge

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Modified Fruit Fly optimization Algorithm for Analysis of Large Antenna Array

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INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION 2015年第Pt.3期2015卷 124675.1-124675.1页

作者： Mhudtongon, Nattaset Phongcharoenpanich, Chuwong Kawdungta, Supakit King Mongkuts Inst Technol Ladkrabang Fac Engn Bangkok 10520 Thailand Rajamangala Univ Technol Lanna Fac Engn Muang 50300 Chiangmai Thailand

This research paper deals with the optimization of a large antenna array for maximum directivity using a modified fruit fly optimization algorithm (MFOA) with random search of two groups of swarm and adaptive fruit fly swarm population size. The MFOA is utilized to determine three nonlinear mathematical test functions, analysis of the optimal number of elements and optimal element spacing of the large antenna array, and analysis of nonuniform amplitude of antenna array. The numerical results demonstrate that the MFOA is effective in solving all test function and electromagnetic problems. The advantages of the proposed algorithm are ease of implementation, large search range, less processing time, and reduced memory requirement.

关键词： Drosophila Elements Range searching Antenna arrays Analysis optimization algorithms Function dike swarms memory requirements

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An Efficient Energy-Aware Mechanism for Virtual Machine Migration

An Efficient Energy-Aware Mechanism for Virtual Machine Migr...

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Global Information Infrastructure and Networking Symposium (GIIS)

作者： Cardoso, Leonardo P. Mattos, Diogo M. F. Ferraz, Lyno Henrique G. Duarte, Otto Carlos M. B. Pujolle, Guy Univ Fed Rio de Janeiro COPPE UFRJ Grp Teleinformat & Automacao Rio De Janeiro Brazil Univ Paris 06 Sorbonne Univ Lab Informat Paris 6 Paris France

ISBN: (纸本)9781467377072

A major concern for cloud infrastructure providers is to decrease both their carbon footprint and their energy consumption. In this paper, we propose an elastic and energy-aware virtual machine migration mechanism that decreases power consumption by turning off physical machines and turns them on according to the demand. We develop heuristics that reallocate virtual machines in a smaller number of physical machines, turns off the idle physical machines and, consequently, saves energy. When the demand increases, the proposal turns on physical machines to supply the required resources. The contributions of the paper are four-fold: i) an efficient and elastic mechanism for energy saving on data centers;ii) a simple formal model for minimization of idle physical machines;iii) an implementation in a real environment, and iv) a simulation of the optimization algorithm for larger scenarios. The mechanism was developed and tested in Future Internet Testbed with Security (FITS). The results show the effectiveness of the mechanism on reallocating virtual machines to decrease power consumption.

关键词： Cloud computing Energy consumption Power demand Proposals Resource management Simulated annealing Virtual machining virtual machines Power demand energy consumption Cloud Computing simulated annealing management of resources virtual machining Turning machine machinery optimization algorithms Power consumption

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Nonlinear Model Predictive Control of a Hydraulic Excavator using Hammerstein Models 6

Nonlinear Model Predictive Control of a Hydraulic Excavator ...

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6th International Conference on Automation, Robotics and Applications (ICARA)

作者： Bender, Frank A. Sonntag, Marcus Sawodny, Oliver Univ Stuttgart Inst Syst Dynam D-70550 Stuttgart Germany

ISBN: (纸本)9781479964666

Hydraulic excavators play a crucial role on worldwide construction sites. Efficient operation of these machines therefore contributes to a quick completion of the construction task. In particular, optimized control strategies can lead to improvements with regard to machine performance, fuel consumption, and pollutant emissions. In this work, a nonlinear model of a hydraulic excavator is considered. It is shown that a simplified nonlinear model with Hammerstein structure can accurately represent the underlying dynamics for the purpose of control. Based on this model, a nonlinear model predictive control approach including an optimization algorithm is developed in order to have the excavator perform a task given through target positions of the four motion axes. Simulation results based on an application of the developed controller to a complex physical model of the excavator indicate good tracking performance and fast execution of the task.

关键词： Hydraulic shovels nonlinear model predictive control Nonlinear Models optimization algorithms construction sites visual tracking EXCAVATOR

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Anticipation of Brain Shift in Deep Brain Stimulation Automatic Planning 37

Anticipation of Brain Shift in Deep Brain Stimulation Automa...

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37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Hamze, Noura Bilger, Alexandre Duriez, Christian Cotin, Stephane Essert, Caroline Univ Strasbourg ICube Strasbourg France Univ Luxembourg Luxembourg Luxembourg INRIA Strasbourg France Inst Hosp Univ Strasbourg Strasbourg France

ISBN: (纸本)9781424492701

Deep Brain Stimulation is a neurosurgery procedure consisting in implanting an electrode in a deep structure of the brain. This intervention requires a preoperative planning phase, with a millimetric accuracy, in which surgeons decide the best placement of the electrode depending on a set of surgical rules. However, brain tissues may deform during the surgery because of the brain shift phenomenon, leading the electrode to mistake the target, or moreover to damage a vital anatomical structure. In this paper, we present a patient-specific automatic planning approach for DBS procedures which accounts for brain deformation. Our approach couples an optimization algorithm with FEM based brain shift simulation. The system was tested successfully on a patient-specific 3D model, and was compared to a planning without considering brain shift. The obtained results point out the importance of performing planning in dynamic conditions.

关键词： Anticipation Brain Shift Deep Brain Stimulation Automatic Planning anticipation Cerebrum Deep Brain Stimulation Brain Stimulation Electrodes Shift optimization algorithms deep-seated structures

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