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American Control Conference

作者： Yan, Yuan Mostofi, Yasamin Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)9781479932740

In this paper, we consider a dynamic coverage problem where a team of mobile robots needs to cover a set of time-varying Points of Interest (POIs), while maintaining their connectivity to a remote station in a realistic communication environment. Our goal is to design the motion and communication strategies of the robots such that they periodically visit the POIs, communicate the gathered information to a remote station, minimize their total energy costs, including motion, sensing and communication energy, and satisfy other system constraints. In our previous work [1], we have shown how to pose this problem as a Mixed Integer Linear Program (MILP), which is computationally expensive. In this paper, we focus on designing a considerably more computationally-efficient heuristic approach to tackle this problem. More specifically, we propose to utilize the space-filling curves to efficiently assign the POIs and plan the trajectories of the robots. Under certain conditions, we mathematically show that our heuristic approach is at most a constant factor away from the global optimum. Our simulation results then confirm that our approach is considerably faster than solving the MILP, especially when the dimension of the problem is high. They further show that the energy consumption of our approach is only around 26% more than the optimum.

关键词： Dynamics Mobile robots Partitioning algorithms Robot sensing systems Trajectory Agents-based systems optimization algorithms

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Optimal and Robust Production of High Pressure Steam 13

Optimal and Robust Production of High Pressure Steam

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13th European Control Conference (ECC)

作者： Kristoffersen, Torstein Thode Snarheim, Dagfinn Imsland, Lars Govatsmark, Marius Store Norwegian Univ Sci & Technol N-7034 Trondheim Norway

ISBN: (纸本)9783952426913

Steam delivery networks are large energy-consuming processes and an important part in many processing plants. Often, there is a potential for improved operation and reduction in energy consumption by application of advanced control algorithms and real time optimization. In this article, such a solution is investigated by implementing a model predictive controller to control the common header pressure of the steam delivery network. Furthermore, the energy consumption is reduced by incorporating a real time optimizer on top of the model predictive controller providing optimal operating points for the boilers. The potential reduction in energy consumption is examined using data for a real plant, and the application of the model predictive controller with the overlying real time optimization algorithm is examined using a rigorous process simulator.

关键词： Boilers Fuels IP networks optimization Process control Production Turbines Boilers Internet Protocol networks energy consumption turbines Predictive controllers Process control high pressure steam Fuels boilers Optimal process simulation optimization algorithms

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A MCMC/Bernstein Approach to Chance Constrained Programs

A MCMC/Bernstein Approach to Chance Constrained Programs

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American Control Conference

作者： Zhao, Zinan Kumar, Mrinal Univ Florida Dept Mech & Aerosp Engn Gainesville FL 32608 USA

ISBN: (纸本)9781479932740

This paper presents an extension of convex Bernstein approximations to non-affine and dependent chance constrained optimization problems. The Bernstein approximation technique transcribes probabilistic constraints into conservative convex deterministic constraints, relying heavily upon the evaluation of exponential moment generating functions. This is a computationally burdensome task for non-affine probabilistic constraints involving dependent random variables. In this paper, the theoretical framework of Bernstein approximations is combined with the practical benefits of Markov chain Monte Carlo (MCMC) integration for its use in a range of high dimensional applications. Numerical results for the combined Bernstein/MCMC approach are compared with scenario approximations.

关键词： Approximation methods Monte Carlo methods optimization Portfolios Probabilistic logic Random variables Vectors optimization algorithms Randomized algorithms

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Qualitative assessment of a collaborative multi-user tool for enhancing the daily replanning and control of visits in Home Care services 5

Qualitative assessment of a collaborative multi-user tool fo...

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5th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Lanzarone, Ettore Masclet, Cedric Noel, Frederic CNR IMATI I-00185 Rome Italy Unversit Grenoble Alpes CNRS G SCOP Lab Grenoble France

ISBN: (纸本)9781479972807

Home Care (HC) refers to nurse visits and other services provided at patients' homes rather than in hospitals or other health facilities. Planning human resources in HC is a complex activity, which includes several tasks and requires considering uncertain future patients' demands. We focus on the daily rescheduling of nurse visits in HC, for which automatic optimization algorithms fail to provide efficient solutions able to react to stochastic events in real time. In these cases, the process must be driven by human decisions. To simplify human analysis, the responsibility of planners is separated through various criteria, e.g., a planner is in charge of a specific region and a pool of nurses. In addition, in case of complex decisions, planners collaborate to solve issues by exchanging nurses or acting on a territory they are not in charge of. In this paper, we consider a human-centered tool to support the daily rescheduling of nurse visits in HC, which is intended to be complementary to optimization algorithms. A prototype tool has been developed to provide a better support to collaboration, and it was demonstrated that this tool simplifies the perception of the replanning problem thanks to a new representation of data. In this paper, we present an improved tool that simplifies interactions, and we add a first qualitative assessment of the complexity levels that are managed.

关键词： decision making health care medical administrative data processing optimisation patient care planning scheduling stochastic processes automatic optimization algorithms collaborative multiuser tool daily nurse visits rescheduling daily replanning enhancement home care services human centered tool human decision making process human resources planning planner collaboration qualitative complexity levels assessment stochastic event uncertain future patient demand Collaboration Complexity theory Data visualization Decision making Medical services Schedules Home Care Services physician services Data visualisation Complexity theory Markov chain Home Health Care Services Hydrocarbons decision making Patient Care Visiting Nurses Health Care quick decision making processes manager Medicine optimization algorithms

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A New Global optimization Algorithm for Solving a Class of Nonconvex Programming Problems

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JOURNAL OF APPLIED MATHEMATICS 2014年第unknown期2014卷 697321-1-697321-10页

作者： Zhou, Xue-Gang Cao, Bing-Yuan Guangzhou Univ Key Lab Math & Interdisciplinary Sci Guangdong Higher Educ Inst Sch Math & Informat Sci Guangzhou 510006 Guangdong Peoples R China Guangdong Univ Finance Dept Appl Math Guangzhou 510521 Guangdong Peoples R China

A new two-part parametric linearization technique is proposed globally to a class of nonconvex programming problems (NPP). Firstly, a two-part parametric linearizationmethod is adopted to construct the underestimator of objective and constraint functions, by utilizing a transformation and a parametric linear upper bounding function (LUBF) and a linear lower bounding function (LLBF) of a natural logarithm function and an exponential function with e as the base, respectively. Then, a sequence of relaxation lower linear programming problems, which are embedded in a branch-and-bound algorithm, are derived in an initial nonconvex programming problem. The proposed algorithm is converged to global optimal solution by means of a subsequent solution to a series of linear programming problems. Finally, some examples are given to illustrate the feasibility of the presented algorithm.

关键词： Problems optimization Global Parametric optimization algorithms EXPONENTIAL FUNCTIONS Logarithm functions linear programming linearization techniques Global optimization

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Assessing the performance of the non-dominated sorting genetic algorithm in optimizing construction site planning

Assessing the performance of the non-dominated sorting genet...

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2014 International Conference on Computing in Civil and Building Engineering

作者： Khalafallah, A.M. Department of Architectural and Manufacturing Sciences Western Kentucky University Bowling GreenKY United States

ISBN: (纸本)9780784413616

Genetic algorithms are techniques inspired by the mechanics of natural selection and genetics. They adopt survival of the fittest and structured exchange of information as basic mechanisms for optimization, and they are deemed suitable for construction site planning. Among the commonly-used multi-objective genetic algorithms, the Non-dominated Sorting Genetic Algorithm stands out as a robust optimization algorithm for such type of construction optimization problems. The main objective of this study is to investigate the performance of the algorithm under the alteration of optimization parameters. Specifically, the study investigates the performance of the algorithm under the variation of the population size, number of generations, type and value of cross-over probability, and mutation likelihood. This study should provide a better understanding of the behavior of the algorithm in solving site planning problems, and identify strategies that could help accelerate convergence toward optimal solutions. © ASCE 2014.

关键词： Genetic Algorithm (GA) natural selection construction sites algorithms Parameter optimization information exchange grade Understanding behavior optimal solution optimization algorithms Probability mechanic Mechanics sorting programs site planning

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Knowledge-based holistic energy management of public buildings

Knowledge-based holistic energy management of public buildin...

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2014 International Conference on Computing in Civil and Building Engineering

作者： Howell, S.K. Rezgui, Y. Yuce, B. BRE Institute of Sustainable Engineering Cardiff University Queen's Buildings The Parade Cardiff United Kingdom

ISBN: (纸本)9780784413616

Much recent work has been conducted towards reducing the energy consumption of mixed mode buildings through rule-based automation. This paper presents a novel rule generation methodology through the simultaneous use of historical sensor data and theoretical models. The theoretical rule generation methodology will be explained, encompassing the development of an energy model to the inclusion of rules within the building specific ontology. This will include the development of use-case scenarios, their refinement through a sensitivity analysis and the generation of rules through an artificial neural network embedded evolutionary optimisation algorithm. Following a review of relevant literature, the methodology will be contextualised within the architecture of the KnoholEM project and applied to the first demonstration object, a mixed use public building in the Netherlands. An example of a rule generated will then be presented and the system will be considered within the existing solution space before comments regarding future developments. © ASCE 2014.

关键词： Public architecture optimization algorithms ENERGY MODELS learning (artificial intelligence) Information Extraction Rule Solution space Sensor Data Energy management Technological forecasting Sensitivity analysis Volition Artificial neural networks Concurrency energy consumption

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FOPID Controller Tuning for Fractional FOPDT Plants subject to Design Specifications in the Frequency Domain

FOPID Controller Tuning for Fractional FOPDT Plants subject ...

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European Control Conference

作者： Aleksei Tepljakov Eduard Petlenkov Juri Belikov Department of Computer Control Tallinn University of Technology Institute of Cybernetics Tallinn University of Technology

ISBN: (纸本)9781467371605

In this paper, the problem of fractional-order proportional-integral-derivative (FOPID) controller tuning for fractional-order first-order plus dead time plants (FFOPDT) is considered. The designed controller must fulfill the prescribed specifications in the frequency domain. To this end, the fractional orders of the integrator and differentiator components are selected using a set of rules based on the observation of essential plant dynamics, while a numerical optimization algorithm is employed for obtaining the gains of the controller based on three dimensional Newton's method. All the necessary equations for computing the elements of the Jacobian matrix are provided. The proposed algorithm is detailed. It is also implemented and verified on an embedded device. The proposed solution may be useful in developing automatic tuning algorithms for FOPID controllers.

关键词： Frequency-domain analysis Jacobian matrix controller tuning fractional order Controllers Newton method optimization algorithms Design specifications Specifications integrators

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Simultaneous Information and Power Transfer in MISO Interference Systems

Simultaneous Information and Power Transfer in MISO Interfer...

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IEEE China Summit and International Conference on Signal and Information Processing

作者： Muhammad R. A. Khandaker Kai-Kit Wong Dept. of Electronic and Electrical Engineering University College London

ISBN: (纸本)9781479919499

This paper considers simultaneous wireless information and power transfer (SWIPT) in multiple-input single-output (MISO) interference systems in presence of energy harvesting nodes. We investigate the interference temperature minimization problem while satisfying signal-to-interference-and-noise ratio (SINR) and energy harvesting thresholds at the information and energy receivers, respectively. The objective is to improve the received SINR as well as to reduce cross-link information leakage in order to improve physical-layer security. The formulation leads to a non-convex problem which we solve using semidefinite relaxation (SDR) technique. A rank-constrained optimization algorithm is proposed and a rank reduction procedure is developed in order to achieve a lower rank solution. Interestingly, we show that the SDR is in fact tight and an optimal rank-one solution can be developed in certain scenarios. Numerical simulations are performed to demonstrate the effectiveness of the proposed algorithm.

关键词： power transfer multiple-input single-output energy harvesting SDPR gene Non-Convex SINR optimization algorithms

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An Energy-Driven Road-to-Driver Assistance System for Intersections

An Energy-Driven Road-to-Driver Assistance System for Inters...

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European Control Conference

作者： Matteo Corno Andrea Bisoffi Carlo Ongini Sergio M. Savaresi Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Dipartimento di Ingegneria Industriale University of Trento

ISBN: (纸本)9781467371605

Several municipalities are investigating smart road infrastructures to help reducing pollution and traffic congestion. In this paper, a road to vehicle assistance system is presented. The system continuously suggests the optimal velocity the driver should adopt in order to minimize fuel consumption in a long urban road with frequent intersection controlled by traffic lights. Fuel saving is enabled by the apriori knowledge of the signal timing and phasing. The advantage of the algorithm is that it is minimally invasive as it does not require complex communication protocols. The method is based on an offline velocity profile optimization. In the paper, the optimization algorithm is detailed and the potential for fuel saving evaluated in simulation. The method is entirely focused on fuel efficiency. It is shown that average fuel savings up to 55% are to be expected with an average reduction of the traveling time of 28%.

关键词： Intersection Signal timing Driver Assistance Systems Fuels Communication protocols traffic congestion Fuel efficiency optimization algorithms road infrastructure Fuel consumption optimal velocity Urban road Traffic lights

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