Controlling geometric phase optically in a single spin in diamond
Yale, Christopher G.
Geometric phase, or Berry phase, is an intriguing quantum mechanical phenomenon that arises from the cyclic evolution of a quantum state. Unlike dynamical phases, which rely on the time and energetics of the interaction, the geometric phase is determined solely by the geometry of the path travelled in parameter space. As such, it is robust to certain types of noise that preserve the area enclosed by the path, and shows promise for the development of fault-tolerant logic gates. Here, we demonstrate the optical control of geometric phase within a solid-state spin qubit, the nitrogen-vacancy center in diamond. Using stimulated Raman adiabatic passage (STIRAP), we evolve a coherent dark state along `tangerine slice' trajectories on the Bloch sphere and probe these paths through time-resolved state tomography. We then measure the accumulated geometric phase through phase reference to a third ground spin state. In addition, we examine the limits of this control due to adiabatic breakdown as well as the longer timescale effect of far-detuned optical fields. Finally, we intentionally introduce noise into the experimental control parameters, and measure the distributions of the resulting phases to probe the resilience of the phase to differing types of noise. We also examine this robustness as a function of traversal time as well as the noise amplitude. Through these studies, we demonstrate that geometric phase is a promising route toward fault-tolerant quantum information processing. This work is supported by the AFOSR, the NSF, and the German Research Foundation.
Creating and Controlling Single Spins in Silicon Carbide
Christle, David
Silicon carbide (SiC) is a well-established commercial semiconductor used in high-power electronics, optoelectronics, and nanomechanical devices, and has recently shown promise for semiconductor-based implementations of quantum information technologies. In particular, a set of divacancy-related point defects have improved coherence properties relative to the prominent nitrogen-vacancy center in diamond, are addressable at near-telecom wavelengths, and reside in a material for which there already exist advanced growth, doping, and microfabrication capabilities. These properties suggest divacancies in SiC have compelling advantages for photonics and micromechanical applications, yet their relatively recent discovery means crucial aspects of their fundamental physics for these applications are not well understood. I will review our progress on manipulating spin defects in SiC, and discuss efforts towards isolating and controlling them at the single defect limit. In particular, our most recent experimental results demonstrate isolation and control of long-lived (T2 = 0 . 9 ms) divacancies in a form of SiC that can be grown epitaxially on silicon. By studying the time-resolved photoluminescence of a single divacancy, we reveal its fundamental orbital structure and characterize in detail the dynamics of its special optical cycle. Finally, we probe individual divacancies using resonant laser techniques and reveal an efficient spin-photon interface with figures of merit comparable to those reported for NV centers in diamond. These results suggest a pathway towards photon-mediated entanglement of SiC defect spins over long distances. This work was supported by NSF, AFOSR, the Argonne CNM, the Knut & Alice Wallenberg Foundation, the Linköping Linnaeus Initiative, the Swedish Government Strategic Research Area, and the Ministry of Education, Science, Sports and Culture of Japan.
Spin-Light Coherence for Single-Spin Measurement and Control in Diamond
Buckley, B. B.; Fuchs, G. D.; Bassett, L. C.; Awschalom, D. D.
2010-11-01
The exceptional spin coherence of nitrogen-vacancy centers in diamond motivates their function in emerging quantum technologies. Traditionally, the spin state of individual centers is measured optically and destructively. We demonstrate dispersive, single-spin coupling to light for both nondestructive spin measurement, through the Faraday effect, and coherent spin manipulation, through the optical Stark effect. These interactions can enable the coherent exchange of quantum information between single nitrogen-vacancy spins and light, facilitating coherent measurement, control, and entanglement that is scalable over large distances.
TRANSVERSITY SINGLE SPIN ASYMMETRIES.
Energy Technology Data Exchange (ETDEWEB)
BOER,D.
2001-04-27
The theoretical aspects of two leading twist transversity single spin asymmetries, one arising from the Collins effect and one from the interference fragmentation functions, are reviewed. Issues of factorization, evolution and Sudakov factors for the relevant observables are discussed. These theoretical considerations pinpoint the most realistic scenarios towards measurements of transversity.
Coherent manipulation of single spins in semiconductors.
Hanson, Ronald; Awschalom, David D
2008-06-19
During the past few years, researchers have gained unprecedented control over spins in the solid state. What was considered almost impossible a decade ago, in both conceptual and practical terms, is now a reality: single spins can be isolated, initialized, coherently manipulated and read out using both electrical and optical techniques. Progress has been made towards full control of the quantum states of single and coupled spins in a variety of semiconductors and nanostructures, and towards understanding the mechanisms through which spins lose coherence in these systems. These abilities will allow pioneering investigations of fundamental quantum-mechanical processes and provide pathways towards applications in quantum information processing.
Optimization and Optimal Control
Chinchuluun, Altannar; Enkhbat, Rentsen; Tseveendorj, Ider
2010-01-01
During the last four decades there has been a remarkable development in optimization and optimal control. Due to its wide variety of applications, many scientists and researchers have paid attention to fields of optimization and optimal control. A huge number of new theoretical, algorithmic, and computational results have been observed in the last few years. This book gives the latest advances, and due to the rapid development of these fields, there are no other recent publications on the same topics. Key features: Provides a collection of selected contributions giving a state-of-the-art accou
Aschepkov, Leonid T; Kim, Taekyun; Agarwal, Ravi P
2016-01-01
This book is based on lectures from a one-year course at the Far Eastern Federal University (Vladivostok, Russia) as well as on workshops on optimal control offered to students at various mathematical departments at the university level. The main themes of the theory of linear and nonlinear systems are considered, including the basic problem of establishing the necessary and sufficient conditions of optimal processes. In the first part of the course, the theory of linear control systems is constructed on the basis of the separation theorem and the concept of a reachability set. The authors prove the closure of a reachability set in the class of piecewise continuous controls, and the problems of controllability, observability, identification, performance and terminal control are also considered. The second part of the course is devoted to nonlinear control systems. Using the method of variations and the Lagrange multipliers rule of nonlinear problems, the authors prove the Pontryagin maximum principle for prob...
Autonomous calibration of single spin qubit operations
Frank, Florian; Unden, Thomas; Zoller, Jonathan; Said, Ressa S.; Calarco, Tommaso; Montangero, Simone; Naydenov, Boris; Jelezko, Fedor
2017-12-01
Fully autonomous precise control of qubits is crucial for quantum information processing, quantum communication, and quantum sensing applications. It requires minimal human intervention on the ability to model, to predict, and to anticipate the quantum dynamics, as well as to precisely control and calibrate single qubit operations. Here, we demonstrate single qubit autonomous calibrations via closed-loop optimisations of electron spin quantum operations in diamond. The operations are examined by quantum state and process tomographic measurements at room temperature, and their performances against systematic errors are iteratively rectified by an optimal pulse engineering algorithm. We achieve an autonomous calibrated fidelity up to 1.00 on a time scale of minutes for a spin population inversion and up to 0.98 on a time scale of hours for a single qubit π/2 -rotation within the experimental error of 2%. These results manifest a full potential for versatile quantum technologies.
Control and optimization system
Xinsheng, Lou
2013-02-12
A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Schaft, A.J. van der
1987-01-01
It is argued that the existence of symmetries may simplify, as in classical mechanics, the solution of optimal control problems. A procedure for obtaining symmetries for the optimal Hamiltonian resulting from the Maximum Principle is given; this avoids the actual calculation of the optimal
Integrated controls design optimization
Lou, Xinsheng; Neuschaefer, Carl H.
2015-09-01
A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
Single spin asymmetries in hadron-hadron collisions
Bacchetta, A.; Bomhof, C.J.; Mulders, P.J.G.; Pijlman, F.
2005-01-01
We study weighted azimuthal single spin asymmetries in hadron-hadron scattering using the diagrammatic approach at leading order and assuming factorization. The effects of the intrinsic transverse momenta of the partons are taken into account. We show that the way in which T-odd functions, such as
Decoherence dynamics of a single spin versus spin ensemble
Dobrovitski, V.V.; Feiguin, A.E.; Awschalom, D.D.; Hanson, R.
2008-01-01
We study decoherence of central spins by a spin bath, focusing on the difference between measurement of a single central spin and measurement of a large number of central spins (as found in typical spin-resonance experiments). For a dilute spin bath, the single spin demonstrates Gaussian
On Symmetries in Optimal Control
Schaft, A.J. van der
1986-01-01
We discuss the use of symmetries in solving optimal control problems. In particular a procedure for obtaining symmetries is given which can be performed before the actual calculation of the optimal control and optimal Hamiltonian.
Optimal Control for Fast and Robust Generation of Entangled States in Anisotropic Heisenberg Chains
Zhang, Xiong-Peng; Shao, Bin; Zou, Jian
2017-05-01
Motivated by some recent results of the optimal control (OC) theory, we study anisotropic XXZ Heisenberg spin-1/2 chains with control fields acting on a single spin, with the aim of exploring how maximally entangled state can be prepared. To achieve the goal, we use a numerical optimization algorithm (e.g., the Krotov algorithm, which was shown to be capable of reaching the quantum speed limit) to search an optimal set of control parameters, and then obtain OC pulses corresponding to the target fidelity. We find that the minimum time for implementing our target state depending on the anisotropy parameter Δ of the model. Finally, we analyze the robustness of the obtained results for the optimal fidelities and the effectiveness of the Krotov method under some realistic conditions.
Oil Reservoir Production Optimization using Optimal Control
DEFF Research Database (Denmark)
Völcker, Carsten; Jørgensen, John Bagterp; Stenby, Erling Halfdan
2011-01-01
Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using the adjo...... reservoir using water ooding and smart well technology. Compared to the uncontrolled case, the optimal operation increases the Net Present Value of the oil field by 10%.......Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using...
Optimal control for chemical engineers
Upreti, Simant Ranjan
2013-01-01
Optimal Control for Chemical Engineers gives a detailed treatment of optimal control theory that enables readers to formulate and solve optimal control problems. With a strong emphasis on problem solving, the book provides all the necessary mathematical analyses and derivations of important results, including multiplier theorems and Pontryagin's principle.The text begins by introducing various examples of optimal control, such as batch distillation and chemotherapy, and the basic concepts of optimal control, including functionals and differentials. It then analyzes the notion of optimality, de
Power, control and optimization
Vasant, Pandian; Barsoum, Nader
2013-01-01
The book consists of chapters based on selected papers of international conference „Power, Control and Optimization 2012”, held in Las Vegas, USA. Readers can find interesting chapters discussing various topics from the field of power control, its distribution and related fields. Book discusses topics like energy consumption impacted by climate, mathematical modeling of the influence of thermal power plant on the aquatic environment, investigation of cost reduction in residential electricity bill using electric vehicle at peak times or allocation and size evaluation of distributed generation using ANN model and others. Chapter authors are to the best of our knowledge the originators or closely related to the originators of presented ideas and its applications. Hence, this book certainly is one of the few books discussing the benefit from intersection of those modern and fruitful scientific fields of research with very tight and deep impact on real life and industry. This book is devoted to the studies o...
Single spin asymmetries in hadron-hadron collisions
Bacchetta, A.; Bomhof, C. J.; Mulders, P. J.; Pijlman, F.
2005-01-01
We study weighted azimuthal single spin asymmetries in hadron-hadron scattering using the diagrammatic approach at leading order and assuming factorization. The effects of the intrinsic transverse momenta of the partons are taken into account. We show that the way in which $T$-odd functions, such as the Sivers function, appear in these processes does not merely involve a sign flip when compared with semi-inclusive deep inelastic scattering, such as in the case of the Drell-Yan process. Expres...
Optimal Control of Mechanical Systems
Directory of Open Access Journals (Sweden)
Vadim Azhmyakov
2007-01-01
Full Text Available In the present work, we consider a class of nonlinear optimal control problems, which can be called “optimal control problems in mechanics.” We deal with control systems whose dynamics can be described by a system of Euler-Lagrange or Hamilton equations. Using the variational structure of the solution of the corresponding boundary-value problems, we reduce the initial optimal control problem to an auxiliary problem of multiobjective programming. This technique makes it possible to apply some consistent numerical approximations of a multiobjective optimization problem to the initial optimal control problem. For solving the auxiliary problem, we propose an implementable numerical algorithm.
Optimal Control of Evolutionary Dynamics
Chakrabarti, Raj; McLendon, George
2008-01-01
Elucidating the fitness measures optimized during the evolution of complex biological systems is a major challenge in evolutionary theory. We present experimental evidence and an analytical framework demonstrating how biochemical networks exploit optimal control strategies in their evolutionary dynamics. Optimal control theory explains a striking pattern of extremization in the redox potentials of electron transport proteins, assuming only that their fitness measure is a control objective functional with bounded controls.
Single spin asymmetries in hadron-hadron collisions
Bacchetta, A.; Bomhof, C. J.; Mulders, P. J.; Pijlman, F.
2005-08-01
We study weighted azimuthal single spin asymmetries in hadron-hadron scattering using the diagrammatic approach at leading order and assuming factorization. The effects of the intrinsic transverse momenta of the partons are taken into account. We show that the way in which T-odd functions, such as the Sivers function, appear in these processes does not merely involve a sign flip when compared with semi-inclusive deep inelastic scattering, such as in the case of the Drell-Yan process. Expressions for the weighted scattering cross sections in terms of distribution and fragmentation functions folded with hard cross sections are obtained by introducing modified hard cross sections, referred to as gluonic-pole cross sections.
Calculation of TMD Evolution for Transverse Single Spin Asymmetry Measurements
Energy Technology Data Exchange (ETDEWEB)
Mert Aybat, Ted Rogers, Alexey Prokudin
2012-06-01
In this letter, we show that it is necessary to include the full treatment of QCD evolution of Transverse Momentum Dependent parton densities to explain discrepancies between HERMES data and recent COMPASS data on a proton target for the Sivers transverse single spin asymmetry in Semi-Inclusive Deep Inelastic Scattering (SIDIS). Calculations based on existing fits to TMDs in SIDIS, and including evolution within the Collins-Soper-Sterman with properly defined TMD PDFs are shown to provide a good explanation for the discrepancy. The non-perturbative input needed for the implementation of evolution is taken from earlier analyses of unpolarized Drell-Yan (DY) scattering at high energy. Its success in describing the Sivers function in SIDIS data at much lower energies is strong evidence in support of the unifying aspect of the QCD TMD-factorization formalism.
Single Spin Asymmetries at COMPASS with transverse target polarization
Schill, C
2011-01-01
COMPASS is a fixed target experiment at CERN investigating the spin structure of the nucleon and performing hadron spectroscopy. The transverse spin structure of the nucleon is studied in semi-inclusive deep-inelastic scattering of 160 GeV/c muons off a transversely polarized proton or deuteron target. In 2002-2005, a transversely polarized 6LiD, and in 2007 a transversely polarized NH3 target were used. To get access to the transversity distribution, different single-spin asymmetries have been measured: The Collins asymmetry, the hadron-pair asymmetry and the transverse lambda polarization have been analyzed. In addition, transverse momentum effects of quarks have been studied by the Sivers effect. New results for the Collins and the Sivers asymmetry on the proton for identified pions and kaons will be presented.
Optimal magnetic attitude control
DEFF Research Database (Denmark)
Wisniewski, Rafal; Markley, F.L.
1999-01-01
because control torques can only be generated perpendicular to the local geomagnetic field vector. This has been a serious obstacle for using magnetorquer based control for three-axis stabilization of a low earth orbit satellite. The problem of controlling the spacecraft attitude using only magnetic......Magnetic torquing is attractive as means of control for small satellites. The actuation principle is to use the interaction between the earth's magnetic field and a magnetic field generated by a coil set in the satellite. This control principle is inherently time-varying, and difficult to use...
Optimal control in thermal engineering
Badescu, Viorel
2017-01-01
This book is the first major work covering applications in thermal engineering and offering a comprehensive introduction to optimal control theory, which has applications in mechanical engineering, particularly aircraft and missile trajectory optimization. The book is organized in three parts: The first part includes a brief presentation of function optimization and variational calculus, while the second part presents a summary of the optimal control theory. Lastly, the third part describes several applications of optimal control theory in solving various thermal engineering problems. These applications are grouped in four sections: heat transfer and thermal energy storage, solar thermal engineering, heat engines and lubrication.Clearly presented and easy-to-use, it is a valuable resource for thermal engineers and thermal-system designers as well as postgraduate students.
Alirezaei, M.; Kanarachos, S.A.; Scheepers, B.T.M.; Maurice, J.P.
2013-01-01
The Integrated Vehicle Safety Department of TNO (Dutch Organization for Applied Scientific Research) investigates the application of modern control methods in the Integrated Vehicle Dynamics Control (IVDC) field, as a strategic research topic of the Beyond Safe framework. The aim of IVDC is to
Symposium on Optimal Control Theory
1987-01-01
Control theory can be roughly classified as deterministic or stochastic. Each of these can further be subdivided into game theory and optimal control theory. The central problem of control theory is the so called constrained maximization (which- with slight modifications--is equivalent to minimization). One can then say, heuristically, that the major problem of control theory is to find the maximum of some performance criterion (or criteria), given a set of constraints. The starting point is, of course, a mathematical representation of the performance criterion (or criteria)- sometimes called the objective functional--along with the constraints. When the objective functional is single valued (Le. , when there is only one objective to be maximized), then one is dealing with optimal control theory. When more than one objective is involved, and the objectives are generally incompatible, then one is dealing with game theory. The first paper deals with stochastic optimal control, using the dynamic programming ...
Optimal control theory an introduction
Kirk, Donald E
2004-01-01
Optimal control theory is the science of maximizing the returns from and minimizing the costs of the operation of physical, social, and economic processes. Geared toward upper-level undergraduates, this text introduces three aspects of optimal control theory: dynamic programming, Pontryagin's minimum principle, and numerical techniques for trajectory optimization.Chapters 1 and 2 focus on describing systems and evaluating their performances. Chapter 3 deals with dynamic programming. The calculus of variations and Pontryagin's minimum principle are the subjects of chapters 4 and 5, and chapter
Fault Tolerant Optimal Control.
1982-08-01
4.15) error covariance 1-)=Ar P extrapolation k kik-i (k-l)’(k.) +(r ) k-i y (l)(416 X-estimate A r k- C~kxk( (417update Xk xk k1 Prk tD (rkul J...control we choose. That is, 127 u 2 N-1 V (x ,r =1) =mm. 2 VN-i N-i N- l ) P(=nl;xN) [XN+VN (XN, rN=1)]UN-1 + p (1,2 :xN)x [ 2VN (Xr=2)] 2 N-1 min 2...2.75 the best value of xN in the interval (-1,1) isx 1. This is achieved if N x -a(1)x(X ) N N-1 UN- N-1 b(l) =1 XN-1 and the resulting cost is 2VN - (xN
Optimal control linear quadratic methods
Anderson, Brian D O
2007-01-01
This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material.The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the
Optimal control of native predators
Martin, Julien; O'Connell, Allan F.; Kendall, William L.; Runge, Michael C.; Simons, Theodore R.; Waldstein, Arielle H.; Schulte, Shiloh A.; Converse, Sarah J.; Smith, Graham W.; Pinion, Timothy; Rikard, Michael; Zipkin, Elise F.
2010-01-01
We apply decision theory in a structured decision-making framework to evaluate how control of raccoons (Procyon lotor), a native predator, can promote the conservation of a declining population of American Oystercatchers (Haematopus palliatus) on the Outer Banks of North Carolina. Our management objective was to maintain Oystercatcher productivity above a level deemed necessary for population recovery while minimizing raccoon removal. We evaluated several scenarios including no raccoon removal, and applied an adaptive optimization algorithm to account for parameter uncertainty. We show how adaptive optimization can be used to account for uncertainties about how raccoon control may affect Oystercatcher productivity. Adaptive management can reduce this type of uncertainty and is particularly well suited for addressing controversial management issues such as native predator control. The case study also offers several insights that may be relevant to the optimal control of other native predators. First, we found that stage-specific removal policies (e.g., yearling versus adult raccoon removals) were most efficient if the reproductive values among stage classes were very different. Second, we found that the optimal control of raccoons would result in higher Oystercatcher productivity than the minimum levels recommended for this species. Third, we found that removing more raccoons initially minimized the total number of removals necessary to meet long term management objectives. Finally, if for logistical reasons managers cannot sustain a removal program by removing a minimum number of raccoons annually, managers may run the risk of creating an ecological trap for Oystercatchers.
Optimal control with aerospace applications
Longuski, James M; Prussing, John E
2014-01-01
Want to know not just what makes rockets go up but how to do it optimally? Optimal control theory has become such an important field in aerospace engineering that no graduate student or practicing engineer can afford to be without a working knowledge of it. This is the first book that begins from scratch to teach the reader the basic principles of the calculus of variations, develop the necessary conditions step-by-step, and introduce the elementary computational techniques of optimal control. This book, with problems and an online solution manual, provides the graduate-level reader with enough introductory knowledge so that he or she can not only read the literature and study the next level textbook but can also apply the theory to find optimal solutions in practice. No more is needed than the usual background of an undergraduate engineering, science, or mathematics program: namely calculus, differential equations, and numerical integration. Although finding optimal solutions for these problems is a...
Optimization and optimal control in automotive systems
Kolmanovsky, Ilya; Steinbuch, Maarten; Re, Luigi
2014-01-01
This book demonstrates the use of the optimization techniques that are becoming essential to meet the increasing stringency and variety of requirements for automotive systems. It shows the reader how to move away from earlier approaches, based on some degree of heuristics, to the use of more and more common systematic methods. Even systematic methods can be developed and applied in a large number of forms so the text collects contributions from across the theory, methods and real-world automotive applications of optimization. Greater fuel economy, significant reductions in permissible emissions, new drivability requirements and the generally increasing complexity of automotive systems are among the criteria that the contributing authors set themselves to meet. In many cases multiple and often conflicting requirements give rise to multi-objective constrained optimization problems which are also considered. Some of these problems fall into the domain of the traditional multi-disciplinary optimization applie...
Control and optimal control theories with applications
Burghes, D N
2004-01-01
This sound introduction to classical and modern control theory concentrates on fundamental concepts. Employing the minimum of mathematical elaboration, it investigates the many applications of control theory to varied and important present-day problems, e.g. economic growth, resource depletion, disease epidemics, exploited population, and rocket trajectories. An original feature is the amount of space devoted to the important and fascinating subject of optimal control. The work is divided into two parts. Part one deals with the control of linear time-continuous systems, using both transfer fun
Optimal control of hybrid vehicles
Jager, Bram; Kessels, John
2013-01-01
Optimal Control of Hybrid Vehicles provides a description of power train control for hybrid vehicles. The background, environmental motivation and control challenges associated with hybrid vehicles are introduced. The text includes mathematical models for all relevant components in the hybrid power train. The power split problem in hybrid power trains is formally described and several numerical solutions detailed, including dynamic programming and a novel solution for state-constrained optimal control problems based on Pontryagin’s maximum principle. Real-time-implementable strategies that can approximate the optimal solution closely are dealt with in depth. Several approaches are discussed and compared, including a state-of-the-art strategy which is adaptive for vehicle conditions like velocity and mass. Two case studies are included in the book: · a control strategy for a micro-hybrid power train; and · experimental results obtained with a real-time strategy implemented in...
Optimal control of hydroelectric facilities
Zhao, Guangzhi
This thesis considers a simple yet realistic model of pump-assisted hydroelectric facilities operating in a market with time-varying but deterministic power prices. Both deterministic and stochastic water inflows are considered. The fluid mechanical and engineering details of the facility are described by a model containing several parameters. We present a dynamic programming algorithm for optimizing either the total energy produced or the total cash generated by these plants. The algorithm allows us to give the optimal control strategy as a function of time and to see how this strategy, and the associated plant value, varies with water inflow and electricity price. We investigate various cases. For a single pumped storage facility experiencing deterministic power prices and water inflows, we investigate the varying behaviour for an oversimplified constant turbine- and pump-efficiency model with simple reservoir geometries. We then generalize this simple model to include more realistic turbine efficiencies, situations with more complicated reservoir geometry, and the introduction of dissipative switching costs between various control states. We find many results which reinforce our physical intuition about this complicated system as well as results which initially challenge, though later deepen, this intuition. One major lesson of this work is that the optimal control strategy does not differ much between two differing objectives of maximizing energy production and maximizing its cash value. We then turn our attention to the case of stochastic water inflows. We present a stochastic dynamic programming algorithm which can find an on-average optimal control in the face of this randomness. As the operator of a facility must be more cautious when inflows are random, the randomness destroys facility value. Following this insight we quantify exactly how much a perfect hydrological inflow forecast would be worth to a dam operator. In our final chapter we discuss the
Real-space imaging of non-collinear antiferromagnetic order with a single-spin magnetometer
Gross, I.; Akhtar, W.; Garcia, V.; Martínez, L. J.; Chouaieb, S.; Garcia, K.; Carrétéro, C.; Barthélémy, A.; Appel, P.; Maletinsky, P.; Kim, J.-V.; Chauleau, J. Y.; Jaouen, N.; Viret, M.; Bibes, M.; Fusil, S.; Jacques, V.
2017-09-01
Although ferromagnets have many applications, their large magnetization and the resulting energy cost for switching magnetic moments bring into question their suitability for reliable low-power spintronic devices. Non-collinear antiferromagnetic systems do not suffer from this problem, and often have extra functionalities: non-collinear spin order may break space-inversion symmetry and thus allow electric-field control of magnetism, or may produce emergent spin-orbit effects that enable efficient spin-charge interconversion. To harness these traits for next-generation spintronics, the nanoscale control and imaging capabilities that are now routine for ferromagnets must be developed for antiferromagnetic systems. Here, using a non-invasive, scanning single-spin magnetometer based on a nitrogen-vacancy defect in diamond, we demonstrate real-space visualization of non-collinear antiferromagnetic order in a magnetic thin film at room temperature. We image the spin cycloid of a multiferroic bismuth ferrite (BiFeO3) thin film and extract a period of about 70 nanometres, consistent with values determined by macroscopic diffraction. In addition, we take advantage of the magnetoelectric coupling present in BiFeO3 to manipulate the cycloid propagation direction by an electric field. Besides highlighting the potential of nitrogen-vacancy magnetometry for imaging complex antiferromagnetic orders at the nanoscale, these results demonstrate how BiFeO3 can be used in the design of reconfigurable nanoscale spin textures.
Optimal control of effective Hamiltonians
Energy Technology Data Exchange (ETDEWEB)
Verdeny Vilalta, Albert; Mintert, Florian [Freiburg Institute for Advanced Studies, Albert-Ludwigs University of Freiburg, Freiburg 79104 (Germany); Mueller, Cord A. [Centre for Quantum Technologies, National University of Singapore, Singapore 117543 (Singapore)
2013-07-01
Periodically driven Hamiltonians can be approximately described by a time-independent effective Hamiltonian if the driving is sufficiently fast. There exist, however, many different drivings that result in the same effective Hamiltonian. Using optimal control techniques, we investigate which driving yields the best approximation to the dynamics induced by a desired effective Hamiltonian. The viability of our approach is proven for the simplest example of a driven three-level Lambda system, and shall ultimately help to improve the precision of quantum simulations.
Optimal switching using coherent control
DEFF Research Database (Denmark)
Kristensen, Philip Trøst; Heuck, Mikkel; Mørk, Jesper
2013-01-01
We introduce a general framework for the analysis of coherent control in coupled optical cavity-waveguide systems. Within this framework, we use an analytically solvable model, which is validated by independent numerical calculations, to investigate switching in a micro cavity and demonstrate...... that the switching time, in general, is not limited by the cavity lifetime. Therefore, the total energy required for switching is a more relevant figure of merit than the switching speed, and for a particular two-pulse switching scheme we use calculus of variations to optimize the switching in terms of input energy....
Transverse Single-Spin Asymmetries in Proton-Proton Collisions at the AFTER@LHC Experiment
Directory of Open Access Journals (Sweden)
K. Kanazawa
2015-01-01
Full Text Available We present results for transverse single-spin asymmetries in proton-proton collisions at kinematics relevant for AFTER, a proposed fixed-target experiment at the Large Hadron Collider. These include predictions for pion, jet, and direct photon production from analytical formulas already available in the literature. We also discuss specific measurements that will benefit from the higher luminosity of AFTER, which could help resolve an almost 40-year puzzle of what causes transverse single-spin asymmetries in proton-proton collisions.
Transverse single spin asymmetry in Drell-Yan production in polarized pA collisions
Zhou, J.
2015-01-01
We study the transverse single spin asymmetry in Drell-Yan production in pA collisions with incoming protons being transversely polarized. We carry out the calculation using a newly developed hybrid approach. The polarized cross section computed in the hybrid approach is consistent with that
Transverse target single-spin asymmetry in inclusive electroproduction of charged pions and kaons
Airapetian, A.; Blok, H.P.
2014-01-01
Single-spin asymmetries were investigated in inclusive electroproduction of charged pions and kaons from transversely polarized protons at the Hermes experiment. The asymmetries were studied as a function of the azimuthal angle ψ about the beam direction between the target-spin direction and the
Transverse Single Spin Asymmetries in Hadronic Interactions: An Experimental Overview and Outlook
Directory of Open Access Journals (Sweden)
Bland L.C.
2015-01-01
Full Text Available Transverse single-spin asymmetries (SSA are expected to be small in perturbative QCD because of the chiral nature of the theory. Experiment shows there are large transverse SSA for particles produced in special kinematics. This contribution reviews the experimental situation and provides an outlook for future measurements.
Adaptive, predictive controller for optimal process control
Energy Technology Data Exchange (ETDEWEB)
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
1995-12-01
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
Optimal control of ODEs and DAEs
Gerdts, Matthias
2011-01-01
The intention of this textbook is to provide both, the theoretical and computational tools that are necessary to investigate and to solve optimal control problems with ordinary differential equations and differential-algebraic equations. An emphasis is placed on the interplay between the continuous optimal control problem, which typically is defined and analyzed in a Banach space setting, and discrete optimal control problems, which are obtained by discretization and lead to finite dimensional optimization problems.
Single-spin addressing in an atomic Mott insulator
DEFF Research Database (Denmark)
Weitenberg, Christof; Endres, Manuel; Sherson, Jacob
2011-01-01
Ultracold atoms in optical lattices provide a versatile tool with which to investigate fundamental properties of quantum many-body systems. In particular, the high degree of control of experimental parameters has allowed the study of many interesting phenomena, such as quantum phase transitions a...
Constrained Optimization and Optimal Control for Partial Differential Equations
Leugering, Günter; Griewank, Andreas
2012-01-01
This special volume focuses on optimization and control of processes governed by partial differential equations. The contributors are mostly participants of the DFG-priority program 1253: Optimization with PDE-constraints which is active since 2006. The book is organized in sections which cover almost the entire spectrum of modern research in this emerging field. Indeed, even though the field of optimal control and optimization for PDE-constrained problems has undergone a dramatic increase of interest during the last four decades, a full theory for nonlinear problems is still lacking. The cont
Glaser, Steffen J.; Boscain, Ugo; Calarco, Tommaso; Koch, Christiane P.; Köckenberger, Walter; Kosloff, Ronnie; Kuprov, Ilya; Luy, Burkhard; Schirmer, Sophie; Schulte-Herbrüggen, Thomas; Sugny, Dominique; Wilhelm, Frank K.
2015-12-01
It is control that turns scientific knowledge into useful technology: in physics and engineering it provides a systematic way for driving a dynamical system from a given initial state into a desired target state with minimized expenditure of energy and resources. As one of the cornerstones for enabling quantum technologies, optimal quantum control keeps evolving and expanding into areas as diverse as quantum-enhanced sensing, manipulation of single spins, photons, or atoms, optical spectroscopy, photochemistry, magnetic resonance (spectroscopy as well as medical imaging), quantum information processing and quantum simulation. In this communication, state-of-the-art quantum control techniques are reviewed and put into perspective by a consortium of experts in optimal control theory and applications to spectroscopy, imaging, as well as quantum dynamics of closed and open systems. We address key challenges and sketch a roadmap for future developments.
Fuzzy logic control and optimization system
Lou, Xinsheng [West Hartford, CT
2012-04-17
A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Near optimal decentralized H_inf control
DEFF Research Database (Denmark)
Stoustrup, J.; Niemann, Hans Henrik
It is shown that foir a class of decentralized control problems there does not exist a sequence of controllers of bounded order which obtains near optimal control. Neither does there exist an infinity dimentional optimal controller. Using the insight of the line of proof of these results, a heuri...
Nearly optimal quantum control: an analytical approach
Sun, Chen; Saxena, Avadh; Sinitsyn, Nikolai A.
2017-09-01
We propose nearly optimal control strategies for changing the states of a quantum system. We argue that quantum control optimization can be studied analytically within some protocol families that depend on a small set of parameters for optimization. This optimization strategy can be preferred in practice because it is physically transparent and does not lead to combinatorial complexity in multistate problems. As a demonstration, we design optimized control protocols that achieve switching between orthogonal states of a naturally biased quantum two-level system.
Control derivative to optimal control analysis | Omolehin | Journal of ...
African Journals Online (AJOL)
Optimal control theory, generally, is to determine the control signals which will cause a process to satisfy the physical constraints and at the same time optimize some performance criterion. In this work, a numerical method for finding solution to linear optimal control problems with bounded state constraints is examined.
Optimal control of raw timber production processes
Ivan Kolenka
1978-01-01
This paper demonstrates the possibility of optimal planning and control of timber harvesting activ-ities with mathematical optimization models. The separate phases of timber harvesting are represented by coordinated models which can be used to select the optimal decision for the execution of any given phase. The models form a system whose components are connected and...
Optimal Control and Optimization of Stochastic Supply Chain Systems
Song, Dong-Ping
2013-01-01
Optimal Control and Optimization of Stochastic Supply Chain Systems examines its subject in the context of the presence of a variety of uncertainties. Numerous examples with intuitive illustrations and tables are provided, to demonstrate the structural characteristics of the optimal control policies in various stochastic supply chains and to show how to make use of these characteristics to construct easy-to-operate sub-optimal policies. In Part I, a general introduction to stochastic supply chain systems is provided. Analytical models for various stochastic supply chain systems are formulated and analysed in Part II. In Part III the structural knowledge of the optimal control policies obtained in Part II is utilized to construct easy-to-operate sub-optimal control policies for various stochastic supply chain systems accordingly. Finally, Part IV discusses the optimisation of threshold-type control policies and their robustness. A key feature of the book is its tying together of ...
Adaptive optimization and control using neural networks
Energy Technology Data Exchange (ETDEWEB)
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
1993-10-22
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Berman, G P; Chapline, G; Gurvitz, S A; Hammel, P C; Pelekhov, D V; Suter, A; Tsifrinovich, V I
2003-01-01
We consider the process of a single-spin measurement using magnetic resonance force microscopy (MRFM) with a cyclic adiabatic inversion (CAI). This technique is also important for different applications, including a measurement of a qubit state in quantum computation. The measurement takes place through the interaction of a single spin with a cantilever modelled by a quantum oscillator in a coherent state in a quasi-classical range of parameters. The entire system is treated rigorously within the framework of the Schroedinger equation. For a many-spin system our equations accurately describe conventional MRFM experiments involving CAI of the spin system. Our computer simulations of the quantum spin-cantilever dynamics show that the probability distribution for the cantilever position develops two asymmetric peaks with the total relative probabilities mainly dependent on the initial angle between the directions of the average spin and the effective magnetic field, in the rotating frame. We show that each of th...
Transverse Single Spin and Azimuthal Asymmetries in Hadronic Collisions at STAR
Directory of Open Access Journals (Sweden)
Vossen Anselm
2015-01-01
Full Text Available Hadronic collisions with transversely polarized protons are an important part of the quest to understand the transverse spin structure of the proton. Experiments at RHIC collected large datasets at center of mass energies of 200 GeV and 500 GeV, accessing a kinematic regime where factorization is expected to hold. The STAR detector at RHIC, due to its azimuthal symmetry, particle identification capabilities and large acceptance compared with other experiments with polarized protons, is in a unique position to study transverse spin phenomena in p + p↑. This contribution will highlight measurements of transversity using di-hadron correlations, transverse single spin asymmetries in jets, measurements sensitive to the origins of the large single spin asymmetries measured in the forward direction, transverse spin asymmetries in W production, which are sensitive to modified universality effects of Sivers function as well as short and long-term upgrades at STAR.
Thermodynamics of a sufficient small singly spinning Kerr-AdS black hole
Energy Technology Data Exchange (ETDEWEB)
Pourhassan, Behnam, E-mail: b.pourhassan@du.ac.ir [School of Physics, Damghan University, Damghan (Iran, Islamic Republic of); Faizal, Mir, E-mail: mirfaizalmir@gmail.com [Irving K. Barber School of Arts and Sciences, University of British Columbia – Okanagan, Kelowna, BC V1V 1V7 (Canada); Department of Physics and Astronomy, University of Lethbridge, Lethbridge, AB T1K 3M4 (Canada)
2016-12-15
In this paper, we will analyze the thermodynamics of a small singly spinning Kerr-AdS black hole. As the black hole will be sufficient small, its temperature will be large and so we can not neglect the effects of thermal fluctuations. We will demonstrate that these thermal fluctuations correct the entropy of singly spinning Kerr-AdS black hole by a logarithmic correction term. We will analyze the implications of the logarithmic correction on other thermodynamic properties of this black hole, and analyze the stability of such a black hole. We will observe that this form of correction becomes important when the size of the black hole is sufficient small. We will also analyze the effect of these thermal fluctuations on the critical phenomena for such a black hole.
Lewis, Nicole; Phenix Collaboration
2017-09-01
Large transverse single spin asymmetries for hadron production in proton-proton collisions were some of the first indicators of significant nonperturbative spin-momentum correlations in the proton. They have been found to persist up to collision energies of 510 GeV, yet their origin remains poorly understood. Measurements of different final-state particles in a wide variety of collision systems over a range of kinematics can help to identify and separate contributions from the proton versus hadronization, and from different parton flavors. Depending on the rapidity pion production can provide access to both initial- and final-state effects for a mix of parton flavors, while direct photons depend only on initial-state effects and are particularly sensitive to gluon dynamics in RHIC kinematics. The status of transverse single spin measurements for neutral pions and direct photons performed for p+p, p+Al, and p+Au collisions at PHENIX will be presented.
Quark-photon-quark correlation and transverse target single spin asymmetry in inclusive DIS
Burkardt, Matthias; Alhalholy, Tareq
2017-07-01
We calculate the q γ q correlation function associated to transverse target lepton-nucleon inclusive deep-inelastic scattering by direct evaluation of the corresponding matrix element utilizing the electromagnetic impact parameter fields for a transversely polarized nucleon. The results are compared with the two existing models for the q γ q correlator. Using the calculated q γ q correlation function, we estimate the transverse target single-spin asymmetry in an inclusive DIS process.
Mixed-Strategy Chance Constrained Optimal Control
Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J.
2013-01-01
This paper presents a novel chance constrained optimal control (CCOC) algorithm that chooses a control action probabilistically. A CCOC problem is to find a control input that minimizes the expected cost while guaranteeing that the probability of violating a set of constraints is below a user-specified threshold. We show that a probabilistic control approach, which we refer to as a mixed control strategy, enables us to obtain a cost that is better than what deterministic control strategies can achieve when the CCOC problem is nonconvex. The resulting mixed-strategy CCOC problem turns out to be a convexification of the original nonconvex CCOC problem. Furthermore, we also show that a mixed control strategy only needs to "mix" up to two deterministic control actions in order to achieve optimality. Building upon an iterative dual optimization, the proposed algorithm quickly converges to the optimal mixed control strategy with a user-specified tolerance.
Optimization analysis of propulsion motor control efficiency
Directory of Open Access Journals (Sweden)
CAI Qingnan
2017-12-01
Full Text Available [Objectives] This paper aims to strengthen the control effect of propulsion motors and decrease the energy used during actual control procedures.[Methods] Based on the traditional propulsion motor equivalence circuit, we increase the iron loss current component, introduce the definition of power matching ratio, calculate the highest efficiency of a motor at a given speed and discuss the flux corresponding to the power matching ratio with the highest efficiency. In the original motor vector efficiency optimization control module, an efficiency optimization control module is added so as to achieve motor efficiency optimization and energy conservation.[Results] MATLAB/Simulink simulation data shows that the efficiency optimization control method is suitable for most conditions. The operation efficiency of the improved motor model is significantly higher than that of the original motor model, and its dynamic performance is good.[Conclusions] Our motor efficiency optimization control method can be applied in engineering to achieve energy conservation.
Almost optimal adaptive LQ control: SISO case
Polderman, Jan W.; Daams, Jasper
2002-01-01
In this paper an almost optimal indirect adaptive controller for input/output dynamical systems is proposed. The control part of the adaptive control scheme is based on a modified LQ control law: by adding a time-varying gain to the certainty equivalent control law the conflict between
Neural Networks for Optimal Control
DEFF Research Database (Denmark)
Sørensen, O.
1995-01-01
Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....
Optimizing control of quality management
Directory of Open Access Journals (Sweden)
Fliginskih Tatyana Nikolayevna
2012-05-01
Full Text Available This paper describes the technology that permits controlling of business processes in industry. An example of the use of control charts as one of the most effective methods of statistical quality control of products. The author provides a definition that best reveals the understanding of quality and quality control.
Optimal control of renewable economic resources
Energy Technology Data Exchange (ETDEWEB)
Adelani, L.A.
1987-01-01
Two main problems are studied: economic optimization, and determination of the optimal age of harvest for an initially immature population which follows a Bertalanffy-type growth law. Conditions are derived on the economic parameters that make maximization of economic rent biologically superior to maximization of sustainable yield. A general equation is derived for the optimal equilibrium biomass size when maximization of present value is the control objective. Also, it is shown that under perfectly elastic demand for the resource, a critical price level exists beyond which economic optimization has to be sacrificed in order to enhance conservation of the resource. An equation is derived whose solution represents the optimal age of harvest for an initially immature population stock. In certain circumstances, analytic forms are obtained for the optimal age of harvest. Some properties of the optimal age of harvest are also investigated.
Optimal Control of Evolution Mixed Variational Inclusions
Energy Technology Data Exchange (ETDEWEB)
Alduncin, Gonzalo, E-mail: alduncin@geofisica.unam.mx [Universidad Nacional Autónoma de México, Departamento de Recursos Naturales, Instituto de Geofísica (Mexico)
2013-12-15
Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory.
Energy Optimal Control of Induction Motor Drives
DEFF Research Database (Denmark)
Abrahamsen, Flemming
This thesis deals with energy optimal control of small and medium-size variable speed induction motor drives for especially Heating, Ventilation and Air-Condition (HVAC) applications. Optimized efficiency is achieved by adapting the magnetization level in the motor to the load, and the basic...... purpose is demonstrate how this can be done for low-cost PWM-VSI drives without bringing the robustness of the drive below an acceptable level. Four drives are investigated with respect to energy optimal control: 2.2 kW standard and high-efficiency motor drives, 22 kW and 90 kW standard motor drives....... The method has been to make extensive efficiency measurements within the specified operating area with optimized efficiency and with constant air-gap flux, and to establish reliable converter and motor loss models based on those measurements. The loss models have been used to analyze energy optimal control...
Optimal Speed Control for Cruising
DEFF Research Database (Denmark)
Blanke, M.
1994-01-01
With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability......With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability...
Optimal control and the calculus of variations
Pinch, Enid R
1993-01-01
This introduction to optimal control theory is intended for undergraduate mathematicians and for engineers and scientists with some knowledge of classical analysis. It includes sections on classical optimization and the calculus of variations. All the important theorems are carefully proved. There are many worked examples and exercises for the reader to attempt.
Optimal Control Design for a Solar Greenhouse
Ooteghem, van R.J.C.
2010-01-01
Abstract: An optimal climate control has been designed for a solar greenhouse to achieve optimal crop production with sustainable instead of fossil energy. The solar greenhouse extends a conventional greenhouse with an improved roof cover, ventilation with heat recovery, a heat pump, a heat
Greenhouse climate management : an optimal control approach
Henten, van E.J.
1994-01-01
In this thesis a methodology is developed for the construction and analysis of an optimal greenhouse climate control system.
In chapter 1, the results of a literature survey are presented and the research objectives are defined. In the literature, optimal greenhouse climate
A Feedback Optimal Control Algorithm with Optimal Measurement Time Points
Directory of Open Access Journals (Sweden)
Felix Jost
2017-02-01
Full Text Available Nonlinear model predictive control has been established as a powerful methodology to provide feedback for dynamic processes over the last decades. In practice it is usually combined with parameter and state estimation techniques, which allows to cope with uncertainty on many levels. To reduce the uncertainty it has also been suggested to include optimal experimental design into the sequential process of estimation and control calculation. Most of the focus so far was on dual control approaches, i.e., on using the controls to simultaneously excite the system dynamics (learning as well as minimizing a given objective (performing. We propose a new algorithm, which sequentially solves robust optimal control, optimal experimental design, state and parameter estimation problems. Thus, we decouple the control and the experimental design problems. This has the advantages that we can analyze the impact of measurement timing (sampling independently, and is practically relevant for applications with either an ethical limitation on system excitation (e.g., chemotherapy treatment or the need for fast feedback. The algorithm shows promising results with a 36% reduction of parameter uncertainties for the Lotka-Volterra fishing benchmark example.
Optimal Control of Electrodynamic Tethers
2008-06-01
unachievable sun-synchronous orbits. One advantage would be that a satellite could reside in a desired orbit while maintaining optimal solar panel ...9) ( )h v s B e( )1 22 2 2 * *1 23 2 p pm e oL c B e μ μ ω θ ρ τ−− = − − θ ( ) 2 *1 2v s B eθ fined ( )1 22 23 2 p pm e...Likewise the kinetic energy for mass 2 is ( ) ( )( ) 2 22 T m= ⋅ =2 2v v 22 2 2 1 2 2 2 2 2 m mmm M M μ μ⎧ ⎫′ ′ ′ ′⋅ + + ⋅ + ⋅ × + ⋅ + ⋅ × + × ⋅ ×⎨ ⎬ ⎩ ⎭ r
Optimal control for Malaria disease through vaccination
Munzir, Said; Nasir, Muhammad; Ramli, Marwan
2018-01-01
Malaria is a disease caused by an amoeba (single-celled animal) type of plasmodium where anopheles mosquito serves as the carrier. This study examines the optimal control problem of malaria disease spread based on Aron and May (1982) SIR type models and seeks the optimal solution by minimizing the prevention of the spreading of malaria by vaccine. The aim is to investigate optimal control strategies on preventing the spread of malaria by vaccination. The problem in this research is solved using analytical approach. The analytical method uses the Pontryagin Minimum Principle with the symbolic help of MATLAB software to obtain optimal control result and to analyse the spread of malaria with vaccination control.
Optimal Corrosion Control Treatment Evaluation Technical Recommendations
This document provides technical recommendations that both systems and primacy agencies can use to comply with LCR CCT requirements and effective evaluation and designation of optimal corrosion control treatment (OCCT).
Fluid Limits of Optimally Controlled Queueing Networks
Guodong Pang; Day, Martin V.
2007-01-01
We consider a class of queueing processes represented by a Skorokhod problem coupled with a controlled point process. Posing a discounted control problem for such processes, we show that the optimal value functions converge, in the fluid limit, to the value of an analogous deterministic control problem for fluid processes. Peer Reviewed
Fluid Limits of Optimally Controlled Queueing Networks
Directory of Open Access Journals (Sweden)
Guodong Pang
2007-01-01
Full Text Available We consider a class of queueing processes represented by a Skorokhod problem coupled with a controlled point process. Posing a discounted control problem for such processes, we show that the optimal value functions converge, in the fluid limit, to the value of an analogous deterministic control problem for fluid processes.
Computational procedures for implementing the optimal control ...
African Journals Online (AJOL)
The Extended Conjugate Gradient Method, ECGM, [1] was used to compute the control and state gradients of the unconstrained optimal control problem for higher-order nondispersive wave. Also computed are the descent directions for both the control and the state variables. These functions are the most important ...
Robust Structured Control Design via LMI Optimization
DEFF Research Database (Denmark)
Adegas, Fabiano Daher; Stoustrup, Jakob
2011-01-01
This paper presents a new procedure for discrete-time robust structured control design. Parameter-dependent nonconvex conditions for stabilizable and induced L2-norm performance controllers are solved by an iterative linear matrix inequalities (LMI) optimization. A wide class of controller...
Single-Spin Polarization Effects and the Determination of Timelike Proton Form Factors
Energy Technology Data Exchange (ETDEWEB)
Brodsky, S
2003-10-24
We show that measurements of the proton's polarization in e{sup +}e{sup -} {yields} p{bar p} strongly discriminate between analytic forms of models which fit the proton form factors in the spacelike region. In particular, the single-spin asymmetry normal to the scattering plane measures the relative phase difference between the timelike G{sub E} and G{sub M} form factors. The expected proton polarization in the timelike region is large, of order of several tens of percent.
Azimuthal and single spin asymmetry in deep-inelasticlepton-nucleon scattering
Energy Technology Data Exchange (ETDEWEB)
Liang, Zuo-tang; Wang, Xin-Nian
2006-09-21
The collinear expansion technique is generalized to thefactorization of unintegrated parton distributions and other higher twistparton correlations from the corresponding collinear hard parts thatinvolve multiple parton final state interaction. Such a generalizedfactorization provides a consistent approach to the calculation ofinclusive and semi-inclusive cross sections of deep-inelasticlepton-nucleon scattering. As an example, the azimuthal asymmetry iscalculated to the order of 1/Q in semi-inclusive deeply inelasticlepton-nucleon scattering with transversely polarized target. Anon-vanishing single-spin asymmetry in the "triggered inclusive process"is predicted to be 1/Q suppressed with a part of the coefficient relatedto a moment of the Sivers function.
Chemical optimization algorithm for fuzzy controller design
Astudillo, Leslie; Castillo, Oscar
2014-01-01
In this book, a novel optimization method inspired by a paradigm from nature is introduced. The chemical reactions are used as a paradigm to propose an optimization method that simulates these natural processes. The proposed algorithm is described in detail and then a set of typical complex benchmark functions is used to evaluate the performance of the algorithm. Simulation results show that the proposed optimization algorithm can outperform other methods in a set of benchmark functions. This chemical reaction optimization paradigm is also applied to solve the tracking problem for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application
Optimal control problem for the extended Fisher–Kolmogorov equation
Indian Academy of Sciences (India)
In this paper, the optimal control problem for the extended Fisher–Kolmogorov equation is studied. The optimal control under boundary condition is given, the existence of optimal solution to the equation is proved and the optimality system is established.
Optimal Wentzell Boundary Control of Parabolic Equations
Energy Technology Data Exchange (ETDEWEB)
Luo, Yousong, E-mail: yousong.luo@rmit.edu.au [RMIT University, School of Mathematical and Geospatial Sciences (Australia)
2017-04-15
This paper deals with a class of optimal control problems governed by an initial-boundary value problem of a parabolic equation. The case of semi-linear boundary control is studied where the control is applied to the system via the Wentzell boundary condition. The differentiability of the state variable with respect to the control is established and hence a necessary condition is derived for the optimal solution in the case of both unconstrained and constrained problems. The condition is also sufficient for the unconstrained convex problems. A second order condition is also derived.
Optimal control novel directions and applications
Aronna, Maria; Kalise, Dante
2017-01-01
Focusing on applications to science and engineering, this book presents the results of the ITN-FP7 SADCO network’s innovative research in optimization and control in the following interconnected topics: optimality conditions in optimal control, dynamic programming approaches to optimal feedback synthesis and reachability analysis, and computational developments in model predictive control. The novelty of the book resides in the fact that it has been developed by early career researchers, providing a good balance between clarity and scientific rigor. Each chapter features an introduction addressed to PhD students and some original contributions aimed at specialist researchers. Requiring only a graduate mathematical background, the book is self-contained. It will be of particular interest to graduate and advanced undergraduate students, industrial practitioners and to senior scientists wishing to update their knowledge.
Optimal control of flow with discontinuities
Homescu, Chris; Navon, I. M.
2003-05-01
Optimal control of the 1-D Riemann problem of Euler equations is studied, with the initial values for pressure and density as control parameters. The least-squares type cost functional employs either distributed observations in time or observations calculated at the end of the assimilation window. Existence of solutions for the optimal control problem is proven. Smooth and nonsmooth optimization methods employ the numerical gradient (respectively, a subgradient) of the cost functional, obtained from the adjoint of the discrete forward model. The numerical flow obtained with the optimal initial conditions obtained from the nonsmooth minimization matches very well with the observations. The algorithm for smooth minimization converges for the shorter time horizon but fails to perform satisfactorily for the longer time horizon, except when the observations corresponding to shocks are detected and removed.
OPTIMAL CONTROL FOR ELECTRIC VEHICLE STABILIZATION
Directory of Open Access Journals (Sweden)
MARIAN GAICEANU
2016-01-01
Full Text Available This main objective of the paper is to stabilize an electric vehicle in optimal manner to a step lane change maneuver. To define the mathematical model of the vehicle, the rigid body moving on a plane is taken into account. An optimal lane keeping controller delivers the adequate angles in order to stabilize the vehicle’s trajectory in an optimal way. Two degree of freedom linear bicycle model is adopted as vehicle model, consisting of lateral and yaw motion equations. The proposed control maintains the lateral stability by taking the feedback information from the vehicle transducers. In this way only the lateral vehicle’s dynamics are enough to considerate. Based on the obtained linear mathematical model the quadratic optimal control is designed in order to maintain the lateral stability of the electric vehicle. The numerical simulation results demonstrate the feasibility of the proposed solution.
Optimal control of a CSTR process
Directory of Open Access Journals (Sweden)
A. Soukkou
2008-12-01
Full Text Available Designing an effective criterion and learning algorithm for find the best structure is a major problem in the control design process. In this paper, the fuzzy optimal control methodology is applied to the design of the feedback loops of an Exothermic Continuous Stirred Tank Reactor system. The objective of design process is to find an optimal structure/gains of the Robust and Optimal Takagi Sugeno Fuzzy Controller (ROFLC. The control signal thus obtained will minimize a performance index, which is a function of the tracking/regulating errors, the quantity of the energy of the control signal applied to the system, and the number of fuzzy rules. The genetic learning is proposed for constructing the ROFLC. The chromosome genes are arranged into two parts, the binary-coded part contains the control genes and the real-coded part contains the genes parameters representing the fuzzy knowledge base. The effectiveness of this chromosome formulation enables the fuzzy sets and rules to be optimally reduced. The performances of the ROFLC are compared to these found by the traditional PD controller with Genetic Optimization (PD_GO. Simulations demonstrate that the proposed ROFLC and PD_GO has successfully met the design specifications.
Yang, Xi-Feng; Zhou, Wen-Qian; Hong, Xue-Kun; Liu, Yu-Shen; Wang, Xue-Feng; Feng, Jin-Fu
2015-01-14
Ab initio calculations combining density-functional theory and nonequilibrium Green's function are performed to investigate the effects of either single B atom or single N atom dopant in zigzag-edged graphene nanoribbons (ZGNRs) with the ferromagnetic state on the spin-dependent transport properties and thermospin performances. A spin-up (spin-down) localized state near the Fermi level can be induced by these dopants, resulting in a half-metallic property with 100% negative (positive) spin polarization at the Fermi level due to the destructive quantum interference effects. In addition, the highly spin-polarized electric current in the low bias-voltage regime and single-spin negative differential resistance in the high bias-voltage regime are also observed in these doped ZGNRs. Moreover, the large spin-up (spin-down) Seebeck coefficient and the very weak spin-down (spin-up) Seebeck effect of the B(N)-doped ZGNRs near the Fermi level are simultaneously achieved, indicating that the spin Seebeck effect is comparable to the corresponding charge Seebeck effect.
Optimal control of radiator systems; Optimal reglering av radiatorsystem
Energy Technology Data Exchange (ETDEWEB)
Wollerstrand, J.; Ljunggren, P.; Johansson, P.O.
2007-07-01
This report presents results from a study aiming to considerably improve the development towards minimizing the primary return temperature from a district heating (DH) substation by optimizing the control algorithm for the space heating system. The investigation of this research field started about 20 years ago in Sweden when low flow operation of space heating systems was introduced. Following a couple of years of partly confused discussions, the method was accepted by many, but was rejected by others. Our thesis is that further improvement of cooling of DH water is possible when advanced, but robust, control algorithms are used for the space heating system. A space heating system is traditionally designed for a specific constant circulation flow combined with a suitable control curve for the space heating supply temperature as a function of the outdoor temperature. Optimal choice of the control curve varies from case to case and is an issue both we and others have dealt with in previous work. A large step was to derive theoretical control curves for optimal control of the space heating system, with an analysis of how temperature and circulation flow varies with heat load. The estimated gain varies strongly depending on the conditions, however, with realistic conditions it can be as much as 5 deg C decreased DH return temperature on yearly average. To be able to work properly under varying physical circumstances, a control algorithm must be able to combine variation of space heating supply temperature and circulation flow as a function of the heat load. By regulating the rotation speed of the circulation pump this can be achieved. Such regulation can be adjusted for each and every building by regulating a few parameters in a regulator. The results from this work are, that important theoretical knowledge has been completed, to show results systematically and to find support from practical experiments. A hands-on description of the method for optimizing DH water
Theoretical model of the single spin-echo relaxation time for spherical magnetic perturbers.
Kurz, Felix T; Kampf, Thomas; Heiland, Sabine; Bendszus, Martin; Schlemmer, Heinz-Peter; Ziener, Christian H
2014-05-01
Magnetically labeled cells and tissue iron deposits provide qualitative means to detect and monitor cardiovascular and cerebrovascular diseases with magnetic resonance imaging. However, to quantitatively examine the extent of pathological micromorphological changes, detailed knowledge about microstructural parameters and relaxation times is required. The complex geometrical arrangement of spherical magnetic perturbers is considered in an external magnetic field. They create a magnetic dipole field, whose corresponding spin-echo formation is investigated by analyzing the diffusion process in the dephasing volume. Quantitative predictions of the present analysis are compared with experimental data and empirical models. Single spin-echo relaxation times can be characterized by morphological parameters such as magnetic particle concentration and size as well as tissue diffusion coefficient and local magnetic susceptibility properties. As expected, no formation of a static dephasing plateau is observed in contrast to the gradient-echo relaxation time. Instead, the relaxation rate drops for large particle sizes and exhibits a prominent maximal value at intermediate sizes. These findings agree well with experimental data and previous theoretical results. Obtained results for the single spin-echo relaxation time allow to accurately quantify pathological processes in neurodegenerative disease and migration dynamics of magnetically labeled cells with the help of magnetic resonance imaging. Copyright © 2014 Wiley Periodicals, Inc.
Cyclic Control Optimization for a Smart Rotor
DEFF Research Database (Denmark)
Bergami, Leonardo; Henriksen, Lars Christian
2012-01-01
bending moment within a rotor revolution. The method is applied to a rotor equipped with trailing edge flaps, and capable of individual blade pitching. Results show that the optimized cyclic control significantly alleviates the load variations from periodic disturbances; the combination of both cyclic......The paper presents a method to determine cyclic control trajectories for a smart rotor undergoing periodic-deterministic load variations. The control trajectories result from a constrained optimization problem, where the cost function to minimize is given by the variation of the blade root flapwise...... flap and pitch allows to reduce the action (and hence the wear) on the pitch actuators, and still to achieve considerable load alleviation....
Algorithm For Optimal Control Of Large Structures
Salama, Moktar A.; Garba, John A..; Utku, Senol
1989-01-01
Cost of computation appears competitive with other methods. Problem to compute optimal control of forced response of structure with n degrees of freedom identified in terms of smaller number, r, of vibrational modes. Article begins with Hamilton-Jacobi formulation of mechanics and use of quadratic cost functional. Complexity reduced by alternative approach in which quadratic cost functional expressed in terms of control variables only. Leads to iterative solution of second-order time-integral matrix Volterra equation of second kind containing optimal control vector. Cost of algorithm, measured in terms of number of computations required, is of order of, or less than, cost of prior algoritms applied to similar problems.
Centralized Stochastic Optimal Control of Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Malikopoulos, Andreas [ORNL
2015-01-01
In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.
An example in linear quadratic optimal control
Weiss, George; Zwart, Heiko J.
1998-01-01
We construct a simple example of a quadratic optimal control problem for an infinite-dimensional linear system based on a shift semigroup. This system has an unbounded control operator. The cost is quadratic in the input and the state, and the weighting operators are bounded. Despite its extreme
Energy Technology Data Exchange (ETDEWEB)
., Nuruzzaman [Hampton Univ., Hampton, VA (United States)
2014-12-01
The Q-weak experiment in Hall-C at the Thomas Jefferson National Accelerator Facility has made the first direct measurement of the weak charge of the proton through the precision measurement of the parity-violating asymmetry in elastic electron-proton scattering at low momentum transfer. There is also a parity conserving Beam Normal Single Spin Asymmetry or transverse asymmetry (B_n) on H_2 with a sin(phi)-like dependence due to two-photon exchange. If the size of elastic B_n is a few ppm, then a few percent residual transverse polarization in the beam, combined with small broken azimuthal symmetries in the detector, would require a few ppb correction to the Q-weak data. As part of a program of B_n background studies, we made the first measurement of B_n in the N-to-Delta(1232) transition using the Q-weak apparatus. The final transverse asymmetry, corrected for backgrounds and beam polarization, was found to be B_n = 42.82 ± 2.45 (stat) ± 16.07 (sys) ppm at beam energy E_beam = 1.155 GeV, scattering angle theta = 8.3 deg, and missing mass W = 1.2 GeV. B_n from electron-nucleon scattering is a unique tool to study the gamma^* Delta Delta form factors, and this measurement will help to improve the theoretical models on beam normal single spin asymmetry and thereby our understanding of the doubly virtual Compton scattering process. To help correct false asymmetries from beam noise, a beam modulation system was implemented to induce small position, angle, and energy changes at the target to characterize detector response to the beam jitter. Two air-core dipoles separated by ~10 m were pulsed at a time to produce position and angle changes at the target, for virtually any tune of the beamline. The beam energy was modulated using an SRF cavity. The hardware and associated control instrumentation will be described in this dissertation. Preliminary detector sensitivities were extracted which helped to reduce the width of the measured asymmetry. The beam modulation system
Multiobjective Optimization of PID Controller of PMSM
Directory of Open Access Journals (Sweden)
Qingyang Xu
2014-01-01
Full Text Available PID controller is used in most of the current-speed closed-loop control of permanent magnet synchronous motors (PMSM servo system. However, Kp, Ki, and Kd of PID are difficult to tune due to the multiple objectives. In order to obtain the optimal PID parameters, we adopt a NSGA-II to optimize the PID parameters in this paper. According to the practical requirement, several objective functions are defined. NSGA-II can search the optimal parameters according to the objective functions with better robustness. This approach provides a more theoretical basis for the optimization of PID parameters than the aggregation function method. The simulation results indicate that the system is valid, and the NSGA-II can obtain the Pareto front of PID parameters.
2016 Network Games, Control, and Optimization Conference
Jimenez, Tania; Solan, Eilon
2017-01-01
This contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other relate...
Optimal control applications in electric power systems
Christensen, G S; Soliman, S A
1987-01-01
Significant advances in the field of optimal control have been made over the past few decades. These advances have been well documented in numerous fine publications, and have motivated a number of innovations in electric power system engineering, but they have not yet been collected in book form. Our purpose in writing this book is to provide a description of some of the applications of optimal control techniques to practical power system problems. The book is designed for advanced undergraduate courses in electric power systems, as well as graduate courses in electrical engineering, applied mathematics, and industrial engineering. It is also intended as a self-study aid for practicing personnel involved in the planning and operation of electric power systems for utilities, manufacturers, and consulting and government regulatory agencies. The book consists of seven chapters. It begins with an introductory chapter that briefly reviews the history of optimal control and its power system applications and also p...
Optimal temperature control for batch beer fermentation.
Gee, D A; Ramirez, W F
1988-02-20
Optimal control theory was applied to the process of batch beer fermentation. The performance functional considered was a weighted sum of maximum ethanol production and minimum time. Calculations were based on the model of Engasser et al. modified to include temperature effects. Model parameters were determined from isothermal batch fermentations. The fermentor cooling duty was the single available control. Temperature state variable constraints as well as control variable constraints were considered. The optimal control law is shown to be bang-bang control with the existence of a singular arc corresponding to isothermal operation at the maximum temperature constraint. An iterative algorithm is presented for computing appropriate switching times using a penalty-function-augmented performance functional.
Optimal control application to an Ebola model
Directory of Open Access Journals (Sweden)
Ebenezer Bonyah
2016-04-01
Full Text Available Ebola virus is a severe, frequently fatal illness, with a case fatality rate up to 90%. The outbreak of the disease has been acknowledged by World Health Organization as Public Health Emergency of International Concern. The threat of Ebola in West Africa is still a major setback to the socioeconomic development. Optimal control theory is applied to a system of ordinary differential equations which is modeling Ebola infection through three different routes including contact between humans and a dead body. In an attempt to reduce infection in susceptible population, a preventive control is put in the form of education and campaign and two treatment controls are applied to infected and late-stage infected (super human population. The Pontryagins maximum principle is employed to characterize optimality control, which is then solved numerically. It is observed that time optimal control is existed in the model. The activation of each control showed a positive reduction of infection. The overall effect of activation of all the controls simultaneously reduced the effort required for the reduction of the infection quickly. The obtained results present a good framework for planning and designing cost-effective strategies for good interventions in dealing with Ebola disease. It is established that in order to reduce Ebola threat all the three controls must be taken into consideration concurrently.
Optimal control with multiple human papillomavirus vaccines.
Malik, Tufail; Imran, Mudassar; Jayaraman, Raja
2016-03-21
A two-sex, deterministic ordinary differential equations model for human papillomavirus (HPV) is constructed and analyzed for optimal control strategies in a vaccination program administering three types of vaccines in the female population: a bivalent vaccine that targets two HPV types and provides longer duration of protection and cross-protection against some non-target types, a quadrivalent vaccine which targets an additional two HPV types, and a nonavalent vaccine which targets nine HPV types (including those covered by the quadrivalent vaccine), but with lesser type-specific efficacy. Considering constant vaccination controls, the disease-free equilibrium and the effective reproduction number Rv for the autonomous model are computed in terms of the model parameters. Local-asymptotic stability of the disease-free equilibrium is established in terms of Rv. Uncertainty and Sensitivity analyses are carried out to study the influence of various important model parameters on the HPV infection prevalence. Assuming the HPV infection prevalence in the population under the constant control, optimal control theory is used to devise optimal vaccination strategies for the associated non-autonomous model when the vaccination rates are functions of time. The impact of these strategies on the number of infected individuals and the accumulated cost is assessed and compared with the constant control case. Switch times from one vaccine combination to a different combination including the nonavalent vaccine are assessed during an optimally designed HPV immunization program. Copyright © 2016 Elsevier Ltd. All rights reserved.
Entangled Absorption of a Single Photon with a Single Spin in Diamond
Kosaka, Hideo; Niikura, Naeko
2015-02-01
Quantum entanglement, a key resource for quantum information science, is inherent in a solid. It has been recently shown that entanglement between a single optical photon and a single spin qubit in a solid is generated via spontaneous emission. However, entanglement generation by measurement is rather essential for quantum operations. We here show that the physics behind the entangled emission can be time reversed to demonstrate entangled absorption mediated by an inherent spin-orbit entanglement in a single nitrogen vacancy center in diamond. Optical arbitrary spin state preparation and complete spin state tomography reveal the fidelity of the entangled absorption to be 95%. With the entangled emission and absorption of a photon, materials can be spontaneously entangled or swap their quantum state based on the quantum teleportation scheme.
Resonance estimates for single spin asymmetries in elastic electron-nucleon scattering
Energy Technology Data Exchange (ETDEWEB)
Barbara Pasquini; Marc Vanderhaeghen
2004-07-01
We discuss the target and beam normal spin asymmetries in elastic electron-nucleon scattering which depend on the imaginary part of two-photon exchange processes between electron and nucleon. We express this imaginary part as a phase space integral over the doubly virtual Compton scattering tensor on the nucleon. We use unitarity to model the doubly virtual Compton scattering tensor in the resonance region in terms of {gamma}* N {yields} {pi} N electroabsorption amplitudes. Taking those amplitudes from a phenomenological analysis of pion electroproduction observables, we present results for beam and target normal single spin asymmetries for elastic electron-nucleon scattering for beam energies below 1 GeV and in the 1-3 GeV region, where several experiments are performed or are in progress.
The role of three-gluon correlation functions in the single spin asymmetry
Directory of Open Access Journals (Sweden)
Beppu Hiroo
2015-01-01
Full Text Available We study the twist-3 three-gluon contribution to the single spin asymmetry in the light-hadron production in pp collision in the framework of the collinear factorization. We derive the corresponding cross section formula in the leading order with respect to the QCD coupling constant. We also present a numerical calculation of the asymmetry at the RHIC energy, using a model for the three-gluon correlation functions suggested by the asymmetry for the D-meson production at RHIC. We found that the asymmetries for the light-hadron and the jet productions are very useful to constrain the magnitude and form of the correlation functions. Since the three-gluon correlation functions shift the asymmetry for all kinds of hadrons in the same direction, it is unlikely that they become a main source of the asymmetry.
Transverse target single-spin asymmetry in inclusive electroproduction of charged pions and kaons
Energy Technology Data Exchange (ETDEWEB)
Airapetian, A. [Giessen Univ. (Germany). 2. Physikalisches Inst.; Michigan Univ., Ann Arbor, MI (United States). Randall Laboratory of Physics; Akopov, N. [Yerevan Physics Institute (Argentina); Akopov, Z. [DESY Hamburg (Germany)] [and others; Collaboration: HERMES Collaboration
2013-10-15
Single-spin asymmetries were investigated in inclusive electroproduction of charged pions and kaons from transversely polarized protons at the HERMES experiment. The asymmetries were studied as a function of the azimuthal angle {psi} about the beam direction between the target-spin direction and the hadron production plane, the transverse hadron momentum P{sub T} relative to the direction of the incident beam, and the Feynman variable x{sub F}. The sin {psi} amplitudes are positive for {pi}{sup +} and K{sup +}, slightly negative for {pi}{sup -} consistent with zero for K{sup -}, with particular P{sub T} but weak x{sub F} dependences. Especially large asymmetries are observed for two small subsamples of events, where also the scattered electron was recorded by the spectrometer.
Transverse target single-spin asymmetry in inclusive electroproduction of charged pions and kaons
Airapetian, A; Akopov, Z; Aschenauer, E C; Augustyniak, W; Avakian, R; Avetissian, A; Avetisyan, E; Belostotski, S; Bianchi, N; Blok, H P; Borissov, A; Bowles, J; Bryzgalov, V; Burns, J; Capiluppi, M; Capitani, G P; Cisbani, E; Ciullo, G; Contalbrigo, M; Dalpiaz, P F; Deconinck, W; De Leo, R; De Nardo, L; De Sanctis, E; Diefenthaler, M; Di Nezza, P; Düren, M; Ehrenfried, M; Elbakian, G; Ellinghaus, F; Fabbri, R; Fantoni, A; Felawka, L; Frullani, S; Gabbert, D; Gapienko, G; Gapienko, V; Gavrilov, G; Gharibyan, V; Giordano, F; Gliske, S; Golembiovskaya, M; Hadjidakis, C; Hartig, M; Hasch, D; Hillenbrand, A; Hoek, M; Holler, Y; Hristova, I; Ivanilov, A; Jackson, H E; Joosten, S; Kaiser, R; Karyan, G; Keri, T; Kinney, E; Kisselev, A; Korotkov, V; Kozlov, V; Kravchenko, P; Krivokhijine, V G; Lagamba, L; Lapikás, L; Lehmann, I; Lenisa, P; Ruiz, A López; Lorenzon, W; Ma, B -Q; Mahon, D; Makins, N C R; Manaenkov, S I; Mao, Y; Marianski, B; de la Ossa, A Martinez; Marukyan, H; Miller, C A; Miyachi, Y; Movsisyan, A; Muccifora, V; Murray, M; Mussgiller, A; Nappi, E; Naryshkin, Y; Nass, A; Negodaev, M; Nowak, W -D; Pappalardo, L L; Perez-Benito, R; Petrosyan, A; Raithel, M; Reimer, P E; Reolon, A R; Riedl, C; Rith, K; Rosner, G; Rostomyan, A; Rubin, J; Ryckbosch, D; Salomatin, Y; Sanftl, F; Schäfer, A; Schnell, G; Seitz, B; Shibata, T -A; Shutov, V; Stancari, M; Statera, M; Steffens, E; Steijger, J J M; Stewart, J; Stinzing, F; Taroian, S; Terkulov, A; Truty, R; Trzcinski, A; Tytgat, M; Van Haarlem, Y; Van Hulse, C; Veretennikov, D; Vikhrov, V; Vilardi, I; Wang, S; Yaschenko, S; Ye, Z; Yen, S; Yu, W; Zagrebelnyy, V; Zeiler, D; Zihlmann, B; Zupranski, P
2013-01-01
Single-spin asymmetries were investigated in inclusive electroproduction of charged pions and kaons from transversely polarized protons at the HERMES experiment. The asymmetries were studied as a function of the azimuthal angle $\\psi$ about the beam direction between the target-spin direction and the hadron production plane, the transverse hadron momentum relative to the direction of the incident beam, and the Feynman variable $x_F$. The $\\sin(\\psi)$ amplitudes are positive for positive pions and kaons, slightly negative for negative pions and consistent with zero for negative kaons, with particular transverse-momentum but weak $x_F$ dependences. Especially large asymmetries are observed for two small subsamples of events, where also the scattered electron was recorded by the spectrometer.
Efficient evolutionary algorithms for optimal control
López Cruz, I.L.
2002-01-01
If optimal control problems are solved by means of gradient based local search methods, convergence to local solutions is likely. Recently, there has been an increasing interest in the use
Optimal control design for a solar greenhouse
Ooteghem, van R.J.C.
2007-01-01
The research of this thesis was part of a larger project aiming at the design of a greenhouse and an associated climate control that achieves optimal crop production with sustainable instead of fossil energy. This so called solar greenhouse design extends a conventional greenhouse with an improved
Automatic Synthesis of Robust and Optimal Controllers
DEFF Research Database (Denmark)
Cassez, Franck; Jessen, Jan Jacob; Larsen, Kim Guldstrand
2009-01-01
In this paper, we show how to apply recent tools for the automatic synthesis of robust and near-optimal controllers for a real industrial case study. We show how to use three different classes of models and their supporting existing tools, Uppaal-TiGA for synthesis, phaver for verification...
Optimally Controlled Flexible Fuel Powertrain System
Energy Technology Data Exchange (ETDEWEB)
Hakan Yilmaz; Mark Christie; Anna Stefanopoulou
2010-12-31
The primary objective of this project was to develop a true Flex Fuel Vehicle capable of running on any blend of ethanol from 0 to 85% with reduced penalty in usable vehicle range. A research and development program, targeting 10% improvement in fuel economy using a direct injection (DI) turbocharged spark ignition engine was conducted. In this project a gasoline-optimized high-technology engine was considered and the hardware and configuration modifications were defined for the engine, fueling system, and air path. Combined with a novel engine control strategy, control software, and calibration this resulted in a highly efficient and clean FFV concept. It was also intended to develop robust detection schemes of the ethanol content in the fuel integrated with adaptive control algorithms for optimized turbocharged direct injection engine combustion. The approach relies heavily on software-based adaptation and optimization striving for minimal modifications to the gasoline-optimized engine hardware system. Our ultimate objective was to develop a compact control methodology that takes advantage of any ethanol-based fuel mixture and not compromise the engine performance under gasoline operation.
Augmented Lagrangian Method For Discretized Optimal Control ...
African Journals Online (AJOL)
In this paper, we are concerned with one-dimensional time invariant optimal control problem, whose objective function is quadratic and the dynamical system is a differential equation with initial condition .Since most real life problems are nonlinear and their analytical solutions are not readily available, we resolve to ...
Optimal control of Rydberg lattice gases
DEFF Research Database (Denmark)
Cui, Jian; Bijnen, Rick van; Pohl, Thomas
2017-01-01
We present optimal control protocols to prepare different many-body quantum states of Rydberg atoms in optical lattices. Specifically, we show how to prepare highly ordered many-body ground states, GHZ states as well as some superposition of symmetric excitation number Fock states, that inherit...
Optimal control solutions to sodic soil reclamation
Mau, Yair; Porporato, Amilcare
2016-05-01
We study the reclamation process of a sodic soil by irrigation with water amended with calcium cations. In order to explore the entire range of time-dependent strategies, this task is framed as an optimal control problem, where the amendment rate is the control and the total rehabilitation time is the quantity to be minimized. We use a minimalist model of vertically averaged soil salinity and sodicity, in which the main feedback controlling the dynamics is the nonlinear coupling of soil water and exchange complex, given by the Gapon equation. We show that the optimal solution is a bang-bang control strategy, where the amendment rate is discontinuously switched along the process from a maximum value to zero. The solution enables a reduction in remediation time of about 50%, compared with the continuous use of good-quality irrigation water. Because of its general structure, the bang-bang solution is also shown to work for the reclamation of other soil conditions, such as saline-sodic soils. The novelty in our modeling approach is the capability of searching the entire "strategy space" for optimal time-dependent protocols. The optimal solutions found for the minimalist model can be then fine-tuned by experiments and numerical simulations, applicable to realistic conditions that include spatial variability and heterogeneities.
Optimization and Development of Swellable Controlled Porosity ...
African Journals Online (AJOL)
Purpose: To develop swellable controlled porosity osmotic pump tablet of theophylline and to define the formulation and process variables responsible for drug release by applying statistical optimization technique. Methods: Formulations were prepared based on Taguchi Orthogonal Array design and Fraction Factorial ...
Optimal control tuning of a redundant robot
Jaulin, Luc
2012-01-01
International audience; A robot can generally be described by a vector first-order differential equation, named state equations. A robot is said to be redundant if it has more actuators than necessary. In this case, the number of inputs is higher than the number of outputs (variables to be controlled) and there exists many different ways to achieve the control requirements. We can thus take advantage of the extra number of freedom degrees in order to optimize some performance criterion (invol...
Optimization-based controller design for rotorcraft
Tsing, N.-K.; Fan, M. K. H.; Barlow, J.; Tits, A. L.; Tischler, M. B.
1993-01-01
An optimization-based methodology for linear control system design is outlined by considering the design of a controller for a UH-60 rotorcraft in hover. A wide range of design specifications is taken into account: internal stability, decoupling between longitudinal and lateral motions, handling qualities, and rejection of windgusts. These specifications are investigated while taking into account physical limitations in the swashplate displacements and rates of displacement. The methodology crucially relies on user-machine interaction for tradeoff exploration.
Optimal control of electrodynamic tether satellites
Stevens, Robert E.
Low thrust propulsion systems offer a fuel-efficient means to maneuver satellites to new orbits, however they can only perform such maneuvers when they are continuously operated for a long time. Such long-term maneuvers occur over many orbital revolutions often rendering short time scale trajectory optimization methods ineffective. An approach to multirevolution, long time scale optimal control of an electrodynamic tether is investigated for a tethered satellite system in Low Earth Orbit with atmospheric drag. Control is assumed to be periodic over several orbits since under the assumptions of a nearly circular orbit, periodic control yields the only solution that significantly contributes to secular changes in the orbital parameters. The optimal control problem is constructed in such a way as to maneuver the satellite to a new orbit while minimizing a cost function subject to the constraints of the time-averaged equations of motion by controlling current in the tether. To accurately capture the tether orbital dynamics, libration is modeled and controlled over long time scales in a similar manner to the orbital states. Libration is addressed in two parts; equilibrium and stability analysis, and control. Libration equations of motion are derived and analyzed to provide equilibrium and stability criteria that define the constraints of the design. A new libration mean square state is introduced and constrained to maintain libration within an acceptable envelope throughout a given maneuver. Optimal control solutions are achieved using a pseudospectral method that maneuver an electrodynamic tether to new orbits over long time scales while managing librational motion using only current in a wire.
Algorithms for optimizing CT fluence control
Hsieh, Scott S.; Pelc, Norbert J.
2014-03-01
The ability to customize the incident x-ray fluence in CT via beam-shaping filters or mA modulation is known to improve image quality and/or reduce radiation dose. Previous work has shown that complete control of x-ray fluence (ray-by-ray fluence modulation) would further improve dose efficiency. While complete control of fluence is not currently possible, emerging concepts such as dynamic attenuators and inverse-geometry CT allow nearly complete control to be realized. Optimally using ray-by-ray fluence modulation requires solving a very high-dimensional optimization problem. Most optimization techniques fail or only provide approximate solutions. We present efficient algorithms for minimizing mean or peak variance given a fixed dose limit. The reductions in variance can easily be translated to reduction in dose, if the original variance met image quality requirements. For mean variance, a closed form solution is derived. The peak variance problem is recast as iterated, weighted mean variance minimization, and at each iteration it is possible to bound the distance to the optimal solution. We apply our algorithms in simulations of scans of the thorax and abdomen. Peak variance reductions of 45% and 65% are demonstrated in the abdomen and thorax, respectively, compared to a bowtie filter alone. Mean variance shows smaller gains (about 15%).
Hover flight control of helicopter using optimal control theory
Ahmed ABOULFTOUH; Gamal EL-BAYOUMI; Mohamed MADBOULI
2015-01-01
This paper represents the optimal control theory and its application to the full scale helicopters. Generally the control of a helicopter is a hard task, because its system is very nonlinear, coupled and sensitive to the control inputs and external disturbances which might destabilize the system. As a result of these instabilities, it is essential to use a control process that helps to improve the systems performance, confirming stability and robustness. The main objective of this part is to ...
Recent developments in cooperative control and optimization
Murphey, Robert; Pardalos, Panos
2004-01-01
Over the past several years, cooperative control and optimization has un questionably been established as one of the most important areas of research in the military sciences. Even so, cooperative control and optimization tran scends the military in its scope -having become quite relevant to a broad class of systems with many exciting, commercial, applications. One reason for all the excitement is that research has been so incredibly diverse -spanning many scientific and engineering disciplines. This latest volume in the Cooperative Systems book series clearly illustrates this trend towards diversity and creative thought. And no wonder, cooperative systems are among the hardest systems control science has endeavored to study, hence creative approaches to model ing, analysis, and synthesis are a must! The definition of cooperation itself is a slippery issue. As you will see in this and previous volumes, cooperation has been cast into many different roles and therefore has assumed many diverse meanings. P...
Bulgakov, V. K.; Strigunov, V. V.
2009-05-01
The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.
Breakdown of single spin-fluid model in the heavily hole-doped superconductor CsFe2As2
Zhao, D.; Li, S. J.; Wang, N. Z.; Li, J.; Song, D. W.; Zheng, L. X.; Nie, L. P.; Luo, X. G.; Wu, T.; Chen, X. H.
2018-01-01
Although Fe-based superconductors are correlated electronic systems with multiorbital, previous nuclear magnetic resonance (NMR) measurement suggests that a single spin-fluid model is sufficient to describe its spin behavior. Here, we first observed the breakdown of single spin-fluid model in a heavily hole-doped Fe-based superconductor CsFe2As2 by site-selective NMR measurement. At high-temperature regime, both Knight shift and nuclear spin-lattice relaxation at 133Cs and 75As nuclei exhibit distinct temperature-dependent behavior, suggesting the breakdown of the single spin-fluid model in CsFe2As2 . This is ascribed to the coexistence of both localized and itinerant spin degree of freedom at 3 d orbitals, which is consistent with the orbital-selective Mott phase. With decreasing temperature, the single spin-fluid behavior is recovered below T*˜75 K due to a coherent state among 3 d orbitals. The Kondo liquid scenario is proposed to understand the low-temperature coherent state.
Hover flight control of helicopter using optimal control theory
Directory of Open Access Journals (Sweden)
Ahmed ABOULFTOUH
2015-09-01
Full Text Available This paper represents the optimal control theory and its application to the full scale helicopters. Generally the control of a helicopter is a hard task, because its system is very nonlinear, coupled and sensitive to the control inputs and external disturbances which might destabilize the system. As a result of these instabilities, it is essential to use a control process that helps to improve the systems performance, confirming stability and robustness. The main objective of this part is to develop a control system design technique using Linear Quadratic Regulator (LQR to stabilize the helicopter near hover flight. In order to achieve this objective, firstly, the nonlinear model of the helicopter is linearized using small disturbance theory. The linear optimal control theory is applied to the linearized state space model of the helicopter to design the LQR controller. To clarify robustness of the controller, the effects of external wind gusts and mass change are taken into concern. Wind gusts are taken as disturbances in all directions which are simulated as a sine wave. Many simulations were made to validate and verify the response of the linear controller of the helicopter. The results show that the use of an optimal control process as LQR is a good solution for MIMO helicopter system, achieving a good stabilization and refining the final behavior of the helicopter and handling the external wind gusts disturbances as shown in the different simulations.
Iterative learning control an optimization paradigm
Owens, David H
2016-01-01
This book develops a coherent theoretical approach to algorithm design for iterative learning control based on the use of optimization concepts. Concentrating initially on linear, discrete-time systems, the author gives the reader access to theories based on either signal or parameter optimization. Although the two approaches are shown to be related in a formal mathematical sense, the text presents them separately because their relevant algorithm design issues are distinct and give rise to different performance capabilities. Together with algorithm design, the text demonstrates that there are new algorithms that are capable of incorporating input and output constraints, enable the algorithm to reconfigure systematically in order to meet the requirements of different reference signals and also to support new algorithms for local convergence of nonlinear iterative control. Simulation and application studies are used to illustrate algorithm properties and performance in systems like gantry robots and other elect...
Optimal Control of Switching Linear Systems
Directory of Open Access Journals (Sweden)
Ali Benmerzouga
2004-06-01
Full Text Available A solution to the control of switching linear systems with input constraints was given in Benmerzouga (1997 for both the conventional enumeration approach and the new approach. The solution given there turned out to be not unique. The main objective in this work is to determine the optimal control sequences {Ui(k , i = 1,..., M ; k = 0, 1, ..., N -1} which transfer the system from a given initial state X0 to a specific target state XT (or to be as close as possible by using the same discrete time solution obtained in Benmerzouga (1997 and minimizing a running cost-to-go function. By using the dynamic programming technique, the optimal solution is found for both approaches given in Benmerzouga (1997. The computational complexity of the modified algorithm is also given.
Modeling, Optimization & Control of Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat
2014-01-01
in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply....... The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used...... to solve nonlinear optimal control problems. In the water supply system model, the hydraulic resistance of the valve is estimated by real data and it is considered to be a disturbance. The disturbance in our system is updated every 24 hours based on the amount of water usage by consumers every day. Model...
Linear systems optimal and robust control
Sinha, Alok
2007-01-01
Introduction Overview Contents of the Book State Space Description of a Linear System Transfer Function of a Single Input/Single Output (SISO) System State Space Realizations of a SISO System SISO Transfer Function from a State Space Realization Solution of State Space Equations Observability and Controllability of a SISO System Some Important Similarity Transformations Simultaneous Controllability and Observability Multiinput/Multioutput (MIMO) Systems State Space Realizations of a Transfer Function Matrix Controllability and Observability of a MIMO System Matrix-Fraction Description (MFD) MFD of a Transfer Function Matrix for the Minimal Order of a State Space Realization Controller Form Realization from a Right MFD Poles and Zeros of a MIMO Transfer Function Matrix Stability Analysis State Feedback Control and Optimization State Variable Feedback for a Single Input System Computation of State Feedback Gain Matrix for a Multiinput System State Feedback Gain Matrix for a Multi...
Stochastic optimal control of state constrained systems
van den Broek, Bart; Wiegerinck, Wim; Kappen, Bert
2011-03-01
In this article we consider the problem of stochastic optimal control in continuous-time and state-action space of systems with state constraints. These systems typically appear in the area of robotics, where hard obstacles constrain the state space of the robot. A common approach is to solve the problem locally using a linear-quadratic Gaussian (LQG) method. We take a different approach and apply path integral control as introduced by Kappen (Kappen, H.J. (2005a), 'Path Integrals and Symmetry Breaking for Optimal Control Theory', Journal of Statistical Mechanics: Theory and Experiment, 2005, P11011; Kappen, H.J. (2005b), 'Linear Theory for Control of Nonlinear Stochastic Systems', Physical Review Letters, 95, 200201). We use hybrid Monte Carlo sampling to infer the control. We introduce an adaptive time discretisation scheme for the simulation of the controlled dynamics. We demonstrate our approach on two examples, a simple particle in a halfspace and a more complex two-joint manipulator, and we show that in a high noise regime our approach outperforms the iterative LQG method.
Computational Methods for Design, Control and Optimization
2007-10-01
Sensitivity Computations, 49 (2005), pp. 1889 - 1903.. 8. Y. Cao, T. L. Herdman and Y. Xu, A Hybrid Collocation Method for Volterra Integral Equations ...scaleRiccati equations that arise in a variety of control and estimation problems. The results imply that, even when the Riccati equations are used for...and optimization of hybrid systems governed by partial differential equations that are typical in aerospace systems. The focus of the research is on non
Optimal control of multiplicative control systems arising from cancer therapy
Bahrami, K.; Kim, M.
1975-01-01
This study deals with ways of curtailing the rapid growth of cancer cell populations. The performance functional that measures the size of the population at the terminal time as well as the control effort is devised. With use of the discrete maximum principle, the Hamiltonian for this problem is determined and the condition for optimal solutions are developed. The optimal strategy is shown to be a bang-bang control. It is shown that the optimal control for this problem must be on the vertices of an N-dimensional cube contained in the N-dimensional Euclidean space. An algorithm for obtaining a local minimum of the performance function in an orderly fashion is developed. Application of the algorithm to the design of antitumor drug and X-irradiation schedule is discussed.
Optimal Control Applications in Space Situational Awareness
Holzinger, Marcus J.
There are currently more than 19,000 trackable objects in Earth orbit, 1,300 of which are active. With so many objects populating the space object catalog and new objects being added at an ever increasing rate, ensuring continued access to space is quickly becoming a cornerstone of national security policies. Space Situational Awareness (SSA) supports space operations, space flight safety, implementing international treaties and agreements, protecting of space capabilities, and protecting of national interests. With respect to objects in orbit, this entails determining their location, orientation, size, shape, status, purpose, current tasking, and future tasking. For active spacecraft capable of propulsion, the problem of determining these characteristics becomes significantly more difficult. Optimal control techniques can be applied to object correlation, maneuver detection, maneuver/spacecraft characterization, fuel usage estimation, operator priority inference, intercept capability characterization, and fuel-constrained range set determination. A detailed mapping between optimal control applications and SSA object characterization support is reviewed and related literature visited. Each SSA application will be addressed starting from first-principles using optimal control techniques. For each application, several examples of potential utility are given and discussed.
Optimal control of complex atomic quantum systems
van Frank, S.; Bonneau, M.; Schmiedmayer, J.; Hild, S.; Gross, C.; Cheneau, M.; Bloch, I.; Pichler, T.; Negretti, A.; Calarco, T.; Montangero, S.
2016-10-01
Quantum technologies will ultimately require manipulating many-body quantum systems with high precision. Cold atom experiments represent a stepping stone in that direction: a high degree of control has been achieved on systems of increasing complexity. However, this control is still sub-optimal. In many scenarios, achieving a fast transformation is crucial to fight against decoherence and imperfection effects. Optimal control theory is believed to be the ideal candidate to bridge the gap between early stage proof-of-principle demonstrations and experimental protocols suitable for practical applications. Indeed, it can engineer protocols at the quantum speed limit - the fastest achievable timescale of the transformation. Here, we demonstrate such potential by computing theoretically and verifying experimentally the optimal transformations in two very different interacting systems: the coherent manipulation of motional states of an atomic Bose-Einstein condensate and the crossing of a quantum phase transition in small systems of cold atoms in optical lattices. We also show that such processes are robust with respect to perturbations, including temperature and atom number fluctuations.
Applied optimal control theory of distributed systems
Lurie, K A
1993-01-01
This book represents an extended and substantially revised version of my earlierbook, Optimal Control in Problems ofMathematical Physics,originally published in Russian in 1975. About 60% of the text has been completely revised and major additions have been included which have produced a practically new text. My aim was to modernize the presentation but also to preserve the original results, some of which are little known to a Western reader. The idea of composites, which is the core of the modern theory of optimization, was initiated in the early seventies. The reader will find here its implementation in the problem of optimal conductivity distribution in an MHD-generatorchannel flow.Sincethen it has emergedinto an extensive theory which is undergoing a continuous development. The book does not pretend to be a textbook, neither does it offer a systematic presentation of the theory. Rather, it reflects a concept which I consider as fundamental in the modern approach to optimization of dis tributed systems. ...
Single-spin asymmetries in semi-inclusive deep inelastic scattering and Drell-Yan processes
Energy Technology Data Exchange (ETDEWEB)
Brodsky, Stanley J.; Hwang, Dae Sung; Kovchegov, Yuri V.; Schmidt, Ivan; Sievert, Matthew D.
2013-07-01
We examine in detail the diagrammatic mechanisms which provide the change of sign between the single transverse spin asymmetries measured in semi-inclusive deep inelastic scattering (SIDIS) and in the Drell-Yan process (DY). This asymmetry is known to arise due to the transverse spin dependence of the target proton combined with a T-odd complex phase. Using the discrete symmetry properties of transverse spinors, we show that the required complex phase originates in the denominators of rescattering diagrams and their respective cuts. For simplicity, we work in a model where the proton consists of a valence quark and a scalar diquark. We then show that the phases generated in SIDIS and in DY originate from distinctly different cuts in the amplitudes, which at first appears to obscure the relationship between the single-spin asymmetries in the two processes. Nevertheless, further analysis demonstrates that the contributions of these cuts are identical in the leading-twist Bjorken kinematics considered, resulting in the standard sign-flip relation between the Sivers functions in SIDIS and DY. Physically, this fundamental, but yet untested, prediction occurs because the Sivers effect in the Drell-Yan reaction is modified by the initial-state “lensing” interactions of the annihilating antiquark, in contrast to the final-state lensing which produces the Sivers effect in deep inelastic scattering.
Eyser, Oleg; STAR Collaboration
2017-09-01
Transverse single-spin asymmetries in high energy collisions offer unique ways to study the nucleon structure beyond the conventional leading twist collinear picture in hard QCD processes. While transverse momentum dependent distribution and fragmentation functions require two scales (hard and soft), observables with a single hard scale can be described in a collinear framework with multiparton correlations (twist-3). Both are related when the intrinsic transverse momentum is integrated. Initial and final state effects can contribute to different probes and need to be disentangled. In 2015, the STAR experiment at RHIC has extended the forward calorimeter, 2.5< η<4.0 with a preshower detector in order to study transverse asymmetries of direct photon production in proton-proton collisions at a center of mass energy of 200 GeV. This measurement will contribute to the universality test of initial state spin-orbit correlations (sign-change between hadronic collisions and deep inelastic scattering) and serve as first input to a proper evolution of higher twist functions as function of momentum transfer. We will present the status of the analysis and discuss implications on the theoretical description.
Optimal control of HIV/AIDS dynamic: Education and treatment
Sule, Amiru; Abdullah, Farah Aini
2014-07-01
A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.
On the Optimal Dynamic Control Strategy of Disruptive Computer Virus
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Jichao Bi
2017-01-01
Full Text Available Disruptive computer viruses have inflicted huge economic losses. This paper addresses the development of a cost-effective dynamic control strategy of disruptive viruses. First, the development problem is modeled as an optimal control problem. Second, a criterion for the existence of an optimal control is given. Third, the optimality system is derived. Next, some examples of the optimal dynamic control strategy are presented. Finally, the performance of actual dynamic control strategies is evaluated.
Kinematically Optimal Robust Control of Redundant Manipulators
Galicki, M.
2017-12-01
This work deals with the problem of the robust optimal task space trajectory tracking subject to finite-time convergence. Kinematic and dynamic equations of a redundant manipulator are assumed to be uncertain. Moreover, globally unbounded disturbances are allowed to act on the manipulator when tracking the trajectory by the endeffector. Furthermore, the movement is to be accomplished in such a way as to minimize both the manipulator torques and their oscillations thus eliminating the potential robot vibrations. Based on suitably defined task space non-singular terminal sliding vector variable and the Lyapunov stability theory, we derive a class of chattering-free robust kinematically optimal controllers, based on the estimation of transpose Jacobian, which seem to be effective in counteracting both uncertain kinematics and dynamics, unbounded disturbances and (possible) kinematic and/or algorithmic singularities met on the robot trajectory. The numerical simulations carried out for a redundant manipulator of a SCARA type consisting of the three revolute kinematic pairs and operating in a two-dimensional task space, illustrate performance of the proposed controllers as well as comparisons with other well known control schemes.
Induction heating processes optimization a general optimal control approach
Favennec, Y; Bay, F
2003-01-01
A general automatic optimization procedure coupled to a finite element induction heating process simulation has been developed. The mathematical model and the numerical methods are presented along with results validating the model. The first part of this paper presents the direct induction heating mathematical model, the related main numerical choices and especially the ultra-weak coupling procedure. The general optimization problem is then presented with the full detailed transposition of the ultra-weak coupling procedure to the adjoint problem. Numerical results provided at the end prove the efficiency and robustness of the adjoint model in optimizing induction heating processes.
Optimal haptic feedback control of artificial muscles
Chen, Daniel; Besier, Thor; Anderson, Iain; McKay, Thomas
2014-03-01
As our population ages, and trends in obesity continue to grow, joint degenerative diseases like osteoarthritis (OA) are becoming increasingly prevalent. With no cure currently in sight, the only effective treatments for OA are orthopaedic surgery and prolonged rehabilitation, neither of which is guaranteed to succeed. Gait retraining has tremendous potential to alter the contact forces in the joints due to walking, reducing the risk of one developing hip and knee OA. Dielectric Elastomer Actuators (DEAs) are being explored as a potential way of applying intuitive haptic feedback to alter a patient's walking gait. The main challenge with the use of DEAs in this application is producing large enough forces and strains to induce sensation when coupled to a patient's skin. A novel controller has been proposed to solve this issue. The controller uses simultaneous capacitive self-sensing and actuation which will optimally apply a haptic sensation to the patient's skin independent of variability in DEAs and patient geometries.
Optimal Control of Solar Heating System
Huang, Bin-Juine
2017-02-21
Forced-circulation solar heating system has been widely used in process and domestic heating applications. Additional pumping power is required to circulate the water through the collectors to absorb the solar energy. The present study intends to develop a maximum-power point tracking control (MPPT) to obtain the minimum pumping power consumption at an optimal heat collection. The net heat energy gain Qnet (= Qs − Wp/ηe) was found to be the cost function for MPPT. The step-up-step-down controller was used in the feedback design of MPPT. The field test results show that the pumping power is 89 W at Qs = 13.7 kW and IT = 892 W/m2. A very high electrical COP of the solar heating system (Qs/Wp = 153.8) is obtained.
Novel QCD Aspects of Hard Diffraction,Antishadowing, and Single-Spin Asymmetries
Energy Technology Data Exchange (ETDEWEB)
Brodsky, S.
2004-10-15
It is usually assumed--following the parton model--that the leading-twist structure functions measured in deep inelastic lepton-proton scattering are simply the probability distributions for finding quarks and gluons in the target nucleon. In fact, gluon exchange between the outgoing quarks and the target spectators effects the leading-twist structure functions in a profound way, leading to diffractive leptoproduction processes, shadowing and antishadowing of nuclear structure functions, and target spin asymmetries, physics not incorporated in the light-front wavefunctions of the target computed in isolation. In particular, final-state interactions from gluon exchange lead to single-spin asymmetries in semi-inclusive deep inelastic lepton-proton scattering which are not power-law suppressed in the Bjorken limit. The shadowing and antishadowing of nuclear structure functions in the Gribov-Glauber picture is due respectively to the destructive and constructive interference of amplitudes arising from the multiple-scattering of quarks in the nucleus. The effective quark-nucleon scattering amplitude includes Pomeron and Odderon contributions from multi-gluon exchange as well as Reggeon quark-exchange contributions. Part of the anomalous NuTeV result for sin{sup 2} {theta}{sub W} could be due to the non-universality of nuclear antishadowing for charged and neutral currents. Detailed measurements of the nuclear dependence of individual quark structure functions are thus needed to establish the distinctive phenomenology of shadowing and antishadowing and to make the NuTeV results definitive. I also discuss diffraction dissociation as a tool for resolving hadron substructure Fock state by Fock state and for producing leading heavy quark systems.
Sivers effect in single spin asymmetry based on the covariant parton model
Saffar, H. Mahdizadeh; Mirjalili, A.; Tehrani, S. Atashbar; Yazdanpanah, M. M.
2017-10-01
Sivers effect is describing the correlation between the transverse polarization of nucleon and the transverse momentum, k⊥, of its unpolarized constituent partons. This effect is an outstanding subject and in this regard, a great deal in recent years has been considered from experimental and phenomenological points of view. It also plays an essential role to extend our understanding from nucleon structure. Semi-inclusive DIS (SIDIS) process provides us an opportunity to access to Sivers function which is dependent on transverse momentum of partons. In this paper, for the first time the covariant parton model is used to deliver us the k⊥ and x dependence part of Sivers function. Based on this model, this combinatory dependence is arising out from the HERAPDF parametrization group. In this paper the other required parametrized functions in Sivers function is also changed with respect to Ref. 1. The unknown parameters which exist in Sivers function can be extracted, doing a global fit over the recent available experimental data, including HERMES, COMPASS and JLAB collaborations for the single spin asymmetry (SSA) in π‑ and π+ meson production as well as kaon production to constrain the evolved strange quark. This is done, considering advanced mathematical manipulations to overcome the difficulties which exist to compute the required multiple integrals and finally employing the CERN MINIUTE program to do a global fit. Our results for SSA are in good agreement with the available experimental data. For more confirmation a comparison between our results and the ones from Ref. 2 is also done.
Single spin asymmetry AN in polarized proton–proton elastic scattering √s=200 GeV
Adamczyk, L.; Agakishiev, G.; La Pointe, S.L.; Zyzak, M.
2013-01-01
We report a high precision measurement of the transverse single spin asymmetry AN at the center of mass energy √s = 200 GeV in elastic proton–proton scattering by the STAR experiment at RHIC. The AN was measured in the four-momentum transfer squared t range 0.003 |t| 0.035 (GeV/c)2, the region of a
Control Optimization of Solar Thermally Driven Chillers
Directory of Open Access Journals (Sweden)
Antoine Dalibard
2016-10-01
Full Text Available Many installed solar thermally driven cooling systems suffer from high auxiliary electric energy consumption which makes them not more efficient than conventional compression cooling systems. A main reason for this is the use of non-efficient controls with constant set points that do not allow a chiller power modulation at partial-load and therefore lead to unnecessary high power consumption of the parasitics. The aims of this paper are to present a method to control efficiently solar thermally driven chillers, to demonstrate experimentally its applicability and to quantify the benefits. It has been shown that the cooling capacity of a diffusion absorption chiller can be modulated very effectively by adjusting both the temperature and the flow rate of the cooling water. With the developed approach and the use of optimization algorithms, both the temperature and the flow rate can be controlled simultaneously in a way that the cooling load is matched and the electricity consumption is minimized. Depending on the weather and operating conditions, electricity savings between 20% and 60% can be achieved compared to other tested control approaches. The highest savings are obtained when the chiller is operated at partial load. The presented method is not restricted to solar cooling systems and can also be applied to other conventional heating ventilation and air conditioning (HVAC systems.
Optimal Sliding Mode Controllers for Attitude Stabilization of Flexible Spacecraft
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Chutiphon Pukdeboon
2011-01-01
Full Text Available The robust optimal attitude control problem for a flexible spacecraft is considered. Two optimal sliding mode control laws that ensure the exponential convergence of the attitude control system are developed. Integral sliding mode control (ISMC is applied to combine the first-order sliding mode with optimal control and is used to control quaternion-based spacecraft attitude manoeuvres with external disturbances and an uncertainty inertia matrix. For the optimal control part the state-dependent Riccati equation (SDRE and optimal Lyapunov techniques are employed to solve the infinite-time nonlinear optimal control problem. The second method of Lyapunov is used to guarantee the stability of the attitude control system under the action of the proposed control laws. An example of multiaxial attitude manoeuvres is presented and simulation results are included to verify the usefulness of the developed controllers.
Directory of Open Access Journals (Sweden)
Azin Ayatollahi
2017-01-01
Full Text Available Introduction and Objective: Platelet-rich plasma (PRP is an autologous preparation of platelets in concentrated plasma. The platelet is a natural source of different growth factors and cytokines. These growth factors act on stem cells in the bulge area of the follicles and stimulate the development of new follicles, and promote neovascularization. The aim of this study was to investigate the efficacy and safety of PRP injections in androgenetic alopecia (AGA in men. Patients and Methods: Fifteen male patients (mean age: 39 ± 9.7 years with AGA grades III–VI were enrolled in the study. Five injections of 2–4 ml PRP (Regenlab PRP Kit-RegenACR®, Le Mont-sur-Lausanne Switzerland by single spin process were administered every 2 weeks. Standard photographs, trichogram, and measurement of hair density and diameter in an area marked with a tattoo (with digital photographic hair analyzer were done at baseline and 3 months after the last injection. In addition, patients completed a patient satisfaction questionnaire at each visit on a −2 to +2 score (−2: much worse, −1: slightly worse, 0: without change, +1: slightly better, +2: much better. Results: Thirteen patients completed the study. The number of hairs increased slightly from 149.62 ± 49.56 to 168.46 ± 43.703/cm2, however, this increase was not statistically significant (P = 0.24. On the other hand, the thickness of hairs decreased from 0.051 ± 0.105 to 0.045 ± 0.011 mm, which was also not significant (P = 0.37. There was a significant decrease in anagen hairs and increase in telogen hairs, and anagen/telogen ratio decreased significantly from 6.38 ± 4.57 to 2.67 ± 1.87 (P = 0.003. Conclusion: Our study could not show any benefit from PRP injections in the treatment of male AGA. There is a strong need for well-designed, randomized controlled trials with large sample size, proper control group, standard treatment protocols (concerning the amount, number and interval of PRP
Optimal control of a delayed SLBS computer virus model
Chen, Lijuan; Hattaf, Khalid; Sun, Jitao
2015-06-01
In this paper, a delayed SLBS computer virus model is firstly proposed. To the best of our knowledge, this is the first time to discuss the optimal control of the SLBS model. By using the optimal control strategy, we present an optimal strategy to minimize the total number of the breakingout computers and the cost associated with toxication or detoxication. We show that an optimal control solution exists for the control problem. Some examples are presented to show the efficiency of this optimal control.
Singular Optimal Controls of Rocket Motion (Survey)
Kiforenko, B. N.
2017-05-01
Survey of modern state and discussion of problems of the perfection of methods of investigation of variational problems with a focus on mechanics of space flight are presented. The main attention is paid to the enhancement of the methods of solving of variational problems of rocket motion in the gravitational fields, including rocket motion in the atmosphere. These problems are directly connected with the permanently actual problem of the practical astronautics to increase the payload that is orbited by the carrier rockets in the circumplanetary orbits. An analysis of modern approaches to solving the problems of control of rockets and spacecraft motion on the trajectories with singular arcs that are optimal for the motion of the variable mass body in the medium with resistance is given. The presented results for some maneuvers can serve as an information source for decision making on designing promising rocket and space technology
Measurement of transverse single-spin asymmetries in inclusive electroproduction at HERMES
Energy Technology Data Exchange (ETDEWEB)
Lopez Ruiz, Alejandro
2012-12-15
This dissertation describes the measurement of two single-spin asymmetries (SSAs) in the production of particles from inelastic lepton-proton collisions. SSAs are a convenient observable for investigating the spin-dependent part of the electron-proton cross section. The analyzed data were taken by the HERMES experiment at DESY, using a 27.6 GeV electron/positron beam and a static hydrogen target in which the proton spin was polarized transversely to the direction of the beam. In the first case, SSAs were investigated in the inclusive electroproduction of charged pions and kaons. The asymmetries were studied as a function of the hadron momentum, p{sub T}, relative to the direction of the incident beam, and the Feynman variable x{sub F}. In the kinematic range 0.08 GeV
On a Highly Nonlinear Self-Obstacle Optimal Control Problem
Energy Technology Data Exchange (ETDEWEB)
Di Donato, Daniela, E-mail: daniela.didonato@unitn.it [University of Trento, Department of Mathematics (Italy); Mugnai, Dimitri, E-mail: dimitri.mugnai@unipg.it [Università di Perugia, Dipartimento di Matematica e Informatica (Italy)
2015-10-15
We consider a non-quadratic optimal control problem associated to a nonlinear elliptic variational inequality, where the obstacle is the control itself. We show that, fixed a desired profile, there exists an optimal solution which is not far from it. Detailed characterizations of the optimal solution are given, also in terms of approximating problems.
Dynamic optimization the calculus of variations and optimal control in economics and management
Kamien, Morton I
2012-01-01
Since its initial publication, this text has defined courses in dynamic optimization taught to economics and management science students. The two-part treatment covers the calculus of variations and optimal control. 1998 edition.
Skinner Rusk unified formalism for optimal control systems and applications
Barbero-Liñán, María; Echeverría-Enríquez, Arturo; Martín de Diego, David; Muñoz-Lecanda, Miguel C.; Román-Roy, Narciso
2007-10-01
A geometric approach to time-dependent optimal control problems is proposed. This formulation is based on the Skinner and Rusk formalism for Lagrangian and Hamiltonian systems. The corresponding unified formalism developed for optimal control systems allows us to formulate geometrically the necessary conditions given by a weak form of Pontryagin's maximum principle, provided that the differentiability with respect to controls is assumed and the space of controls is open. Furthermore, our method is also valid for implicit optimal control systems and, in particular, for the so-called descriptor systems (optimal control problems including both differential and algebraic equations).
Xu, Kebiao; Xie, Tianyu; Li, Zhaokai; Xu, Xiangkun; Wang, Mengqi; Ye, Xiangyu; Kong, Fei; Geng, Jianpei; Duan, Changkui; Shi, Fazhan; Du, Jiangfeng
2017-03-31
The adiabatic quantum computation is a universal and robust method of quantum computing. In this architecture, the problem can be solved by adiabatically evolving the quantum processor from the ground state of a simple initial Hamiltonian to that of a final one, which encodes the solution of the problem. Adiabatic quantum computation has been proved to be a compatible candidate for scalable quantum computation. In this Letter, we report on the experimental realization of an adiabatic quantum algorithm on a single solid spin system under ambient conditions. All elements of adiabatic quantum computation, including initial state preparation, adiabatic evolution (simulated by optimal control), and final state read-out, are realized experimentally. As an example, we found the ground state of the problem Hamiltonian S_{z}I_{z} on our adiabatic quantum processor, which can be mapped to the factorization of 35 into its prime factors 5 and 7.
Neural Network for Optimization of Existing Control Systems
DEFF Research Database (Denmark)
Madsen, Per Printz
1995-01-01
The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems.......The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems....
Optimal Power Flow Control by Rotary Power Flow Controller
Directory of Open Access Journals (Sweden)
KAZEMI, A.
2011-05-01
Full Text Available This paper presents a new power flow model for rotary power flow controller (RPFC. RPFC injects a series voltage into the transmission line and provides series compensation and phase shifting simultaneously. Therefore, it is able to control the transmission line impedance and the active power flow through it. An RPFC is composed mainly of two rotary phase shifting transformers (RPST and two conventional (series and shunt transformers. Structurally, an RPST consists of two windings (stator and rotor windings. The rotor windings of the two RPSTs are connected in parallel and their stator windings are in series. The injected voltage is proportional to the vector sum of the stator voltages and so its amplitude and angle are affected by the rotor position of the two RPSTs. This paper, describes the steady state operation and single-phase equivalent circuit of the RPFC. Also in this paper, a new power flow model, based on power injection model of flexible ac transmission system (FACTS controllers, suitable for the power flow analysis is introduced. Proposed model is used to solve optimal power flow (OPF problem in IEEE standard test systems incorporating RPFC and the optimal settings and location of the RPFC is determined.
Optimal Control Of Nonlinear Wave Energy Point Converters
DEFF Research Database (Denmark)
Nielsen, Søren R.K.; Zhou, Qiang; Kramer, Morten
2013-01-01
In this paper the optimal control law for a single nonlinear point absorber in irregular sea-states is derived, and proven to be a closed-loop controller with feedback from measured displacement, velocity and acceleration of the floater. However, a non-causal integral control component dependent...... on future velocities appears in the optimal control law, rendering the optimal control law less useful for real time implementation. To circumvent this problem a causal closed-loop controller with the same feedback information is proposed, based on a slight modification of the optimal control law. The basic...... idea behind the control strategy is to enforce the stationary velocity response of the absorber into phase with the wave excitation force at any time. The controller is optimal under monochromatic wave excitation. It is demonstrated that the devised causal controller, in plane irregular sea states...
Optimization of Fuzzy Control for Magnetorheological Damping Structures
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Jianguo Ding
2017-01-01
Full Text Available Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of a magnetorheological damping structure that adopts semiactive control. Fuzzy control is a relatively appropriate control method, but fuzzy control design is susceptible to human subjective experience, which will decrease the control effect. This paper proposes new fuzzy control rules based on a genetic algorithm (GA and particle swarm optimization (PSO and performs a numerical simulation for a three-layer reinforced concrete frame structure under conditions of an uncontrolled structure, fuzzy control, fuzzy control optimized by GA, fuzzy control optimized by PSO, and GA-optimized FLC control (GA-FLC proposed by Ali and Ramaswamy (2008. The results show that (1 the fitness values of the convergence of the two types of optimized fuzzy control are close. The speed of the convergence of the fuzzy control optimized by PSO is faster than that of the fuzzy control optimized by GA, but its running speed is slower. (2 Comparing the acceleration and displacement of the structure under the conditions of three different seismic waves, the effect of the optimized fuzzy control is better than that of the human experience fuzzy control and GA-FLC.
A Multiobjective Optimization Framework for Stochastic Control of Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Malikopoulos, Andreas [ORNL; Maroulas, Vasileios [ORNL; Xiong, Professor Jie [The University of Tennessee
2015-01-01
This paper addresses the problem of minimizing the long-run expected average cost of a complex system consisting of subsystems that interact with each other and the environment. We treat the stochastic control problem as a multiobjective optimization problem of the one-stage expected costs of the subsystems, and we show that the control policy yielding the Pareto optimal solution is an optimal control policy that minimizes the average cost criterion for the entire system. For practical situations with constraints consistent to those we study here, our results imply that the Pareto control policy may be of value in deriving online an optimal control policy in complex systems.
Reference-shaping adaptive control by using gradient descent optimizers.
Alagoz, Baris Baykant; Kavuran, Gurkan; Ates, Abdullah; Yeroglu, Celaleddin
2017-01-01
This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC) method for several test scenarios. An experimental study demonstrates application of method for rotor control.
Optimal control of quantum systems by chirped pulses
DEFF Research Database (Denmark)
Amstrup, Bjarne; Doll, J. D.; Sauerbrey, R. A.
1993-01-01
Research on optimal control of quantum systems has been severely restricted by the lack of experimentally feasible control pulses. Here, to overcome this obstacle, optimal control is considered with the help of chirped pulses. Simulated annealing is used as the optimizing procedure. The examples...... treated are pulsed population inversion between electronic levels, and optimization of vibronic excitation in the presence of another electronic level. In the problem of population inversion effective potentials of displaced harmonic oscillators are used. For optimizing vibronic excitation the CsI model...
Optimally controlled optomechanical work cycle for a molecular locomotive
Energy Technology Data Exchange (ETDEWEB)
Wang, Z S [Institute of Modern Physics, Fudan University, Shanghai 200433 (China)
2005-11-30
This work seeks to apply the laser optimal control technique to light-driven molecular motors. Taking a recently proposed molecular locomotive as a model system, a control loop is developed specifically for it, and concrete schemes for experimentally closing the loop are devised. A list of unique control objectives is rigorously formulated from the nanomachinery perspective, and corresponding optimization is made feasible by an innovative application of the established technique of closed-loop learning control. The optimization may be pursued for individual laser operational steps as well as for the overall nanolocomotion performance of the entire work cycle. The locomotive optimal control, capable of co-adapting the laser procedure and the periodically driven molecular dynamics, essentially leads to an optimally performing optomechanical work cycle for the locomotive beyond any model-based pre-designed version. These findings reveal a great potential of laser optimally controlled nanowork cycles in the emerging field of nanomachinery.
Presentation of Malaria Epidemics Using Multiple Optimal Controls
Directory of Open Access Journals (Sweden)
Abid Ali Lashari
2012-01-01
Full Text Available An existing model is extended to assess the impact of some antimalaria control measures, by re-formulating the model as an optimal control problem. This paper investigates the fundamental role of three type of controls, personal protection, treatment, and mosquito reduction strategies in controlling the malaria. We work in the nonlinear optimal control framework. The existence and the uniqueness results of the solution are discussed. A characterization of the optimal control via adjoint variables is established. The optimality system is solved numerically by a competitive Gauss-Seidel-like implicit difference method. Finally, numerical simulations of the optimal control problem, using a set of reasonable parameter values, are carried out to investigate the effectiveness of the proposed control measures.
Optimization of microgrids based on controller designing for ...
African Journals Online (AJOL)
The power quality of microgrid during islanded operation is strongly related with the controller performance of DGs. Therefore a new optimal control strategy for distributed generation based inverter to connect to the generalized microgrid is proposed. This work shows developing optimal control algorithms for the DG ...
Optimization and control methods in industrial engineering and construction
Wang, Xiangyu
2014-01-01
This book presents recent advances in optimization and control methods with applications to industrial engineering and construction management. It consists of 15 chapters authored by recognized experts in a variety of fields including control and operation research, industrial engineering, and project management. Topics include numerical methods in unconstrained optimization, robust optimal control problems, set splitting problems, optimum confidence interval analysis, a monitoring networks optimization survey, distributed fault detection, nonferrous industrial optimization approaches, neural networks in traffic flows, economic scheduling of CCHP systems, a project scheduling optimization survey, lean and agile construction project management, practical construction projects in Hong Kong, dynamic project management, production control in PC4P, and target contracts optimization. The book offers a valuable reference work for scientists, engineers, researchers and practitioners in industrial engineering and c...
Fast Direct Multiple Shooting Algorithms for Optimal Robot Control
Diehl, Moritz; Bock, Hans Georg; Diedam, Holger; Wieber, Pierre-Brice
2005-01-01
International audience; In this overview paper, we ﬁrst survey numerical approaches to solve nonlinear optimal control problems, and second, we present our most recent algorithmic developments for real-time optimization in nonlinear model predictive control. In the survey part, we discuss three direct optimal control approaches in detail: (i) single shooting, (ii) collocation, and (iii) multiple shooting, and we specify why we believe the direct multiple shooting method to be the method of ch...
Measurement of the Transverse Single-Spin Asymmetry in p^{↑}+p→W^{±}/Z^{0} at RHIC.
Adamczyk, L; Adkins, J K; Agakishiev, G; Aggarwal, M M; Ahammed, Z; Alekseev, I; Aparin, A; Arkhipkin, D; Aschenauer, E C; Attri, A; Averichev, G S; Bai, X; Bairathi, V; Banerjee, A; Bellwied, R; Bhasin, A; Bhati, A K; Bhattarai, P; Bielcik, J; Bielcikova, J; Bland, L C; Bordyuzhin, I G; Bouchet, J; Brandenburg, J D; Brandin, A V; Bunzarov, I; Butterworth, J; Caines, H; Calderón de la Barca Sánchez, M; Campbell, J M; Cebra, D; Chakaberia, I; Chaloupka, P; Chang, Z; Chattopadhyay, S; Chen, X; Chen, J H; Cheng, J; Cherney, M; Christie, W; Contin, G; Crawford, H J; Das, S; De Silva, L C; Debbe, R R; Dedovich, T G; Deng, J; Derevschikov, A A; di Ruzza, B; Didenko, L; Dilks, C; Dong, X; Drachenberg, J L; Draper, J E; Du, C M; Dunkelberger, L E; Dunlop, J C; Efimov, L G; Engelage, J; Eppley, G; Esha, R; Evdokimov, O; Eyser, O; Fatemi, R; Fazio, S; Federic, P; Fedorisin, J; Feng, Z; Filip, P; Fisyak, Y; Flores, C E; Fulek, L; Gagliardi, C A; Garand, D; Geurts, F; Gibson, A; Girard, M; Greiner, L; Grosnick, D; Gunarathne, D S; Guo, Y; Gupta, A; Gupta, S; Guryn, W; Hamad, A; Hamed, A; Haque, R; Harris, J W; He, L; Heppelmann, S; Heppelmann, S; Hirsch, A; Hoffmann, G W; Hofman, D J; Horvat, S; Huang, X; Huang, H Z; Huang, B; Huang, T; Huck, P; Humanic, T J; Igo, G; Jacobs, W W; Jang, H; Jentsch, A; Jia, J; Jiang, K; Judd, E G; Kabana, S; Kalinkin, D; Kang, K; Kauder, K; Ke, H W; Keane, D; Kechechyan, A; Khan, Z H; Kikoła, D P; Kisel, I; Kisiel, A; Kochenda, L; Koetke, D D; Kosarzewski, L K; Kraishan, A F; Kravtsov, P; Krueger, K; Kumar, L; Lamont, M A C; Landgraf, J M; Landry, K D; Lauret, J; Lebedev, A; Lednicky, R; Lee, J H; Li, C; Li, Y; Li, W; Li, X; Li, X; Lin, T; Lisa, M A; Liu, F; Ljubicic, T; Llope, W J; Lomnitz, M; Longacre, R S; Luo, X; Ma, R; Ma, L; Ma, G L; Ma, Y G; Magdy, N; Majka, R; Manion, A; Margetis, S; Markert, C; McDonald, D; Meehan, K; Mei, J C; Minaev, N G; Mioduszewski, S; Mishra, D; Mohanty, B; Mondal, M M; Morozov, D A; Mustafa, M K; Nandi, B K; Nasim, Md; Nayak, T K; Nigmatkulov, G; Niida, T; Nogach, L V; Noh, S Y; Novak, J; Nurushev, S B; Odyniec, G; Ogawa, A; Oh, K; Okorokov, V A; Olvitt, D; Page, B S; Pak, R; Pan, Y X; Pandit, Y; Panebratsev, Y; Pawlik, B; Pei, H; Perkins, C; Pile, P; Pluta, J; Poniatowska, K; Porter, J; Posik, M; Poskanzer, A M; Pruthi, N K; Putschke, J; Qiu, H; Quintero, A; Ramachandran, S; Raniwala, R; Raniwala, S; Ray, R L; Ritter, H G; Roberts, J B; Rogachevskiy, O V; Romero, J L; Roy, A; Ruan, L; Rusnak, J; Rusnakova, O; Sahoo, N R; Sahu, P K; Sakrejda, I; Salur, S; Sandweiss, J; Sarkar, A; Schambach, J; Scharenberg, R P; Schmah, A M; Schmidke, W B; Schmitz, N; Seger, J; Seyboth, P; Shah, N; Shahaliev, E; Shanmuganathan, P V; Shao, M; Sharma, M K; Sharma, B; Shen, W Q; Shi, Z; Shi, S S; Shou, Q Y; Sichtermann, E P; Sikora, R; Simko, M; Singha, S; Skoby, M J; Smirnov, D; Smirnov, N; Solyst, W; Song, L; Sorensen, P; Spinka, H M; Srivastava, B; Stanislaus, T D S; Stepanov, M; Stock, R; Strikhanov, M; Stringfellow, B; Sumbera, M; Summa, B; Sun, Y; Sun, Z; Sun, X M; Surrow, B; Svirida, D N; Tang, A H; Tang, Z; Tarnowsky, T; Tawfik, A; Thäder, J; Thomas, J H; Timmins, A R; Tlusty, D; Todoroki, T; Tokarev, M; Trentalange, S; Tribble, R E; Tribedy, P; Tripathy, S K; Tsai, O D; Ullrich, T; Underwood, D G; Upsal, I; Van Buren, G; van Nieuwenhuizen, G; Vandenbroucke, M; Varma, R; Vasiliev, A N; Vertesi, R; Videbæk, F; Vokal, S; Voloshin, S A; Vossen, A; Wang, J S; Wang, Y; Wang, F; Wang, Y; Wang, H; Wang, G; Webb, J C; Webb, G; Wen, L; Westfall, G D; Wieman, H; Wissink, S W; Witt, R; Wu, Y; Xiao, Z G; Xie, X; Xie, W; Xin, K; Xu, N; Xu, Y F; Xu, Z; Xu, Q H; Xu, J; Xu, H; Yang, Q; Yang, Y; Yang, S; Yang, Y; Yang, C; Yang, Y; Ye, Z; Ye, Z; Yepes, P; Yi, L; Yip, K; Yoo, I-K; Yu, N; Zbroszczyk, H; Zha, W; Zhang, S; Zhang, Z; Zhang, S; Zhang, J B; Zhang, Y; Zhang, J; Zhang, J; Zhang, X P; Zhao, J; Zhong, C; Zhou, L; Zhu, X; Zoulkarneeva, Y; Zyzak, M
2016-04-01
We present the measurement of the transverse single-spin asymmetry of weak boson production in transversely polarized proton-proton collisions at sqrt[s]=500 GeV by the STAR experiment at RHIC. The measured observable is sensitive to the Sivers function, one of the transverse-momentum-dependent parton distribution functions, which is predicted to have the opposite sign in proton-proton collisions from that observed in deep inelastic lepton-proton scattering. These data provide the first experimental investigation of the nonuniversality of the Sivers function, fundamental to our understanding of QCD.
Directory of Open Access Journals (Sweden)
Colin Barschel
2015-01-01
Full Text Available We discuss the application of an open storage cell as gas target for a proposed LHC fixed-target experiment AFTER@LHC. The target provides a high areal density at minimum gas input, which may be polarized 1H, 2H, or 3He gas or heavy inert gases in a wide mass range. For the study of single-spin asymmetries in pp interaction, luminosities of nearly 1033/cm2 s can be produced with existing techniques.
Optimal Control Structure For Variable Speed Wind Power System
Directory of Open Access Journals (Sweden)
Emil CEANGA
2002-12-01
Full Text Available This paper presents an optimal control structure for variable speed, fixed pitch wind turbine. The control objective results from the optimization criterion that includes two contradictory demands: maximization of the energy captured from the wind and minimization of the damage caused by mechanical fatigue. We admit, as a modeling assumption, that wind speed has two components: a slowly varying component, named seasonal and a rapidly varying component, named turbulence. Hence, two control structures, which should function simultaneously, are identified in the optimal control problem.The first optimization structure aims to maximize the wind turbine energetic efficiency by maintaining operational point on optimal regime characteristics (ORC. According to the slowly varying seasonal component of wind speed, a control loop adjusts system operating point in order to maintain it on ORC. In the second optimization structure, the system is considered to be operating on “static” optimal point assured by the above mentioned control loop, with the turbulence component being the input variable. The second control loop aims dynamic optimization that implies the minimization of the tip speed ratio variations around its optimal value, while minimizing the torque variations, thus the mechanical stress. Mathematically, this objective is defined as an integral criterion, belonging to linear quadratic optimization.
Optimal Control Strategies for Constrained Relative Orbits
National Research Council Canada - National Science Library
Irvin , Jr, David J
2007-01-01
.... This research finds optimal trajectories, produced with discrete-thrusts, that minimize fuel spent per unit time and stay within the user-defened volume, thus providing a practical hover capability...
Nonlinear model predictive control based on collective neurodynamic optimization.
Yan, Zheng; Wang, Jun
2015-04-01
In general, nonlinear model predictive control (NMPC) entails solving a sequential global optimization problem with a nonconvex cost function or constraints. This paper presents a novel collective neurodynamic optimization approach to NMPC without linearization. Utilizing a group of recurrent neural networks (RNNs), the proposed collective neurodynamic optimization approach searches for optimal solutions to global optimization problems by emulating brainstorming. Each RNN is guaranteed to converge to a candidate solution by performing constrained local search. By exchanging information and iteratively improving the starting and restarting points of each RNN using the information of local and global best known solutions in a framework of particle swarm optimization, the group of RNNs is able to reach global optimal solutions to global optimization problems. The essence of the proposed collective neurodynamic optimization approach lies in the integration of capabilities of global search and precise local search. The simulation results of many cases are discussed to substantiate the effectiveness and the characteristics of the proposed approach.
Computational Biomathematics: Toward Optimal Control of Complex Biological Systems
2016-09-26
Pareto optimization. In general, genetic algorithms returned the best results in most cases. Pareto optimization is a means of multi-objective...optimization, wherein one does not have to determine a cost function ahead of time, but rather only specify the variables of interest. For example, if we...wish to determine a controller that reduces cost and maximizes efficiency, Pareto optimization allows us to conduct a search without specifying
Nakagawa, I.
2016-08-01
Large single spin asymmetries in very forward neutron production seen using the PHENIX zero-degree calorimeters are a long established feature of transversely polarized proton-proton collisions at RHIC. Neutron production near zero degrees is well described by the one-pion exchange framework. The absorptive correction to the OPE generates the asymmetry as a consequence of a phase shift between the spin flip and non-spin flip amplitudes. However, the amplitude predicted by the OPE is too small to explain the large observed asymmetries. A model introducing interference of pion and a 1-Reggeon exchanges has been successful in reproducing the experimental data. During the RHIC experiment in year 2015, RHIC delivered polarized proton collisions with Au and Al nuclei for the first time, enabling the exploration of the mechanism of transverse single-spin asymmetries with nuclear collisions. The observed asymmetries showed surprisingly strong A-dependence in the inclusive forward neutron production, while the existing framework which was successfull in p+p only predicts moderate A- dependence. Thus the observed data are absolutely unexpected and unpredicted. In this report, experimental and theoretical efforts are discussed to disentangle the observed A-dependence using somewhat semi-inclusive type measurements and Monte-Carlo study, respectively.
Optimal control of stochastic difference Volterra equations an introduction
Shaikhet, Leonid
2015-01-01
This book showcases a subclass of hereditary systems, that is, systems with behaviour depending not only on their current state but also on their past history; it is an introduction to the mathematical theory of optimal control for stochastic difference Volterra equations of neutral type. As such, it will be of much interest to researchers interested in modelling processes in physics, mechanics, automatic regulation, economics and finance, biology, sociology and medicine for all of which such equations are very popular tools. The text deals with problems of optimal control such as meeting given performance criteria, and stabilization, extending them to neutral stochastic difference Volterra equations. In particular, it contrasts the difference analogues of solutions to optimal control and optimal estimation problems for stochastic integral Volterra equations with optimal solutions for corresponding problems in stochastic difference Volterra equations. Optimal Control of Stochastic Difference Volterra Equation...
Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System
Qiang Gao; Jilin Chen; Li Wang; Shiqing Xu; Yuanlong Hou
2013-01-01
Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution...
PID control for chaotic synchronization using particle swarm optimization
Energy Technology Data Exchange (ETDEWEB)
Chang, W.-D. [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)], E-mail: wdchang@mail.stu.edu.tw
2009-01-30
In this paper, we attempt to use the proportional-integral-derivative (PID) controller to achieve the chaos synchronization for delayed discrete chaotic systems. Three PID control gains can be optimally determined by means of using a novel optimization algorithm, called the particle swarm optimization (PSO). The algorithm is motivated from the organism behavior of fish schooling and bird flocking, and involves the social psychology principles in socio-cognition human agents and evolutionary computations. It has a good numerical convergence for solving optimization problem. To show the validity of the PSO-based PID control for chaos synchronization, several cases with different initial populations are considered and some simulation results are shown.
Optimal Control for a Class of Chaotic Systems
Directory of Open Access Journals (Sweden)
Jianxiong Zhang
2012-01-01
Full Text Available This paper proposes the optimal control methods for a class of chaotic systems via state feedback. By converting the chaotic systems to the form of uncertain piecewise linear systems, we can obtain the optimal controller minimizing the upper bound on cost function by virtue of the robust optimal control method of piecewise linear systems, which is cast as an optimization problem under constraints of bilinear matrix inequalities (BMIs. In addition, the lower bound on cost function can be achieved by solving a semidefinite programming (SDP. Finally, numerical examples are given to illustrate the results.
Optimal Control with Time Delays via the Penalty Method
Directory of Open Access Journals (Sweden)
Mohammed Benharrat
2014-01-01
Full Text Available We prove necessary optimality conditions of Euler-Lagrange type for a problem of the calculus of variations with time delays, where the delay in the unknown function is different from the delay in its derivative. Then, a more general optimal control problem with time delays is considered. Main result gives a convergence theorem, allowing us to obtain a solution to the delayed optimal control problem by considering a sequence of delayed problems of the calculus of variations.
Optimal Vibration Control for Tracked Vehicle Suspension Systems
Directory of Open Access Journals (Sweden)
Yan-Jun Liang
2013-01-01
Full Text Available Technique of optimal vibration control with exponential decay rate and simulation for vehicle active suspension systems is developed. Mechanical model and dynamic system for a class of tracked vehicle suspension vibration control is established and the corresponding system of state space form is described. In order to prolong the working life of suspension system and improve ride comfort, based on the active suspension vibration control devices and using optimal control approach, an optimal vibration controller with exponential decay rate is designed. Numerical simulations are carried out, and the control effects of the ordinary optimal controller and the proposed controller are compared. Numerical simulation results illustrate the effectiveness of the proposed technique.
Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies
Carmona Morales, D.; Jimenez-Hornero, J. E.; Vazquez, F.; Morilla, F.
2012-01-01
In this paper, an optimal tuning tool is presented for control structures based on multivariable proportional-integral-derivative (PID) control, using genetic algorithms as an alternative to traditional optimization algorithms. From an educational point of view, this tool provides students with the necessary means to consolidate their knowledge on…
A hybrid iterative scheme for optimal control problems governed by ...
African Journals Online (AJOL)
MRT
obtaining approximate solutions of optimal control problems governed by some Fredholm integral equations. By some numerical ... Trace of numerical approaches in optimal control problems can be found in many applications and academic literatures. ...... Progress In Electromagnetics Research 78: 361–376. Ghasemi, M.
Optimization and Control of Electric Power Systems
Energy Technology Data Exchange (ETDEWEB)
Lesieutre, Bernard C. [Univ. of Wisconsin, Madison, WI (United States); Molzahn, Daniel K. [Univ. of Wisconsin, Madison, WI (United States)
2014-10-17
The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.
Optimal Control with Partial Information for Stochastic Volterra Equations
Directory of Open Access Journals (Sweden)
Bernt øksendal
2010-01-01
Full Text Available In the first part of the paper we obtain existence and characterizations of an optimal control for a linear quadratic control problem of linear stochastic Volterra equations. In the second part, using the Malliavin calculus approach, we deduce a general maximum principle for optimal control of general stochastic Volterra equations. The result is applied to solve some stochastic control problem for some stochastic delay equations.
Intrinsic Optimal Control for Mechanical Systems on Lie Group
Directory of Open Access Journals (Sweden)
Chao Liu
2017-01-01
Full Text Available The intrinsic infinite horizon optimal control problem of mechanical systems on Lie group is investigated. The geometric optimal control problem is built on the intrinsic coordinate-free model, which is provided with Levi-Civita connection. In order to obtain an analytical solution of the optimal problem in the geometric viewpoint, a simplified nominal system on Lie group with an extra feedback loop is presented. With geodesic distance and Riemann metric on Lie group integrated into the cost function, a dynamic programming approach is employed and an analytical solution of the optimal problem on Lie group is obtained via the Hamilton-Jacobi-Bellman equation. For a special case on SO(3, the intrinsic optimal control method is used for a quadrotor rotation control problem and simulation results are provided to show the control performance.
Discrete-time optimal control and games on large intervals
Zaslavski, Alexander J
2017-01-01
Devoted to the structure of approximate solutions of discrete-time optimal control problems and approximate solutions of dynamic discrete-time two-player zero-sum games, this book presents results on properties of approximate solutions in an interval that is independent lengthwise, for all sufficiently large intervals. Results concerning the so-called turnpike property of optimal control problems and zero-sum games in the regions close to the endpoints of the time intervals are the main focus of this book. The description of the structure of approximate solutions on sufficiently large intervals and its stability will interest graduate students and mathematicians in optimal control and game theory, engineering, and economics. This book begins with a brief overview and moves on to analyze the structure of approximate solutions of autonomous nonconcave discrete-time optimal control Lagrange problems.Next the structures of approximate solutions of autonomous discrete-time optimal control problems that are discret...
Development and Optimization of controlled drug release ...
African Journals Online (AJOL)
Formulation variables like type of osmotic agent (sodium chloride, mannitol, lactose), level of pore former and plasticizer and percent weight gain were found to affect the drug release from the developed formulations. The release performance of diclofenac sodium from the optimized formulations was studied over a period of ...
Energy Technology Data Exchange (ETDEWEB)
Waidyawansa, Dinayadura Buddhini [Ohio Univ., Athens, OH (United States)
2013-08-01
The beam normal single spin asymmetry generated in the scattering of transversely polarized electrons from unpolarized nucleons is an observable of the imaginary part of the two-photon exchange process. Moreover, it is a potential source of false asymmetry in parity violating electron scattering experiments. The Q{sub weak} experiment uses parity violating electron scattering to make a direct measurement of the weak charge of the proton. The targeted 4% measurement of the weak charge of the proton probes for parity violating new physics beyond the Standard Model. The beam normal single spin asymmetry at Q{sub weak} kinematics is at least three orders of magnitude larger than 5 ppb precision of the parity violating asymmetry. To better understand this parity conserving background, the Q{sub weak} Collaboration has performed elastic scattering measurements with fully transversely polarized electron beam on the proton and aluminum. This dissertation presents the analysis of the 3% measurement (1.3% statistical and 2.6% systematic) of beam normal single spin asymmetry in electronproton scattering at a Q2 of 0.025 (GeV/c)2. It is the most precise existing measurement of beam normal single spin asymmetry available at the time. A measurement of this precision helps to improve the theoretical models on beam normal single spin asymmetry and thereby our understanding of the doubly virtual Compton scattering process.
Optimization of nonlinear controller with an enhanced biogeography approach
Directory of Open Access Journals (Sweden)
Mohammed Salem
2014-07-01
Full Text Available This paper is dedicated to the optimization of nonlinear controllers basing of an enhanced Biogeography Based Optimization (BBO approach. Indeed, The BBO is combined to a predator and prey model where several predators are used with introduction of a modified migration operator to increase the diversification along the optimization process so as to avoid local optima and reach the optimal solution quickly. The proposed approach is used in tuning the gains of PID controller for nonlinear systems. Simulations are carried out over a Mass spring damper and an inverted pendulum and has given remarkable results when compared to genetic algorithm and BBO.
Optimal Control and Forecasting of Complex Dynamical Systems
Grigorenko, Ilya
2006-01-01
This important book reviews applications of optimization and optimal control theory to modern problems in physics, nano-science and finance. The theory presented here can be efficiently applied to various problems, such as the determination of the optimal shape of a laser pulse to induce certain excitations in quantum systems, the optimal design of nanostructured materials and devices, or the control of chaotic systems and minimization of the forecast error for a given forecasting model (for example, artificial neural networks). Starting from a brief review of the history of variational calcul
Simulation and Optimization of Wind Farm Controllers
DEFF Research Database (Denmark)
Soerensen, Poul; Hansen, Anca D.; Thomsen, Kenneth
2004-01-01
This paper describes the development of wind farm controllers for different types of wind farms. The overall aim of the wind farm controllers is to enable the wind farms to contribute to the control of voltage and frequency in the power system. Still, the controllers should meet the conventional...... aims of wind turbine controllers, which are first of all to maximise the production and to minimize the structural loads and lifetime consumption on the wind turbine components. To meet these aims, the idea is that the wind farm controllers use wind speed predictions....
5th International Conference on Optimization and Control with Applications
Teo, Kok; Zhang, Yi
2014-01-01
This book presents advances in state-of-the-art solution methods and their applications to real life practical problems in optimization, control and operations research. Contributions from world-class experts in the field are collated here in two parts, dealing first with optimization and control theory and then with techniques and applications. Topics covered in the first part include control theory on infinite dimensional Banach spaces, history-dependent inclusion and linear programming complexity theory. Chapters also explore the use of approximations of Hamilton-Jacobi-Bellman inequality for solving periodic optimization problems and look at multi-objective semi-infinite optimization problems, and production planning problems. In the second part, the authors address techniques and applications of optimization and control in a variety of disciplines, such as chaos synchronization, facial expression recognition and dynamic input-output economic models. Other applications considered here include image retr...
Optimal control of switched systems arising in fermentation processes
Liu, Chongyang
2014-01-01
The book presents, in a systematic manner, the optimal controls under different mathematical models in fermentation processes. Variant mathematical models – i.e., those for multistage systems; switched autonomous systems; time-dependent and state-dependent switched systems; multistage time-delay systems and switched time-delay systems – for fed-batch fermentation processes are proposed and the theories and algorithms of their optimal control problems are studied and discussed. By putting forward novel methods and innovative tools, the book provides a state-of-the-art and comprehensive systematic treatment of optimal control problems arising in fermentation processes. It not only develops nonlinear dynamical system, optimal control theory and optimization algorithms, but can also help to increase productivity and provide valuable reference material on commercial fermentation processes.
Multiobjective Optimization of PID Controller of PMSM
National Research Council Canada - National Science Library
Xu, Qingyang; Zhang, Chengjin; Zhang, Li; Wang, Chaoyang
2014-01-01
PID controller is used in most of the current-speed closed-loop control of permanent magnet synchronous motors (PMSM) servo system. However, [subscript]Kp[/subscript] , [subscript]Ki[/subscript] , and [subscript]Kd[/subscript...
Optimal resonant control of flexible structures
DEFF Research Database (Denmark)
Krenk, Steen; Høgsberg, Jan Becker
2009-01-01
When introducing a resonant controller for a particular vibration mode in a structure this mode splits into two. A design principle is developed for resonant control based oil equal damping of these two modes. First the design principle is developed for control of a system with a single degree of...
Finding optimal ventilation control for highway tunnels
Ferki, Lukáš; Meinsma, Gjerrit
2007-01-01
A control scheme for highway tunnels is designed based on a static model of the highway tunnel. The controller is designed to keep the exhaust levels inside the tunnel below given limits. The control is then simulated on a dynamical model of a highway tunnel.
CONTROL OPTIMAL SOBRE ESPACIOS HOMOGENEOS Y APLICACIONES.
RODRIGUEZ, JULIO CESAR
2009-01-01
Esta investigación trata problemas (lerivados (le la Teoría (le Coiitrol y Pro- (esos de Control Optinial. En esta tesis nos concentraremos especialmente sol)re la clase (le sistemiia.s (le control l)ilineal (SCB) y sistemas de control afín (SCA). Los sis 192p.
Scalable algorithms for optimal control of stochastic PDEs
Ghattas, Omar
2016-01-07
We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.
Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO
Directory of Open Access Journals (Sweden)
Adel Taieb
2017-01-01
Full Text Available This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO Fuzzy Optimal Model Predictive Control (FOMPC using the Adaptive Particle Swarm Optimization (APSO algorithm. The aim of this proposed control, called FOMPC-APSO, is to develop an efficient algorithm that is able to have good performance by guaranteeing a minimal control. This is done by determining the optimal weights of the objective function. Our method is considered an optimization problem based on the APSO algorithm. The MIMO system to be controlled is modeled by a Takagi-Sugeno (TS fuzzy system whose parameters are identified using weighted recursive least squares method. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, Continuous Stirred Tank Reactor (CSTR and Tank system, where the proposed approach provides better performances compared with other methods.
Discrete-time inverse optimal control for nonlinear systems
Sanchez, Edgar N
2013-01-01
Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and trajectory tracking of discrete-time nonlinear systems. This avoids the need to solve the associated Hamilton-Jacobi-Bellman equation and minimizes a cost functional, resulting in a more efficient controller. Design More Efficient Controllers for Stabilization and Trajectory Tracking of Discrete-Time Nonlinear Systems The book presents two approaches for controller synthesis: the first based on passivity theory and the second on a control Lyapunov function (CLF). Th
Structured controllers for uncertain systems a stochastic optimization approach
Toscano, Rosario
2013-01-01
Structured Controllers for Uncertain Systems focuses on the development of easy-to-use design strategies for robust low-order or fixed-structure controllers (particularly the industrially ubiquitous PID controller). These strategies are based on a recently-developed stochastic optimization method termed the "Heuristic Kalman Algorithm" (HKA) the use of which results in a simplified methodology that enables the solution of the structured control problem without a profusion of user-defined parameters. An overview of the main stochastic methods employable in the context of continuous non-convex optimization problems is also provided and various optimization criteria for the design of a structured controller are considered; H∞, H2, and mixed H2/H∞ each merits a chapter to itself. Time-domain-performance specifications can be easily incorporated in the design. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technolo...
IMPORTANCE OF KINETIC MEASURES IN TRAJECTORY PREDICTION WITH OPTIMAL CONTROL
Directory of Open Access Journals (Sweden)
Ömer GÜNDOĞDU
2001-02-01
Full Text Available A two-dimensional sagittally symmetric human-body model was established to simulate an optimal trajectory for manual material handling tasks. Nonlinear control techniques and genetic algorithms were utilized in the optimizations to explore optimal lifting patterns. The simulation results were then compared with the experimental data. Since the kinetic measures such as joint reactions and moments are vital parameters in injury determination, the importance of comparing kinetic measures rather than kinematical ones was emphasized.
Optimal control of electrostatic self-assembly of binary monolayers
Energy Technology Data Exchange (ETDEWEB)
Shestopalov, N V; Henkelman, G; Powell, C T; Rodin, G J [Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX 78712 (United States)], E-mail: nikolay@ices.utexas.edu
2009-05-15
A simple macroscopic model is used to determine an optimal annealing schedule for self-assembly of binary monolayers of spherical particles. The model assumes that a single rate-controlling mechanism is responsible for the formation of spatially ordered structures and that its rate follows an Arrhenius form. The optimal schedule is derived in an analytical form using classical optimization methods. Molecular dynamics simulations of the self-assembly demonstrate that the proposed schedule outperforms other schedules commonly used for simulated annealing.
Time dependent optimal switching controls in online selling models
Energy Technology Data Exchange (ETDEWEB)
Bradonjic, Milan [Los Alamos National Laboratory; Cohen, Albert [MICHIGAN STATE UNIV
2010-01-01
We present a method to incorporate dishonesty in online selling via a stochastic optimal control problem. In our framework, the seller wishes to maximize her average wealth level W at a fixed time T of her choosing. The corresponding Hamilton-Jacobi-Bellmann (HJB) equation is analyzed for a basic case. For more general models, the admissible control set is restricted to a jump process that switches between extreme values. We propose a new approach, where the optimal control problem is reduced to a multivariable optimization problem.
ON THE OPTIMAL CONTROL OF A PROBLEM OF ENVIRONMENTAL POLLUTION
Directory of Open Access Journals (Sweden)
José Dávalos Chuquipoma
2016-06-01
Full Text Available This article is studied the optimal control of distributed parameter systems applied to an environmental pollution problem. The model consists of a differential equation partial parabolic modeling of a pollutant transport in a fluid. The model is considered the speed with which the pollutant spreads in the environment and degradation that suffers the contaminant by the presence of a factor biological inhibitor, which breaks the contaminant at a rate that is not dependent on space and time. Using the method of Lagrange multipliers is possible to prove the existence solving the problem of control and obtaining optimality conditions for optimal control.
Engineering applications of discrete-time optimal control
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Ravn, Hans V.
1990-01-01
Many problems of design and operation of engineering systems can be formulated as optimal control problems where time has been discretisized. This is also true even if 'time' is not involved in the formulation of the problem, but rather another one-dimensional parameter. This paper gives a review...... of some well-known and new results in discrete time optimal control methods applicable to practical problem solving within engineering. Emphasis is placed on dynamic programming, the classical maximum principle and generalized versions of the maximum principle for optimal control of discrete time systems...
Galerkin approximations of nonlinear optimal control problems in Hilbert spaces
Directory of Open Access Journals (Sweden)
Mickael D. Chekroun
2017-07-01
Full Text Available Nonlinear optimal control problems in Hilbert spaces are considered for which we derive approximation theorems for Galerkin approximations. Approximation theorems are available in the literature. The originality of our approach relies on the identification of a set of natural assumptions that allows us to deal with a broad class of nonlinear evolution equations and cost functionals for which we derive convergence of the value functions associated with the optimal control problem of the Galerkin approximations. This convergence result holds for a broad class of nonlinear control strategies as well. In particular, we show that the framework applies to the optimal control of semilinear heat equations posed on a general compact manifold without boundary. The framework is then shown to apply to geoengineering and mitigation of greenhouse gas emissions formulated here in terms of optimal control of energy balance climate models posed on the sphere $\\mathbb{S}^2$.
Wang, Z.; Turteltaub, S.R.; Abdalla, M.M.
2017-01-01
This work is concerned with the development of a framework to solve shape optimization problems for transient heat conduction problems within the context of isogeometric analysis (IGA). A general objective functional is used to accommodate both shape optimization and passive control problems
The Sivers effect and the Single Spin Asymmetry A_N in p(transv. pol.) p --> h X processes
Energy Technology Data Exchange (ETDEWEB)
Anselmino, Mauro [TORINO, INFN-TORINO; Boglione, Mariaelena [TORINO, INFN-TORINO; D& #x27; Alesio, Umberto [INFN Cagliari; Melis, Stefano [TORINO, INFN-TORINO; Murgia, Francesco [INFN Cagliari; Prokudin, Alexei [JLAB
2013-09-01
The single spin asymmetry A_N, for large P_T single inclusive particle production in p(transv. pol.) p collisions, is considered within a generalised parton model and a transverse momentum dependent factorisation scheme. The focus is on the Sivers effect and the study of its potential contribution to A_N, based on a careful analysis of the Sivers functions extracted from azimuthal asymmetries in semi-inclusive deep inelastic scattering processes. It is found that such Sivers functions could explain most features of the A_N data, including some recent STAR results which show the persistence of a non zero A_N up to surprisingly large P_T values.
Tsunoda, M
2002-01-01
The origin of the magnetic anisotropy of the antiferromagnetic (AF) layer and the role of it in the magnetization process of exchange coupled ferromagnetic/antiferromagnetic bilayers are discussed. Through the magnetic torque analysis of a pseudo-single crystalline Ni-Fe/Mn-Ni bilayer and a polycrystalline Ni-Fe/Mn-Ir bilayer, the magnetocrystalline anisotropy of the antiferromagnet is strongly suggested to be the origin of the magnetic anisotropy of the antiferromagnetic (AF) layer. The single spin ensemble model is newly introduced for polycrystalline bilayers, taking into account the two-dimensionally random distribution of the magnetic anisotropy axes of the AF grains. The mechanism of a well-known experimental fact, the reversible induction of the exchange anisotropy along desirable directions by field cooling procedure, is successfully elucidated with the new model.
Energy Technology Data Exchange (ETDEWEB)
Anselmino, Mauro; Mariaelena, Boglione; D' Alesio, Umberto; Melis, Stefano; Murgia, Francesco; Prokudin, Alexey [JLAB
2014-06-01
Some estimates for the transverse Single Spin Asymmetry, A_N, in the inclusive processes l p(transv. Pol.) --> h X, given in a previous paper, are expanded and compared with new experimental data. The predictions are based on the Sivers distributions and the Collins fragmentation functions which fit the azimuthal asymmetries measured in Semi-Inclusive Deep Inelastic Scattering (SIDIS) processes (l p(transv. Pol.) --> l' h X). The factorisation in terms of Transverse Momentum Dependent distribution and fragmentation functions (TMD factorisation) -- i.e., the theoretical framework in which SIDIS azimuthal asymmetries are analysed -- is assumed to hold also for the inclusive process l p --> h X at large P_T. The values of A_N thus obtained agree in sign and shape with the data. Some predictions are given for future experiments.
Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
Ünal, Muhammet; Topuz, Vedat; Erdal, Hasan
2013-01-01
Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books available on these subjects only provide a cursory discussion of theory, the present book gives special emphasis to the theoretical background that is behind these algorithms and their applications. Moreover, this book introduces a novel real time control algorithm, that uses genetic algorithm and ant colony optimization algorithms for optimizing PID controller parameters. In general, the present book represents a solid survey on artificial neural networks, genetic algorithms and the ant colony optimization algorithm and introduces novel practical elements related to the application of these methods to process system control.
Optimal Thyristor Control Series Capacitor Neuro-Controller for Damping Oscillations
M. Magaji; M. W. Mustafa
2009-01-01
This study applies a neural-network-based optimal TCSC controller for damping oscillations. Optimal neural network controller is related to model-reference adaptive control, the network controller is developed based on the recursive “pseudo-linear regression. Problem statement: The optimal NN controller is designed to damp out the low frequency local and inter-area oscillations of the large power system. Approach: Two multilayer-perceptron neural networks are used in the design-the iden...
Closed Loop Optimal Control of a Stewart Platform Using an Optimal Feedback Linearization Method
Directory of Open Access Journals (Sweden)
Hami Tourajizadeh
2016-06-01
Full Text Available Optimal control of a Stewart robot is performed in this paper using a sequential optimal feedback linearization method considering the jack dynamics. One of the most important applications of a Stewart platform is tracking a machine along a specific path or from a defined point to another point. However, the control procedure of these robots is more challenging than that of serial robots since their dynamics are extremely complicated and non-linear. In addition, saving energy, together with achieving the desired accuracy, is one of the most desirable objectives. In this paper, a proper non-linear optimal control is employed to gain the maximum accuracy by applying the minimum force distribution to the jacks. Dynamics of the jacks are included in this paper to achieve more accurate results. Optimal control is performed for a six-DOF hexapod robot and its accuracy is increased using a sequential feedback linearization method, while its energy optimization is realized using the LQR method for the linearized system. The efficiency of the proposed optimal control is verified by simulating a six-DOF hexapod robot in MATLAB, and its related results are gained and analysed. The actual position of the end-effector, its velocity, the initial and final forces of the jacks and the length and velocity of the jacks are obtained and then compared with open loop and non-optimized systems; analytical comparisons show the efficiency of the proposed methods.
Directory of Open Access Journals (Sweden)
Carlos Villaseñor
2017-12-01
Full Text Available Nowadays, there are several meta-heuristics algorithms which offer solutions for multi-variate optimization problems. These algorithms use a population of candidate solutions which explore the search space, where the leadership plays a big role in the exploration-exploitation equilibrium. In this work, we propose to use a Germinal Center Optimization algorithm (GCO which implements temporal leadership through modeling a non-uniform competitive-based distribution for particle selection. GCO is used to find an optimal set of parameters for a neural inverse optimal control applied to all-terrain tracked robot. In the Neural Inverse Optimal Control (NIOC scheme, a neural identifier, based on Recurrent High Orden Neural Network (RHONN trained with an extended kalman filter algorithm, is used to obtain a model of the system, then, a control law is design using such model with the inverse optimal control approach. The RHONN identifier is developed without knowledge of the plant model or its parameters, on the other hand, the inverse optimal control is designed for tracking velocity references. Applicability of the proposed scheme is illustrated using simulations results as well as real-time experimental results with an all-terrain tracked robot.
Evolutionary Computing for Intelligent Power System Optimization and Control
DEFF Research Database (Denmark)
This new book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization the...... theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems....
Patient related factors for optimal blood pressure control in patients ...
African Journals Online (AJOL)
Background: Patient related factors hindering optimal blood pressure (BP) control in patients with hypertension are unclear. Objectives: To investigate the barriers to optimal hypertension management. Methods: A survey on the awareness and management of hypertension was conducted in 556 patients (365 males, mean ...
Optimal Selective Harmonic Control for Power Harmonics Mitigation
DEFF Research Database (Denmark)
Zhou, Keliang; Yang, Yongheng; Blaabjerg, Frede
2015-01-01
of power harmonics. The proposed optimal SHC is of hybrid structure: all recursive SHC modules with weighted gains are connected in parallel. It bridges the real “nk+-m order RC” and the complex “parallel structure RC”. Compared to other IMP based control solutions, it offers an optimal trade-off among...
Design of optimal laser pulses to control molecular rovibrational ...
Indian Academy of Sciences (India)
Abstract. Optimal control theory in combination with time-dependent quantum dynamics is employed to design laser pulses which can perform selective vibrational and rotational excitations in a heteronuclear diatomic system. We have applied the conjugate gradient method for the constrained optimization of a suit-.
Design of optimal laser pulses to control molecular rovibrational ...
Indian Academy of Sciences (India)
Optimal control theory in combination with time-dependent quantum dynamics is employed to design laser pulses which can perform selective vibrational and rotational excitations in a heteronuclear diatomic system. We have applied the conjugate gradient method for the constrained optimization of a suitably designed ...
Use of reduced-order models in well control optimization
Jansen, J.D.; Durlofsky, L.J.
2016-01-01
Many aspects of reservoir management can be expected to benefit from the application of computational optimization procedures. The focus of this review paper is on well control optimization, which entails the determination of well settings, such as flow rates or bottom hole pressures, that maximize
Closed-Loop Optimal Control Implementations for Space Applications
2016-12-01
COVERED Master’s thesis , Jan-Dec 2016 4. TITLE AND SUBTITLE CLOSED-LOOP OPTIMAL CONTROL IMPLEMENTATIONS FOR SPACE APPLICATIONS 5. FUNDING NUMBERS... Mechanical and Aerospace Engineering iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT This thesis explores concepts for a closed-loop optimal...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release. Distribution is unlimited. CLOSED-LOOP
Control and Optimization Methods for Electric Smart Grids
Ilić, Marija
2012-01-01
Control and Optimization Methods for Electric Smart Grids brings together leading experts in power, control and communication systems,and consolidates some of the most promising recent research in smart grid modeling,control and optimization in hopes of laying the foundation for future advances in this critical field of study. The contents comprise eighteen essays addressing wide varieties of control-theoretic problems for tomorrow’s power grid. Topics covered include: Control architectures for power system networks with large-scale penetration of renewable energy and plug-in vehicles Optimal demand response New modeling methods for electricity markets Control strategies for data centers Cyber-security Wide-area monitoring and control using synchronized phasor measurements. The authors present theoretical results supported by illustrative examples and practical case studies, making the material comprehensible to a wide audience. The results reflect the exponential transformation that today’s grid is going...
Analysis and Design of Software-Based Optimal PID Controllers
Garpinger, Olof
2015-01-01
A large process industry can have somewhere between five hundred and five thousand control loops, and PID controllers are used in 90–97% of the cases. It is well-known that only 20–30% of the controllers in the process industry are tuned satisfactorily, but with the methods available today it is considered too time-consuming to optimize each single controller. This thesis presents tools for analysis and design of optimal PID controllers, and suggests when and how to use them efficiently. High...
Optimal design of distributed control and embedded systems
Çela, Arben; Li, Xu-Guang; Niculescu, Silviu-Iulian
2014-01-01
Optimal Design of Distributed Control and Embedded Systems focuses on the design of special control and scheduling algorithms based on system structural properties as well as on analysis of the influence of induced time-delay on systems performances. It treats the optimal design of distributed and embedded control systems (DCESs) with respect to communication and calculation-resource constraints, quantization aspects, and potential time-delays induced by the associated communication and calculation model. Particular emphasis is put on optimal control signal scheduling based on the system state. In order to render this complex optimization problem feasible in real time, a time decomposition is based on periodicity induced by the static scheduling is operated. The authors present a co-design approach which subsumes the synthesis of the optimal control laws and the generation of an optimal schedule of control signals on real-time networks as well as the execution of control tasks on a single processor. The a...
Optimal Inventory Control with Advance Supply Information
Directory of Open Access Journals (Sweden)
Marko Jaksic
2016-09-01
Full Text Available It has been shown in numerous situations that sharing information between the companies leads to improved performance of the supply chain. We study a positive lead time periodic-review inventory system of a retailer facing stochastic demand from his customer and stochastic limited supply capacity of the manufacturer supplying the products to him. The consequence of stochastic supply capacity is that the orders might not be delivered in full, and the exact size of the replenishment might not be known to the retailer. The manufacturer is willing to share the so-called advance supply information (ASI about the actual replenishment of the retailer's pipeline order with the retailer. ASI is provided at a certain time after the orders have been placed and the retailer can now use this information to decrease the uncertainty of the supply, and thus improve its inventory policy. For this model, we develop a dynamic programming formulation, and characterize the optimal ordering policy as a state-dependent base-stock policy. In addition, we show some properties of the base-stock level. While the optimal policy is highly complex, we obtain some additional insights by comparing it to the state-dependent myopic inventory policy. We conduct the numerical analysis to estimate the in uence of the system parameters on the value of ASI. While we show that the interaction between the parameters is relatively complex, the general insight is that due to increasing marginal returns, the majority of the benets are gained only in the case of full, or close to full, ASI visibility.
Performance investigation of multigrid optimization for DNS-based optimal control problems
Nita, Cornelia; Vandewalle, Stefan; Meyers, Johan
2016-11-01
Optimal control theory in Direct Numerical Simulation (DNS) or Large-Eddy Simulation (LES) of turbulent flow involves large computational cost and memory overhead for the optimization of the controls. In this context, the minimization of the cost functional is typically achieved by employing gradient-based iterative methods such as quasi-Newton, truncated Newton or non-linear conjugate gradient. In the current work, we investigate the multigrid optimization strategy (MGOpt) in order to speed up the convergence of the damped L-BFGS algorithm for DNS-based optimal control problems. The method consists in a hierarchy of optimization problems defined on different representation levels aiming to reduce the computational resources associated with the cost functional improvement on the finest level. We examine the MGOpt efficiency for the optimization of an internal volume force distribution with the goal of reducing the turbulent kinetic energy or increasing the energy extraction in a turbulent wall-bounded flow; problems that are respectively related to drag reduction in boundary layers, or energy extraction in large wind farms. Results indicate that in some cases the multigrid optimization method requires up to a factor two less DNS and adjoint DNS than single-grid damped L-BFGS. The authors acknowledge support from OPTEC (OPTimization in Engineering Center of Excellence, KU Leuven, Grant No PFV/10/002).
Using Chemicals to Optimize Conformance Control in Fractured Reservoirs
Energy Technology Data Exchange (ETDEWEB)
Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Wang, Ying; Kumar, Ananad; Wavrik, Kathryn
2001-10-29
This report describes work performed during the third and final year of the project, Using Chemicals to Optimize Conformance Control in Fractured Reservoirs. This research project had three objectives. The first objective was to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective was to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective was to develop procedures to optimize blocking agent placement in naturally fractured reservoirs.
Optimal Control Surface Layout for an Aeroservoelastic Wingbox
Stanford, Bret K.
2017-01-01
This paper demonstrates a technique for locating the optimal control surface layout of an aeroservoelastic Common Research Model wingbox, in the context of maneuver load alleviation and active utter suppression. The combinatorial actuator layout design is solved using ideas borrowed from topology optimization, where the effectiveness of a given control surface is tied to a layout design variable, which varies from zero (the actuator is removed) to one (the actuator is retained). These layout design variables are optimized concurrently with a large number of structural wingbox sizing variables and control surface actuation variables, in order to minimize the sum of structural weight and actuator weight. Results are presented that demonstrate interdependencies between structural sizing patterns and optimal control surface layouts, for both static and dynamic aeroelastic physics.
Optimal control of wind turbines in a turbulent boundary layer
Yilmaz, Ali Emre; Meyers, Johan
2016-11-01
In recent years, optimal control theory was combined with large-eddy simulations to study the optimal control of wind farms and their interaction with the atmospheric boundary layer. The individual turbine's induction factors were dynamically controlled in time with the aim of increasing overall power extraction. In these studies, wind turbines were represented using an actuator disk method. In the current work, we focus on optimal control on a much finer mesh (and a smaller computational domain), representing turbines with an actuator line method. Similar to Refs., optimization is performed using a gradient-based method, and gradients are obtained employing an adjoint formulation. Different cases are investigated, that include a single and a double turbine case both with uniform inflow, and with turbulent-boundary-layer inflow. The authors acknowledge support from the European Research Council (FP7-Ideas, Grant No. 306471).
EPA Optimal Corrosion Control Treatment Regional Training Workshops
EPA is hosting face-to-face regional training workshops throughout 2016-2017 on optimal corrosion control treatment (OCCT). These will be held at each of the Regions and is intended for primacy agency staff and technical assistance providers.
Benchmarking model-free and model-based optimal control
Koryakovskiy, I.; Kudruss, M.; Babuska, R.; Caarls, W.; Kirches, Christian; Mombaur, Katja; Schlöder, Johannes P.; Vallery, H.
2017-01-01
Model-free reinforcement learning and nonlinear model predictive control are two different approaches for controlling a dynamic system in an optimal way according to a prescribed cost function. Reinforcement learning acquires a control policy through exploratory interaction with the system, while
Optimization and Control of Bilinear Systems Theory, Algorithms, and Applications
Pardalos, Panos M
2008-01-01
Covers developments in bilinear systems theory Focuses on the control of open physical processes functioning in a non-equilibrium mode Emphasis is on three primary disciplines: modern differential geometry, control of dynamical systems, and optimization theory Includes applications to the fields of quantum and molecular computing, control of physical processes, biophysics, superconducting magnetism, and physical information science
A novel technique for active vibration control, based on optimal ...
Indian Academy of Sciences (India)
In the last few decades, researchers have proposed many control techniques to suppress unwanted vibrations in a structure. In this work, a novel and simple technique is proposed for the active vibration control. In this technique, an optimal tracking control is employed to suppress vibrations in a structure by simultaneously ...
A novel technique for active vibration control, based on optimal ...
Indian Academy of Sciences (India)
BEHROUZ KHEIRI SARABI
2017-07-11
Jul 11, 2017 ... Abstract. In the last few decades, researchers have proposed many control techniques to suppress unwanted vibrations in a structure. In this work, a novel and simple technique is proposed for the active vibration control. In this technique, an optimal tracking control is employed to suppress vibrations in a ...
Economics-based optimal control of greenhouse tomato crop production
Tap, F.
2000-01-01
The design and testing of an optimal control algorithm, based on scientific models of greenhouse and tomato crop and an economic criterion (goal function), to control greenhouse climate, is described. An important characteristic of this control is that it aims at maximising an economic
Optimal Excitation Controller Design for Wind Turbine Generator
Directory of Open Access Journals (Sweden)
A. K. Boglou
2011-01-01
Full Text Available An optimal excitation controller design based on multirate-output controllers (MROCs having a multirate sampling mechanismwith different sampling period in each measured output of the system is presented. The proposed H∞ -control techniqueis applied to the discrete linear open-loop system model which represents a wind turbine generator supplying an infinite busthrough a transmission line.
The maximum principle in optimal control of systems driven by ...
African Journals Online (AJOL)
We study the relaxed optimal stochastic control problem for systems governed by stochastic differential equations (SDEs), driven by an orthogonal continuous martingale measure, where the control is allowed to enter both the drift and diffusion coeffcient. The set of admissible controls is a set of measure-valued processes.
Optimal and robust feedback controller estimation for a vibrating plate
Fraanje, P.R.; Verhaegen, M.; Doelman, N.J.; Berkhoff, A.
2004-01-01
This paper presents a method to estimate the H2 optimal and a robust feedback controller by means of Subspace Model Identification using the internal model control (IMC) approach. Using IMC an equivalent feed forward control problem is obtained, which is solved by the Causal Wiener filter for the H2
The Determination of Optimal Parameters of Fuzzy PI Sugeno Controller
Kudinov, Y. I.; Kudinov, I. Yu; Volkova, A. A.; Durgarjan, I. S.; Pashchenko, F. F.
2017-11-01
Describe the procedure for determining by means of Matlab and Simulink optimal parameters of the fuzzy PI controller Sugeno, where some indicators of the quality of the transition process in a closed system control with this controller satisfies the specified conditions.
Optimal control of a social epidemic model with media coverage.
Huo, Hai-Feng; Huang, Shui-Rong; Wang, Xun-Yang; Xiang, Hong
2017-12-01
A new social epidemic model to depict alcoholism with media coverage is proposed in this paper. Some fundamental properties of the model including existence and positivity as well as boundedness of equilibria are investigated. Stability of all equilibria are studied. The existence of the optimal control pair and mathematical expressions of optimal control are obtained by Pontryagin's maximum principle. Numerical simulations are also performed to illustrate our results. Our results show that media coverage is an effective measure to quit drinking.
Risk-sensitive control and an optimal investment model II
Fleming, W. H.; Sheu, S. J.
2002-01-01
We consider an optimal investment problem proposed by Bielecki and Pliska. The goal of the investment problem is to optimize the long-term growth of expected utility of wealth. We consider HARA utility functions with exponent $-\\infty< \\gamma< 1$. The problem can be reformulated as an infinite time horizon risk-sensitive control problem. Some useful ideas and results from the theory of risk-sensitive control can be used in the analysis. Especially, we analyze the associated ...
Robust Optimal Adaptive Trajectory Tracking Control of Quadrotor Helicopter
Directory of Open Access Journals (Sweden)
M. Navabi
Full Text Available Abstract This paper focuses on robust optimal adaptive control strategy to deal with tracking problem of a quadrotor unmanned aerial vehicle (UAV in presence of parametric uncertainties, actuator amplitude constraints, and unknown time-varying external disturbances. First, Lyapunov-based indirect adaptive controller optimized by particle swarm optimization (PSO is developed for multi-input multi-output (MIMO nonlinear quadrotor to prevent input constraints violation, and then disturbance observer-based control (DOBC technique is aggregated with the control system to attenuate the effects of disturbance generated by an exogenous system. The performance of synthesis control method is evaluated by a new performance index function in time-domain, and the stability analysis is carried out using Lyapunov theory. Finally, illustrative numerical simulations are conducted to demonstrate the effectiveness of the presented approach in altitude and attitude tracking under several conditions, including large time-varying uncertainty, exogenous disturbance, and control input constraints.
Optimal boundary control and boundary stabilization of hyperbolic systems
Gugat, Martin
2015-01-01
This brief considers recent results on optimal control and stabilization of systems governed by hyperbolic partial differential equations, specifically those in which the control action takes place at the boundary. The wave equation is used as a typical example of a linear system, through which the author explores initial boundary value problems, concepts of exact controllability, optimal exact control, and boundary stabilization. Nonlinear systems are also covered, with the Korteweg-de Vries and Burgers Equations serving as standard examples. To keep the presentation as accessible as possible, the author uses the case of a system with a state that is defined on a finite space interval, so that there are only two boundary points where the system can be controlled. Graduate and post-graduate students as well as researchers in the field will find this to be an accessible introduction to problems of optimal control and stabilization.
Near Optimal Decentralized H-infinity Control: Bounded vs. Unbounded Controller Order
DEFF Research Database (Denmark)
Stoustrup, Jakob; Niemann, H.H.
1997-01-01
It is shown that for a class of decentralized control problems there does not exist a sequence of controllers of bounded order which obtains near optimal control. Neither does there exist an infinite dimensional optimal controller. Using the insight of the line of proof of these results, a heuris...
Combining optimal control theory and molecular dynamics for protein folding.
Directory of Open Access Journals (Sweden)
Yaman Arkun
Full Text Available A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD. In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the Cα atoms of a Coarse-Grained (CG protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the Cα atoms. In turn, MD simulation provides an all-atom conformation whose Cα positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the Cα atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization-MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages.
Optimal control of a waste water cleaning plant
Directory of Open Access Journals (Sweden)
Ellina V. Grigorieva
2010-09-01
Full Text Available In this work, a model of a waste water treatment plant is investigated. The model is described by a nonlinear system of two differential equations with one bounded control. An optimal control problem of minimizing concentration of the polluted water at the terminal time T is stated and solved analytically with the use of the Pontryagin Maximum Principle. Dependence of the optimal solution on the initial conditions is established. Computer simulations of a model of an industrial waste water treatment plant show the advantage of using our optimal strategy. Possible applications are discussed.
Multidimensional optimal droop control for wind resources in DC microgrids
Bunker, Kaitlyn J.
Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.
Genetic Algorithm Optimizes Q-LAW Control Parameters
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Augmented Lagrangian Method For Discretized Optimal Control ...
African Journals Online (AJOL)
With the aid of Augmented Lagrangian method, a quadratic function with a control operator (penalized matrix) amenable to conjugate gradient method is generated. Numerical experiments verify the efficiency of the proposed technique which compares much more favourably to the existing scheme. Keywords: Trapezoidal ...
Optimal control of vibrational transitions of HCl
Indian Academy of Sciences (India)
Control of fundamental and overtone transitions of a vibration are studied for the diatomic molecule, HCl. Specifically, the results of the effect of variation of the penalty factor on the physical attributes of the system (i.e., probabilities) and pulse (i.e., amplitudes) considering three different pulse durations for each value of the ...
Allaoua, Boumediene; Laoufi, Abdellah; Gasbaoui, Brahim; Abdelfatah NASRI; Abdessalam ABDERRAHMANI
2008-01-01
In this paper, an intelligent controller of the DC (Direct current) Motor drive is designed using fuzzy logic-genetic algorithms optimization. First, a controller is designed according to fuzzy rules such that the systems are fundamentally robust. To obtain the globally optimal values, parameters of the fuzzy controller are improved by genetic algorithms optimization model. Computer MATLAB work space demonstrate that the fuzzy controller associated to the genetic algorithms approach became ve...
PSO Algorithm for an Optimal Power Controller in a Microgrid
Al-Saedi, W.; Lachowicz, S.; Habibi, D.; Bass, O.
2017-07-01
This paper presents the Particle Swarm Optimization (PSO) algorithm to improve the quality of the power supply in a microgrid. This algorithm is proposed for a real-time selftuning method that used in a power controller for an inverter based Distributed Generation (DG) unit. In such system, the voltage and frequency are the main control objectives, particularly when the microgrid is islanded or during load change. In this work, the PSO algorithm is implemented to find the optimal controller parameters to satisfy the control objectives. The results show high performance of the applied PSO algorithm of regulating the microgrid voltage and frequency.
Optimally Controlled Flexible Fuel Powertrain System
Energy Technology Data Exchange (ETDEWEB)
Duncan Sheppard; Bruce Woodrow; Paul Kilmurray; Simon Thwaite
2011-06-30
A multi phase program was undertaken with the stated goal of using advanced design and development tools to create a unique combination of existing technologies to create a powertrain system specification that allowed minimal increase of volumetric fuel consumption when operating on E85 relative to gasoline. Although on an energy basis gasoline / ethanol blends typically return similar fuel economy to straight gasoline, because of its lower energy density (gasoline ~ 31.8MJ/l and ethanol ~ 21.1MJ/l) the volume based fuel economy of gasoline / ethanol blends are typically considerably worse. This project was able to define an initial engine specification envelope, develop specific hardware for the application, and test that hardware in both single and multi-cylinder test engines to verify the ability of the specified powertrain to deliver reduced E85 fuel consumption. Finally, the results from the engine testing were used in a vehicle drive cycle analysis tool to define a final vehicle level fuel economy result. During the course of the project, it was identified that the technologies utilized to improve fuel economy on E85 also enabled improved fuel economy when operating on gasoline. However, the E85 fueled powertrain provided improved vehicle performance when compared to the gasoline fueled powertrain due to the improved high load performance of the E85 fuel. Relative to the baseline comparator engine and considering current market fuels, the volumetric fuel consumption penalty when running on E85 with the fully optimized project powertrain specification was reduced significantly. This result shows that alternative fuels can be utilized in high percentages while maintaining or improving vehicle performance and with minimal or positive impact on total cost of ownership to the end consumer. The justification for this project was two-fold. In order to reduce the US dependence on crude oil, much of which is imported, the US Environmental Protection Agency (EPA
Process control and optimization with simple interval calculation method
DEFF Research Database (Denmark)
Pomerantsev, A.; Rodionova, O.; Høskuldsson, Agnar
2006-01-01
Methods of process control and optimization are presented and illustrated with a real world example. The optimization methods are based on the PLS block modeling as well as on the simple interval calculation methods of interval prediction and object status classification. It is proposed to employ...... for the quality improvement in the course of production. The latter is an active quality optimization, which takes into account the actual history of the process. The advocate approach is allied to the conventional method of multivariate statistical process control (MSPC) as it also employs the historical process...... the series of expanding PLS/SIC models in order to support the on-line process improvements. This method helps to predict the effect of planned actions on the product quality and thus enables passive quality control. We have also considered an optimization approach that proposes the correcting actions...
Distributed population dynamics: Optimization and control applications
Barreiro-Gómez, Julián; Obando, Germán; Quijano Silva, Nicanor
2017-01-01
© 2017 IEEE. Personal use for this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to serves or lists, or reuse of any copyrighted component of this work in other works. Population dynamics have been widely used in the design of learning and control systems for networked enginee...
Distributed population dynamics: Optimization and control applications
Barreiro-Gómez, Julian; Obando, Germán; Quijano, Nicanor
2016-01-01
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Population dynamics have been widely used in the design of learning and control systems for networked engineer...
On Optimizing Command and Control Structures
2011-06-01
example a pendulum or train moving at a fixed speed have predictable trajectories and would have considerably lower entropic drag than systems whose...given above, we also ran each graph through two slightly modified simulations. In the first modification, a sensor node in HOLD will perform another... Efficacy (Information Flow with Actuation) To test the efficacy of different hierarchical control structures (in terms of total actuated information
Developments in model-based optimization and control distributed control and industrial applications
Grancharova, Alexandra; Pereira, Fernando
2015-01-01
This book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization. The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on: · complexity and structure in model predictive control (MPC); · collaborative MPC; · distributed MPC; · optimization-based analysis and desi...
Multiobjective optimization design of a fractional order PID controller for a gun control system.
Gao, Qiang; Chen, Jilin; Wang, Li; Xu, Shiqing; Hou, Yuanlong
2013-01-01
Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method.
Robust and optimal control a two-port framework approach
Tsai, Mi-Ching
2014-01-01
A Two-port Framework for Robust and Optimal Control introduces an alternative approach to robust and optimal controller synthesis procedures for linear, time-invariant systems, based on the two-port system widespread in electrical engineering. The novel use of the two-port system in this context allows straightforward engineering-oriented solution-finding procedures to be developed, requiring no mathematics beyond linear algebra. A chain-scattering description provides a unified framework for constructing the stabilizing controller set and for synthesizing H2 optimal and H∞ sub-optimal controllers. Simple yet illustrative examples explain each step. A Two-port Framework for Robust and Optimal Control features: · a hands-on, tutorial-style presentation giving the reader the opportunity to repeat the designs presented and easily to modify them for their own programs; · an abundance of examples illustrating the most important steps in robust and optimal design; and · �...
Embedded Optimal Control of Robot Manipulators with Passive Joints
Directory of Open Access Journals (Sweden)
Alberto Olivares
2015-01-01
Full Text Available This paper studies the optimal control problem for planar underactuated robot manipulators with two revolute joints and brakes at the unactuated joints in the presence of gravity. The presence of a brake at an unactuated joint gives rise to two operating modes for that joint: free and braked. As a consequence, there exist two operating modes for a robot manipulator with one unactuated joint and four operating modes for a manipulator with two unactuated joints. Since these systems can change dynamics, they can be regarded as switched dynamical systems. The optimal control problem for these systems is solved using the so-called embedding approach. The main advantages of this technique are that assumptions about the number of switches are not necessary, integer or binary variables do not have to be introduced to model switching decisions between modes, and the optimal switching times between modes are not unknowns of the optimal control problem. As a consequence, the resulting problem is a classical continuous optimal control problem. In this way, a general method for the solution of optimal control problems for switched dynamical systems is obtained. It is shown in this paper that it can deal with nonintegrable differential constraints.
Optimal traffic control in highway transportation networks using linear programming
Li, Yanning
2014-06-01
This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.
Optimal Bilinear Control of Gross--Pitaevskii Equations
Hintermüller, Michael
2013-01-01
A mathematical framework for optimal bilinear control of nonlinear Schrödinger equations of Gross--Pitaevskii type arising in the description of Bose--Einstein condensates is presented. The obtained results generalize earlier efforts found in the literature in several aspects. In particular, the cost induced by the physical workload over the control process is taken into account rather than the often used L^2- or H^1-norms for the cost of the control action. Well-posedness of the problem and existence of an optimal control are proved. In addition, the first order optimality system is rigorously derived. Also a numerical solution method is proposed, which is based on a Newton-type iteration, and used to solve several coherent quantum control problems.
Total energy control system autopilot design with constrained parameter optimization
Ly, Uy-Loi; Voth, Christopher
1990-01-01
A description is given of the application of a multivariable control design method (SANDY) based on constrained parameter optimization to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the direct synthesis of a multiloop AFCS inner-loop feedback control system based on total energy control system (TECS) principles. The design procedure offers a structured approach for the determination of a set of stabilizing controller design gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The approach can be extended to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by proper formulation of the design objectives and constraints. Satisfactory designs are usually obtained in few iterations. Performance characteristics of the optimized TECS design have been improved, particularly in the areas of closed-loop damping and control activity in the presence of turbulence.
Directory of Open Access Journals (Sweden)
Mohd Ariffanan Mohd Basri
2015-09-01
Full Text Available Quadrotor unmanned aerial vehicle (UAV is an unstable nonlinear control system. Therefore, the development of a high performance controller for such a multi-input and multi-output (MIMO system is important. The backstepping controller (BC has been successfully applied to control a variety of nonlinear systems. Conventionally, control parameters of a BC are usually chosen arbitrarily. The problems in this method are the adjustment is time demanding and a designer can never tell exactly what are the optimal control parameters should be selected. In this paper, the contribution is focused on an optimal control design for stabilization and trajectory tracking of a quadrotor UAV. Firstly, a dynamic model of the aerial vehicle is mathematically formulated. Then, an optimal backstepping controller (OBC is proposed. The particle swarm optimization (PSO algorithm is used to compute control parameters of the OBC. Finally, simulation results of a highly nonlinear quadrotor system are presented to demonstrate the effectiveness of the proposed control method. From the simulation results it is observed that the OBC tuned by PSO provides a high control performance of an autonomous quadrotor UAV.
Polynomial Method for PLL Controller Optimization
Directory of Open Access Journals (Sweden)
Tsung-Yu Chiou
2011-06-01
Full Text Available The Phase-Locked Loop (PLL is a key component of modern electronic communication and control systems. PLL is designed to extract signals from transmission channels. It plays an important role in systems where it is required to estimate the phase of a received signal, such as carrier tracking from global positioning system satellites. In order to robustly provide centimeter-level accuracy, it is crucial for the PLL to estimate the instantaneous phase of an incoming signal which is usually buried in random noise or some type of interference. This paper presents an approach that utilizes the recent development in the semi-definite programming and sum-of-squares field. A Lyapunov function will be searched as the certificate of the pull-in range of the PLL system. Moreover, a polynomial design procedure is proposed to further refine the controller parameters for system response away from the equilibrium point. Several simulation results as well as an experiment result are provided to show the effectiveness of this approach.
Reynoso Meza, Gilberto; Sanchis Saez, Javier; Herrero Durá, Juan Manuel
2017-01-01
This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO). It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.
Optimal control and design of a cold store using dynamic optimization
Lukasse, L.; Broeze, J.; Sluis, S. van der
2009-01-01
The design of controlled processes is a combined optimal control and design problem (OCDP). Literature on solving large OCDPs is rare. This paper presents an algorithm for solving large OCDPs. For this algorithm system dynamics, objective function and their first-order derivatives must be continuous
Boutin, Samuel; Camirand Lemyre, Julien; Turcotte, Sara; Pioro-LadrièRe, Michel; Garate, Ion
Inspired by the success of optimal control theory algorithms in the design of new, fast and accurate gates for quantum information processing, we import the mindset of these time-domain optimization strategies to static real-space functions in solid-state systems. Combining ideas from the GRAPE (Gradient Ascent Pulse Engineering) algorithm and transport calculations, we devise a new gradient-based algorithm for the optimization of transport-related quantities through the real-space variation of experimentally controllable parameters. This technique can be useful for the design of experiments in mesoscopic solid-state systems. As an example, we apply our algorithm to the optimization of the topological visibility of Majorana fermions in superconducting nanowires without spin-orbit coupling in a non-uniform magnetic field.
Optimal control of inverted pendulum system using PID controller, LQR and MPC
Varghese, Elisa Sara; Vincent, Anju K.; Bagyaveereswaran, V.
2017-11-01
Inverted pendulum is a highly nonlinear system. Here we propose an optimal control technique for the control of an inverted Pendulum - cart system. The system is modeled, linearized and controlled. Here, the control objective is to control the system such that when the cart reaches a desired position the inverted pendulum stabilizes in the upright position. Initially PID controller is used to control the system. Later, Linear Quadratic Regulator (LQR) a well-known optimal control technique which makes use of the states of the dynamical system and control input to frame the optimal control decision is used. Various combinations of both PID and LQR controllers are implemented. To validate the robustness of the controller, the system is simulated with and without disturbance. Finally the system is also controlled using Model Predictive controller (MPC). MPC has well predictive ability to calculate future events and implement necessary control actions. The performance of the system is compared and analyzed.
Optimal control problems for impulsive systems with integral boundary conditions
Directory of Open Access Journals (Sweden)
Allaberen Ashyralyev
2013-03-01
Full Text Available In this article, the optimal control problem is considered when the state of the system is described by the impulsive differential equations with integral boundary conditions. Applying the Banach contraction principle the existence and uniqueness of the solution is proved for the corresponding boundary problem by the fixed admissible control. The first and second variation of the functional is calculated. Various necessary conditions of optimality of the first and second order are obtained by the help of the variation of the controls.
Optimal control theory applications to management science and economics
Sethi, Suresh P
2006-01-01
Optimal control methods are used to determine the best ways to control a dynamic system. This book applies theoretical work to business management problems developed from the authors' research and classroom instruction. The thoroughly revised new edition has been refined with careful attention to the text and graphic material presentation. Chapters cover a range of topics including finance, production and inventory problems, marketing problems, machine maintenance and replacement, problems of optimal consumption of natural resources, and applications of control theory to economics. The book in
Optimization of an Aeroservoelastic Wing with Distributed Multiple Control Surfaces
Stanford, Bret K.
2015-01-01
This paper considers the aeroelastic optimization of a subsonic transport wingbox under a variety of static and dynamic aeroelastic constraints. Three types of design variables are utilized: structural variables (skin thickness, stiffener details), the quasi-steady deflection scheduling of a series of control surfaces distributed along the trailing edge for maneuver load alleviation and trim attainment, and the design details of an LQR controller, which commands oscillatory hinge moments into those same control surfaces. Optimization problems are solved where a closed loop flutter constraint is forced to satisfy the required flight margin, and mass reduction benefits are realized by relaxing the open loop flutter requirements.
Numerical methods for optimal control problems with state constraints
Pytlak, Radosław
1999-01-01
While optimality conditions for optimal control problems with state constraints have been extensively investigated in the literature the results pertaining to numerical methods are relatively scarce. This book fills the gap by providing a family of new methods. Among others, a novel convergence analysis of optimal control algorithms is introduced. The analysis refers to the topology of relaxed controls only to a limited degree and makes little use of Lagrange multipliers corresponding to state constraints. This approach enables the author to provide global convergence analysis of first order and superlinearly convergent second order methods. Further, the implementation aspects of the methods developed in the book are presented and discussed. The results concerning ordinary differential equations are then extended to control problems described by differential-algebraic equations in a comprehensive way for the first time in the literature.
Hybrid Quantum-Classical Approach to Quantum Optimal Control.
Li, Jun; Yang, Xiaodong; Peng, Xinhua; Sun, Chang-Pu
2017-04-14
A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely, computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving answers from the quantum simulator, classical computing devices update the control parameters until an optimal control solution is found. To demonstrate the quantum-classical scheme in experiment, we use a seven-qubit nuclear magnetic resonance system, on which we have succeeded in optimizing state preparation without involving classical computation of the large Hilbert space evolution.
Directory of Open Access Journals (Sweden)
Mykola Bokalo
2017-03-01
Full Text Available We consider an optimal control problem for systems described by a Fourier problem for parabolic equations. We prove the existence of solutions, and obtain necessary conditions of the optimal control in the case of final observation when the control functions occur in the coefficients.
Optimization of traffic light control system of an intersection using ...
African Journals Online (AJOL)
Optimization of traffic light control system of an intersection using fuzzy inference system. ... This clearly demonstrates the efficacy and potential of our solution strategy to address the traffic scheduling problem. Keywords: Fuzzy Logic; Traffic Control Systems; Dynamic Phase Scheduling; Static Phase Scheduling, Fuzzy Sets ...
Controller Design Automation for Aeroservoelastic Design Optimization of Wind Turbines
Ashuri, T.; Van Bussel, G.J.W.; Zaayer, M.B.; Van Kuik, G.A.M.
2010-01-01
The purpose of this paper is to integrate the controller design of wind turbines with structure and aerodynamic analysis and use the final product in the design optimization process (DOP) of wind turbines. To do that, the controller design is automated and integrated with an aeroelastic simulation
Pareto optimality for nonlinear infinite dimensional control systems
Directory of Open Access Journals (Sweden)
Evgenios P. Avgerinos
1990-01-01
Full Text Available In this note we establish the existence of Pareto optimal solutions for nonlinear, infinite dimensional control systems with state dependent control constraints and an integral criterion taking values in a separable, reflexive Banach lattice. An example is also presented in detail. Our result extends earlier ones obtained by Cesari and Suryanarayana.
Algorithms for Optimal Model Distributions in Adaptive Switching Control Schemes
Ghosh, D.; Baldi, S.
2016-01-01
Several multiple model adaptive control architectures have been proposed in the literature. Despite many advances in theory, the crucial question of how to synthesize the pairs model/controller in a structurally optimal way is to a large extent not addressed. In particular, it is not clear how to
Optimal detection and control strategies for invasive species management
Shefali V. Mehta; Robert G. Haight; Frances R. Homans; Stephen Polasky; Robert C. Venette
2007-01-01
The increasing economic and environmental losses caused by non-native invasive species amplify the value of identifying and implementing optimal management options to prevent, detect, and control invasive species. Previous literature has focused largely on preventing introductions of invasive species and post-detection control activities; few have addressed the role of...
A Decomposition Algorithm for Optimal Control of Distributed Energy System
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Edlund, Kristian; Standardi, Laura
2013-01-01
In economic model predictive control of distributed energy systems, the constrained optimal control problem can be expressed as a linear program with a block-angular structure. In this paper, we present an efficient Dantzig-Wolfe decomposition algorithm specifically tailored to problems...
Optimizing Optics For Remotely Controlled Underwater Vehicles
Billet, A. B.
1984-09-01
The past decade has shown a dramatic increase in the use of unmanned tethered vehicles in worldwide marine fields. These vehicles are used for inspection, debris removal and object retrieval. With advanced robotic technology, remotely operated vehicles (ROVs) are now able to perform a variety of jobs previously accomplished only by divers. The ROVs can be used at greater depths and for riskier jobs, and safety to the diver is increased, freeing him for safer, more cost-effective tasks requiring human capabilities. Secondly, the ROV operation becomes more cost effective to use as work depth increases. At 1000 feet a diver's 10 minutes of work can cost over $100,000 including support personnel, while an ROV operational cost might be 1/20 of the diver cost per day, based on the condition that the cost for ROV operation does not change with depth, as it does for divers. In the ROV operation the television lens must be as good as the human eye, with better light gathering capability than the human eye. The RCV-150 system is an example of these advanced technology vehicles. With the requirements of manueuverability and unusual inspection, a responsive, high performance, compact vehicle was developed. The RCV-150 viewing subsystem consists of a television camera, lights, and topside monitors. The vehicle uses a low light level Newvicon television camera. The camera is equipped with a power-down iris that closes for burn protection when the power is off. The camera can pan f 50 degrees and tilt f 85 degrees on command from the surface. Four independently controlled 250 watt quartz halogen flood lamps illuminate the viewing area as required; in addition, two 250 watt spotlights are fitted. A controlled nine inch CRT monitor provides real time camera pictures for the operator. The RCV-150 vehicle component system consists of the vehicle structure, the vehicle electronics, and hydraulic system which powers the thruster assemblies and the manipulator. For this vehicle, a light
Optimal control of information epidemics modeled as Maki Thompson rumors
Kandhway, Kundan; Kuri, Joy
2014-12-01
We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin's Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas. We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns.
Multiobjective optimal control of the linear wave equation
Directory of Open Access Journals (Sweden)
Hassan Zarei
2014-12-01
Full Text Available In this paper, we propose a method for the solution of a multiobjective optimal control problem (MOOCP in a linear distributed-parameter system governed by a wave equation. An explicit solution for the wave equation is derived and the control problem of this distributed-parameter system is reduced to an approximate multiobjective programming problem. The fuzzy goals are incorporated for objectives and the equilibrium problem in terms of maximization of the degree of attainment for the aggregated fuzzy goals is considered. The solution of the equilibrium optimization problem is a Pareto optimal solution with the best satisfaction performance which is achieved by using a metaheuristic algorithm such as the simulated annealing (SA together with the simplex method of linear programming (LP problems. An illustrative numerical example is presented to indicate the efficiency of the proposed method and the capability of the SA in finding optimal solution compared with two popular metaheurestics.
Optimal Control of Polymer Flooding Based on Maximum Principle
Directory of Open Access Journals (Sweden)
Yang Lei
2012-01-01
Full Text Available Polymer flooding is one of the most important technologies for enhanced oil recovery (EOR. In this paper, an optimal control model of distributed parameter systems (DPSs for polymer injection strategies is established, which involves the performance index as maximum of the profit, the governing equations as the fluid flow equations of polymer flooding, and the inequality constraint as the polymer concentration limitation. To cope with the optimal control problem (OCP of this DPS, the necessary conditions for optimality are obtained through application of the calculus of variations and Pontryagin’s weak maximum principle. A gradient method is proposed for the computation of optimal injection strategies. The numerical results of an example illustrate the effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Mostafa Lotfi Forushani
2012-04-01
Full Text Available This paper presents an optimized controller around the longitudinal axis of multivariable system in one of the aircraft flight conditions. The controller is introduced in order to control the angle of attack from the pitch attitude angle independently (that is required for designing a set of direct force-modes for the longitudinal axis based on particle swarm optimization (PSO algorithm. The autopilot system for military or civil aircraft is an essential component and in this paper, the autopilot system via 6 degree of freedom model for the control and guidance of aircraft in which the autopilot design will perform based on defining the longitudinal and the lateral-directional axes are supposed. The effectiveness of the proposed controller is illustrated by considering HIMAT aircraft. The simulation results verify merits of the proposed controller.
Application of Intensified Current Search to Multiobjective PID Controller Optimization
Auttarat Nawikavatan; Satean Tunyasrirut; Deacha Puangdownreong
2016-01-01
The intelligent control system design has been changed from the conventional approach to the optimization framework solved by efficient metaheuristics. The intensified current search (ICS) has been recently proposed as one of the most powerful metaheuristics for solving optimization problems. The ICS, the latest modified version of the conventional current search (CS), possesses the memory list (ML) regarded as the exploration strategy and the adaptive radius (AR) a...
Optimal location of piezoelectric patches for active vibration control
Labanie, Mohammad F.; Ali, J. S. Mohamed; Shaik Dawood, M. S. I.
2017-03-01
This paper focuses on finding the optimal location for a piezoelectric patch for minimizing the settling time of an excited isotropic and orthotropic plate. COMSOL Multiphysics has been used to design and model the plate with PID controller. Classical Optimization tool called Parametric Sweep has been used to achieve the objective of the experiment. Five different stacking sequences were used in the study of orthotropic plate. The results obtained by the FEA software indicated that by placing the piezoelectric patches at the optimal location, the settling time of a plate can decrease by 40% compared to placing it at the centre of the fixed end.
Dynamic Modeling, Optimization, and Advanced Control for Large Scale Biorefineries
DEFF Research Database (Denmark)
Prunescu, Remus Mihail
plant [3]. The goal of the project is to utilize realtime data extracted from the large scale facility to formulate and validate first principle dynamic models of the plant. These models are then further exploited to derive model-based tools for process optimization, advanced control and real...... with building a plantwide model-based optimization layer, which searches for optimal values regarding the pretreatment temperature, enzyme dosage in liquefaction, and yeast seed in fermentation such that profit is maximized [7]. When biomass is pretreated, by-products are also created that affect the downstream...
Exploring the complexity of quantum control optimization trajectories.
Nanduri, Arun; Shir, Ofer M; Donovan, Ashley; Ho, Tak-San; Rabitz, Herschel
2015-01-07
The control of quantum system dynamics is generally performed by seeking a suitable applied field. The physical objective as a functional of the field forms the quantum control landscape, whose topology, under certain conditions, has been shown to contain no critical point suboptimal traps, thereby enabling effective searches for fields that give the global maximum of the objective. This paper addresses the structure of the landscape as a complement to topological critical point features. Recent work showed that landscape structure is highly favorable for optimization of state-to-state transition probabilities, in that gradient-based control trajectories to the global maximum value are nearly straight paths. The landscape structure is codified in the metric R ≥ 1.0, defined as the ratio of the length of the control trajectory to the Euclidean distance between the initial and optimal controls. A value of R = 1 would indicate an exactly straight trajectory to the optimal observable value. This paper extends the state-to-state transition probability results to the quantum ensemble and unitary transformation control landscapes. Again, nearly straight trajectories predominate, and we demonstrate that R can take values approaching 1.0 with high precision. However, the interplay of optimization trajectories with critical saddle submanifolds is found to influence landscape structure. A fundamental relationship necessary for perfectly straight gradient-based control trajectories is derived, wherein the gradient on the quantum control landscape must be an eigenfunction of the Hessian. This relation is an indicator of landscape structure and may provide a means to identify physical conditions when control trajectories can achieve perfect linearity. The collective favorable landscape topology and structure provide a foundation to understand why optimal quantum control can be readily achieved.
Optimal control and quantum simulations in superconducting quantum devices
Energy Technology Data Exchange (ETDEWEB)
Egger, Daniel J.
2014-10-31
Quantum optimal control theory is the science of steering quantum systems. In this thesis we show how to overcome the obstacles in implementing optimal control for superconducting quantum bits, a promising candidate for the creation of a quantum computer. Building such a device will require the tools of optimal control. We develop pulse shapes to solve a frequency crowding problem and create controlled-Z gates. A methodology is developed for the optimisation towards a target non-unitary process. We show how to tune-up control pulses for a generic quantum system in an automated way using a combination of open- and closed-loop optimal control. This will help scaling of quantum technologies since algorithms can calibrate control pulses far more efficiently than humans. Additionally we show how circuit QED can be brought to the novel regime of multi-mode ultrastrong coupling using a left-handed transmission line coupled to a right-handed one. We then propose to use this system as an analogue quantum simulator for the Spin-Boson model to show how dissipation arises in quantum systems.
Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm
Svečko, Rajko
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749
Parameter optimization in AQM controller design to support TCP traffic
Yang, Wei; Yang, Oliver W.
2004-09-01
TCP congestion control mechanism has been widely investigated and deployed on Internet in preventing congestion collapse. We would like to employ modern control theory to specify quantitatively the control performance of the TCP communication system. In this paper, we make use of a commonly used performance index called the Integral of the Square of the Error (ISE), which is a quantitative measure to gauge the performance of a control system. By applying the ISE performance index into the Proportional-plus-Integral controller based on Pole Placement (PI_PP controller) for active queue management (AQM) in IP routers, we can further tune the parameters for the controller to achieve an optimum control minimizing control errors. We have analyzed the dynamic model of the TCP congestion control under this ISE, and used OPNET simulation tool to verify the derived optimized parameters of the controllers.
Optimally Convex Controller and Model Reduction for a Dynamic System
Directory of Open Access Journals (Sweden)
P. S. KHUNTIA
2008-07-01
Full Text Available This paper presents analysis and design of a family of controllers based on numerical convex optimization for an aircraft pitch control system. A design method is proposed here to solve control system design problems in which a set of multiple closed loop performance specifications are simultaneously satisfied. The transfer matrix of the system is determined through the convex combination of the transfer matrices of the plant and the controllers. The present system with optimal convex controller has been tested for stability using Kharitonov’s Stability Criteria. The simulation deals here withthe problem of pitch control system of a BRAVO fighter aircraft which results in higher order close loop transfer function. So the order of the higher order transfer function is reduced to minimize the complexity of the system.
Violation of a temporal bell inequality for single spins in a diamond defect center.
Waldherr, G; Neumann, P; Huelga, S F; Jelezko, F; Wrachtrup, J
2011-08-26
Quantum nonlocality has been experimentally investigated by testing different forms of Bell's inequality, yet a loophole-free realization has not been achieved up to now. Much less explored are temporal Bell inequalities, which are not subject to the locality assumption, but impose a constraint on the system's time correlations. In this Letter, we report on the experimental violation of a temporal Bell's inequality using a nitrogen-vacancy (NV) defect in diamond and provide a novel quantitative test of quantum coherence. Such a test requires strong control over the system, and we present a new technique to initialize the electronic state of the NV with high fidelity, a necessary requirement also for reliable quantum information processing and/or the implementation of protocols for quantum metrology. © 2011 American Physical Society
Operational predictive optimal control of Barcelona water transport network
Pascual, J.; Romera, J.; Puig, V.; Cembrano, G.; Creus, R.; Minoves, M.
2013-01-01
This paper describes the application of model-based predictive control (MPC) techniques to the supervisory flow management in large-scale drinking water networks including a telemetry/telecontrol system. MPC is used to generate flow control strategies (set-points for the regulatory controllers) from the sources to the consumer areas to meet future demands, optimizing performance indexes associated to operational goals such as economic cost, safety storage volumes in the network and smoothness...
The 16th IFAC Workshop on Control Applications of Optimization
2015-10-09
infinite optimal control problem is transformed to finite dimensional Nonlinear Programming Problem ( NLP ) (Betts, 1998) . The resulting NLP can be...solved using state-of-the-art structure exploit- ing NLP solvers . This enables easier handling of inequality path constraints in comparison to...1, direct opt imal control methods and hence NLP solvers shall be used as optimizat ion solvers. Direct methods use a finite dimensional control
Real Time Optimal Control of Supercapacitor Operation for Frequency Response
Energy Technology Data Exchange (ETDEWEB)
Luo, Yusheng; Panwar, Mayank; Mohanpurkar, Manish; Hovsapian, Rob
2016-07-01
Supercapacitors are gaining wider applications in power systems due to fast dynamic response. Utilizing supercapacitors by means of power electronics interfaces for power compensation is a proven effective technique. For applications such as requency restoration if the cost of supercapacitors maintenance as well as the energy loss on the power electronics interfaces are addressed. It is infeasible to use traditional optimization control methods to mitigate the impacts of frequent cycling. This paper proposes a Front End Controller (FEC) using Generalized Predictive Control featuring real time receding optimization. The optimization constraints are based on cost and thermal management to enhance to the utilization efficiency of supercapacitors. A rigorous mathematical derivation is conducted and test results acquired from Digital Real Time Simulator are provided to demonstrate effectiveness.
Tuning PID Controller Using Multiobjective Ant Colony Optimization
Directory of Open Access Journals (Sweden)
Ibtissem Chiha
2012-01-01
Full Text Available This paper treats a tuning of PID controllers method using multiobjective ant colony optimization. The design objective was to apply the ant colony algorithm in the aim of tuning the optimum solution of the PID controllers (Kp, Ki, and Kd by minimizing the multiobjective function. The potential of using multiobjective ant algorithms is to identify the Pareto optimal solution. The other methods are applied to make comparisons between a classic approach based on the “Ziegler-Nichols” method and a metaheuristic approach based on the genetic algorithms. Simulation results demonstrate that the new tuning method using multiobjective ant colony optimization has a better control system performance compared with the classic approach and the genetic algorithms.
Turbine Control Strategies for Wind Farm Power Optimization
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Göçmen Bozkurt, Tuhfe; Giebel, Gregor
2015-01-01
In recent decades there has been increasing interest in green energies, of which wind energy is the most important one. In order to improve the competitiveness of the wind power plants, there are ongoing researches to decrease cost per energy unit and increase the efficiency of wind turbines...... and wind farms. One way of achieving these goals is to optimize the power generated by a wind farm. One optimization method is to choose appropriate operating points for the individual wind turbines in the farm. We have made three models of a wind farm based on three difference control strategies....... Basically, the control strategies determine the steady state operating points of the wind turbines. Except the control strategies of the individual wind turbines, the wind farm models are similar. Each model consists of a row of 5MW reference wind turbines. In the models we are able to optimize...
Quadratic Optimization in the Problems of Active Control of Sound
Loncaric, J.; Tsynkov, S. V.; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
We analyze the problem of suppressing the unwanted component of a time-harmonic acoustic field (noise) on a predetermined region of interest. The suppression is rendered by active means, i.e., by introducing the additional acoustic sources called controls that generate the appropriate anti-sound. Previously, we have obtained general solutions for active controls in both continuous and discrete formulations of the problem. We have also obtained optimal solutions that minimize the overall absolute acoustic source strength of active control sources. These optimal solutions happen to be particular layers of monopoles on the perimeter of the protected region. Mathematically, minimization of acoustic source strength is equivalent to minimization in the sense of L(sub 1). By contrast. in the current paper we formulate and study optimization problems that involve quadratic functions of merit. Specifically, we minimize the L(sub 2) norm of the control sources, and we consider both the unconstrained and constrained minimization. The unconstrained L(sub 2) minimization is certainly the easiest problem to address numerically. On the other hand, the constrained approach allows one to analyze sophisticated geometries. In a special case, we call compare our finite-difference optimal solutions to the continuous optimal solutions obtained previously using a semi-analytic technique. We also show that the optima obtained in the sense of L(sub 2) differ drastically from those obtained in the sense of L(sub 1).
Allada, K; Aniol, K; Annand, J R M; Averett, T; Benmokhtar, F; Bertozzi, W; Bradshaw, P C; Bosted, P; Camsonne, A; Canan, M; Cates, G D; Chen, C; Chen, J -P; Chen, W; Chirapatpimol, K; Chudakov, E; Cisbani, E; Cornejo, J C; Cusanno, F; Dalton, M; Deconinck, W; de Jager, C W; De Leo, R; Deng, X; Deur, A; Ding, H; Dolph, P A M; Dutta, C; Dutta, D; Fassi, L El; Frullani, S; Gao, H; Garibaldi, F; Gaskell, D; Gilad, S; Gilman, R; Glamazdin, O; Golge, S; Guo, L; Hamilton, D; Hansen, O; Higinbotham, D W; Holmstrom, T; Huang, J; Huang, M; Ibrahim, H F; Iodice, M; Jiang, X; Jin, G; Jones, M K; Katich, J; Kelleher, A; Kim, W; Kolarkar, A; Korsch, W; LeRose, J J; Li, X; Li, Y; Lindgren, R; Liyanage, N; Long, E; Lu, H -J; Margaziotis, D J; Markowitz, P; Marrone, S; McNulty, D; Meziani, Z -E; Michaels, R; Moffit, B; Camacho, C Munoz; Nanda, S; Narayan, A; Nelyubin, V; Norum, B; Oh, Y; Osipenko, M; Parno, D; Peng, J -C; Phillips, S K; Posik, M; Puckett, A J R; Qian, X; Qiang, Y; Rakhman, A; Ransome, R; Riordan, S; Saha, A; Sawatzky, B; Schulte, E; Shahinyan, A; Shabestari, M H; Sirca, S; Stepanyan, S; Subedi, R; Sulkosky, V; Tang, L -G; Tobias, A; Urciuoli, G M; Vilardi, I; Wang, K; Wang, Y; Wojtsekhowski, B; Yan, X; Yao, H; Ye, Y; Ye, Z; Yuan, L; Zhan, X; Zhang, Y; Zhang, Y -W; Zhao, B; Zheng, X; Zhu, L; Zhu, X; Zong, X
2013-01-01
We report the first measurement of target single-spin asymmetries (A$_N$) in the inclusive hadron production reaction, $e $+$ ^3\\text{He}^{\\uparrow}\\rightarrow h+X$, using a transversely polarized $^3$He target at an electron-nucleon center-of-mass energy $\\sqrt{s}$=3.45 GeV. The experiment was conducted at Jefferson Lab in Hall A using a 5.9-GeV electron beam. Three types of hadrons ($\\pi^{\\pm}$, $\\text{K}^{\\pm}$ and proton) were detected with an average momentum $$=2.35 GeV/c, and an average transverse momentum $$=0.64 GeV/c. The observed asymmetry strongly depends on the type of hadron. A positive asymmetry is observed for $\\pi^+$ and $\\text{K}^+$. A negative asymmetry is observed for $\\pi^{-}$. The magnitudes of the asymmetries follow $|A^{\\pi^-}| < |A^{\\pi^+}| < |A^{K^+}|$. The K$^{-}$ and proton asymmetries are consistent with zero within the experimental uncertainties. The $\\pi^{+}$ and $\\pi^{-}$ asymmetries measured for the $^3$He target and extracted for neutrons are opposite in sign with a sma...
Kraishan, Amani; STAR Collaboration
2017-09-01
The production of W-bosons in longitudinally polarized p+p collisions at RHIC is an ideal tool to study the spin-flavor structure of the proton at a high momentum scale, Q MW . W - (+) bosons are produced in u + d (d + u) collisions and can be detected through their leptonic decays, e- +νe (e+ +νe) . The charged lepton can be detected by the Time Projection Chamber | η | < 1.3 and the Electromagnetic Calorimeters (Barrel | η | < 1.0 and EndCap 1 < η < 2). The parity-violating nature of the weak production process gives rise to large longitudinal single-spin asymmetries, AL. The measurement of AL of W-bosons as a function of lepton pseudorapidity ηe at STAR provides a unique probe to the valence and sea quark helicity distribution for the fractional momentum range of 0.05 < x < 0.2 .In 2013 the STAR experiment collected an integrated luminosity about 250 pb-1 at √{ s}= 510 GeV with an average beam polarization of 53 % . The preliminary results of W-bosons AL from 2013 data sample will be presented.
Energy Technology Data Exchange (ETDEWEB)
Nuruzzaman, nfn [Hampton Univ., Hampton, VA (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)
2016-08-01
The beam normal single spin asymmetry ($B_{\\rm n}$) is generated in the scattering of transversely polarized electrons from unpolarized nuclei. The asymmetry arises from the interference of the imaginary part of the two-photon exchange with the one-photon exchange amplitude. The $Q_{\\rm weak}$ experiment has made the first measurement of $B_{\\rm n}$ in the production of the $\\Delta$(1232) resonance, using the $Q_{\\rm weak}$ apparatus in Hall-C at the Thomas Jefferson National Accelerator Facility. The final transverse asymmetry, corrected for backgrounds and beam polarization, is $B_{\\rm n}$ = 43 $\\pm$ 16 ppm at beam energy 1.16 GeV at an average scattering angle of about 8.3 degrees, and invariant mass of 1.2 GeV. The measured preliminary $B_{\\rm n}$ agrees with a preliminary theoretical calculation. $B_{\\rm n}$ for the $\\Delta$ is the only known observable that is sensitive to the $\\Delta$ elastic form-factors ($\\gamma$*$\\Delta\\Delta$) in addition to the generally studied transition form-factors ($\\gamma$*N$\\Delta$), but extracting this information will require significant theoretical input.
Optimized PID control of depth of hypnosis in anesthesia.
Padula, Fabrizio; Ionescu, Clara; Latronico, Nicola; Paltenghi, Massimiliano; Visioli, Antonio; Vivacqua, Giulio
2017-06-01
This paper addresses the use of proportional-integral-derivative controllers for regulating the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. In fact, introducing an automatic control system might provide significant benefits for the patient in reducing the risk for under- and over-dosing. In this study, the controller parameters are obtained through genetic algorithms by solving a min-max optimization problem. A set of 12 patient models representative of a large population variance is used to test controller robustness. The worst-case performance in the considered population is minimized considering two different scenarios: the induction case and the maintenance case. Our results indicate that including a gain scheduling strategy enables optimal performance for induction and maintenance phases, separately. Using a single tuning to address both tasks may results in a loss of performance up to 102% in the induction phase and up to 31% in the maintenance phase. Further on, it is shown that a suitably designed low-pass filter on the controller output can handle the trade-off between the performance and the noise effect in the control variable. Optimally tuned PID controllers provide a fast induction time with an acceptable overshoot and a satisfactory disturbance rejection performance during maintenance. These features make them a very good tool for comparison when other control algorithms are developed. Copyright © 2017 Elsevier B.V. All rights reserved.
Optimal Control Strategy for Abnormal Innate Immune Response
Directory of Open Access Journals (Sweden)
Jinying Tan
2015-01-01
Full Text Available Innate immune response plays an important role in control and clearance of pathogens following viral infection. However, in the majority of virus-infected individuals, the response is insufficient because viruses are known to use different evasion strategies to escape immune response. In this study, we use optimal control theory to investigate how to control the innate immune response. We present an optimal control model based on an ordinary-differential-equation system from a previous study, which investigated the dynamics and regulation of virus-triggered innate immune signaling pathways, and we prove the existence of a solution to the optimal control problem involving antiviral treatment or/and interferon therapy. We conduct numerical experiments to investigate the treatment effects of different control strategies through varying the cost function and control efficiency. The results show that a separate treatment, that is, only inhibiting viral replication (u1(t or enhancing interferon activity (u2(t, has more advantages for controlling viral infection than a mixed treatment, that is, controlling both (u1(t and (u2(t simultaneously, including the smallest cost and operability. These findings would provide new insight for developing effective strategies for treatment of viral infectious diseases.
Optimal control design of preparation pulses for contrast optimization in MRI
Van Reeth, Eric; Ratiney, Hélène; Tesch, Michael; Grenier, Denis; Beuf, Olivier; Glaser, Steffen J.; Sugny, Dominique
2017-06-01
This work investigates the use of MRI radio-frequency (RF) pulses designed within the framework of optimal control theory for image contrast optimization. The magnetization evolution is modeled with Bloch equations, which defines a dynamic system that can be controlled via the application of the Pontryagin Maximum Principle (PMP). This framework allows the computation of optimal RF pulses that bring the magnetization to a given state to obtain the desired contrast after acquisition. Creating contrast through the optimal manipulation of Bloch equations is a new way of handling contrast in MRI, which can explore the theoretical limits of the system. Simulation experiments carried out on-resonance quantify the contrast improvement when compared to standard T1 or T2 weighting strategies. The use of optimal pulses is also validated for the first time in both in vitro and in vivo experiments on a small-animal 4.7 T MR system. Results demonstrate their robustness to static field inhomogeneities as well as the fact that they can be embedded in standard imaging sequences without affecting standard parameters such as slice selection or echo type. In vivo results on rat and mouse brains illustrate the ability of optimal contrast pulses to create non-trivial contrasts on well-studied structures (white matter versus gray matter).
Production and process management: An optimal control approach
Directory of Open Access Journals (Sweden)
Biswas Haider Ali
2016-01-01
Full Text Available Optimal control and efficient management of industrial products are the key for sustainable development in industrial and process engineering. It is well-known that proper maintenance of process performance, ensuring the quality products after a long time operation of the system, is desirable in any industry. Nonlinear dynamical systems may play crucial role to appropriately design the model and obtain optimal control strategy in production and process management. This paper deals with a mathematical model in terms of ordinary differential equations (ODEs that describe control of production and process arising in industrial engineering. The optimal control technique in the form of maximum principle, used to control the quality products in the operation processes, is applied to analyze the model. It is shown that the introduction of state constraint can be advantageous for obtaining good products during the longer operation process. We investigate the model numerically, using some known nonlinear optimal control solvers, and we present the simulation results to illustrate the significance of introducing state constraint onto the dynamics of the model.
Optimal pulse design in quantum control: a unified computational method.
Li, Jr-Shin; Ruths, Justin; Yu, Tsyr-Yan; Arthanari, Haribabu; Wagner, Gerhard
2011-02-01
Many key aspects of control of quantum systems involve manipulating a large quantum ensemble exhibiting variation in the value of parameters characterizing the system dynamics. Developing electromagnetic pulses to produce a desired evolution in the presence of such variation is a fundamental and challenging problem in this research area. We present such robust pulse designs as an optimal control problem of a continuum of bilinear systems with a common control function. We map this control problem of infinite dimension to a problem of polynomial approximation employing tools from geometric control theory. We then adopt this new notion and develop a unified computational method for optimal pulse design using ideas from pseudospectral approximations, by which a continuous-time optimal control problem of pulse design can be discretized to a constrained optimization problem with spectral accuracy. Furthermore, this is a highly flexible and efficient numerical method that requires low order of discretization and yields inherently smooth solutions. We demonstrate this method by designing effective broadband π/2 and π pulses with reduced rf energy and pulse duration, which show significant sensitivity enhancement at the edge of the spectrum over conventional pulses in 1D and 2D NMR spectroscopy experiments.
An optimal performance control scheme for a 3D crane
Maghsoudi, Mohammad Javad; Mohamed, Z.; Husain, A. R.; Tokhi, M. O.
2016-01-01
This paper presents an optimal performance control scheme for control of a three dimensional (3D) crane system including a Zero Vibration shaper which considers two control objectives concurrently. The control objectives are fast and accurate positioning of a trolley and minimum sway of a payload. A complete mathematical model of a lab-scaled 3D crane is simulated in Simulink. With a specific cost function the proposed controller is designed to cater both control objectives similar to a skilled operator. Simulation and experimental studies on a 3D crane show that the proposed controller has better performance as compared to a sequentially tuned PID-PID anti swing controller. The controller provides better position response with satisfactory payload sway in both rail and trolley responses. Experiments with different payloads and cable lengths show that the proposed controller is robust to changes in payload with satisfactory responses.
Modelling, Optimization and Optimal Control of Small Scale Stirred Tank Bioreactors
Directory of Open Access Journals (Sweden)
Mitko Petrov
2004-10-01
Full Text Available Models of the mass-transfer in a stirred tank bioreactor depending on general indexes of the processes of aeration and mixing in concrete simplifications of the hydrodynamic structure of the flows are developed. The offered combined model after parameters identification is used for optimization of the parameters of the apparatus construction. The optimization problem is solved by using of the fuzzy sets theory and in this way the unspecified as a result of the model simplification are read. In conclusion an optimal control of a fed-batch fermentation process of E. coli is completed by using Neuro-Dynamic programming. The received results after optimization show a considerable improvement of the mass-transfer indexes and the quantity indexes at the end of the process.
Torque-based optimal acceleration control for electric vehicle
Lu, Dongbin; Ouyang, Minggao
2014-03-01
The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin's maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle(EV) has not been reported. In this paper, the permanent magnet synchronous motor(PMSM) is controlled by the field oriented control(FOC) method and the electric drive system for the EV(including the PMSM, the inverter and the battery) is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming(DP). This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV's acceleration process and the analytical algorithm is easy to be implemented in real-time control.
Optimal control of quaternion propagation errors in spacecraft navigation
Vathsal, S.
1986-01-01
Optimal control techniques are used to drive the numerical error (truncation, roundoff, commutation) in computing the quaternion vector to zero. The normalization of the quaternion is carried out by appropriate choice of a performance index, which can be optimized. The error equations are derived from Friedland's (1978) theoretical development, and a matrix Riccati equation results for the computation of the gain matrix. Simulation results show that a high precision of the order of 10 to the -12th can be obtained using this technique in meeting the q(T)q=1 constraint. The performance of the estimator in the presence of the feedback control that maintains the normalization, is studied.
Approximated Solutions of Linear Quadratic Fractional Optimal Control Problems
Directory of Open Access Journals (Sweden)
Soradi Zeid S.
2016-12-01
Full Text Available In this study we apply the Adomian decomposition method (ADM to approximate the solution of fractional optimal control problems (FOCPs where the dynamic of system is a linear control system with constant coefficient and the cost functional is defined in a quadratic form. First we stated the necessary optimality conditions in a form of fractional two point boundary value problem (TPBVP, then the ADM is used to solve the resulting fractional differential equations (FDEs. Some examples are provided to demonstrate the validity and applicability of the proposed method.
Migrating Storms and Optimal Control of Urban Sewer Networks
Directory of Open Access Journals (Sweden)
Upaka Rathnayake
2015-11-01
Full Text Available Uniform storms are generally applied in most of the research on sewer systems. This is for modeling simplicity. However, in the real world, these conditions may not be applicable. It is very important to consider the migration behavior of storms not only in the design of combined sewers, but also in controlling them. Therefore, this research was carried out to improve Rathnayake and Tanyimboh’s optimal control algorithm for migrating storms. Promising results were found from the model improvement. Feasible solutions were obtained from the multi-objective optimization and, in addition, the role of on-line storage tanks was well placed.
Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms
Directory of Open Access Journals (Sweden)
Haifa Mehdi
2011-11-01
Full Text Available This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov-based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO algorithm. For designing the PSO method, different index performances are considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach.
Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms
Directory of Open Access Journals (Sweden)
Haifa Mehdi
2011-11-01
Full Text Available This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov‐based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO algorithm. For designing the PSOmethod,differentindexperformancesare considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach.
Optimal Control Problems for Partial Differential Equations on Reticulated Domains
Kogut, Peter I
2011-01-01
In the development of optimal control, the complexity of the systems to which it is applied has increased significantly, becoming an issue in scientific computing. In order to carry out model-reduction on these systems, the authors of this work have developed a method based on asymptotic analysis. Moving from abstract explanations to examples and applications with a focus on structural network problems, they aim at combining techniques of homogenization and approximation. Optimal Control Problems for Partial Differential Equations on Reticulated Domains is an excellent reference tool for gradu
Attitude Optimal Backstepping Controller Based Quaternion for a UAV
Directory of Open Access Journals (Sweden)
Kaddouri Djamel
2016-01-01
Full Text Available A hierarchical controller design based on nonlinear H∞ theory and backstepping technique is developed for a nonlinear and coupled dynamic attitude system using conventional quaternion based method. The derived controller combines the attractive features of H∞ optimal controller and the advantages of the backstepping technique leading to a control law which avoids winding phenomena. Performance issues of the controller are illustrated in a simulation study made for a four-rotor vertical take-off and landing (VTOL aerial robot prototype known as the quadrotor aircraft.
Digitally-Controlled Optimal Position Servo Of Induction Motors
Haneda, H.; Nagao, A.
1987-10-01
The purpose of the paper is to propose a new high-performance optimal position servo of an induction motor fully controlled by a micro-computer, which was designed and realized through a waterfall type top-down design in a newly developed CAD environment. Field-orientation control was used to design a new voltage-controlled optimal regulator for position control. Globally stable observers were designed and utilized to overcome the restricted availability of sensed variables: winding voltages & currents and shaft speed & angle. The digital scheme was experimentally tested and verified. Also shown is the effect of quantization errors and sampling period in A/D's & D/A's on the response and accuracy of the control system.
Genetic optimization of fuzzy fractional PD+I controllers.
Jesus, Isabel S; Barbosa, Ramiro S
2015-07-01
Fractional order calculus is a powerful emerging mathematical tool in science and engineering. There is currently an increasing interest in generalizing classical control theories and developing novel control strategies. The genetic algorithms (GA) are a stochastic search and optimization methods based on the reproduction processes found in biological systems, used for solving engineering problems. In the context of process control, the fuzzy logic usually means variables that are described by imprecise terms, and represented by quantities that are qualitative and vague. In this article we consider the development of an optimal fuzzy fractional PD+I controller in which the parameters are tuned by a GA. The performance of the proposed fuzzy fractional control is illustrated through some application examples. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Decentralized Optimization for a Novel Control Structure of HVAC System
Directory of Open Access Journals (Sweden)
Shiqiang Wang
2016-01-01
Full Text Available A decentralized control structure is introduced into the heating, ventilation, and air conditioning (HVAC system to solve the high maintenance and labor cost problem in actual engineering. Based on this new control system, a decentralized optimization method is presented for sensor fault repair and optimal group control of HVAC equipment. Convergence property of the novel method is theoretically analyzed considering both convex and nonconvex systems with constraints. In this decentralized control system, traditional device is fitted with a control chip such that it becomes a smart device. The smart device can communicate and operate collaboratively with the other devices to accomplish some designated tasks. The effectiveness of the presented method is verified by simulations and hardware tests.
Active flutter control using discrete optimal constrained dynamic compensators
Broussard, J. R.; Halyo, N.
1983-01-01
A method for synthesizing digital active flutter suppression controllers using the concept of optimal output feedback is presented. A recently developd convergent algorithm is employed to determine constrained control law parameters that minimize an infinite-time discrete quadratic performance index. Low-order compensator dynamics are included in the control law and the compensator parameters are computed along with the output feedback gain as part of the optimization process. An input noise adjustment procedure is used to improve the stability margins of the digital active flutter controller. Results from investigations into sample rate variation, prefilter pole variation, and effects of varying flight condtions are discussed. The study indicates that a digital control law which accommodates computation delay can stabilize the wing with reasonable rms performance and adequate stability margins.
Optimization and Control of Cyber-Physical Vehicle Systems.
Bradley, Justin M; Atkins, Ella M
2015-09-11
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.
Optimization and Control of Cyber-Physical Vehicle Systems
Bradley, Justin M.; Atkins, Ella M.
2015-01-01
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541
Optimization and Control of Cyber-Physical Vehicle Systems
Directory of Open Access Journals (Sweden)
Justin M. Bradley
2015-09-01
Full Text Available A cyber-physical system (CPS is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.
Model-based dynamic control and optimization of gas networks
Energy Technology Data Exchange (ETDEWEB)
Hofsten, Kai
2001-07-01
This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum
Using Chemicals to Optimize Conformance Control in Fractured Reservoirs
Energy Technology Data Exchange (ETDEWEB)
Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Liu, Jin; Wavrik, Kathryn
1999-09-27
This report describes work performed during the first year of the project, ''Using Chemicals to Optimize Conformance Control in Fractured Reservoirs.'' This research project has three objectives. The first objective is to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective is to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective is to develop procedures to optimize blocking agent placement in naturally fractured reservoirs. This research project consists of three tasks, each of which addresses one of the above objectives. Our work is directed at both injection wells and production wells and at vertical, horizontal, and highly deviated wells.
Terminal Control Area Aircraft Scheduling and Trajectory Optimization Approaches
Directory of Open Access Journals (Sweden)
Samà Marcella
2017-01-01
Full Text Available Aviation authorities are seeking optimization methods to better use the available infrastructure and better manage aircraft movements. This paper deals with the realtime scheduling of take-off and landing aircraft at a busy terminal control area and with the optimization of aircraft trajectories during the landing procedures. The first problem aims to reduce the propagation of delays, while the second problem aims to either minimize the travel time or reduce the fuel consumption. Both problems are particularly complex, since the first one is NP-hard while the second one is nonlinear and a combined solution needs to be computed in a short-time during operations. This paper proposes a framework for the lexicographic optimization of the two problems. Computational experiments are performed for the Milano Malpensa airport and show the existing gaps between the performance indicators of the two problems when different lexicographic optimization approaches are considered.
Model predictive control for continuous piecewise affine systems using optimistic optimization
Xu, J.; van den Boom, A.J.J.; Busoniu, L; De Schutter, B.H.K.; Chiu, George; Johnson, Katie; Abramovitch, Danny
2016-01-01
This paper considers model predictive control for continuous piecewise affine (PWA) systems. In general, this leads to a nonlinear, nonconvex optimization problem. We introduce an approach based on optimistic optimization to solve the resulting optimization problem. Optimistic optimization is based
Neural network based optimal control of HVAC&R systems
Ning, Min
Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the
2011-09-01
tics for a suboptimal approach to landing on a power line that may be sufficient for 169 systems with significant computational limitations, as may be...Contributions to the Theory of Optimal Control. Boletin de la Sociedad Mathematica Mexicana, 1960. [61] Kalmár-Nagy, Tamás, Raffaello D’Andrea, and Pritam
Topology optimization of embedded piezoelectric actuators considering control spillover effects
Gonçalves, Juliano F.; De Leon, Daniel M.; Perondi, Eduardo A.
2017-02-01
This article addresses the problem of active structural vibration control by means of embedded piezoelectric actuators. The topology optimization method using the solid isotropic material with penalization (SIMP) approach is employed in this work to find the optimum design of actuators taken into account the control spillover effects. A coupled finite element model of the structure is derived assuming a two-phase material and this structural model is written into the state-space representation. The proposed optimization formulation aims to determine the distribution of piezoelectric material which maximizes the controllability for a given vibration mode. The undesirable effects of the feedback control on the residual modes are limited by including a spillover constraint term containing the residual controllability Gramian eigenvalues. The optimization of the shape and placement of the conventionally embedded piezoelectric actuators are performed using a Sequential Linear Programming (SLP) algorithm. Numerical examples are presented considering the control of the bending vibration modes for a cantilever and a fixed beam. A Linear-Quadratic Regulator (LQR) is synthesized for each case of controlled structure in order to compare the influence of the additional constraint.
Efficiency optimized control of medium-size induction motor drives
DEFF Research Database (Denmark)
Abrahamsen, F.; Blaabjerg, Frede; Pedersen, John Kim
2000-01-01
The efficiency of a variable speed induction motor drive can be optimized by adaption of the motor flux level to the load torque. In small drives (small converter losses, but for medium-size drives (10-1000 kW) the losses can...... not be disregarded without further analysis. The importance of the converter losses on efficiency optimization in medium-size drives is analyzed in this paper. Based on the experiments with a 90 kW drive it is found that it is not critical if the converter losses are neglected in the control, except...... that the robustness towards load disturbances may unnecessarily be reduced. Both displacement power factor and model-based efficiency optimizing control methods perform well in medium-size drives. The last strategy is also tested on a 22 kW drive with good results....
Charting the circuit QED design landscape using optimal control theory
Goerz, Michael H.; Motzoi, Felix; Whaley, K. Birgitta; Koch, Christiane P.
2017-09-01
With recent improvements in coherence times, superconducting transmon qubits have become a promising platform for quantum computing. They can be flexibly engineered over a wide range of parameters, but also require us to identify an efficient operating regime. Using state-of-the-art quantum optimal control techniques, we exhaustively explore the landscape for creation and removal of entanglement over a wide range of design parameters. We identify an optimal operating region outside of the usually considered strongly dispersive regime, where multiple sources of entanglement interfere simultaneously, which we name the quasi-dispersive straddling qutrits regime. At a chosen point in this region, a universal gate set is realized by applying microwave fields for gate durations of 50 ns, with errors approaching the limit of intrinsic transmon coherence. Our systematic quantum optimal control approach is easily adapted to explore the parameter landscape of other quantum technology platforms.
Mucoadhesive controlled release microcapsules of indomethacin: optimization and stability study.
Ibrahim, Hany M; Ahmed, Tarek A; Lila, Ahmed E A; Samy, Ahmed M; Kaseem, Ala A; Nutan, Mohammad T H
2010-01-01
The aim of this project was to develop and optimize indomethacin microcapsules composed of multiple mucoadhesive polymers for high drug entrapment, good mucoadhesiveness and drug release in a controlled fashion over a longer period of time. Microcapsules containing sodium alginate, sodium carboxymethylcellulose, methylcellulose, Carbopol 934 and hydroxypropyl methylcellulose were prepared by orifice-ionic gelation method. The effects of composition of microcapsules on drug entrapment efficacy, drug release and mucoadhesive character were determined by mixture statistical design. Most formulations exhibited good mucoadhesive property in everted intestinal sac test. Drug entrapment efficiency (68-94%) was dependent on the type of polymers. Drug release (92-100%) extended over 12 h. The optimized formulation resulted in drug entrapment efficiency of 89.3%, drug release of 94.8% and mucoadhesiveness of 30.4%. All formulations were stable for more than 1.5 years. The optimized mucoadhesive microcapsules are promising for controlled delivery of indomethacin with twice a day oral administration.
Quantum optimal control theory applied to transitions in diatomic molecules
Lysebo, Marius; Veseth, Leif
2014-12-01
Quantum optimal control theory is applied to control electric dipole transitions in a real multilevel system. The specific system studied in the present work is comprised of a multitude of hyperfine levels in the electronic ground state of the OH molecule. Spectroscopic constants are used to obtain accurate energy eigenstates and electric dipole matrix elements. The goal is to calculate the optimal time-dependent electric field that yields a maximum of the transition probability for a specified initial and final state. A further important objective was to study the detailed quantum processes that take place during such a prescribed transition in a multilevel system. Two specific transitions are studied in detail. The computed optimal electric fields as well as the paths taken through the multitude of levels reveal quite interesting quantum phenomena.
Learning the optimal control of coordinated eye and head movements.
Directory of Open Access Journals (Sweden)
Sohrab Saeb
2011-11-01
Full Text Available Various optimality principles have been proposed to explain the characteristics of coordinated eye and head movements during visual orienting behavior. At the same time, researchers have suggested several neural models to underly the generation of saccades, but these do not include online learning as a mechanism of optimization. Here, we suggest an open-loop neural controller with a local adaptation mechanism that minimizes a proposed cost function. Simulations show that the characteristics of coordinated eye and head movements generated by this model match the experimental data in many aspects, including the relationship between amplitude, duration and peak velocity in head-restrained and the relative contribution of eye and head to the total gaze shift in head-free conditions. Our model is a first step towards bringing together an optimality principle and an incremental local learning mechanism into a unified control scheme for coordinated eye and head movements.
Charting the circuit QED design landscape using optimal control theory
DEFF Research Database (Denmark)
Goerz, Michael H.; Motzoi, Felix; Whaley, K. Birgitta
2017-01-01
control techniques, we exhaustively explore the landscape for creation and removal of entanglement over a wide range of design parameters. We identify an optimal operating region outside of the usually considered strongly dispersive regime, where multiple sources of entanglement interfere simultaneously......, which we name the quasi-dispersive straddling qutrits regime. At a chosen point in this region, a universal gate set is realized by applying microwave fields for gate durations of 50 ns, with errors approaching the limit of intrinsic transmon coherence. Our systematic quantum optimal control approach......With recent improvements in coherence times, superconducting transmon qubits have become a promising platform for quantum computing. They can be flexibly engineered over a wide range of parameters, but also require us to identify an efficient operating regime. Using state-of-the-art quantum optimal...
Numerical aspects of optimal control of penicillin production.
Pčolka, Matej; Celikovský, Sergej
2014-01-01
Since their discovery, fermentation processes have gone along not only with the industrial beverages production and breweries, but since the times of Alexander Fleming, they have become a crucial part of the health care due to antibiotics production. However, complicated dynamics and strong nonlinearities cause that the production with the use of linear control methods achieves only suboptimal yields. From the variety of nonlinear approaches, gradient method has proved the ability to handle these issues--nevertheless, its potential in the field of fermentation processes has not been revealed completely. This paper describes constant vaporization control strategy based on a double-input optimization approach with a successful reduction to a single-input optimization task. To accomplish this, model structure used in the previous work is modified so that it corresponds with the new optimization strategy. Furthermore, choice of search step is explored and various alternatives are evaluated and compared.
Health benefit modelling and optimization of vehicular pollution control strategies
Sonawane, Nayan V.; Patil, Rashmi S.; Sethi, Virendra
2012-12-01
This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific
Improved Sensitivity Relations in State Constrained Optimal Control
Energy Technology Data Exchange (ETDEWEB)
Bettiol, Piernicola, E-mail: piernicola.bettiol@univ-brest.fr [Université de Bretagne Occidentale, Laboratoire de Mathematiques (France); Frankowska, Hélène, E-mail: frankowska@math.jussieu.fr [Université Pierre et Marie Curie (Paris 6), CNRS and Institut de Mathématiques de Jussieu (France); Vinter, Richard B., E-mail: r.vinter@imperial.ac.uk [Imperial College London, Department of Electrical and Electronic Engineering (United Kingdom)
2015-04-15
Sensitivity relations in optimal control provide an interpretation of the costate trajectory and the Hamiltonian, evaluated along an optimal trajectory, in terms of gradients of the value function. While sensitivity relations are a straightforward consequence of standard transversality conditions for state constraint free optimal control problems formulated in terms of control-dependent differential equations with smooth data, their verification for problems with either pathwise state constraints, nonsmooth data, or for problems where the dynamic constraint takes the form of a differential inclusion, requires careful analysis. In this paper we establish validity of both ‘full’ and ‘partial’ sensitivity relations for an adjoint state of the maximum principle, for optimal control problems with pathwise state constraints, where the underlying control system is described by a differential inclusion. The partial sensitivity relation interprets the costate in terms of partial Clarke subgradients of the value function with respect to the state variable, while the full sensitivity relation interprets the couple, comprising the costate and Hamiltonian, as the Clarke subgradient of the value function with respect to both time and state variables. These relations are distinct because, for nonsmooth data, the partial Clarke subdifferential does not coincide with the projection of the (full) Clarke subdifferential on the relevant coordinate space. We show for the first time (even for problems without state constraints) that a costate trajectory can be chosen to satisfy the partial and full sensitivity relations simultaneously. The partial sensitivity relation in this paper is new for state constraint problems, while the full sensitivity relation improves on earlier results in the literature (for optimal control problems formulated in terms of Lipschitz continuous multifunctions), because a less restrictive inward pointing hypothesis is invoked in the proof, and because
Control theoretic splines optimal control, statistical, and path planning
Egerstedt, Magnus
2010-01-01
Splines, both interpolatory and smoothing, have a long and rich history that has largely been application driven. This book unifies these constructions in a comprehensive and accessible way, drawing from the latest methods and applications to show how they arise naturally in the theory of linear control systems. Magnus Egerstedt and Clyde Martin are leading innovators in the use of control theoretic splines to bring together many diverse applications within a common framework. In this book, they begin with a series of problems ranging from path planning to statistics to approximation.
Control and Optimization of Network in Networked Control System
Directory of Open Access Journals (Sweden)
Wang Zhiwen
2014-01-01
Full Text Available In order to avoid quality of performance (QoP degradation resulting from quality of service (QoS, the solution to network congestion from the point of control theory, which marks departure of our results from the existing methods, is proposed in this paper. The congestion and bandwidth are regarded as state and control variables, respectively; then, the linear time-invariant (LTI model between congestion state and bandwidth of network is established. Consequently, linear quadratic method is used to eliminate the network congestion by allocating bandwidth dynamically. At last, numerical simulation results are given to illustrate the effectiveness of this modeling approach.
Turnpike theory of continuous-time linear optimal control problems
Zaslavski, Alexander J
2015-01-01
Individual turnpike results are of great interest due to their numerous applications in engineering and in economic theory; in this book the study is focused on new results of turnpike phenomenon in linear optimal control problems. The book is intended for engineers as well as for mathematicians interested in the calculus of variations, optimal control, and in applied functional analysis. Two large classes of problems are studied in more depth. The first class studied in Chapter 2 consists of linear control problems with periodic nonsmooth convex integrands. Chapters 3-5 consist of linear control problems with autonomous nonconvex and nonsmooth integrands. Chapter 6 discusses a turnpike property for dynamic zero-sum games with linear constraints. Chapter 7 examines genericity results. In Chapter 8, the description of structure of variational problems with extended-valued integrands is obtained. Chapter 9 ends the exposition with a study of turnpike phenomenon for dynamic games with extended value integran...
Photovoltaic Inverter Controllers Seeking AC Optimal Power Flow Solutions
Energy Technology Data Exchange (ETDEWEB)
Dall' Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.
2016-07-01
This paper considers future distribution networks featuring inverter-interfaced photovoltaic (PV) systems, and addresses the synthesis of feedback controllers that seek real- and reactive-power inverter setpoints corresponding to AC optimal power flow (OPF) solutions. The objective is to bridge the temporal gap between long-term system optimization and real-time inverter control, and enable seamless PV-owner participation without compromising system efficiency and stability. The design of the controllers is grounded on a dual ..epsilon..-subgradient method, while semidefinite programming relaxations are advocated to bypass the non-convexity of AC OPF formulations. Global convergence of inverter output powers is analytically established for diminishing stepsize rules for cases where: i) computational limits dictate asynchronous updates of the controller signals, and ii) inverter reference inputs may be updated at a faster rate than the power-output settling time.
Understanding optimal control results by reducing the complexity
Energy Technology Data Exchange (ETDEWEB)
Bartelt, Andreas F. [Lawrence Berkeley National Laboratory (LBNL), Advanced Light Source, 1 Cyclotron Road, Berkeley, CA 94720 (United States)], E-mail: afbartelt@lbl.gov; Feurer, Thomas [Institute of Applied Physics, University of Bern, Sidlerstr. 5, 3012 Bern (Switzerland); Woeste, Ludger [Institute of Experimental Physics, Free University of Berlin, Arnimallee 14, D-14195 Berlin (Germany)
2005-11-22
Deciphering control mechanisms from control pulse structures found in closed-loop learning experiments is often complicated due to the complexity of the pulse structure. Simplification of pulse forms is demonstrated by systematically reducing the complexity of the search space, applied on the model-like multi-photon ionization of NaK. Reducing the pulse complexity leads to the exclusion of participating excited states, thereby restricting the involved pathways. The phase function is parameterized by a sinusoidal spectral phase modulation, whose parameters are investigated with respect to the yield and the obtained optimal field. By progressively reducing the number of parameters and thereby the complexity of the phase modulation, control pulses are generated which are more and more reduced to the molecule's primary dynamical properties. This enables to find optimized control pulses that can be subject to a simple intuitive interpretation.
Discover for Yourself: An Optimal Control Model in Insect Colonies
Winkel, Brian
2013-01-01
We describe the enlightening path of self-discovery afforded to the teacher of undergraduate mathematics. This is demonstrated as we find and develop background material on an application of optimal control theory to model the evolutionary strategy of an insect colony to produce the maximum number of queen or reproducer insects in the colony at…
A "Hybrid" Approach for Synthesizing Optimal Controllers of Hybrid Systems
DEFF Research Database (Denmark)
Zhao, Hengjun; Zhan, Naijun; Kapur, Deepak
2012-01-01
We propose an approach to reduce the optimal controller synthesis problem of hybrid systems to quantifier elimination; furthermore, we also show how to combine quantifier elimination with numerical computation in order to make it more scalable but at the same time, keep arising errors due...
Planning Framework for Mesolevel Optimization of Urban Runoff Control Schemes
Energy Technology Data Exchange (ETDEWEB)
Zhou, Qianqian; Blohm, Andrew; Liu, Bo
2017-04-01
A planning framework is developed to optimize runoff control schemes at scales relevant for regional planning at an early stage. The framework employs less sophisticated modeling approaches to allow a practical application in developing regions with limited data sources and computing capability. The methodology contains three interrelated modules: (1)the geographic information system (GIS)-based hydrological module, which aims at assessing local hydrological constraints and potential for runoff control according to regional land-use descriptions; (2)the grading module, which is built upon the method of fuzzy comprehensive evaluation. It is used to establish a priority ranking system to assist the allocation of runoff control targets at the subdivision level; and (3)the genetic algorithm-based optimization module, which is included to derive Pareto-based optimal solutions for mesolevel allocation with multiple competing objectives. The optimization approach describes the trade-off between different allocation plans and simultaneously ensures that all allocation schemes satisfy the minimum requirement on runoff control. Our results highlight the importance of considering the mesolevel allocation strategy in addition to measures at macrolevels and microlevels in urban runoff management. (C) 2016 American Society of Civil Engineers.
Structural analysis of complex ecological economic optimal control problems
Kiseleva, T.
2011-01-01
This thesis demonstrates the importance and effectiveness of methods of bifurcation theory applied to studying non-convex optimal control problems. It opens up a new methodological approach to investigation of parameterized economic models. While standard analytical methods are not efficient and
Optimal Control of Beer Fermentation Process Using Differential ...
African Journals Online (AJOL)
ADOWIE PERE
Optimal Control of Beer Fermentation Process. 753. SHEHU, MD; JIYA, M; ELEBUTE, KO; AHMED, HO. Table 1: Description of State Parameter Used in the Model. Parameters. Description. Unit. µ. Ethanol production rate. 1 h− γ. Specific rate of latent fermentation. 1 h− α. Specific yeast settling down rate. /g l δ. Ethyl acetate ...
The Relationship between Pupil Control Ideology and Academic Optimism
Gilbert, Michael J.
2012-01-01
This study investigates the relationship between pupil control ideology and academic optimism. Information was generated through responses to a questionnaire emailed to teachers in two school districts in Central New Jersey. The districts were categorized GH, as determined by the State's district factor grouping. The research concludes that there…
Optimal Control of Diesel Engines with Waste Heat Recovery System
Willems, F.P.T.; Donkers, M.C.F.; Kupper, F.
2014-01-01
This study presents an integrated energy and emission management strategy for a Euro-VI diesel engine with Waste Heat Recovery (WHR) system. This Integrated Powertrain Control (IPC) strategy optimizes the CO2-NOx trade-off by minimizing the operational costs associated with fuel and AdBlue
A hybrid iterative scheme for optimal control problems governed by ...
African Journals Online (AJOL)
This paper presents an iterative approach based on hybrid of perturbation and parametrization methods for obtaining approximate solutions of optimal control problems governed by some Fredholm integral equations. By some numerical examples, it is emphasized that this scheme is very effective and it produces ...
Real-Time Optimization for Economic Model Predictive Control
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Edlund, Kristian; Frison, Gianluca
2012-01-01
In this paper, we develop an efficient homogeneous and self-dual interior-point method for the linear programs arising in economic model predictive control. To exploit structure in the optimization problems, the algorithm employs a highly specialized Riccati iteration procedure. Simulations show...
An optimal control framework for estimating autopilot safety margins
Govindarjan, N.; De Visser, C.C.; Van Kampen, E.; Krishnakumar, K.; Barlow, J.; Stepanyan, V.
2014-01-01
This paper presents an optimal control framework to determine a collection of open-loop command signals that mathematically guarantees operation of an aircraft within certain prescribed state constraints. The framework is specifically applied to estimate margins for the reference command inputs of
Robust time-optimal control of uncertain structural dynamic systems
Wie, Bong; Sinha, Ravi; Liu, Qiang
1993-01-01
A time-optimal open-loop control problem of flexible spacecraft in the presence of modeling uncertainty has been investigated. The results indicate that the proposed approach significantly reduces the residual structural vibrations caused by modeling uncertainty. The results also indicate the importance of proper jet placement for practical tradeoffs among the maneuvering time, fuel consumption, and performance robustness.
Optimal adaptive scheduling and control of beer membrane filtration
Willigenburg, van L.G.; Vollebregt, H.M.; Sman, van der R.G.M.
2015-01-01
An adaptive optimal scheduling and controller design is presented that attempts to improve the performance of beer membrane filtration over the ones currently obtained by operators. The research was performed as part of a large European research project called EU Cafe with the aim to investigate the
Optimal control of neutral systems with nonlinear base (The ...
African Journals Online (AJOL)
By a careful analysis of the maximum principle, necessary and sufficient conditions for the existence and uniqueness of optimal controls are deduced. This work is a great improvement of existing works providing a relationship between the attainable and reachable sets. JONAMP Vol. 11 2007: pp.269-274 ...
Optimal interventions to control campylobacter in broilers in Denmark
DEFF Research Database (Denmark)
Rosenquist, Hanne; Sommer, Helle Mølgaard; Bodil Hald, Anna
In a multi disciplinary project we have evaluated interventions against Campylobacter in the broiler production chain. Taking into account risk reduction, costs, practicability and public acceptance of decontamination, it was concluded that at present the optimal control measure for the Danish si...... situation is screening broiler houses with fly nets....
Efficient Approximation of Optimal Control for Markov Games
DEFF Research Database (Denmark)
Fearnley, John; Rabe, Markus; Schewe, Sven
2011-01-01
We study the time-bounded reachability problem for continuous-time Markov decision processes (CTMDPs) and games (CTMGs). Existing techniques for this problem use discretisation techniques to break time into discrete intervals, and optimal control is approximated for each interval separately...
On the application of Discrete Time Optimal Control Concepts to ...
African Journals Online (AJOL)
An extension of the use of the maximum principle to solve Discrete-time Optimal Control Problems (DTOCP), in which the state equations are in the form of general equations, rather than difference equations has been examined. Comparing the previous maximum principle to the proposed, revealed that the only difference, ...
Optimizing a mobile robot control system using GPU acceleration
Tuck, Nat; McGuinness, Michael; Martin, Fred
2012-01-01
This paper describes our attempt to optimize a robot control program for the Intelligent Ground Vehicle Competition (IGVC) by running computationally intensive portions of the system on a commodity graphics processing unit (GPU). The IGVC Autonomous Challenge requires a control program that performs a number of different computationally intensive tasks ranging from computer vision to path planning. For the 2011 competition our Robot Operating System (ROS) based control system would not run comfortably on the multicore CPU on our custom robot platform. The process of profiling the ROS control program and selecting appropriate modules for porting to run on a GPU is described. A GPU-targeting compiler, Bacon, is used to speed up development and help optimize the ported modules. The impact of the ported modules on overall performance is discussed. We conclude that GPU optimization can free a significant amount of CPU resources with minimal effort for expensive user-written code, but that replacing heavily-optimized library functions is more difficult, and a much less efficient use of time.
Optimal control problem for the extended Fisher–Kolmogorov equation
Indian Academy of Sciences (India)
the long-time behavior of solution to the extended Fisher–Kolmogorov equation. We also noticed that some investigations of the Fisher–Kolmogorov equation were studied, such as in [2, 5, 7, 10, 17] and so on. In past decades, the optimal control of distributed parameter system had received much attention in the academic ...
Optimal Model-Based Control in HVAC Systems
DEFF Research Database (Denmark)
Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik
2008-01-01
This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system...
An Optimal Control Scheme to Minimize Loads in Wind Farms
DEFF Research Database (Denmark)
Soleimanzadeh, Maryam; Wisniewski, Rafal
2012-01-01
This work presents a control algorithm for wind farms that optimizes the power production of the farm and helps to increase the lifetime of wind turbines components. The control algorithm is a centralized approach, and it determines the power reference signals for individual wind turbines...... such that the structural loads of the wind turbines in low frequencies are reduced. The controller is relatively easy to implement on a wind farm, and in here the results of simulating the controller on a small wind farm is presented....
Optimization Settings in the Fuzzy Combined Mamdani PID Controller
Kudinov, Y. I.; Pashchenko, F. F.; Pashchenko, A. F.; Kelina, A. Y.; Kolesnikov, V. A.
2017-11-01
In the present work the actual problem of determining the optimal settings of fuzzy parallel proportional-integral-derivative (PID) controller is considered to control nonlinear plants that is not always possible to perform with classical linear PID controllers. In contrast to the linear fuzzy PID controllers there are no analytical methods of settings calculation. In this paper, we develop a numerical optimization approach to determining the coefficients of a fuzzy PID controller. Decomposition method of optimization is proposed, the essence of which was as follows. All homogeneous coefficients were distributed to the relevant groups, for example, three error coefficients, the three coefficients of the changes of errors and the three coefficients of the outputs P, I and D components. Consistently in each of such groups the search algorithm was selected that has determined the coefficients under which we receive the schedule of the transition process satisfying all the applicable constraints. Thus, with the help of Matlab and Simulink in a reasonable time were found the factors of a fuzzy PID controller, which meet the accepted limitations on the transition process.
Optimal control analysis of the dynamic growth behavior of microorganisms.
Mandli, Aravinda R; Modak, Jayant M
2014-12-01
Understanding the growth behavior of microorganisms using modeling and optimization techniques is an active area of research in the fields of biochemical engineering and systems biology. In this paper, we propose a general modeling framework, based on Monod model, to model the growth of microorganisms. Utilizing the general framework, we formulate an optimal control problem with the objective of maximizing a long-term cellular goal and solve it analytically under various constraints for the growth of microorganisms in a two substrate batch environment. We investigate the relation between long term and short term cellular goals and show that the objective of maximizing cellular concentration at a fixed final time is equivalent to maximization of instantaneous growth rate. We then establish the mathematical connection between the generalized framework and optimal and cybernetic modeling frameworks and derive generalized governing dynamic equations for optimal and cybernetic models. We finally illustrate the influence of various constraints in the cybernetic modeling framework on the optimal growth behavior of microorganisms by solving several dynamic optimization problems using genetic algorithms. Copyright © 2014. Published by Elsevier Inc.
Genetic algorithms for optimal design and control of adaptive structures
Ribeiro, Rui; da Mota Silva, Suzana; Rodrigues, Jose D.; Vaz, Mario A. P.
2000-06-01
Future High Energy Physics experiments require the use of light and stable structures to support their most precise radiation detection elements. These large structures must be light, highly stable, stiff and radiation tolerant in an environment where external vibrations, high radiation levels, material aging, temperature and humidity gradients are not negligible. Unforeseen factors and the unknown result of the coupling of environmental conditions, together with external vibrations, may affect the position stability of the detectors and their support structures compromising their physics performance. Careful optimization of static and dynamic behavior must be an essential part of the engineering design. Genetic Algorithms (GA) belong to the group of probabilistic algorithms, combining elements of direct and stochastic search. They are more robust than existing directed search methods with the advantage of maintaining a population of potential solutions. There is a class of optimization problems for which Genetic Algorithms can be effectively applied. Among them are the ones related to shape control and optimal placement of sensors/actuators for active control of vibrations. In this paper these two problems are addressed and numerically investigated. The finite element method is used for the analysis of the dynamic characteristics. For the case of the optimal placement of sensors/actuators a performance index, proportional to the damping of the system in closed- loop, is used. Genetic algorithms prove their efficiency in this kind of optimization problems.
Optimal control of batch emulsion polymerization of vinyl chloride
Energy Technology Data Exchange (ETDEWEB)
Damslora, Andre Johan
1998-12-31
The highly exothermic polymerization of vinyl chloride (VC) is carried out in large vessels where the heat removal represents a major limitation of the production rate. Many emulsion polymerization reactors are operated in such a way that a substantial part of the heat transfer capacity is left unused for a significant part of the total batch time. To increase the reaction rate so that it matches the heat removal capacity during the course of the reaction, this thesis proposes the use of a sufficiently flexible initiator system to obtain a reaction rate which is high throughout the reaction and real-time optimization to compute the addition policy for the initiator. This optimization based approach provides a basis for an interplay between design and control and between production and research. A simple model is developed for predicting the polymerization rate. The model is highly nonlinear and open-loop unstable and may serve as an interesting case for comparison of nonlinear control strategies. The model is fitted to data obtained in a laboratory scale reactor. Finally, the thesis discusses optimal control of the emulsion polymerization reactor. Reduction of the batch cycle time is of major economic importance, as long as the quality parameters are within their specifications. The control parameterization had a major influence on the performance. A differentiable spline parameterization was applied and the optimization is illustrated in a number of cases. The best performance is obtained when the reactor temperature is obtained when the optimization is combined with some form of closed-loop control of the reactor temperature. 112 refs., 48 figs., 4 tabs.
Kanazawa, Koichi; Koike, Yuji; Metz, Andreas; Pitonyak, Daniel
2014-06-01
We study the transverse single-spin asymmetry for single-hadron production in proton-proton collisions within the framework of collinear twist-3 factorization in quantum chromodynamics. By taking into account the contribution due to parton fragmentation, we obtain a very good description of all high transverse-momentum data for neutral and charged pion production from the Relativistic Heavy Ion Collider. Our study may provide the crucial step toward a final solution to the long-standing problem of what causes transverse single-spin asymmetries in hadronic collisions within quantum chromodynamics. We show for the first time that it is possible to simultaneously describe spin/azimuthal asymmetries in proton-proton collisions, semi-inclusive deep-inelastic scattering, and electron-positron annihilation by using collinear twist-3 factorization in the first process along with transverse-momentum-dependent functions extracted from the latter two reactions.
Optimal Backlight Modulation With Crosstalk Control in Stereoscopic Display
DEFF Research Database (Denmark)
Jiao, Liangbao; Shu, Xiao; Cheng, Yong
2014-01-01
Crosstalk between the left-eye and right-eye images is one of the main artifacts affecting the visual quality of stereoscopic liquid crystal display (LCD) systems. In this paper, a novel technique, called Optimal Backlight Modulation (OBM), is proposed to reduce crosstalk by taking the advantage....... A simple closed-form approximation of the optimization problem can be easily employed and solved in real time on LCD control hardware. Simulation results show that the proposed OBM algorithm provides the same or higher luminance while reducing the crosstalk by 60% compared with the other tested methods....
Amplification of the parametric dynamical Casimir effect via optimal control
Hoeb, Fabian; Angaroni, Fabrizio; Zoller, Jonathan; Calarco, Tommaso; Strini, Giuliano; Montangero, Simone; Benenti, Giuliano
2017-09-01
We introduce different strategies to enhance photon generation in a cavity within the Rabi model in the ultrastrong coupling regime. We show that a bang-bang strategy allows one to enhance the effect up to 1 order of magnitude with respect to simply driving the system in resonance for a fixed time. Moreover, up to about another order of magnitude can be gained by exploiting quantum optimal control strategies. Finally, we show that such optimized protocols are robust with respect to systematic errors and noise, paving the way to future experimental implementations of such strategies.
Modelling of Rabies Transmission Dynamics Using Optimal Control Analysis
Directory of Open Access Journals (Sweden)
Joshua Kiddy K. Asamoah
2017-01-01
Full Text Available We examine an optimal way of eradicating rabies transmission from dogs into the human population, using preexposure prophylaxis (vaccination and postexposure prophylaxis (treatment due to public education. We obtain the disease-free equilibrium, the endemic equilibrium, the stability, and the sensitivity analysis of the optimal control model. Using the Latin hypercube sampling (LHS, the forward-backward sweep scheme and the fourth-order Range-Kutta numerical method predict that the global alliance for rabies control’s aim of working to eliminate deaths from canine rabies by 2030 is attainable through mass vaccination of susceptible dogs and continuous use of pre- and postexposure prophylaxis in humans.
Optimal Charge control of Electric Vehicles in Electricity Markets
DEFF Research Database (Denmark)
Lan, Tian; Hu, Junjie; Wu, Guang
2011-01-01
Environment constraints, petroleum scarcity, high price on fuel resources and recent advancements in battery technology have led to emergence of Electric Vehicles (EVs). As increasing numbers of EVs enter the electricity market, these extra loads may cause peak load and need to be properly...... controlled. In this paper, an algorithm is presented for every individual vehicles to minimize the charging cost while satisfying the vehicle owner’s requirements. The algorithm is based on a given future electricity prices and uses dynamic programming. Optimization aims to find the economically optimal...... solution for each vehicle....
Price-based Optimal Control of Electrical Power Systems
Energy Technology Data Exchange (ETDEWEB)
Jokic, A.
2007-09-10
The research presented in this thesis is motivated by the following issue of concern for the operation of future power systems: Future power systems will be characterized by significantly increased uncertainties at all time scales and, consequently, their behavior in time will be difficult to predict. In Chapter 2 we will present a novel explicit, dynamic, distributed feedback control scheme that utilizes nodal-prices for real-time optimal power balance and network congestion control. The term explicit means that the controller is not based on solving an optimization problem on-line. Instead, the nodal prices updates are based on simple, explicitly defined and easily comprehensible rules. We prove that the developed control scheme, which acts on the measurements from the current state of the system, always provide the correct nodal prices. In Chapter 3 we will develop a novel, robust, hybrid MPC control (model predictive controller) scheme for power balance control with hard constraints on line power flows and network frequency deviations. The developed MPC controller acts in parallel with the explicit controller from Chapter 2, and its task is to enforce the constraints during the transient periods following suddenly occurring power imbalances in the system. In Chapter 4 the concept of autonomous power networks will be presented as a concise formulation to deal with economic, technical and reliability issues in power systems with a large penetration of distributed generating units. With autonomous power networks as new market entities, we propose a novel operational structure of ancillary service markets. In Chapter 5 we will consider the problem of controlling a general linear time-invariant dynamical system to an economically optimal operating point, which is defined by a multiparametric constrained convex optimization problem related with the steady-state operation of the system. The parameters in the optimization problem are values of the exogenous inputs to
PID controller tuning using metaheuristic optimization algorithms for benchmark problems
Gholap, Vishal; Naik Dessai, Chaitali; Bagyaveereswaran, V.
2017-11-01
This paper contributes to find the optimal PID controller parameters using particle swarm optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm. The algorithms were developed through simulation of chemical process and electrical system and the PID controller is tuned. Here, two different fitness functions such as Integral Time Absolute Error and Time domain Specifications were chosen and applied on PSO, GA and SA while tuning the controller. The proposed Algorithms are implemented on two benchmark problems of coupled tank system and DC motor. Finally, comparative study has been done with different algorithms based on best cost, number of iterations and different objective functions. The closed loop process response for each set of tuned parameters is plotted for each system with each fitness function.
Smart helicopter rotors optimization and piezoelectric vibration control
Ganguli, Ranjan; Viswamurthy, Sathyamangalam Ramanarayanan
2016-01-01
Exploiting the properties of piezoelectric materials to minimize vibration in rotor-blade actuators, this book demonstrates the potential of smart helicopter rotors to achieve the smoothness of ride associated with jet-engined, fixed-wing aircraft. Vibration control is effected using the concepts of trailing-edge flaps and active-twist. The authors’ optimization-based approach shows the advantage of multiple trailing-edge flaps and algorithms for full-authority control of dual trailing-edge-flap actuators are presented. Hysteresis nonlinearity in piezoelectric stack actuators is highlighted and compensated by use of another algorithm. The idea of response surfaces provides for optimal placement of trailing-edge flaps. The concept of active twist involves the employment of piezoelectrically induced shear actuation in rotating beams. Shear is then demonstrated for a thin-walled aerofoil-section rotor blade under feedback-control vibration minimization. Active twist is shown to be significant in reducing vibra...
High-fidelity quantum state preparation using neighboring optimal control
Peng, Yuchen; Gaitan, Frank
2017-10-01
We present an approach to single-shot high-fidelity preparation of an n-qubit state based on neighboring optimal control theory. This represents a new application of the neighboring optimal control formalism which was originally developed to produce single-shot high-fidelity quantum gates. To illustrate the approach, and to provide a proof-of-principle, we use it to prepare the two-qubit Bell state |β _{01}\\rangle = (1/√{2})[ |01\\rangle + |10\\rangle ] with an error probability ɛ ˜ 10^{-6} (10^{-5}) for ideal (non-ideal) control. Using standard methods in the literature, these high-fidelity Bell states can be leveraged to fault-tolerantly prepare the logical state |\\overline{β }_{01}\\rangle.
Locally optimal symplectic control of multimode Gaussian states
Shackerley-Bennett, Uther; Carlini, Alberto; Giovannetti, Vittorio; Serafini, Alessio
2017-12-01
The relaxation of a system to a steady state is a central point of interest in many attempts to advance control over the quantum world. In this paper, we consider control through instantaneous Gaussian unitary operations on the ubiquitous lossy channel, and find locally optimal conditions for the cooling and heating of a multimode Gaussian state subject to losses and possibly thermal noise. This is done by isolating the parameters that encode entropy and temperature and by deriving an equation for their evolution. This equation is in such a form that it grants clear insight into how relaxation may be helped by instantaneous quantum control. It is thus shown that squeezing is a crucial element in optimising the rate of change of entropic properties under these channels. Exact relaxation times for heating and cooling are derived, up to an arbitrarily small distance from the fixed point of the lossy channel with locally optimal strategies.
Stochastic optimal control of single neuron spike trains
DEFF Research Database (Denmark)
Iolov, Alexandre; Ditlevsen, Susanne; Longtin, Andrë
2014-01-01
Objective. External control of spike times in single neurons can reveal important information about a neuron's sub-threshold dynamics that lead to spiking, and has the potential to improve brain–machine interfaces and neural prostheses. The goal of this paper is the design of optimal electrical...... stimulation of a neuron to achieve a target spike train under the physiological constraint to not damage tissue. Approach. We pose a stochastic optimal control problem to precisely specify the spike times in a leaky integrate-and-fire (LIF) model of a neuron with noise assumed to be of intrinsic or synaptic...... of control degrades with increasing intensity of the noise. Simulations show that our algorithms produce the desired results for the LIF model, but also for the case where the neuron dynamics are given by more complex models than the LIF model. This is illustrated explicitly using the Morris–Lecar spiking...
Direct computation of optimal control of forced linear system
Utku, S.; Kuo, C.-P.; Salama, M.
1985-01-01
It is known that the optimal control of a forced linear system may be reduced to that of tracking the system without forces. The solution of the tracking problem is available via the costate variables method. This procedure is computationally expensive for large order systems. It requires solution of matrix Riccati equation and two final value problems. An alternate approach is outlined for the direct computation of the optimal control. Instead of Riccati equation, a matrix Volterra integral must be solved. For this purpose two computational schemes are described, and an illustrative example is given. The results compare favorably with the classical solution. This alternative approach may be especially useful for the control of large space structure where large order models are required.
Dynamics of underactuated multibody systems modeling, control and optimal design
Seifried, Robert
2014-01-01
Underactuated multibody systems are intriguing mechatronic systems, as they possess fewer control inputs than degrees of freedom. Some examples are modern light-weight flexible robots and articulated manipulators with passive joints. This book investigates such underactuated multibody systems from an integrated perspective. This includes all major steps from the modeling of rigid and flexible multibody systems, through nonlinear control theory, to optimal system design. The underlying theories and techniques from these different fields are presented using a self-contained and unified approach and notation system. Subsequently, the book focuses on applications to large multibody systems with multiple degrees of freedom, which require a combination of symbolical and numerical procedures. Finally, an integrated, optimization-based design procedure is proposed, whereby both structural and control design are considered concurrently. Each chapter is supplemented by illustrated examples.
Optimal control in a model of malaria with differential susceptibility
Hincapié, Doracelly; Ospina, Juan
2014-06-01
A malaria model with differential susceptibility is analyzed using the optimal control technique. In the model the human population is classified as susceptible, infected and recovered. Susceptibility is assumed dependent on genetic, physiological, or social characteristics that vary between individuals. The model is described by a system of differential equations that relate the human and vector populations, so that the infection is transmitted to humans by vectors, and the infection is transmitted to vectors by humans. The model considered is analyzed using the optimal control method when the control consists in using of insecticide-treated nets and educational campaigns; and the optimality criterion is to minimize the number of infected humans, while keeping the cost as low as is possible. One first goal is to determine the effects of differential susceptibility in the proposed control mechanism; and the second goal is to determine the algebraic form of the basic reproductive number of the model. All computations are performed using computer algebra, specifically Maple. It is claimed that the analytical results obtained are important for the design and implementation of control measures for malaria. It is suggested some future investigations such as the application of the method to other vector-borne diseases such as dengue or yellow fever; and also it is suggested the possible application of free software of computer algebra like Maxima.
Synthesis of optimal digital controller of flocculant dosing
Directory of Open Access Journals (Sweden)
A.V. Pismenskiy
2013-06-01
Full Text Available Purpose. The task of automatic process control of the slime water thickening and flotation tailings clarification is the stabilization of thicken product density within the given range and keeping up the solids content in the overflow not above the permissible level with minimum use of the flocculants. In existing systems for automatic control the flocculant dosing is carried out according to the solids content in the device input (the principle of open-loop control. This leads to the excess consumption of the flocculants and increase the dispersion density of the overflow. To perform the synthesis of the optimal digital controller in order to minimize the deviations from the master control and ensure the specified quality of the transition process. Over controlling value should not exceed 5 %. To perform the system operation modeling in order to determine the quality of transient processes. Methodology. Synthesis of the optimal digital controller is based on the method of dynamic programming. Findings. A mathematical model of the object control is represented in the normal form of Cauchy and further in the form of differential equations. The optimum period of quantization as the function from specified error of control and the output coordinate change is calculated. The differential equation of Bellman is obtained and the condition for minimization of the quality functional. Bellman function is represented as a quadratic form from the variables of the system condition. In order to limit possible control, the weight coefficients of the functional are calculated based on maximum permitted values of the system condition variables and the control actions during the transient process. Practical value. Using the modeling of ACS of the flocculant dosing it was established that the over controlling amount is 3.5%, the transient process life 5.6 sec, the transient process is aperiodical, non-static control, which meets the requirements imposed on the
Energy Technology Data Exchange (ETDEWEB)
Zhang, Yawei [Rutgers
2013-10-01
A measurement of the inclusive target single-spin asymmetry has been performed using the quasi-elastic {sup 3}He{up_arrow}(e,e') reaction with a vertically polarized {sup 3}He target at Q{sup 2} values of 0.13, 0.46 and 0.97 GeV{sup 2}. This asymmetry vanishes under the one photon exchange assumption. But the interference between two-photon exchange and one-photon exchange gives rise to an imaginary amplitude, so that a non-zero A{sub y} is allowed. The experiment, conducted in Hall A of Jefferson Laboratory in 2009, used two independent spectrometers to simultaneously measure the target single-spin asymmetry. Using the effective polarization approximation, the neutron single-spin asymmetries were extracted from the measured {sup 3}He asymmetries. The measurement is to establish a non-vanishing A{sub y}. Non-zero asymmetries were observed at all Q{sup 2} points, and the overall precision is an order of magnitude improved over the existing proton data. The data provide new constraints on Generalized Parton Distribution (GPD) models and new information on the dynamics of the two-photon exchange process.
Optimal Stochastic Modeling and Control of Flexible Structures
1988-09-01
Multivariate Stationary Gaussian Processes," SIAM J-control and Optimization, Vol. 23, No. 6, Nov. 1985. 1.14. George Adomian , Stochastic Systems...Systems Whose Coefficients are Functions of Param- eters," IEEE Trans. on Automatic Control, Vol. AC-29, No. 1, Jan. 1984. 1.52. G. Adomian and L.h...Automation and Remote Control, No. 2, February, No. 3, March, pp. 5-19, 1984. 2.3. George Adomian , Stochastic Systems, Academic Press, N.Y., 1983. 2.4. Peter S
Vision-based stereo ranging as an optimal control problem
Menon, P. K. A.; Sridhar, B.; Chatterji, G. B.
1992-01-01
The recent interest in the use of machine vision for flight vehicle guidance is motivated by the need to automate the nap-of-the-earth flight regime of helicopters. Vision-based stereo ranging problem is cast as an optimal control problem in this paper. A quadratic performance index consisting of the integral of the error between observed image irradiances and those predicted by a Pade approximation of the correspondence hypothesis is then used to define an optimization problem. The necessary conditions for optimality yield a set of linear two-point boundary-value problems. These two-point boundary-value problems are solved in feedback form using a version of the backward sweep method. Application of the ranging algorithm is illustrated using a laboratory image pair.
Control and optimization system and method for chemical looping processes
Lou, Xinsheng; Joshi, Abhinaya; Lei, Hao
2015-02-17
A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with one or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.
Stochastic Optimal Control for Online Seller under Reputational Mechanisms
Directory of Open Access Journals (Sweden)
Milan Bradonjić
2015-12-01
Full Text Available In this work we propose and analyze a model which addresses the pulsing behavior of sellers in an online auction (store. This pulsing behavior is observed when sellers switch between advertising and processing states. We assert that a seller switches her state in order to maximize her profit, and further that this switch can be identified through the seller’s reputation. We show that for each seller there is an optimal reputation, i.e., the reputation at which the seller should switch her state in order to maximize her total profit. We design a stochastic behavioral model for an online seller, which incorporates the dynamics of resource allocation and reputation. The design of the model is optimized by using a stochastic advertising model from [1] and used effectively in the Stochastic Optimal Control of Advertising [2]. This model of reputation is combined with the effect of online reputation on sales price empirically verified in [3]. We derive the Hamilton-Jacobi-Bellman (HJB differential equation, whose solution relates optimal wealth level to a seller’s reputation. We formulate both a full model, as well as a reduced model with fewer parameters, both of which have the same qualitative description of the optimal seller behavior. Coincidentally, the reduced model has a closed form analytical solution that we construct.
Optimized flutter control for an aeroelastic delta wing
Richard, Robert Earl
The phenomenon of flutter has been a topic of academic research and since the advent of early aircraft. Attempts to suppress it through passive structural design have achieved limited success at the cost of heavier aircraft motivating the development of active control techniques. This work focuses on one such approach referred to as active local damping. The primary focus is to develop an adaptive-structures based method, using computationally efficient modeling tools and transducer optimization techniques, to extend the flutter boundary---the minimum flow speed at which flutter occurs---of an aeroelastic delta wing through active control. System robustness is achieved primarily through the spatial filtering effects of optimized transducers, providing maximized flutter mode targeting with dramatic response reduction in the higher-order system modes. A multi-disciplinary approach is used that incorporates energy based structural modeling, simulation of piezo patch electromechanical coupling, balanced model reduction, vortex lattice aerodynamic modeling, transmission path analysis using Hankel Singular Value (HSV) estimates, and genetic optimization yielding a cohesive and efficient design technique. The control strategy used is based on the assertion that a linear controller built from a linear (pre-flutter) model, if sufficiently robust, can keep the system response linear and continue to function effectively past the point where a passive system would be non-linear. The feasibility of this overall design approach is demonstrated through experimental implementation, yielding a 14% increase in the flutter boundary of the tested model.
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
Directory of Open Access Journals (Sweden)
Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
Optimal Control of Engine Warmup in Hybrid Vehicles
Directory of Open Access Journals (Sweden)
van Reeven Vital
2016-01-01
Full Text Available An Internal Combustion Engine (ICE under cold conditions experiences increased friction losses due to a high viscosity of the lubricant. With the additional control freedom present in hybrid electric vehicles, the losses during warmup can be minimized and fuel can be saved. In this paper, firstly, a control-oriented model of the ICE, describing the warmup behavior, is developed and validated on measured vehicle data. Secondly, the two-state, non-autonomous fuel optimization, for a parallel hybrid electric vehicle with stop-start functionality, is solved using optimal control theory. The principal behavior of the Lagrange multipliers is explicitly derived, including the discontinuities (jumps that are caused by the constraints on the lubricant temperature and the energy in the battery system. The minimization of the Hamiltonian for this two-state problem is also explicitly solved, resulting in a computationally efficient algorithm. The optimal controller shows the fuel benefit, as a function of the initial temperature, for a long-haul truck simulated on the FTP-75.
Optimal control of psychological processes: a new computational paradigm.
Sinclair, K O; Molenaar, P C M
2008-01-01
In this paper, we use general mathematical-statistical theorems to prove that developmental processes must be studied at the intra-individual level. We demonstrate how to model intra-individual variation using single-participant time series analysis with time-varying parameters. We use advanced signal analysis techniques based on nonlinear state-space modeling to present simulation results obtained with a new Maximum Likelihood technique based on Extended Kalman Filtering with Iteration and Smoothing (EKFIS) embedded in an Expectation Maximization (EM) loop. After showing how EKFIS results yield state-space models with time-varying parameters, we then couple EKFIS to recursive optimal control techniques to produce a receding horizon feedback-feedforward controller. In this way, we obtain a flexible on-line computational paradigm with which we can optimally control observed behavioral processes for an individual person in real time. We will present optimal control techniques using simulated data and outline preliminary applications to real time patient-specific treatment of type I diabetic patients and asthma patients.
Designing a robust PID congestion controller supporting TCP flows based on H∞ optimal control theory
Yu, Li; Shi, Zibo; Chen, Kun; Shu, Yantai
2007-09-01
A robust PID controller for active queue management (AQM) based on modern H∞ optimal control theory is presented in this paper. Taken both robustness and closed loop performance into consideration, most desirable parameters value can be gotten through some straightforward analytical formulas. Our robust PID controller is determined only by one parameter, other than traditional PID controller is by three or more. Additionally, this new parameters determining method can not only be extended to other AQM controller based on classical control theory or optimal control theory, but also be easily understood and implementation. We evaluate the performances of the controller extensively. The results show that the robust PID congestion controller outperform the existing controller, such as PI, RED, on keeping the router queue size at the target value. The most obvious property of the controller is that it takes on robustness such that it can adapt the network dynamic.
Less Conservative Optimal Robust Control of a 3-DOF Helicopter
Directory of Open Access Journals (Sweden)
L. F. S. Buzachero
2015-01-01
Full Text Available This work proposes an improved technique for design and optimization of robust controllers norm for uncertain linear systems, with state feedback, including the possibility of time-varying the uncertainty. The synthesis techniques used are based on LMIs (linear matrix inequalities formulated on the basis of Lyapunov’s stability theory, using Finsler’s lemma. The design has used the addition of the decay rate restriction, including a parameter γ in the LMIs, responsible for decreasing the settling time of the feedback system. Qualitative and quantitative comparisons were made between methods of synthesis and optimization of the robust controllers norm, seeking alternatives with lower cost and better performance that meet the design restrictions. A practical application illustrates the efficiency of the proposed method with a failure purposely inserted in the system.
A model for HIV/AIDS pandemic with optimal control
Sule, Amiru; Abdullah, Farah Aini
2015-05-01
Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is pandemic. It has affected nearly 60 million people since the detection of the disease in 1981 to date. In this paper basic deterministic HIV/AIDS model with mass action incidence function are developed. Stability analysis is carried out. And the disease free equilibrium of the basic model was found to be locally asymptotically stable whenever the threshold parameter (RO) value is less than one, and unstable otherwise. The model is extended by introducing two optimal control strategies namely, CD4 counts and treatment for the infective using optimal control theory. Numerical simulation was carried out in order to illustrate the analytic results.
Backstepping-Based Inverse Optimal Attitude Control of Quadrotor
Directory of Open Access Journals (Sweden)
An Honglei
2013-05-01
Full Text Available Abstract Input saturation must be taken into account for applying rapid reorientation in the large angle manoeuvre of a quadrotor. In this paper, a backstepping-based inverse optimal attitude controller (BIOAC is derived which has the property of a maximum convergence rate in the sense of a control Lyapunov function (CLF under input torque limitation. In the controller, a backstepping technique is used for handling the complexity introducing by the unit quaternion representation of the attitude of a quadrotor with four parameters. Moreover, the inverse optimal approach is employed to circumvent the difficulty of solving the Hamilton-Jacobi-Bellman (HJB equation. The performance of BIOAC is compared with a PD controller in which the input torque limitation is not considered under the same unit quaternion representation using numerical simulation while the results show that BIOAC gains faster convergence with less control effort. Next, BIOAC is realized on a test bed and the effectiveness of the control law is verified by experimental studies.
Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System
Chen, Jilin; Wang, Li; Xu, Shiqing; Hou, Yuanlong
2013-01-01
Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method. PMID:23766721
Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System
Directory of Open Access Journals (Sweden)
Qiang Gao
2013-01-01
Full Text Available Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method.
Optimal boundary control of a contact thawing process for foodstuff
Backi, Christoph Josef; Leth, John; Gravdahl, Jan Tommy
2016-01-01
In this work an approach for thawing blocks of foodstuff, in particular fish, is introduced. The functional principle is based on plate freezer technology, which has been used in industry for decades. The aim of this work is to describe the temperature dynamics of this thawing process by means of partial differential equations (PDEs) and control the boundary conditions in an optimal way. The PDE describing the temperature dynamics is based on the diffusion equation with state-dependent parame...
Approximate Solutions to Nonlinear Optimal Control Problems in Astrodynamics
Francesco Topputo; Franco Bernelli-Zazzera
2013-01-01
A method to solve nonlinear optimal control problems is proposed in this work. The method implements an approximating sequence of time-varying linear quadratic regulators that converge to the solution of the original, nonlinear problem. Each subproblem is solved by manipulating the state transition matrix of the state-costate dynamics. Hard, soft, and mixed boundary conditions are handled. The presented method is a modified version of an algorithm known as “approximating sequence of Riccati e...
Controlled Optimal Design Program for the Logit Dose Response Model
Directory of Open Access Journals (Sweden)
Jiaqiao Hu
2010-10-01
Full Text Available The assessment of dose-response is an integral component of the drug development process. Parallel dose-response studies are conducted, customarily, in preclinical and phase 1, 2 clinical trials for this purpose. Practical constraints on dose range, dose levels and dose proportions are intrinsic issues in the design of dose response studies because of drug toxicity, efficacy, FDA regulations, protocol requirements, clinical trial logistics, and marketing issues. We provide a free on-line software package called Controlled Optimal Design 2.0 for generating controlled optimal designs that can incorporate prior information and multiple objectives, and meet multiple practical constraints at the same time. Researchers can either run the web-based design program or download its stand-alone version to construct the desired multiple-objective controlled Bayesian optimal designs. Because researchers often adopt ad-hoc design schemes such as the equal allocation rules without knowing how efficient such designs would be for the design problem, the program also evaluates the efficiency of user-supplied designs.
Preconditioning for partial differential equation constrained optimization with control constraints
Stoll, Martin
2011-10-18
Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.
Optimal control in microgrid using multi-agent reinforcement learning.
Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin
2012-11-01
This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
The control operator for the optimal control model of higher order ...
African Journals Online (AJOL)
The control operator of the Extended Conjugate Gradient Algorithm for the control of two- dimensional higher order non-dispersive waves was constructed in the paper. Explicit expressions of each elements, Ri,j , of the operator, R, were computed. These elements are useful for the implementation of the Optimal Control ...
Directory of Open Access Journals (Sweden)
Ru Wang
2017-01-01
Full Text Available In order to improve the performance of the hydraulic support electro-hydraulic control system test platform, a self-tuning proportion integration differentiation (PID controller is proposed to imitate the actual pressure of the hydraulic support. To avoid the premature convergence and to improve the convergence velocity for tuning PID parameters, the PID controller is optimized with a hybrid optimization algorithm integrated with the particle swarm algorithm (PSO and genetic algorithm (GA. A selection probability and an adaptive cross probability are introduced into the PSO to enhance the diversity of particles. The proportional overflow valve is installed to control the pressure of the pillar cylinder. The data of the control voltage of the proportional relief valve amplifier and pillar pressure are collected to acquire the system transfer function. Several simulations with different methods are performed on the hydraulic cylinder pressure system. The results demonstrate that the hybrid algorithm for a PID controller has comparatively better global search ability and faster convergence velocity on the pressure control of the hydraulic cylinder. Finally, an experiment is conducted to verify the validity of the proposed method.
Research on Optimization for Motion Control Bus Based on Ethernet
Directory of Open Access Journals (Sweden)
Kai Sun
2013-01-01
Full Text Available Field bus system has been successfully introduced into industrial automation. Nowadays, most of the motion control bus is based on the Ethernet physical layer, and all of the new standards are based on the Ethernet physical layer. This paper introduces a new optimized technology based on motion control bus of the Ethernet physical layer, which includes the prediction mechanism in the arrival of the frames, the retransmission mechanism in advance, and a new mechanism of independent verification of data segment. Tests show that using the mechanisms in this paper can enhance efficiency and reliability in communication process.
On the regularity of optimal control for a parabolic system of order 2m
Directory of Open Access Journals (Sweden)
Ornella Fiodo
1992-05-01
Full Text Available An optimal control problem for a parabolic operator of order 2m with the boundary conditions containing the control is considered. A regularity theorem for the parabolic problem and the regularity of the optimal control is proved.
Simulation and optimal control of wind-farm boundary layers
Meyers, Johan; Goit, Jay
2014-05-01
In large wind farms, the effect of turbine wakes, and their interaction leads to a reduction in farm efficiency, with power generated by turbines in a farm being lower than that of a lone-standing turbine by up to 50%. In very large wind farms or `deep arrays', this efficiency loss is related to interaction of the wind farms with the planetary boundary layer, leading to lower wind speeds at turbine level. Moreover, for these cases it has been demonstrated both in simulations and wind-tunnel experiments that the wind-farm energy extraction is dominated by the vertical turbulent transport of kinetic energy from higher regions in the boundary layer towards the turbine level. In the current study, we investigate the use of optimal control techniques combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large `infinite' wind farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with actuator-disk and actuator-line representations of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind that combines Fourier-spectral discretization in horizontal directions with a fourth-order finite-volume approach in the vertical direction. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in an actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. Optimal model-predictive control (or optimal receding horizon control) is used, where the model simply consists of the full LES equations, and the time horizon is approximately 280 seconds. The optimization is performed using a
Perturbing engine performance measurements to determine optimal engine control settings
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2014-12-30
Methods and systems for optimizing a performance of a vehicle engine are provided. The method includes determining an initial value for a first engine control parameter based on one or more detected operating conditions of the vehicle engine, determining a value of an engine performance variable, and artificially perturbing the determined value of the engine performance variable. The initial value for the first engine control parameter is then adjusted based on the perturbed engine performance variable causing the engine performance variable to approach a target engine performance variable. Operation of the vehicle engine is controlled based on the adjusted initial value for the first engine control parameter. These acts are repeated until the engine performance variable approaches the target engine performance variable.
Optimized Control Strategy For Over Loaded Offshore Wind Turbines
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Knudsen, Torben; Wisniewski, Rafal
2015-01-01
controller tuning for a given wind turbine. It also enables a very safe and robust comparison between a new control strategy and the present one. Main body of abstract Is it true that power de-rating indeed the best way to reduce loads? The power de-rating approach has the drawback of only indirectly......Abstract Optimized control strategy for overloaded offshore wind turbines Introduction Operation and maintenance cost are an important part of cost of energy especially for offshore wind farms. Typically unplanned service is called for due to detection off excessive loads on components, e...... as results of ensuring the load reduction to the given level. A MPC controller is configured and tuned using this novel approach including Pareto fronts. It is compared to the existing de-rating strategy using high fidelity aero-servo-elastic simulation code and the possibilities for reduction of cost...
A nonlinear optimal control approach for chaotic finance dynamics
Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.
2017-11-01
A new nonlinear optimal control approach is proposed for stabilization of the dynamics of a chaotic finance model. The dynamic model of the financial system, which expresses interaction between the interest rate, the investment demand, the price exponent and the profit margin, undergoes approximate linearization round local operating points. These local equilibria are defined at each iteration of the control algorithm and consist of the present value of the systems state vector and the last value of the control inputs vector that was exerted on it. The approximate linearization makes use of Taylor series expansion and of the computation of the associated Jacobian matrices. The truncation of higher order terms in the Taylor series expansion is considered to be a modelling error that is compensated by the robustness of the control loop. As the control algorithm runs, the temporary equilibrium is shifted towards the reference trajectory and finally converges to it. The control method needs to compute an H-infinity feedback control law at each iteration, and requires the repetitive solution of an algebraic Riccati equation. Through Lyapunov stability analysis it is shown that an H-infinity tracking performance criterion holds for the control loop. This implies elevated robustness against model approximations and external perturbations. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven.
Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan
2017-01-01
This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.
Optimal control and cold war dynamics between plant and herbivore.
Low, Candace; Ellner, Stephen P; Holden, Matthew H
2013-08-01
Herbivores eat the leaves that a plant needs for photosynthesis. However, the degree of antagonism between plant and herbivore may depend critically on the timing of their interactions and the intrinsic value of a leaf. We present a model that investigates whether and when the timing of plant defense and herbivore feeding activity can be optimized by evolution so that their interactions can move from antagonistic to neutral. We assume that temporal changes in environmental conditions will affect intrinsic leaf value, measured as potential carbon gain. Using optimal-control theory, we model herbivore evolution, first in response to fixed plant strategies and then under coevolutionary dynamics in which the plant also evolves in response to the herbivore. In the latter case, we solve for the evolutionarily stable strategies of plant defense induction and herbivore hatching rate under different ecological conditions. Our results suggest that the optimal strategies for both plant and herbivore are to avoid direct conflict. As long as the plant has the capability for moderately lethal defense, the herbivore will modify its hatching rate to avoid plant defenses, and the plant will never have to use them. Insights from this model offer a possible solution to the paradox of sublethal defenses and provide a mechanism for stable plant-herbivore interactions without the need for natural enemy control.
Directory of Open Access Journals (Sweden)
Heryanto M Ary
2015-01-01
Full Text Available UAVs are mostly used for surveillance, inspection and data acquisition. We have developed a Quadrotor UAV that is constructed based on a four motors with a lift-generating propeller at each motors. In this paper, we discuss the development of a quadrotor and its neural networks direct inverse control model using the actual flight data. To obtain a better performance of the control system of the UAV, we proposed an Optimized Direct Inverse controller based on re-training the neural networks with the new data generated from optimal maneuvers of the quadrotor. Through simulation of the quadrotor using the developed DIC and Optimized DIC model, results show that both models have the ability to stabilize the quadrotor with a good tracking performance. The optimized DIC model, however, has shown a better performance, especially in the settling time parameter.
Noosphere as Optimal Control. Part 2. Reflective noosphere
Directory of Open Access Journals (Sweden)
Boris Balter
2018-02-01
Full Text Available Conceptual system developed in optimal control theory for technical purposes is used as a philosophical instrument applied to cyclic information processes, which are expected to be the basis of noosphere. Noosphere was perceived by the founding fathers of this concept, Vernadsky, Teilhard de Chardin, e.a. as an outgrowth of the evolutionary process, which begins with cosmogenesis and proceeds through geosphere and biosphere. We attempt to apply the optimal control concepts to all three levels – geospheric, biospheric, and noospheric – due to their having a common structure of information processes (or entropic processes considered as proto-information. These processes include homeostasis, accumulation and expenditure of information, formation of hierarchical information structures, evolution involving the breaks of homeostasis etc. In noosphere, controlled system may have the same informational capabilities as controlling system, so that the term “dialog” is more adequate; in this case, we extend optimal control description to game theory. The cyclic, feedback logic of optimal control seems better adapted to noospheric processes than usual causeeffect logic. This second part of the paper proceeds from the geo- and biospheric levels discussed in the first part to the noospheric level. The basic structure at this level is the fusion of natural matter/energy cycles characteristic for geosphere with anthropogenic information cycles, which extend information accumulation and adaptation inherited from biospheric level into reflective realm. The basic type of informational interaction between these structures is construed in perspective of game theory between reflective players. Its essential feature is the interaction between reflective images that each player forms of other players and of oneself. We describe the nontrivial information flows that can arise in a distributed global system of such structures, including complex interactions
Optimal digital control of a Stirling cycle cooler
Feeley, J.; Feeley, P.; Langford, G.
1990-01-01
This short paper describes work in progress on the conceptual design of a control system for a cryogenic cooler intended for use aboard spacecraft. The cooler will produce 5 watts of cooling at 65 K and will be used to support experiments associated with the following: earth observation; atmospheric measurements; infrared, x-ray, and gamma-ray astronomy; and magnetic field characterization. The cooler has been designed and constructed for NASA/GSFC by Philips Laboratories and is described in detail. The cooler has a number of unique design features intended to enhance long life and maintenance free operation in space including use of the high efficiency Stirling thermodynamic refrigeration cycle, linear magnetic motors, clearance-seals, and magnetic bearings. The proposed control system design is based on optimal control theory and is targeted for custom integrated circuit implementation. The resulting control system will meet the following mission requirements: efficiency, reliability, optimal thermodynamic, electrical, and mechanical performance; freedom from operator intervention; light weight; and small size.
National Research Council Canada - National Science Library
V, Soni; G, Parmar; M, Kumar; S, Panda
2016-01-01
The combination of Grey Wolf Optimization and Pattern Search Technique (hGWO-PS) has been introduced to optimize the parameters of two Degree of Freedom Proportional-Integral-Derivative Controller (2DOF-PID...
Time-dependent optimal heater control using finite difference method
Energy Technology Data Exchange (ETDEWEB)
Li, Zhen Zhe; Heo, Kwang Su; Choi, Jun Hoo; Seol, Seoung Yun [Chonnam National Univ., Gwangju (Korea, Republic of)
2008-07-01
Thermoforming is one of the most versatile and economical process to produce polymer products. The drawback of thermoforming is difficult to control thickness of final products. Temperature distribution affects the thickness distribution of final products, but temperature difference between surface and center of sheet is difficult to decrease because of low thermal conductivity of ABS material. In order to decrease temperature difference between surface and center, heating profile must be expressed as exponential function form. In this study, Finite Difference Method was used to find out the coefficients of optimal heating profiles. Through investigation, the optimal results using Finite Difference Method show that temperature difference between surface and center of sheet can be remarkably minimized with satisfying temperature of forming window.
Adaptive dynamic programming with applications in optimal control
Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang
2017-01-01
This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...
Debbarma, Sanjoy; Saikia, Lalit Chandra; Sinha, Nidul
2014-03-01
Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as I(λ)D(µ) controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of I(λ)D(µ) controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized I(λ)D(µ) controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed I(λ)D(µ) controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized I(λ)D(µ) controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed I(λ)D(µ) controller is also tested against system parameter variations. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Optimal Fuzzy Controller Tuned by TV-PSO for Induction Motor Speed Control
Directory of Open Access Journals (Sweden)
KULIC, F.
2011-02-01
Full Text Available This paper reports an automated procedure for the design of an optimal fuzzy logic controller to be used as an induction motor speed controller. The procedure consists of selection of a suitable well known fuzzy logic controller and tuning via particle swarm optimization optimal for the selected criteria. In this way the time required for tuning of the controller is significantly reduced in comparison with trial and error methods. As a benchmark a proportional-integral (PI controller is used. The PI controller is tuned via the symmetrical optimum procedure, the standard procedure for tuning a speed controller of an induction motor. Simulation results are obtained via a mathematical model developed in Matlab/Simulink. Experimental verification is carried out with a laboratory model based on the DS1104 digital control card. To minimize iron losses and to provide better motor performance for low loads, flux is reduced from nominal and speed is kept below nominal. Results are presented in tables and graphics. The optimal fuzzy logic controller provides a slight practical advantage.
Noosphere as Optimal Control. Part 1. Control Theory, Geosphere and Biosphere
Directory of Open Access Journals (Sweden)
Boris Balter
2017-09-01
Full Text Available The conceptual system developed in optimal control theory for technical purposes is used as a philosophical instrument applied to cyclic information processes, which are expected to be the basis of noosphere. Noosphere was perceived by the founding fathers of this concept, Vladimir Vernadsky, Pierre Teilhard de Chardin, e.a. as an outgrowth of the evolutionary process, which begins with cosmogenesis and proceeds through geosphere and biosphere. We attempt to apply the optimal control concepts to all three levels — geospheric, biospheric, and noospheric — due to their having a common structure of information processes (or entropic processes considered as proto-information. These processes include homeostasis, accumulation and expenditure of information, formation of hierarchical information structures, evolution involving the breaks of homeostasis etc. In noosphere, controlled system may have the same informational capabilities as controlling system, so that the term “dialog” is more adequate; in this case, we extend optimal control description to game theory. The cyclic, feedback logic of optimal control seems better adapted to noospheric processes than usual cause-eff ect logic. The fi rst part of the paper considers the geospheric and biospheric level. We introduce the basic notions characterizing optimal control cycle: duality of observation and control, hierarchy of models, active sounding, balance of information infl ow and outfl ow, optimized criterion, networked (distributed control, etc. Then, natural homeostases at the geospheric level are considered as a form of self-regulation having specifi c optimized criteria. The constitutive feature of this level is the absence of information processing in the strict sense: its place is taken by entropic processes. Therefore, no goal can exist at this level, and we consider it as a part of cosmogenesis, which is allegedly goalless/meaningless. We discuss the anthropic principle as a means
Optimal charging control of electric vehicles in smart grids
Tang, Wanrong
2017-01-01
This book introduces the optimal online charging control of electric vehicles (EVs) and battery energy storage systems (BESSs) in smart grids. The ultimate goal is to minimize the total energy cost as well as reduce the fluctuation of the total power flow caused by the integration of the EVs and renewable energy generators. Using both theoretic analysis and data-driven numerical results, the authors reveal the effectiveness and efficiency of the proposed control techniques. A major benefit of these control techniques is their practicality, since they do not rely on any non-causal knowledge of future information. Researchers, operators of power grids, and EV users will find this to be an exceptional resource. It is also suitable for advanced-level students of computer science interested in networks, electric vehicles, and energy systems.
Hierarchical Control for Optimal and Distributed Operation of Microgrid Systems
DEFF Research Database (Denmark)
Meng, Lexuan
The distributed generation, storage and consumption, as well as the sustainability consideration prompt a revolution to the existing electric power grid. Microgrids (MG) concept has been proposed to liberate the operation of each distribution system fraction, forming in that way a flexible......, a discrete-time domain modeling method is proposed to establish an accurate system level model. Taking into account the different sampling times of real world plant, digital controller and communication devices, the system is modeled with these three parts separately, and with full consideration...... and performance with the proposed control schemes and modeling methods, experimental and hardware-in-the-loop simulation studies are conducted in the intelligent MG lab. The successful realization of online optimization and distributed control functions is expected to be able to provide guidance for real world...
Optimal control of CPR procedure using hemodynamic circulation model
Lenhart, Suzanne M.; Protopopescu, Vladimir A.; Jung, Eunok
2007-12-25
A method for determining a chest pressure profile for cardiopulmonary resuscitation (CPR) includes the steps of representing a hemodynamic circulation model based on a plurality of difference equations for a patient, applying an optimal control (OC) algorithm to the circulation model, and determining a chest pressure profile. The chest pressure profile defines a timing pattern of externally applied pressure to a chest of the patient to maximize blood flow through the patient. A CPR device includes a chest compressor, a controller communicably connected to the chest compressor, and a computer communicably connected to the controller. The computer determines the chest pressure profile by applying an OC algorithm to a hemodynamic circulation model based on the plurality of difference equations.
Quantum demolition filtering and optimal control of unstable systems.
Belavkin, V P
2012-11-28
A brief account of the quantum information dynamics and dynamical programming methods for optimal control of quantum unstable systems is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme, we exploit the separation theorem of filtering and control aspects as in the usual case of quantum stable systems with non-demolition observation. This allows us to start with the Belavkin quantum filtering equation generalized to demolition observations and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to Hamiltonian terms in the filtering equation. An unstable controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.
Optimal Control for Bufferbloat Queue Management Using Indirect Method with Parametric Optimization
Directory of Open Access Journals (Sweden)
Amr Radwan
2016-01-01
Full Text Available Because memory buffers become larger and cheaper, they have been put into network devices to reduce the number of loss packets and improve network performance. However, the consequences of large buffers are long queues at network bottlenecks and throughput saturation, which has been recently noticed in research community as bufferbloat phenomenon. To address such issues, in this article, we design a forward-backward optimal control queue algorithm based on an indirect approach with parametric optimization. The cost function which we want to minimize represents a trade-off between queue length and packet loss rate performance. Through the integration of an indirect approach with parametric optimization, our proposal has advantages of scalability and accuracy compared to direct approaches, while still maintaining good throughput and shorter queue length than several existing queue management algorithms. All numerical analysis, simulation in ns-2, and experiment results are provided to solidify the efficiency of our proposal. In detailed comparisons to other conventional algorithms, the proposed procedure can run much faster than direct collocation methods while maintaining a desired short queue (≈40 packets in simulation and 80 (ms in experiment test.
Fayek, H M; Elamvazuthi, I; Perumal, N; Venkatesh, B
2014-09-01
A computationally-efficient systematic procedure to design an Optimal Type-2 Fuzzy Logic Controller (OT2FLC) is proposed. The main scheme is to optimize the gains of the controller using Particle Swarm Optimization (PSO), then optimize only two parameters per type-2 membership function using Genetic Algorithm (GA). The proposed OT2FLC was implemented in real-time to control the position of a DC servomotor, which is part of a robotic arm. The performance judgments were carried out based on the Integral Absolute Error (IAE), as well as the computational cost. Various type-2 defuzzification methods were investigated in real-time. A comparative analysis with an Optimal Type-1 Fuzzy Logic Controller (OT1FLC) and a PI controller, demonstrated OT2FLC׳s superiority; which is evident in handling uncertainty and imprecision induced in the system by means of noise and disturbances. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Web malware spread modelling and optimal control strategies
Liu, Wanping; Zhong, Shouming
2017-02-01
The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.
Empirically characteristic analysis of chaotic PID controlling particle swarm optimization.
Yan, Danping; Lu, Yongzhong; Zhou, Min; Chen, Shiping; Levy, David
2017-01-01
Since chaos systems generally have the intrinsic properties of sensitivity to initial conditions, topological mixing and density of periodic orbits, they may tactfully use the chaotic ergodic orbits to achieve the global optimum or their better approximation to given cost functions with high probability. During the past decade, they have increasingly received much attention from academic community and industry society throughout the world. To improve the performance of particle swarm optimization (PSO), we herein propose a chaotic proportional integral derivative (PID) controlling PSO algorithm by the hybridization of chaotic logistic dynamics and hierarchical inertia weight. The hierarchical inertia weight coefficients are determined in accordance with the present fitness values of the local best positions so as to adaptively expand the particles' search space. Moreover, the chaotic logistic map is not only used in the substitution of the two random parameters affecting the convergence behavior, but also used in the chaotic local search for the global best position so as to easily avoid the particles' premature behaviors via the whole search space. Thereafter, the convergent analysis of chaotic PID controlling PSO is under deep investigation. Empirical simulation results demonstrate that compared with other several chaotic PSO algorithms like chaotic PSO with the logistic map, chaotic PSO with the tent map and chaotic catfish PSO with the logistic map, chaotic PID controlling PSO exhibits much better search efficiency and quality when solving the optimization problems. Additionally, the parameter estimation of a nonlinear dynamic system also further clarifies its superiority to chaotic catfish PSO, genetic algorithm (GA) and PSO.
Mechanical design and optimal control of humanoid robot (TPinokio
Directory of Open Access Journals (Sweden)
Teck Chew Wee
2014-04-01
Full Text Available The mechanical structure and the control of the locomotion of bipedal humanoid is an important and challenging domain of research in bipedal robots. Accurate models of the kinematics and dynamics of the robot are essential to achieve bipedal locomotion. Toe-foot walking produces a more natural and faster walking speed and it is even possible to perform stretch knee walking. This study presents the mechanical design of a toe-feet bipedal, TPinokio and the implementation of some optimal walking gait generation methods. The optimality in the gait trajectory is achieved by applying augmented model predictive control method and the pole-zero cancellation method, taken into consideration of a trade-off between walking speed and stability. The mechanism of the TPinokio robot is designed in modular form, so that its kinematics can be modelled accurately into a multiple point-mass system, its dynamics is modelled using the single and double mass inverted pendulum model and zero-moment-point concept. The effectiveness of the design and control technique is validated by simulation testing with the robot walking on flat surface and climbing stairs.
Optimization and Control of Pressure Swing Adsorption Processes Under Uncertainty
Khajuria, Harish
2012-03-21
The real-time periodic performance of a pressure swing adsorption (PSA) system strongly depends on the choice of key decision variables and operational considerations such as processing steps and column pressure temporal profiles, making its design and operation a challenging task. This work presents a detailed optimization-based approach for simultaneously incorporating PSA design, operational, and control aspects under the effect of time variant and invariant disturbances. It is applied to a two-bed, six-step PSA system represented by a rigorous mathematical model, where the key optimization objective is to maximize the expected H2 recovery while achieving a closed loop product H2 purity of 99.99%, for separating 70% H2, 30% CH4 feed. The benefits over sequential design and control approach are shown in terms of closed-loop recovery improvement of more than 3%, while the incorporation of explicit/multiparametric model predictive controllers improves the closed loop performance. © 2012 American Institute of Chemical Engineers (AIChE).
Distributed Model Predictive Control of A Wind Farm for Optimal Active Power Control
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai
2015-01-01
This paper presents a dynamic discrete-time Piece- Wise Affine (PWA) model of a wind turbine for the optimal active power control of a wind farm. The control objectives include both the power reference tracking from the system operator and the wind turbine mechanical load minimization. Instead...... of partial linearization of the wind turbine model at selected operating points, the nonlinearities of the wind turbine model are represented by a piece-wise static function based on the wind turbine system inputs and state variables. The nonlinearity identification is based on the clustering-based algorithm......) or other advanced optimal control applications of a wind farm....
Optimal control in a micro gas grid of prosumers using Model Predictive Control
Alkano, Desti; Nefkens, W.J.; Scherpen, Jacqueline M.A.; Volkerts, M.
This paper studies the optimal control of a micro grid of biogas prosumers equipped with local storage devices. Excess biogas can be upgraded and injected into the low- pressure gas grid or, alternatively, shipped per lorry to be used elsewhere in an effort to create revenue. The aim of the control
Energy Technology Data Exchange (ETDEWEB)
Hristova, I.
2007-12-15
We present the analysis of data taken in the years 2002-2004 with the 27.56 GeV positron beam of the HERA storage ring at DESY and the internal transversely polarised hydrogen fixed target of the HERMES experiment. Events with a scattered positron and a produced pion are selected. Exclusive production of single pions, e{sup +}p{yields}e{sup +'}n{pi}{sup +}, is ensured by requiring the missing mass in the event to be equal to the mass of the neutron, which is not detected. The cross section for this process depends on the Bjorken scaling variable, the four-momentum transfer, and the transverse four-momentum transfer, whose average values for our sample are left angle x right angle =0.12, left angle Q{sup 2} right angle =2.3 GeV{sup 2}, left angle t' right angle =-0.18 GeV{sup 2}, respectively, and two azimuthal angles: the angle {phi} between the scattering and production planes (their common line contains the virtual photon), and the angle {phi}{sub S} between the scattering plane and the target polarisation vector. The hard scattering is selected by requiring Q{sup 2}>1 GeV{sup 2}. The asymmetry, also called transverse-target single-spin azimuthal asymmetry, is defined as the ratio of the difference to the sum of the cross sections for positive and negative target polarisation. It is characterised by six azimuthal sine modulations, whose amplitudes can vary from -1 to 1. We measure the asymmetry from a sample of 2093 events with a signal-to-background ratio of 1: 1. At average kinematics, the values of the amplitudes are found to be small or consistent with zero, except for the amplitude A{sup sin{phi}{sub SUT,meas}}=0.38{+-}0.06(stat){sup +0.12}{sub -0.06}(syst). The amplitude of main interest for comparison with theory, A{sup sin({phi}-{phi}{sub S})}{sub UT,meas}=0.09{+-}0.05(stat){sup +0.10}{sub -0.03}(syst), after correction for the background contribution becomes A{sup sin({phi}-{phi}{sub S})}{sub UT,bg.cor}=0.22 {+-}0.13(stat){sup +0.10}{sub -0
A method for unified optimization of systems and controllers
DEFF Research Database (Denmark)
Abildgaard, Ole
1990-01-01
A unified method for solving control system optimization problems is suggested. All system matrices are allowed to be functions of the design variables. The method makes use of an implementation of a sequential quadratic programming algorithm (NLPQL) for solution of general constrained nonlinear...... programming problems. It is shown how to compute the gradients of the objective function and the constraint functions imposing eigenvalue constraints. In an example it is demonstrated how the method can solve a high-dimensional problem, where the initial condition covariance assumption is used to ensure...
Evolutionary algorithms for the optimal laser control of molecular orientation
Energy Technology Data Exchange (ETDEWEB)
Atabek, Osman [Laboratoire de Photophysique Moleculaire du CNRS, Batiment 213, Campus d' Orsay, 91405 Orsay (France); Dion, Claude M [CERMICS, Ecole Nationale des Ponts et Chaussees, 6 and 8, avenue Blaise Pascal, cite Descartes, Champs-sur-Marne, 77455 Marne-la-Vallee (France); Yedder, Adel Ben Haj [CERMICS, Ecole Nationale des Ponts et Chaussees, 6 and 8, avenue Blaise Pascal, cite Descartes, Champs-sur-Marne, 77455 Marne-la-Vallee (France)
2003-12-14
In terms of optimal control, laser-induced molecular orientation is an optimization problem involving a global minimum search on a multi-dimensional surface function of varying parameters characterizing the laser pulse (frequency, peak intensity, temporal shape). Genetic algorithms, aiming at the optimization of different possible targets, may temporarily be trapped in a local minimum, before reaching the global one. A careful study of such local (robust) minima provides a key for the thorough interpretation of the orientation dynamics, in terms of basic mechanisms. Two targets are retained: the first, simple, one searching for an angle between molecular and laser polarization axes as close as possible to zero (orientation) at a given time; the second, hybrid, one combining the efficiency of orientation with its duration. Their respective roles are illustrated referring to two molecular systems, HCN and LiF, taken at a rigid rotor approximation level. A sudden and asymmetric laser pulse (provided by a frequency {omega} superposed on its second harmonic 2{omega} leads to the kick mechanism. The result is a very fast (as compared to the rotational period) angular momentum transfer to the molecule, that turns out to be responsible for an efficient orientation after the laser pulse is turned off.
Optimal Control of Airfoil Flow Separation using Fluidic Excitation
Shahrabi, Arireza F.
as well as F+ were evaluated and discussed. The computational model predictions showed good agreement with the experimental data. It was observed that different angles of attack and flap angles have different requirements for the minimum value of the momentum coefficient, Cμ, in order for the SJA to be effective for control of separation. It was also found that the variation of F + noticeably affects the lift and drag forces acting on the airfoil. The optimum values of parameters during open loop control simulations have been applied in order to introduce the optimal open loop control outcome. An innovative approach has been implemented to formulate optimal frequencies and momentum ratios of vortex shedding which depends on angle of attack and static pressure of the separation zone in the upper chord. Optimal open loop results have been compared with the optimal closed loop results. Cumulative case studies in the matter of angle of attacks, flap angles, Re, Cμ and F+ provide a convincing collection of evidence to the following conclusion. An improvement of a direct closed loop control was demonstrated, and an analytical formula describing the properties of a separated flow and vortex shedding was proposed. Best AFC solutions are offered by providing optimal frequencies and momentum ratios at a variety of flow conditions.
Optimization of electrode placement in electromyographic control of dielectric elastomers
Walbran, Scott H.; Calius, Emilio P.; Dunlop, G. Reg; Anderson, Iain A.
2009-03-01
Human intention recognition is becoming a key part of powered prosthetics research. With the advent of smart materials, the usefulness of powered prosthetics has increased. Correspondingly, there is a greater need for control technology. Electromyography (EMG) has previously been used to control myoelectric hands; however the approach to electrode placement has been speculative at best. Carpi, Raspopovic and De Rossi have shown that dielectric elastomer actuators (DEAs) can be controlled by a variety of human electrophysiological signals, including EMG. To control a DEA device with multiple degrees of freedom using EMG, multiple electrode sites are required. This paper presents an approach to control an array of DEAs using a series of electrodes and an optimized electrode data filtering scheme to maximize classification accuracy when differentiating between hand grasps. A silicon mould of a human forearm was created with an array of electrodes embedded within it. Data from each electrode site was recorded using the Universal Electrophysiological Mapping (UnEmap) system developed at the University of Auckland Bioengineering Institute for the amplification and filtering of multiple biopotential signals. The recorded data was then processed off-line, in order to calculate spatial gradients; this would determine which electrode sites would give the best bipolar readings. The spatial gradients were then compared to each other in order to find the optimal electrode sites. Several points in the extensor compartment of the forearm were found to be useful in recognizing grasping, while several points in the flexor compartment of the forearm were found to be useful in differentiating between grasps.
Passive Motion Paradigm: an alternative to Optimal Control
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Vishwanathan eMohan
2011-12-01
Full Text Available In the last years, optimal control theory (OCT has emerged as the leading approach for investigating neural control of movement and motor cognition for two complementary research lines: behavioural neuroscience and humanoid robotics. In both cases, there are general problems that need to be addressed, such as the ‘degrees of freedom problem’, the common core of production, observation, reasoning, and learning of ‘actions’. OCT, directly derived from engineering design techniques of control systems quantifies task goals as ‘cost functions’ and uses the sophisticated formal tools of optimal control to obtain desired behaviour (and predictions. We propose an alternative ‘softer’ approach (PMP: Passive Motion Paradigm that we believe is closer to the biomechanics and cybernetics of action. The basic idea is that actions (overt and overt are the consequences of an internal simulation process that ‘animates’ the body schema with the attractor dynamics of force fields induced by the goal and task specific constraints. This internal simulation offers the brain a way to dynamically link motor redundancy with task oriented constraints ‘at runtime’, hence solving the ‘degrees of freedom problem’ without explicit kinematic inversion and cost function computation. We argue that the function of such computational machinery is not only to shape motor output during action execution but also to provide the self with information on the feasibility, consequence, understanding and meaning of ‘potential actions’. In this sense, taking into account recent developments in neuroscience (motor imagery, simulation theory, mirror neurons and in embodied robotics, PMP offers a novel framework for understanding motor cognition that goes beyond the engineering control paradigm provided by OCT. Therefore, the paper is at the same time a review of the PMP rationale, as a computational theory, and a perspective presentation of how to develop it
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M. Anselmino
2015-01-01
Full Text Available The inclusive large-pT production of a single pion, jet or direct photon, and Drell-Yan processes, are considered for proton-proton collisions in the kinematical range expected for the fixed-target experiment AFTER, proposed at LHC. For all these processes, predictions are given for the transverse single-spin asymmetry, AN, computed according to a Generalised Parton Model previously discussed in the literature and based on TMD factorisation. Comparisons with the results of a collinear twist-3 approach, recently presented, are made and discussed.
Measurement of the transverse single-spin asymmetry in $p^\\uparrow+p \\to W^{\\pm}/Z^0$ at RHIC
Adamczyk, L; Agakishiev, G; Aggarwal, M M; Ahammed, Z; Alekseev, I; Aparin, A; Arkhipkin, D; Aschenauer, E C; Attri, A; Averichev, G S; Bai, X; Bairathi, V; Banerjee, A; Bellwied, R; Bhasin, A; Bhati, A K; Bhattarai, P; Bielcik, J; Bielcikova, J; Bland, L C; Bordyuzhin, I G; Bouchet, J; Brandenburg, J D; Brandin, A V; Bunzarov, I; Butterworth, J; Caines, H; Sánchez, M Calderón de la Barca; Campbell, J M; Cebra, D; Chakaberia, I; Chaloupka, P; Chang, Z; Chattopadhyay, S; Chen, J H; Chen, X; Cheng, J; Cherney, M; Christie, W; Contin, G; Crawford, H J; Das, S; De Silva, L C; Debbe, R R; Dedovich, T G; Deng, J; Derevschikov, A A; di Ruzza, B; Didenko, L; Dilks, C; Dong, X; Drachenberg, J L; Draper, J E; Du, C M; Dunkelberger, L E; Dunlop, J C; Efimov, L G; Engelage, J; Eppley, G; Esha, R; Evdokimov, O; Eyser, O; Fatemi, R; Fazio, S; Federic, P; Fedorisin, J; Feng, Z; Filip, P; Fisyak, Y; Flores, C E; Fulek, L; Gagliardi, C A; Garand, D; Geurts, F; Gibson, A; Girard, M; Greiner, L; Grosnick, D; Gunarathne, D S; Guo, Y; Gupta, S; Gupta, A; Guryn, W; Hamad, A I; Hamed, A; Haque, R; Harris, J W; He, L; Heppelmann, S; Hirsch, A; Hoffmann, G W; Horvat, S; Huang, H Z; Huang, X; Huang, B; Huang, T; Huck, P; Humanic, T J; Igo, G; Jacobs, W W; Jang, H; Jentsch, A; Jia, J; Jiang, K; Judd, E G; Kabana, S; Kalinkin, D; Kang, K; Kauder, K; Ke, H W; Keane, D; Kechechyan, A; Khan, Z H; Kikoła, D P; Kisel, I; Kisiel, A; Kochenda, L; Koetke, D D; Kosarzewski, L K; Kraishan, A F; Kravtsov, P; Krueger, K; Kumar, L; Lamont, M A C; Landgraf, J M; Landry, K D; Lauret, J; Lebedev, A; Lednicky, R; Lee, J H; Li, X; Li, C; Li, W; Li, Y; Lin, T; Lisa, M A; Liu, F; Ljubicic, T; Llope, W J; Lomnitz, M; Longacre, R S; Luo, X; Ma, G L; Ma, L; Ma, R; Ma, Y G; Magdy, N; Majka, R; Manion, A; Margetis, S; Markert, C; McDonald, D; Meehan, K; Mei, J C; Minaev, N G; Mioduszewski, S; Mishra, D; Mohanty, B; Mondal, M M; Morozov, D A; Mustafa, M K; Nandi, B K; Nasim, Md; Nayak, T K; Nigmatkulov, G; Niida, T; Nogach, L V; Noh, S Y; Novak, J; Nurushev, S B; Odyniec, G; Ogawa, A; Oh, K; Okorokov, V A; Olvitt, D; Page, B S; Pak, R; Pan, Y X; Pandit, Y; Panebratsev, Y; Pawlik, B; Pei, H; Perkins, C; Pile, P; Pluta, J; Poniatowska, K; Porter, J; Posik, M; Poskanzer, A M; Pruthi, N K; Putschke, J; Qiu, H; Quintero, A; Ramachandran, S; Raniwala, S; Raniwala, R; Ray, R L; Ritter, H G; Roberts, J B; Rogachevskiy, O V; Romero, J L; Roy, A; Ruan, L; Rusnak, J; Rusnakova, O; Sahoo, N R; Sahu, P K; Sakrejda, I; Salur, S; Sandweiss, J; Sarkar, A; Schambach, J; Scharenberg, R P; Schmah, A M; Schmidke, W B; Schmitz, N; Seger, J; Seyboth, P; Shah, N; Shahaliev, E; Shanmuganathan, P V; Shao, M; Sharma, M K; Sharma, B; Shen, W Q; Shi, Z; Shi, S S; Shou, Q Y; Sichtermann, E P; Sikora, R; Simko, M; Singha, S; Skoby, M J; Smirnov, D; Smirnov, N; Solyst, W; Song, L; Sorensen, P; Spinka, H M; Srivastava, B; Stanislaus, T D S; Stepanov, M; Stock, R; Strikhanov, M; Stringfellow, B; Sumbera, M; Summa, B; Sun, X M; Sun, Y; Sun, Z; Surrow, B; Svirida, D N; Tang, Z; Tang, A H; Tarnowsky, T; Tawfik, A; Thäder, J; Thomas, J H; Timmins, A R; Tlusty, D; Todoroki, T; Tokarev, M; Trentalange, S; Tribble, R E; Tribedy, P; Tripathy, S K; Tsai, O D; Ullrich, T; Underwood, D G; Upsal, I; Van Buren, G; van Nieuwenhuizen, G; Vandenbroucke, M; Varma, R; Vasiliev, A N; Vertesi, R; Videbæk, F; Vokal, S; Voloshin, S A; Vossen, A; Wang, H; Wang, G; Wang, F; Wang, Y; Wang, J S; Webb, J C; Webb, G; Wen, L; Westfall, G D; Wieman, H; Wissink, S W; Witt, R; Wu, Y; Xiao, Z G; Xie, W; Xie, G; Xin, K; Xu, J; Xu, Z; Xu, Y F; Xu, Q H; Xu, H; Xu, N; Yang, Q; Yang, Y; Yang, S; Yang, C; Ye, Z; Yepes, P; Yi, L; Yip, K; Yoo, I -K; Yu, N; Zbroszczyk, H; Zha, W; Zhang, J; Zhang, Y; Zhang, S; Zhang, J B; Zhang, Z; Zhang, X P; Zhao, J; Zhong, C; Zhou, L; Zhu, X; Zoulkarneeva, Y; Zyzak, M
2015-01-01
We present the measurement of the transverse single-spin asymmetry of weak boson production in transversely polarized proton-proton collisions at $\\sqrt{s} = 500~\\text{GeV}$ by the STAR experiment at RHIC. The measured observable is sensitive to the Sivers function, one of the transverse momentum dependent parton distribution functions, which is predicted to have the opposite sign in proton-proton collisions from that observed in deep inelastic lepton-proton scattering. These data provide the first experimental investigation of the non-universality of the Sivers function, fundamental to our understanding of QCD.
Directory of Open Access Journals (Sweden)
Nakagawa Itaru
2017-01-01
Full Text Available Two selected topics from the latest RHIC spin results are discussed here. For the transversely polarized spin program, an unexpectedly large single spin asymmetry in the very forward neutron production observed in polarized proton + nucleus collisions at √s = 200 GeV is discussed in this document. For the longitudinal program, the latest highlights from the measurements on the gluon spin components of the proton spin is discussed. After a decade of continuous efforts to hunt for the gluon polarization, the RHIC collaboration is about to catch the tail of the experimental evidence that gluon carries substantially large portion of the proton spin.
Nakagawa, Itaru
2017-04-01
Two selected topics from the latest RHIC spin results are discussed here. For the transversely polarized spin program, an unexpectedly large single spin asymmetry in the very forward neutron production observed in polarized proton + nucleus collisions at √s = 200 GeV is discussed in this document. For the longitudinal program, the latest highlights from the measurements on the gluon spin components of the proton spin is discussed. After a decade of continuous efforts to hunt for the gluon polarization, the RHIC collaboration is about to catch the tail of the experimental evidence that gluon carries substantially large portion of the proton spin.
Multi-model Simulation for Optimal Control of Aeroacoustics.
Energy Technology Data Exchange (ETDEWEB)
Collis, Samuel Scott; Chen, Guoquan
2005-05-01
Flow-generated noise, especially rotorcraft noise has been a serious concern for bothcommercial and military applications. A particular important noise source for rotor-craft is Blade-Vortex-Interaction (BVI)noise, a high amplitude, impulsive sound thatoften dominates other rotorcraft noise sources. Usually BVI noise is caused by theunsteady flow changes around various rotor blades due to interactions with vorticespreviously shed by the blades. A promising approach for reducing the BVI noise isto use on-blade controls, such as suction/blowing, micro-flaps/jets, and smart struc-tures. Because the design and implementation of such experiments to evaluate suchsystems are very expensive, efficient computational tools coupled with optimal con-trol systems are required to explore the relevant physics and evaluate the feasibilityof using various micro-fluidic devices before committing to hardware.In this thesis the research is to formulate and implement efficient computationaltools for the development and study of optimal control and design strategies for com-plex flow and acoustic systems with emphasis on rotorcraft applications, especiallyBVI noise control problem. The main purpose of aeroacoustic computations is todetermine the sound intensity and directivity far away from the noise source. How-ever, the computational cost of using a high-fidelity flow-physics model across thefull domain is usually prohibitive and itmight also be less accurate because of thenumerical diffusion and other problems. Taking advantage of the multi-physics andmulti-scale structure of this aeroacoustic problem, we develop a multi-model, multi-domain (near-field/far-field) method based on a discontinuous Galerkin discretiza-tion. In this approach the coupling of multi-domains and multi-models is achievedby weakly enforcing continuity of normal fluxes across a coupling surface. For ourinterested aeroacoustics control problem, the adjoint equations that determine thesensitivity of the cost
Dendritic Immunotherapy Improvement for an Optimal Control Murine Model
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J. C. Rangel-Reyes
2017-01-01
Full Text Available Therapeutic protocols in immunotherapy are usually proposed following the intuition and experience of the therapist. In order to deduce such protocols mathematical modeling, optimal control and simulations are used instead of the therapist’s experience. Clinical efficacy of dendritic cell (DC vaccines to cancer treatment is still unclear, since dendritic cells face several obstacles in the host environment, such as immunosuppression and poor transference to the lymph nodes reducing the vaccine effect. In view of that, we have created a mathematical murine model to measure the effects of dendritic cell injections admitting such obstacles. In addition, the model considers a therapy given by bolus injections of small duration as opposed to a continual dose. Doses timing defines the therapeutic protocols, which in turn are improved to minimize the tumor mass by an optimal control algorithm. We intend to supplement therapist’s experience and intuition in the protocol’s implementation. Experimental results made on mice infected with melanoma with and without therapy agree with the model. It is shown that the dendritic cells’ percentage that manages to reach the lymph nodes has a crucial impact on the therapy outcome. This suggests that efforts in finding better methods to deliver DC vaccines should be pursued.
Optimal control of metabolic networks with saturable enzyme kinetics.
Oyarzuun, D A
2011-03-01
This note addresses the optimal control of non-linear metabolic networks by means of time-dependent enzyme synthesis rates. The authors consider networks with general topologies described by a control-affine dynamical system coupled with a linear model for enzyme synthesis and degradation. The problem formulation accounts for transitions between two metabolic equilibria, which typically arise in metabolic adaptations to environmental changes, and the minimisation of a quadratic functional that weights the cost/benefit relation between the transcriptional effort required for enzyme synthesis and the transition to the new phenotype. Using a linear time-variant approximation of the non-linear dynamics, the problem is recast as a sequence of linear-quadratic problems, the solution of which involves a sequence of differential Lyapunov equations. The authors provide conditions for convergence to an approximate solution of the original problem, which are naturally satisfied by a wide class of models for saturable enzyme kinetics. As a case study the authors use the method to examine the robustness of an optimal just-in-time gene expression pattern with respect to heterogeneity in the biosynthetic costs of individual proteins.
Statistical process control using optimized neural networks: a case study.
Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid
2014-09-01
The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Optimizing weight control in diabetes: antidiabetic drug selection
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Kalra S
2010-08-01
Full Text Available S Kalra1, B Kalra1, AG Unnikrishnan2, N Agrawal3, S Kumar41Bharti Hospital, Karnal; 2Amrita Institute of Medical Science, Kochi; 3Medical College, Gwalior; 4Excel Life Sciences, Noida, IndiaDate of preparation: 18th August 2010Conflict of interest: SK has received speaker fees from Novo Nordisk, sanofi-aventis, MSD, Eli Lilly, BMS, and AstraZeneca.Clinical question: Which antidiabetic drugs provide optimal weight control in patients with type 2 diabetes?Results: Metformin reduces weight gain, and may cause weight loss, when given alone or in combination with other drugs. Pioglitazone and rosiglitazone use is associated with weight gain. Use of the glucagon-like peptide-1 (GLP-1 analogs, liraglutide and exenatide, is associated with weight loss. Dipeptidyl peptidase-4 (DPP-4 inhibitors are considered weight-neutral. Results with insulin therapy are conflicting. Insulin detemir provides weight control along with glycemic control.Implementation: • Weight gain is considered an inevitable part of good glycemic control using conventional modalities of treatment such as sulfonylureas.• Use of metformin, weight-sparing insulin analogs such as insulin detemir, and liraglutide, should be encouraged as monotherapy, or in combination with other drugs.Keywords: weight control, diabetes
Feasibility of optimizing trimetazidine dihydrochloride release from controlled porosity
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Basant A. Habib
2014-05-01
Full Text Available The aim of this study was to develop and optimize Trimetazidine dihydrochloride (TM controlled porosity osmotic pump (CPOP tablets of directly compressed cores. A 23 full factorial design was used to study the influence of three factors namely: PEG400 (10% and 25% based on coating polymer weight, coating level (10% and 20% of tablet core weight and hole diameter (0 “no hole” and 1 mm. Other variables such as tablet cores, coating mixture of ethylcellulose (4% and dibutylphthalate (2% in 95% ethanol and pan coating conditions were kept constant. The responses studied (Yi were cumulative percentage released after 2 h (Q%2h, 6 h (Q%6h, 12 h (Q%12h and regression coefficient of release data fitted to zero order equation (RSQzero, for Y1, Y2, Y3, and Y4, respectively. Polynomial equations were used to study the influence of different factors on each response individually. Response surface methodology and multiple response optimization were used to search for an optimized formula. Response variables for the optimized formula were restricted to 10% ⩽ Y1 ⩽ 20%, 40% ⩽ Y2 ⩽ 60%, 80% ⩽ Y3 ⩽ 100%, and Y4 > 0.9. The statistical analysis of the results revealed that PEG400 had positive effects on Q%2h, Q%6h and Q%12h, hole diameter had positive effects on all responses and coating level had positive effect on Q%6h, Q%12h and negative effect on RSQzero. Full three factor interaction (3FI equations were used for representation of all responses except Q%2h which was represented by reduced (3FI equation. Upon exploring the experimental space, no formula in the tested range could satisfy the required constraints. Thus, direct compression of TM cores was not suitable for formation of CPOP tablets. Preliminary trials of CPOP tablets with wet granulated cores were promising with an intact membrane for 12 h and high RSQzero. Further improvement of these formulations to optimize TM release will be done in further studies.
Existence of optimal controls for systems governed by mean-field ...
African Journals Online (AJOL)
In this paper, we study the existence of an optimal control for systems, governed by stochastic dierential equations of mean-eld type. For non linear systems, we prove the existence of an optimal relaxed control, by using tightness techniques and Skorokhod selection theorem. The optimal control is a measure valued process ...
Automobile Optimal Driving Control Using Surrounding Information Based on Model Predictive Control
Wu, Dongmei; Xia, Yang; Ogawa, Masatoshi; Ogai, Harutoshi; Kawabe, Taketoshi
In this paper, an optimal driving control system based on model predictive control (MPC) is developed for the purpose of processing more surrounding information which is essential for improving the current intelligent driving assistance and further dealing with traffic issues caused by automobiles. The proposed system provides a method of calculating a desirable driving path based on surrounding traffic environments. The performance of this system is evaluated through simulations which are carried out with introduction of surrounding information such as traffic jams, traffic signal changes, and fuel consumption. Simulation results reveal that the proposed system as a driving assist system has a potential of finding optimal driving paths for drivers.
A Posteriori Error Analysis for the Optimal Control of Magneto-Static Fields
Pauly, Dirk; Yousept, Irwin
2016-01-01
This paper is concerned with the analysis and numerical analysis for the optimal control of first-order magneto-static equations. Necessary and sufficient optimality conditions are established through a rigorous Hilbert space approach. Then, on the basis of the optimality system, we prove functional a posteriori error estimators for the optimal control, the optimal state, and the adjoint state. 3D numerical results illustrating the theoretical findings are presented.
Adjoint-based Optimal Flow Control for Compressible DNS
Otero, J Javier; Sandberg, Richard D
2016-01-01
A novel adjoint-based framework oriented to optimal flow control in compressible direct numerical simulations is presented. Also, a new formulation of the adjoint characteristic boundary conditions is introduced, which enhances the stability of the adjoint simulations. The flow configuration chosen as a case study consists of a two dimensional open cavity flow with aspect ratio $L/H=3$ and Reynolds number $Re=5000$. This flow configuration is of particular interest, as the turbulent and chaotic nature of separated flows pushes the adjoint approach to its limit. The target of the flow actuation, defined as cost, is the reduction of the pressure fluctuations at the sensor location. To exploit the advantages of the adjoint method, a large number of control parameters is used. The control consists of an actuating sub-domain where a two-dimensional body force is applied at every point within the sub-volume. This results in a total of $2.256 \\cdot 10^6$ control parameters. The final actuation achieved a successful ...
Optimizing pain control through the use of implantable pumps
Directory of Open Access Journals (Sweden)
Boris Todoroff
2008-10-01
Full Text Available Wilfried Ilias1, Boris Todoroff21Dept Anesthesiology, Intensive Care Medicine and Pain Therapy, Academic Teaching Hospital St. John of God, Vienna, Austria; 2Dept. Plastic and Reconstructive Surgery, Hospital of St. Vincent, Vienna, AustriaAbstract: Intrathecal therapy represents an effective and well established treatment of nonmalignant as well as malignant pain. Devices available include mechanical constant flow pumps as well as electronic variable flow pumps with patient-controlled bolus release. The latter provide faster dose finding, individual pain control, and good acceptance by patients. New technologies such as membrane pumps and rechargeable devices are expected to be developed to clinical perfection. The available drugs for intrathecal therapy are listed according to the polyanalgesic consensus on intrathecal therapy. The integration of remote patient-controlled analgesia into electronic implantable devices, and the peptide analgesic ziconotide, have significantly improved intrathecal therapy. Complications include infections, catheter ruptures or disconnections, catheter granulomas, and technical dysfunctions. Further possibilities for optimizing intrathecal therapy include development of new drugs, drug side effects, catheter and pump technologies, and surgical techniques.Keywords: intrathecal therapy, implantable pumps, morphine pumps, intrathecal drugs, intrathecal catheters, intrathecal pain control
Optimization of Occupancy Based Demand Controlled Ventilation in Residences
Energy Technology Data Exchange (ETDEWEB)
Mortensen, Dorthe K.; Walker, Iain S.; Sherman, Max H.
2011-05-01
Although it has been used for many years in commercial buildings, the application of demand controlled ventilation in residences is limited. In this study we used occupant exposure to pollutants integrated over time (referred to as 'dose') as the metric to evaluate the effectiveness and air quality implications of demand controlled ventilation in residences. We looked at air quality for two situations. The first is that typically used in ventilation standards: the exposure over a long term. The second is to look at peak exposures that are associated with time variations in ventilation rates and pollutant generation. The pollutant generation had two components: a background rate associated with the building materials and furnishings and a second component related to occupants. The demand controlled ventilation system operated at a low airflow rate when the residence was unoccupied and at a high airflow rate when occupied. We used analytical solutions to the continuity equation to determine the ventilation effectiveness and the long-term chronic dose and peak acute exposure for a representative range of occupancy periods, pollutant generation rates and airflow rates. The results of the study showed that we can optimize the demand controlled airflow rates to reduce the quantity of air used for ventilation without introducing problematic acute conditions.
Empirically characteristic analysis of chaotic PID controlling particle swarm optimization
Yan, Danping; Lu, Yongzhong; Zhou, Min; Chen, Shiping; Levy, David
2017-01-01
Since chaos systems generally have the intrinsic properties of sensitivity to initial conditions, topological mixing and density of periodic orbits, they may tactfully use the chaotic ergodic orbits to achieve the global optimum or their better approximation to given cost functions with high probability. During the past decade, they have increasingly received much attention from academic community and industry society throughout the world. To improve the performance of particle swarm optimization (PSO), we herein propose a chaotic proportional integral derivative (PID) controlling PSO algorithm by the hybridization of chaotic logistic dynamics and hierarchical inertia weight. The hierarchical inertia weight coefficients are determined in accordance with the present fitness values of the local best positions so as to adaptively expand the particles’ search space. Moreover, the chaotic logistic map is not only used in the substitution of the two random parameters affecting the convergence behavior, but also used in the chaotic local search for the global best position so as to easily avoid the particles’ premature behaviors via the whole search space. Thereafter, the convergent analysis of chaotic PID controlling PSO is under deep investigation. Empirical simulation results demonstrate that compared with other several chaotic PSO algorithms like chaotic PSO with the logistic map, chaotic PSO with the tent map and chaotic catfish PSO with the logistic map, chaotic PID controlling PSO exhibits much better search efficiency and quality when solving the optimization problems. Additionally, the parameter estimation of a nonlinear dynamic system also further clarifies its superiority to chaotic catfish PSO, genetic algorithm (GA) and PSO. PMID:28472050
Empirically characteristic analysis of chaotic PID controlling particle swarm optimization.
Directory of Open Access Journals (Sweden)
Danping Yan
Full Text Available Since chaos systems generally have the intrinsic properties of sensitivity to initial conditions, topological mixing and density of periodic orbits, they may tactfully use the chaotic ergodic orbits to achieve the global optimum or their better approximation to given cost functions with high probability. During the past decade, they have increasingly received much attention from academic community and industry society throughout the world. To improve the performance of particle swarm optimization (PSO, we herein propose a chaotic proportional integral derivative (PID controlling PSO algorithm by the hybridization of chaotic logistic dynamics and hierarchical inertia weight. The hierarchical inertia weight coefficients are determined in accordance with the present fitness values of the local best positions so as to adaptively expand the particles' search space. Moreover, the chaotic logistic map is not only used in the substitution of the two random parameters affecting the convergence behavior, but also used in the chaotic local search for the global best position so as to easily avoid the particles' premature behaviors via the whole search space. Thereafter, the convergent analysis of chaotic PID controlling PSO is under deep investigation. Empirical simulation results demonstrate that compared with other several chaotic PSO algorithms like chaotic PSO with the logistic map, chaotic PSO with the tent map and chaotic catfish PSO with the logistic map, chaotic PID controlling PSO exhibits much better search efficiency and quality when solving the optimization problems. Additionally, the parameter estimation of a nonlinear dynamic system also further clarifies its superiority to chaotic catfish PSO, genetic algorithm (GA and PSO.
Directory of Open Access Journals (Sweden)
Meysam Gheisarnezhad
2015-01-01
Full Text Available Fractional-order PID (FOPID controller is a generalization of standard PID controller using fractional calculus. Compared with the Standard PID controller, two adjustable variables “differential order” and “integral order” are added to the PID controller.Three tank system is a nonlinear multivariable process that is a good prototype of chemical industrial processes. Cuckoo Optimization Algorithm (COA, that was recently introduced has shown its good performance in optimization problems. In this study, Improved Cuckoo Optimization Algorithm (ICOA has been presented. The aim of the paper is to compare different controllers tuned with a Improved Cuckoo Optimization Algorithm (ICOA for Three Tank System. In order to compare the performance of the optimized FOPID controller with other controllers, Genetic Algorithm(GA, Particle swarm optimization (PSO, Cuckoo Optimization Algorithm (COA and Imperialist Competitive Algorithm (ICA.
Adare, A; Ajitanand, N N; Akiba, Y; Akimoto, R; Al-Bataineh, H; Alexander, J; Alfred, M; Angerami, A; Aoki, K; Apadula, N; Aramaki, Y; Asano, H; Atomssa, E T; Averbeck, R; Awes, T C; Azmoun, B; Babintsev, V; Bai, M; Baksay, G; Baksay, L; Bandara, N S; Bannier, B; Barish, K N; Bassalleck, B; Basye, A T; Bathe, S; Baublis, V; Baumann, C; Bazilevsky, A; Beaumier, M; Beckman, S; Belikov, S; Belmont, R; Bennett, R; Berdnikov, A; Berdnikov, Y; Bhom, J H; Black, D; Blau, D S; Bok, J; Bok, J S; Boyle, K; Brooks, M L; Bryslawskyj, J; Buesching, H; Bumazhnov, V; Bunce, G; Butsyk, S; Campbell, S; Caringi, A; Chen, C -H; Chi, C Y; Chiu, M; Choi, I J; Choi, J B; Choudhury, R K; Christiansen, P; Chujo, T; Chung, P; Chvala, O; Cianciolo, V; Citron, Z; Cole, B A; del Valle, Z Conesa; Connors, M; Csanád, M; Csörgő, T; Dahms, T; Dairaku, S; Danchev, I; Das, K; Datta, A; Daugherity, M S; David, G; Dayananda, M K; DeBlasio, K; Dehmelt, K; Denisov, A; Deshpande, A; Desmond, E J; Dharmawardane, K V; Dietzsch, O; Ding, L; Dion, A; Do, J H; Donadelli, M; Drapier, O; Drees, A; Drees, K A; Durham, J M; Durum, A; Dutta, D; D'Orazio, L; Edwards, S; Efremenko, Y V; Ellinghaus, F; Engelmore, T; Enokizono, A; En'yo, H; Esumi, S; Eyser, K O; Fadem, B; Feege, N; Fields, D E; Finger, M; Jr., \\,; Fleuret, F; Fokin, S L; Fraenkel, Z; Frantz, J E; Franz, A; Frawley, A D; Fujiwara, K; Fukao, Y; Fusayasu, T; Gal, C; Gallus, P; Garg, P; Garishvili, I; Ge, H; Giordano, F; Glenn, A; Gong, H; Gonin, M; Goto, Y; de Cassagnac, R Granier; Grau, N; Greene, S V; Grim, G; Perdekamp, M Grosse; Gu, Y; Gunji, T; Guragain, H; Gustafsson, H -Å; Hachiya, T; Haggerty, J S; Hahn, K I; Hamagaki, H; Hamblen, J; Han, R; Han, S Y; Hanks, J; Hasegawa, S; Haslum, E; Hayano, R; He, X; Heffner, M; Hemmick, T K; Hester, T; Hill, J C; Hohlmann, M; Hollis, R S; Holzmann, W; Homma, K; Hong, B; Horaguchi, T; Hornback, D; Hoshino, T; Huang, S; Ichihara, T; Ichimiya, R; Ikeda, Y; Imai, K; Imazu, Y; Inaba, M; Iordanova, A; Isenhower, D; Ishihara, M; Issah, M; Ivanischev, D; Ivanishchev, D; Iwanaga, Y; Jacak, B V; Jeon, S J; Jezghani, M; Jia, J; Jiang, X; Jin, J; Johnson, B M; Jones, T; Joo, E; Joo, K S; Jouan, D; Jumper, D S; Kajihara, F; Kamin, J; Kang, J H; Kang, J S; Kapustinsky, J; Karatsu, K; Kasai, M; Kawall, D; Kawashima, M; Kazantsev, A V; Kempel, T; Key, J A; Khachatryan, V; Khanzadeev, A; Kihara, K; Kijima, K M; Kikuchi, J; Kim, A; Kim, B I; Kim, C; Kim, D H; Kim, D J; Kim, E -J; Kim, H -J; Kim, M; Kim, Y -J; Kim, Y K; Kinney, E; Kiss, Á; Kistenev, E; Klatsky, J; Kleinjan, D; Kline, P; Koblesky, T; Kochenda, L; Kofarago, M; Komkov, B; Konno, M; Koster, J; Kotov, D; Král, A; Kravitz, A; Kunde, G J; Kurita, K; Kurosawa, M; Kwon, Y; Kyle, G S; Lacey, R; Lai, Y S; Lajoie, J G; Lebedev, A; Lee, D M; Lee, J; Lee, K B; Lee, K S; Lee, S H; Leitch, M J; Leite, M A L; Leitgab, M; Li, X; Lichtenwalner, P; Liebing, P; Lim, S H; Levy, L A Linden; Liška, T; Liu, H; Liu, M X; Love, B; Lynch, D; Maguire, C F; Makdisi, Y I; Makek, M; Malik, M D; Manion, A; Manko, V I; Mannel, E; Mao, Y; Masui, H; Matathias, F; McCumber, M; McGaughey, P L; McGlinchey, D; McKinney, C; Means, N; Meles, A; Mendoza, M; Meredith, B; Miake, Y; Mibe, T; Mignerey, A C; Miki, K; Miller, A J; Milov, A; Mishra, D K; Mitchell, J T; Miyasaka, S; Mizuno, S; Mohanty, A K; Montuenga, P; Moon, H J; Moon, T; Morino, Y; Morreale, A; Morrison, D P; Moukhanova, T V; Murakami, T; Murata, J; Mwai, A; Nagamiya, S; Nagle, J L; Naglis, M; Nagy, M I; Nakagawa, I; Nakagomi, H; Nakamiya, Y; Nakamura, K R; Nakamura, T; Nakano, K; Nam, S; Nattrass, C; Netrakanti, P K; Newby, J; Nguyen, M; Nihashi, M; Niida, T; Nouicer, R; Novitzky, N; Nyanin, A S; Oakley, C; O'Brien, E; Oda, S X; Ogilvie, C A; Oka, M; Okada, K; Onuki, Y; Koop, J D Orjuela; Oskarsson, A; Ouchida, M; Ozaki, H; Ozawa, K; Pak, R; Pantuev, V; Papavassiliou, V; Park, I H; Park, S; Park, S K; Park, W J; Pate, S F; Patel, L; Patel, M; Pei, H; Peng, J -C; Pereira, H; Perepelitsa, D V; Perera, G D N; Peressounko, D Yu; Perry, J; Petti, R; Pinkenburg, C; Pinson, R; Pisani, R P; Proissl, M; Purschke, M L; Qu, H; Rak, J; Ravinovich, I; Read, K F; Rembeczki, S; Reygers, K; Reynolds, D; Riabov, V; Riabov, Y; Richardson, E; Riveli, N; Roach, D; Roche, G; Rolnick, S D; Rosati, M; Rosen, C A; Rosendahl, S S E; Rowan, Z; Rubin, J G; Ružička, P; Sahlmueller, B; Saito, N; Sakaguchi, T; Sakashita, K; Sako, H; Samsonov, V; Sano, S; Sarsour, M; Sato, S; Sato, T; Sawada, S; Schaefer, B; Schmoll, B K; Sedgwick, K; Seele, J; Seidl, R; Sen, A; Seto, R; Sett, P; Sexton, A; Sharma, D; Shein, I; Shibata, T -A; Shigaki, K; Shimomura, M; Shoji, K; Shukla, P; Sickles, A; Silva, C L; Silvermyr, D; Silvestre, C; Sim, K S; Singh, B K; Singh, C P; Singh, V; Slunečka, M; Soltz, R A; Sondheim, W E; Sorensen, S P; Sourikova, I V; Stankus, P W; Stenlund, E; Stepanov, M; Stoll, S P; Sugitate, T; Sukhanov, A; Sumita, T; Sun, J; Sziklai, J; Takagui, E M; Takahara, A; Taketani, A; Tanabe, R; Tanaka, Y; Taneja, S; Tanida, K; Tannenbaum, M J; Tarafdar, S; Taranenko, A; Themann, H; Thomas, D; Thomas, T L; Timilsina, A; Todoroki, T; Togawa, M; Toia, A; Tomášek, L; Tomášek, M; Torii, H; Towell, M; Towell, R; Towell, R S; Tserruya, I; Tsuchimoto, Y; Vale, C; Valle, H; van Hecke, H W; Vargyas, M; Vazquez-Zambrano, E; Veicht, A; Velkovska, J; Vértesi, R; Virius, M; Vrba, V; Vznuzdaev, E; Wang, X R; Watanabe, D; Watanabe, K; Watanabe, Y; Watanabe, Y S; Wei, F; Wei, R; Wessels, J; Whitaker, S; White, S N; Winter, D; Wolin, S; Woody, C L; Wright, R M; Wysocki, M; Xia, B; Xue, L; Yalcin, S; Yamaguchi, Y L; Yamaura, K; Yang, R; Yanovich, A; Ying, J; Yokkaichi, S; Yoon, I; You, Z; Young, G R; Younus, I; Yushmanov, I E; Zajc, W A; Zelenski, A; Zhou, S
2014-01-01
We present a measurement of the cross section and transverse single-spin asymmetry ($A_N$) for $\\eta$ mesons from $\\sqrt{s}=200$ GeV $p^{\\uparrow}+p$ collisions. The measured cross section for $1.5
Adare, A; Aidala, C; Ajitanand, N N; Akiba, Y; Al-Bataineh, H; Alexander, J; Al-Ta'ani, H; Angerami, A; Aoki, K; Apadula, N; Aphecetche, L; Aramaki, Y; Asai, J; Atomssa, E T; Averbeck, R; Awes, T C; Azmoun, B; Babintsev, V; Bai, M; Baksay, G; Baksay, L; Baldisseri, A; Barish, K N; Barnes, P D; Bassalleck, B; Basye, A T; Bathe, S; Batsouli, S; Baublis, V; Baumann, C; Bazilevsky, A; Belikov, S; Belmont, R; Bennett, R; Berdnikov, A; Berdnikov, Y; Bhom, J H; Bickley, A A; Blau, D S; Boissevain, J G; Bok, J S; Borel, H; Borggren, N; Boyle, K; Brooks, M L; Buesching, H; Bumazhnov, V; Bunce, G; Butsyk, S; Camacho, C M; Campbell, S; Caringi, A; Chang, B S; Chang, W C; Charvet, J -L; Chen, C -H; Chernichenko, S; Chi, C Y; Chiu, M; Choi, I J; Choi, J B; Choudhury, R K; Christiansen, P; Chujo, T; Chung, P; Churyn, A; Chvala, O; Cianciolo, V; Citron, Z; Cole, B A; del Valle, Z Conesa; Connors, M; Constantin, P; Csanád, M; Csörgő, T; Dahms, T; Dairaku, S; Danchev, I; Das, K; Datta, A; David, G; Dayananda, M K; Denisov, A; d'Enterria, D; Deshpande, A; Desmond, E J; Dharmawardane, K V; Dietzsch, O; Dion, A; Donadelli, M; Orazio, L D; Drapier, O; Drees, A; Drees, K A; Dubey, A K; Durham, J M; Durum, A; Dutta, D; Dzhordzhadze, V; Edwards, S; Efremenko, Y V; Ellinghaus, F; Engelmore, T; Enokizono, A; En'yo, H; Esumi, S; Eyser, K O; Fadem, B; Fields, D E; Finger, M; Finger, M; Fleuret, F; Fokin, S L; Fraenkel, Z; Frantz, J E; Franz, A; Frawley, A D; Fujiwara, K; Fukao, Y; Fusayasu, T; Garishvili, I; Glenn, A; Gong, H; Gonin, M; Gosset, J; Goto, Y; de Cassagnac, R Granier; Grau, N; Greene, S V; Grim, G; Perdekamp, M Grosse; Gunji, T; Gustafsson, H -Å; Henni, A Hadj; Haggerty, J S; Hahn, K I; Hamagaki, H; Hamblen, J; Hanks, J; Han, R; Hartouni, E P; Haruna, K; Haslum, E; Hayano, R; Heffner, M; Hemmick, T K; Hester, T; He, X; Hill, J C; Hohlmann, M; Holzmann, W; Homma, K; Hong, B; Horaguchi, T; Hornback, D; Huang, S; Ichihara, T; Ichimiya, R; Iinuma, H; Ikeda, Y; Imai, K; Imrek, J; Inaba, M; Isenhower, D; Ishihara, M; Isobe, T; Issah, M; Isupov, A; Ivanischev, D; Iwanaga, Y; Jacak, B V; Jia, J; Jiang, X; Jin, J; Johnson, B M; Jones, T; Joo, K S; Jouan, D; Jumper, D S; Kajihara, F; Kametani, S; Kamihara, N; Kamin, J; Kang, J H; Kapustinsky, J; Karatsu, K; Kasai, M; Kawall, D; Kawashima, M; Kazantsev, A V; Kempel, T; Khanzadeev, A; Kijima, K M; Kikuchi, J; Kim, A; Kim, B I; Kim, D H; Kim, D J; Kim, E J; Kim, E; Kim, S H; Kim, Y -J; Kinney, E; Kiriluk, K; Kiss, Á; Kistenev, E; Klay, J; Klein-Boesing, C; Kochenda, L; Komkov, B; Konno, M; Koster, J; Kozlov, A; Král, A; Kravitz, A; Kunde, G J; Kurita, K; Kurosawa, M; Kweon, M J; Kwon, Y; Kyle, G S; Lacey, R; Lai, Y S; Lajoie, J G; Layton, D; Lebedev, A; Lee, D M; Lee, J; Lee, K B; Lee, K S; Lee, T; Leitch, M J; Leite, M A L; Lenzi, B; Lichtenwalner, P; Liebing, P; Levy, L A Linden; Liška, T; Litvinenko, A; Liu, H; Liu, M X; Li, X; Love, B; Lynch, D; Maguire, C F; Makdisi, Y I; Malakhov, A; Malik, M D; Manko, V I; Mannel, E; Mao, Y; Mašek, L; Masui, H; Matathias, F; McCumber, M; McGaughey, P L; Means, N; Meredith, B; Miake, Y; Mibe, T; Mignerey, A C; Mikeš, P; Miki, K; Milov, A; Mishra, M; Mitchell, J T; Mohanty, A K; Moon, H J; Morino, Y; Morreale, A; Morrison, D P; Moukhanova, T V; Mukhopadhyay, D; Murakami, T; Murata, J; Nagamiya, S; Nagle, J L; Naglis, M; Nagy, M I; Nakagawa, I; Nakamiya, Y; Nakamura, K R; Nakamura, T; Nakano, K; Nam, S; Newby, J; Nguyen, M; Nihashi, M; Niita, T; Nouicer, R; Nyanin, A S; Oakley, C; O'Brien, E; Oda, S X; Ogilvie, C A; Okada, K; Oka, M; Onuki, Y; Oskarsson, A; Ouchida, M; Ozawa, K; Pak, R; Palounek, A P T; Pantuev, V; Papavassiliou, V; Park, I H; Park, J; Park, S K; Park, W J; Pate, S F; Pei, H; Peng, J -C; Pereira, H; Peresedov, V; Peressounko, D Yu; Petti, R; Pinkenburg, C; Pisani, R P; Proissl, M; Purschke, M L; Purwar, A K; Qu, H; Rak, J; Rakotozafindrabe, A; Ravinovich, I; Read, K F; Rembeczki, S; Reygers, K; Riabov, V; Riabov, Y; Richardson, E; Roach, D; Roche, G; Rolnick, S D; Rosati, M; Rosen, C A; Rosendahl, S S E; Rosnet, P; Rukoyatkin, P; Ružička, P; Rykov, V L; Sahlmueller, B; Saito, N; Sakaguchi, T; Sakai, S; Sakashita, K; Samsonov, V; Sano, S; Sato, T; Sawada, S; Sedgwick, K; Seele, J; Seidl, R; Semenov, A Yu; Semenov, V; Seto, R; Sharma, D; Shein, I; Shibata, T -A; Shigaki, K; Shimomura, M; Shoji, K; Shukla, P; Sickles, A; Silva, C L; Silvermyr, D; Silvestre, C; Sim, K S; Singh, B K; Singh, C P; Singh, V; Slunečka, M; Soldatov, A; Soltz, R A; Sondheim, W E; Sorensen, S P; Sourikova, I V; Staley, F; Stankus, P W; Stenlund, E; Stepanov, M; Ster, A; Stoll, S P; Sugitate, T; Suire, C; Sukhanov, A; Sziklai, J; Takagui, E M; Taketani, A; Tanabe, R; Tanaka, Y; Taneja, S; Tanida, K; Tannenbaum, M J; Tarafdar, S; Taranenko, A; Tarján, P; Themann, H; Thomas, D; Thomas, T L; Togawa, M; Toia, A; Tomášek, L; Tomita, Y; Torii, H; Towell, R S; Tram, V-N; Tserruya, I; Tsuchimoto, Y; Vale, C; Valle, H; van Hecke, H W; Vazquez-Zambrano, E; Veicht, A; Velkovska, J; Vértesi, R; Vinogradov, A A; Virius, M; Vrba, V; Vznuzdaev, E; Wang, X R; Watanabe, D; Watanabe, K; Watanabe, Y; Wei, F; Wessels, J; White, S N; Winter, D; Woody, C L; Wright, R M; Wysocki, M; Xie, W; Yamaguchi, Y L; Yamaura, K; Yang, R; Yanovich, A; Ying, J; Yokkaichi, S; Young, G R; Younus, I; You, Z; Yushmanov, I E; Zajc, W A; Zaudtke, O; Zhang, C; Zhou, S; Zolin, L
2010-01-01
We report the first measurement of transverse single-spin asymmetries in $J/\\psi$ production from transversely polarized $p+p$ collisions at $\\sqrt{s} = 200$ GeV with data taken by the PHENIX experiment in 2006 and 2008. The measurement was performed over the rapidity ranges $1.2 < |y| < 2.2$ and $ |y| < 0.35$ for transverse momenta up to 6 GeV/$c$. $J/\\psi$ production at RHIC is dominated by processes involving initial-state gluons, and transverse single-spin asymmetries of the $J/\\psi$ can provide access to gluon dynamics within the nucleon. Such asymmetries may also shed light on the long-standing question in QCD of the $J/\\psi$ production mechanism. Asymmetries were obtained as a function of $J/\\psi$ transverse momentum and Feynman-$x$, with a value of $-0.086 \\pm 0.026^{\\rm stat} \\pm 0.003^{\\rm syst}$ in the forward region. This result suggests possible nonzero trigluon correlation functions in transversely polarized protons and, if well defined in this reaction, a nonzero gluon Sivers distribut...
Cost Effectiveness Analysis of Optimal Malaria Control Strategies in Kenya
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Gabriel Otieno
2016-03-01
Full Text Available Malaria remains a leading cause of mortality and morbidity among the children under five and pregnant women in sub-Saharan Africa, but it is preventable and controllable provided current recommended interventions are properly implemented. Better utilization of malaria intervention strategies will ensure the gain for the value for money and producing health improvements in the most cost effective way. The purpose of the value for money drive is to develop a better understanding (and better articulation of costs and results so that more informed, evidence-based choices could be made. Cost effectiveness analysis is carried out to inform decision makers on how to determine where to allocate resources for malaria interventions. This study carries out cost effective analysis of one or all possible combinations of the optimal malaria control strategies (Insecticide Treated Bednets—ITNs, Treatment, Indoor Residual Spray—IRS and Intermittent Preventive Treatment for Pregnant Women—IPTp for the four different transmission settings in order to assess the extent to which the intervention strategies are beneficial and cost effective. For the four different transmission settings in Kenya the optimal solution for the 15 strategies and their associated effectiveness are computed. Cost-effective analysis using Incremental Cost Effectiveness Ratio (ICER was done after ranking the strategies in order of the increasing effectiveness (total infections averted. The findings shows that for the endemic regions the combination of ITNs, IRS, and IPTp was the most cost-effective of all the combined strategies developed in this study for malaria disease control and prevention; for the epidemic prone areas is the combination of the treatment and IRS; for seasonal areas is the use of ITNs plus treatment; and for the low risk areas is the use of treatment only. Malaria transmission in Kenya can be minimized through tailor-made intervention strategies for malaria control
Kinematics, Dynamics, and Optimal Control of Pneumatic Hexapod Robot
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Long Bai
2017-01-01
Full Text Available Pneumatic hexapod robot is driven by inert gas carried by itself, which has board application prospect in rescue operation of disaster conditions containing flammable gas. Cruising ability is main constraint for practical engineering application which is influenced by kinematics and dynamics character. The matrix operators and pseudospectral method are used to solve dynamics modeling and numerical calculation problem of robot under straight line walking. Kinematics model is numerically solved and relationship of body, joints, and drive cylinders is obtained. With dynamics model and kinematics boundary conditions, the optimal input gas pressure of leg swing and body moving in one step is obtained by pseudospectral method. According to action character of magnetic valve, calculation results of control inputs satisfy engineering design requirements, and cruising ability under finite gas is obtained.
Optimal drinking water composition for caries control in populations
DEFF Research Database (Denmark)
Bruvo, M.; Ekstrand, K.; Arvin, Erik
2008-01-01
Apart from the well-documented effect of fluoride in drinking water on dental caries, little is known about other chemical effects. Since other ions in drinking water may also theoretically influence caries, as well as binding of fluoride in the oral environment, we hypothesized that the effect...... of drinking water on caries may not be limited to fluoride only. Among 22 standard chemical variables, including 15 ions and trace elements as well as gases, organic compounds, and physical measures, iterative search and testing identified that calcium and fluoride together explained 45% of the variations...... in the numbers of decayed, filled, and missing tooth surfaces (DMF-S) among 52,057 15-year-old schoolchildren in 249 Danish municipalities. Both ions had reducing effects on DMF-S independently of each other, and could be used in combination for the design of optimal drinking water for caries control...
Han, Lanshan; Camlibel, M. Kanat; Pang, Jong-Shi; Heemels, W. P. Maurice H.
2012-01-01
This paper presents a numerical scheme for solving the continuous-time convex linear-quadratic (LQ) optimal control problem with mixed polyhedral state and control constraints. Unifying a discretization of this optimal control problem as often employed in model predictive control and that obtained
Dynamic optimization model for allocating medical resources in epidemic controlling
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Ming Liu
2013-03-01
Full Text Available Purpose: The model proposed in this paper addresses a dynamic optimization model for allocating medical resources in epidemic controlling.Design/methodology/approach: In this work, a three-level and dynamic linear programming model for allocating medical resources based on epidemic diffusion model is proposed. The epidemic diffusion model is used to construct the forecasting mechanism for dynamic demand of medical resources. Heuristic algorithm coupled with MTLAB mathematical programming solver is adopted to solve the model. A numerical example is presented for testing the model’s practical applicability.Findings: The main contribution of the present study is that a discrete time-space network model to study the medical resources allocation problem when an epidemic outbreak is formulated. It takes consideration of the time evolution and dynamic nature of the demand, which is different from most existing researches on medical resources allocation.Practical implications: In our model, the medicine logistics operation problem has been decomposed into several mutually correlated sub-problems, and then be solved systematically in the same decision scheme. Thus, the result will be much more suitable for real operations.Originality/value: In our model, the rationale that the medical resources allocated in early periods will take effect in subduing the spread of the epidemic spread and thus impact the demand in later periods has been for the first time incorporated. A win-win emergency rescue effect is achieved by the integrated and dynamic optimization model. The total rescue cost is controlled effectively, and meanwhile, inventory level in each urban health departments is restored and raised gradually.
Estimation of Saxophone Control Parameters by Convex Optimization.
Wang, Cheng-I; Smyth, Tamara; Lipton, Zachary C
2014-12-01
In this work, an approach to jointly estimating the tone hole configuration (fingering) and reed model parameters of a saxophone is presented. The problem isn't one of merely estimating pitch as one applied fingering can be used to produce several different pitches by bugling or overblowing. Nor can a fingering be estimated solely by the spectral envelope of the produced sound (as it might for estimation of vocal tract shape in speech) since one fingering can produce markedly different spectral envelopes depending on the player's embouchure and control of the reed. The problem is therefore addressed by jointly estimating both the reed (source) parameters and the fingering (filter) of a saxophone model using convex optimization and 1) a bank of filter frequency responses derived from measurement of the saxophone configured with all possible fingerings and 2) sample recordings of notes produced using all possible fingerings, played with different overblowing, dynamics and timbre. The saxophone model couples one of several possible frequency response pairs (corresponding to the applied fingering), and a quasi-static reed model generating input pressure at the mouthpiece, with control parameters being blowing pressure and reed stiffness. Applied fingering and reed parameters are estimated for a given recording by formalizing a minimization problem, where the cost function is the error between the recording and the synthesized sound produced by the model having incremental parameter values for blowing pressure and reed stiffness. The minimization problem is nonlinear and not differentiable and is made solvable using convex optimization. The performance of the fingering identification is evaluated with better accuracy than previous reported value.
A novel technique for active vibration control, based on optimal tracking control
Kheiri Sarabi, Behrouz; Sharma, Manu; Kaur, Damanjeet
2017-08-01
In the last few decades, researchers have proposed many control techniques to suppress unwanted vibrations in a structure. In this work, a novel and simple technique is proposed for the active vibration control. In this technique, an optimal tracking control is employed to suppress vibrations in a structure by simultaneously tracking zero references for modes of vibration. To illustrate the technique, a two-degrees of freedom spring-mass-damper system is considered as a test system. The mathematical model of the system is derived and then converted into a state-space model. A linear quadratic tracking control law is then used to make the disturbed system track zero references.
Information spread in networks: Games, optimal control, and stabilization
Khanafer, Ali
This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack
Pipeline heating method based on optimal control and state estimation
Energy Technology Data Exchange (ETDEWEB)
Vianna, F.L.V. [Dept. of Subsea Technology. Petrobras Research and Development Center - CENPES, Rio de Janeiro, RJ (Brazil)], e-mail: fvianna@petrobras.com.br; Orlande, H.R.B. [Dept. of Mechanical Engineering. POLI/COPPE, Federal University of Rio de Janeiro - UFRJ, Rio de Janeiro, RJ (Brazil)], e-mail: helcio@mecanica.ufrj.br; Dulikravich, G.S. [Dept. of Mechanical and Materials Engineering. Florida International University - FIU, Miami, FL (United States)], e-mail: dulikrav@fiu.edu
2010-07-01
In production of oil and gas wells in deep waters the flowing of hydrocarbon through pipeline is a challenging problem. This environment presents high hydrostatic pressures and low sea bed temperatures, which can favor the formation of solid deposits that in critical operating conditions, as unplanned shutdown conditions, may result in a pipeline blockage and consequently incur in large financial losses. There are different methods to protect the system, but nowadays thermal insulation and chemical injection are the standard solutions normally used. An alternative method of flow assurance is to heat the pipeline. This concept, which is known as active heating system, aims at heating the produced fluid temperature above a safe reference level in order to avoid the formation of solid deposits. The objective of this paper is to introduce a Bayesian statistical approach for the state estimation problem, in which the state variables are considered as the transient temperatures within a pipeline cross-section, and to use the optimal control theory as a design tool for a typical heating system during a simulated shutdown condition. An application example is presented to illustrate how Bayesian filters can be used to reconstruct the temperature field from temperature measurements supposedly available on the external surface of the pipeline. The temperatures predicted with the Bayesian filter are then utilized in a control approach for a heating system used to maintain the temperature within the pipeline above the critical temperature of formation of solid deposits. The physical problem consists of a pipeline cross section represented by a circular domain with four points over the pipe wall representing heating cables. The fluid is considered stagnant, homogeneous, isotropic and with constant thermo-physical properties. The mathematical formulation governing the direct problem was solved with the finite volume method and for the solution of the state estimation problem
Directory of Open Access Journals (Sweden)
T.B. Nikitina
2017-04-01
Full Text Available Purpose. Developed the method for solving the problem of multiobjective synthesis of robust control by multimass electromechanical systems based on the construction of the Pareto optimal solutions using multiswarm stochastic multi-agent optimization of particles swarm, which reduces the time of determining the parameters of robust controls multimass electromechanical systems and satisfy a variety of requirements that apply to the work of such systems in different modes. Methodology. Multiobjective synthesis of robust control of multimass electromechanical systems is reduced to the solution of solving the problem of multiobjective optimization. To correct the above problem solving multiobjective optimization in addition to the vector optimization criteria and constraints must also be aware of the binary preference relations of local solutions against each other. The basis for such a formal approach is to build areas of Pareto-optimal solutions. This approach can significantly narrow down the range of possible solutions of the problem of optimal initial multiobjective optimization and, consequently, reduce the complexity of the person making the decision on the selection of a single version of the optimal solution. Results. The results of the synthesis of multi-criteria electromechanical servo system and a comparison of dynamic characteristics, and it is shown that the use of synthesized robust controllers reduced the error guidance working mechanism and reduced the system sensitivity to changes in the control parameters of the object compared to the existing system with standard controls. Originality. For the first time, based on the construction of the Pareto optimal solutions using a multiswarm stochastic multi-agent optimization particle algorithms improved method for solving formulated multiobjective multiextremal nonlinear programming problem with constraints, to which the problem of multiobjective synthesis of robust controls by multimass
EMBEDDED CONTROLLER BUILDING FOR BALL AND BEAM SYSTEM USING OPTIMAL CONTROL SYNTHESIS
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B. M. HUNG
2017-06-01
Full Text Available The controller design for the Ball and Beam system is particularly crucial in the aviation fields due to its likeness to the aircraft control during the flight and landing under turbulent. Since the actual tests on the aircrafts are not possible, the Ball and Beam system could be necessary as an alternative to these manoeuvring. In addition, the ball and beam system is a nonlinear dynamical model intended to test various control algorithms. The complete system includes a ball, a beam, a motor and several sensors. The input torque is generated from the motor to control the position of the ball on the beam, where the ball rolls on the beam freely. The concise mathematical model has been obtained by linearized around the horizontal region. The presented control strategies are based on the optimal control synthesis including LQR and H2 optimization to manipulate the complete ball-beam system. These control algorithms have been successfully tested to figure out the control performance for specific applications. Finally, the control systems are implemented in the real ball and beam system with a data acquisition card of DSP F28335.
Implementation of an optimal control energy management strategy in a hybrid truck
Mullem, D. van; Keulen, T. van; Kessels, J.T.B.A.; Jager, B. de; Steinbuch, M.
2010-01-01
Energy Management Strategies for hybrid powertrains control the power split, between the engine and electric motor, of a hybrid vehicle, with fuel consumption or emission minimization as objective. Optimal control theory can be applied to rewrite the optimization problem to an optimization
Simultaneously learning and optimizing using controlled variance pricing
den Boer, A.V.; Zwart, Bert
Price experimentation is an important tool for firms to find the optimal selling price of their products. It should be conducted properly, since experimenting with selling prices can be costly. A firm, therefore, needs to find a pricing policy that optimally balances between learning the optimal
Directory of Open Access Journals (Sweden)
Mojtaba Biglar
2014-01-01
Full Text Available This study addresses new formulation for active vibration control of plates by optimal locations of attached piezotransducers. Free vibrations are solved by Rayleigh-Ritz and transient by assumed modes methods. Optimal orientations of patches are determined by spatial controllability/observability, as well as residual modes to reduce spillover. These criteria are used to achieve optimal fitness function defined for genetic algorithm to find optimal locations. To control vibrations, negative velocity feedback control is designed. Results indicate that, by locating piezopatches at optimal positions, depreciation rate increases and amplitudes of vibrations reduce effectively. The effect of number of piezodevices is analyzed.
Optimal Control Approaches to the Aggregate Production Planning Problem
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Yasser A. Davizón
2015-12-01
Full Text Available In the area of production planning and control, the aggregate production planning (APP problem represents a great challenge for decision makers in production-inventory systems. Tradeoff between inventory-capacity is known as the APP problem. To address it, static and dynamic models have been proposed, which in general have several shortcomings. It is the premise of this paper that the main drawback of these proposals is, that they do not take into account the dynamic nature of the APP. For this reason, we propose the use of an Optimal Control (OC formulation via the approach of energy-based and Hamiltonian-present value. The main contribution of this paper is the mathematical model which integrates a second order dynamical system coupled with a first order system, incorporating production rate, inventory level, and capacity as well with the associated cost by work force in the same formulation. Also, a novel result in relation with the Hamiltonian-present value in the OC formulation is that it reduces the inventory level compared with the pure energy based approach for APP. A set of simulations are provided which verifies the theoretical contribution of this work.
Optimally Scaled H(sub infinity) Full Information Control Synthesis with Real Uncertainty
Balas, Gary J.; Lind, Rick; Packard, Andy
1996-01-01
This paper presents an algorithm to synthesize optimal controllers for the scaled H(sub infinity). full information problem with real and complex uncertainty. The control problem is reduced to a linear matrix inequality which can be solved via a finite dimensional convex optimization. This technique is compared with the optimal scaled H(sub infinity). full information with only complex uncertainty and D - K iteration control design to synthesize controllers for a missile autopilot. Directly including real parametric uncertainty into the control design results in improved robust performance of the missile autopilot. The controller synthesized via D - K iteration achieves results similar to the optimal designs.
Optimizing and controlling earthmoving operations using spatial technologies
Alshibani, Adel
This thesis presents a model designed for optimizing, tracking, and controlling earthmoving operations. The proposed model utilizes, Genetic Algorithm (GA), Linear Programming (LP), and spatial technologies including Global Positioning Systems (GPS) and Geographic Information Systems (GIS) to support the management functions of the developed model. The model assists engineers and contractors in selecting near optimum crew formations in planning phase and during construction, using GA and LP supported by the Pathfinder Algorithm developed in a GIS environment. GA is used in conjunction with a set of rules developed to accelerate the optimization process and to avoid generating and evaluating hypothetical and unrealistic crew formations. LP is used to determine quantities of earth to be moved from different borrow pits and to be placed at different landfill sites to meet project constraints and to minimize the cost of these earthmoving operations. On the one hand, GPS is used for onsite data collection and for tracking construction equipment in near real-time. On the other hand, GIS is employed to automate data acquisition and to analyze the collected spatial data. The model is also capable of reconfiguring crew formations dynamically during the construction phase while site operations are in progress. The optimization of the crew formation considers: (1) construction time, (2) construction direct cost, or (3) construction total cost. The model is also capable of generating crew formations to meet, as close as possible, specified time and/or cost constraints. In addition, the model supports tracking and reporting of project progress utilizing the earned-value concept and the project ratio method with modifications that allow for more accurate forecasting of project time and cost at set future dates and at completion. The model is capable of generating graphical and tabular reports. The developed model has been implemented in prototype software, using Object
Data mining Aided Proficient approach for optimal inventory control in supply chain management
Chitriki Thotappa; K. Ravindranath
2010-01-01
Optimal inventory control is one of the significant tasks in supply chain management. The optimal inventory control methodologies intend to reduce the supply chain (SC) cost by controlling the inventory in an effective manner, such that, the SC members will not be affected by surplus as well as shortage of inventory. In this paper, we propose an efficient approach that effectively utilizes the data mining concepts as well as genetic algorithm for optimal inventory control. The proposed approa...
Directory of Open Access Journals (Sweden)
Saifullah Khalid
2016-09-01
Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.
Optimal dynamics for quality control in spatially distributed mitochondrial networks.
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Pinkesh K Patel
Full Text Available Recent imaging studies of mitochondrial dynamics have implicated a cycle of fusion, fission, and autophagy in the quality control of mitochondrial function by selectively increasing the membrane potential of some mitochondria at the expense of the turnover of others. This complex, dynamical system creates spatially distributed networks that are dependent on active transport along cytoskeletal networks and on protein import leading to biogenesis. To study the relative impacts of local interactions between neighboring mitochondria and their reorganization via transport, we have developed a spatiotemporal mathematical model encompassing all of these processes in which we focus on the dynamics of a health parameter meant to mimic the functional state of mitochondria. In agreement with previous models, we show that both autophagy and the generation of membrane potential asymmetry following a fusion/fission cycle are required for maintaining a healthy mitochondrial population. This health maintenance is affected by mitochondrial density and motility primarily through changes in the frequency of fusion events. Health is optimized when the selectivity thresholds for fusion and fission are matched, providing a mechanistic basis for the observed coupling of the two processes through the protein OPA1. We also demonstrate that the discreteness of the components exchanged during fusion is critical for quality control, and that the effects of limiting total amounts of autophagy and biogenesis have distinct consequences on health and population size, respectively. Taken together, our results show that several general principles emerge from the complexity of the quality control cycle that can be used to focus and interpret future experimental studies, and our modeling framework provides a road-map for deconstructing the functional importance of local interactions in communities of cells as well as organelles.
Modelling 3D control of upright stance using an optimal control strategy.
Qu, Xingda; Nussbaum, Maury A
2012-01-01
A 3D balance control model of quiet upright stance is presented, based on an optimal control strategy, and evaluated in terms of its ability to simulate postural sway in both the anterior-posterior and medial-lateral directions. The human body was represented as a two-segment inverted pendulum. Several assumptions were made to linearise body dynamics, for example, that there was no transverse rotation during upright stance. The neural controller was presumed to be an optimal controller that generates ankle control torque and hip control torque according to certain performance criteria. An optimisation procedure was used to determine the values of unspecified model parameters including random disturbance gains and sensory delay times. This model was used to simulate postural sway behaviours characterised by centre-of-pressure (COP)-based measures. Confidence intervals for all normalised COP-based measures contained unity, indicating no significant differences between any of the simulated COP-based measures and corresponding experimental references. In addition, mean normalised errors for the traditional measures were 3D balance control model appears to have the ability to accurately simulate 3D postural sway behaviours.
An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation
Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan
2008-01-01
This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.
Optimal control of multi-level quantum systems
Energy Technology Data Exchange (ETDEWEB)
Fisher, Robert M.
2010-12-02
This thesis is concerned with the control of quantum systems. Given a Hamiltonian model of a quantum system, we are interested in finding controls - typically shaped electromagnetic pulses - that steer the evolution of the system toward a desired target operation. For this we employ a numerical optimisation method known as the GRAPE algorithm. For particular experimental systems, we design control schemes that respect constraints of robustness and addressability, and are within the reach of the experimental hardware. A general procedure is given for specifying a Hamiltonian model of a driven N-level system and converting it to an appropriate rotating frame. This is then applied together with the numerical algorithm to design improved schemes for two different systems, where laser fields manipulate orbital and hyperfine states of Pr{sup 3+} and Rb. The generation of cluster states in Ising-coupled systems is also studied. We find that, in the ideal case, the solution of evolving only under the coupling Hamiltonian is not time-optimal. This surprising result is in contrast to the known cases for unitary gates. For a symmetrised three-qubit example, we provide a geometrical interpretation of this. Numerically optimised control schemes are then developed for a nonideal coupling topology, modelling an experimental configuration of trapped ions. Controls for the implementation of the two-qubit Deutsch and Grover algorithms are designed for a pair of {sup 13}C nuclear spins at a nitrogen vacancy center in diamond. These implementations are robust to experimental errors, and found to be reproduced with high accuracy on a VFG-150 pulse generator. We also consider two-qubit gate synthesis in a system of superconducting qubits coupled by microwave resonators known as the cavity grid. We find that the optimised schemes allow two-qubit operations to be performed between an arbitrary qubit pair on the grid with only a small time overhead, with speedups of 2-4 over the existing
Optimal tuning of a control system for a second-order plant with time delay
Golinko, I. M.
2014-07-01
An engineering method for optimizing the parameters of PI and PID controllers for a second-order controlled plant with time delay is considered. An integral quality criterion involving minimization of the control output is proposed for optimizing the control system, which differs from the existing ones in that the effect the control output has on the technological process is taken into account in a correct way. The use of such control makes it possible to minimize the expenditure of material and/or energy resources, to limit the wear, and to increase the service life of the control devices. The unimodal nature of the proposed quality criterion for solving optimal controller tuning problems is numerically confirmed using the optimization theory. A functional correlation between the optimal controller parameters and dynamic properties of a controlled plant is determined for a single-loop control system with the use of calculation methods. The results from simulating the transients in the control system using the proposed and existing functional dependences are compared. The proposed calculation formulas differ from the existing ones by having simple structure, high accuracy of searching for the optimal controller parameters; they allow efficient control to be obtained and can be used for tuning automatic control systems in a wide range of controlled plant dynamic properties. The obtained calculation formulas are recommended for being used by engineers specializing in automation for designing new and optimizing the existing control systems.
Zhao, Y X; Allada, K; Aniol, K; Annand, J R M; Averett, T; Benmokhtar, F; Bertozzi, W; Bradshaw, P C; Bosted, P; Camsonne, A; Canan, M; Cates, G D; Chen, C; Chen, J -P; Chen, W; Chirapatpimol, K; Chudakov, E; Cisbani, E; Cornejo, J C; Cusanno, F; Dalton, M M; Deconinck, W; de Jager, C W; De Leo, R; Deng, X; Deur, A; Ding, H; Dolph, P A M; Dutta, C; Dutta, D; Fassi, L El; Frullani, S; Gao, H; Garibaldi, F; Gaskell, D; Gilad, S; Gilman, R; Glamazdin, O; Golge, S; Guo, L; Hamilton, D; Hansen, O; Higinbotham, D W; Holmstrom, T; Huang, J; Huang, M; Ibrahim, H F; Iodice, M; Jiang, X; Jin, G; Jones, M K; Katich, J; Kelleher, A; Kim, W; Kolarkar, A; Korsch, W; LeRose, J J; Li, X; Li, Y; Lindgren, R; Liyanage, N; Long, E; Lu, H -J; Margaziotis, D J; Markowitz, P; Marrone, S; McNulty, D; Meziani, Z -E; Michaels, R; Moffit, B; Camacho, C Muñoz; Nanda, S; Narayan, A; Nelyubin, V; Norum, B; Oh, Y; Osipenko, M; Parno, D; Peng, J -C; Phillips, S K; Posik, M; Puckett, A J R; Qian, X; Qiang, Y; Rakhman, A; Ransome, R; Riordan, S; Saha, A; Sawatzky, B; Schulte, E; Shahinyan, A; Shabestari, M H; Širca, S; Stepanyan, S; Subedi, R; Sulkosky, V; Tang, L -G; Tobias, A; Urciuoli, G M; Vilardi, I; Wang, K; Wojtsekhowski, B; Yan, X; Yao, H; Ye, Y; Ye, Z; Yuan, L; Zhan, X; Zhang, Y; Zhang, Y -W; Zhao, B; Zheng, X; Zhu, L; Zhu, X; Zong, X
2014-01-01
We report the first measurement of target single spin asymmetries of charged kaons produced in semi-inclusive deep inelastic scattering of electrons off a transversely polarized $^3{\\rm{He}}$ target. Both the Collins and Sivers moments, which are related to the nucleon transversity and Sivers distributions, respectively, are extracted over the kinematic range of 0.1$<$$x_{bj}$$<$0.4 for $K^{+}$ and $K^{-}$ production. While the Collins and Sivers moments for $K^{+}$ are consistent with zero within the experimental uncertainties, both moments for $K^{-}$ favor negative values. The Sivers moments are compared to the theoretical prediction from a phenomenological fit to the world data. While the $K^{+}$ Sivers moments are consistent with the prediction, the $K^{-}$ results differ from the prediction at the 2-sigma level.
Energy Technology Data Exchange (ETDEWEB)
Sharma, Sitansh, E-mail: sitansh@research.iiit.ac.in [Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032 (India); Singh, Harjinder, E-mail: harjinder.singh@iiit.ac.in [Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032 (India)
2011-11-18
Graphical abstract: Application of genetic algorithm optimization to control dissociation process in the ground electronic state of HF molecule is demonstrated. Highlights: Black-Right-Pointing-Pointer Genetic algorithm optimization for the design of laser pulses. Black-Right-Pointing-Pointer Control of dissociation process in the ground electronic state of HF molecule. Black-Right-Pointing-Pointer Two types of pulses, one with fixed frequency components and the other having non-deterministic components. Black-Right-Pointing-Pointer Optimized laser fields possess simple time and frequency structures. - Abstract: We have applied genetic algorithm optimization for the design of laser pulses to control dissociation process in the ground electronic state of HF molecule, within the mathematical framework of optimal control theory. In order to design the experimentally feasible laser fields, we coded the small set of selected field parameters in the GA parameter space. Two types of pulses, one with fixed frequency components and the other having non-deterministic components have been designed. Optimized laser field obtained using this approach, possesses simple time and frequency structures. We show that the fields having non-deterministic frequency components lead to greater dissociation probability compared to the ones having deterministic frequency components.
Using Chemicals to Optimize Conformance Control in Fractured Reservoirs
Energy Technology Data Exchange (ETDEWEB)
Seright, Randall; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Wang, Ying; Kumar, Anand; Wavrik, Kathryn
2001-09-07
The objectives of this project are: (1) to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas, (2) to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems, and (3) to develop procedures to optimize blocking agent placement in naturally fractured reservoirs. Work was directed at both injection wells and production wells and at vertical, horizontal, and highly deviated wells.
Multi-Level Energy Management and Optimal Control of a Residential DC Microgrid
DEFF Research Database (Denmark)
Diaz, Enrique Rodriguez; Anvari-Moghaddam, Amjad; Quintero, Juan Carlos Vasquez
2017-01-01
of a residential DC microgrid (R-DCMG) with different distributed generations (DGs) and loads is proposed and implemented as an optimal hierarchical control strategy. A system-level optimizer is designed to calculate the optimal operating points of the controllable energy sources (CESs) when needed, while lower......-level controllers are utilized to enforce the CESs to follow optimal set-points.......Extensive exploitation of renewable energies together with the increased role of low-voltage DC (LVDC) micro-sources in the generation mix of the future electricity networks, have become the driving force behind the DC microgrid applications. In this paper, an optimal dispatch model...
Evolution of Fascial Closure Optimization in Damage Control Laparotomy.
Lauerman, Margaret H; Dubose, Joseph J; Stein, Deborah M; Galvagno, Samuel M; Bradley, Matthew J; Diaz, Jose; Scalea, Thomas M
2016-12-01
Management of patients undergoing damage control laparotomy (DCL) involves many surgical, medical, and logistical factors. Ideal patient management optimizing fascial closure with regard to timing and closure techniques remains unclear. A retrospective review of patients undergoing DCL from 2000 to 2012 at an urban Level I trauma center was undertaken. Mortality of DCL decreased over the study period from 62.5 to 34.6 per cent, whereas enterocutaneous fistula rate decreased from 12.5 to 3.8 per cent. Delayed primary fascial closure rate improved from 22.2 to 88.2 per cent. Time to closure (P fascial closure. In subgroup analysis, achievement of delayed primary fascial closure was decreased with time to closure after one week (91.7% vs 52.0%, P = 0.002) and time to first attempted closure after two days (86.5% vs 70.0%, P = 0.042). In multivariate analysis, time to closure (odds ratio: 0.13, 95% confidence interval: 0.04-0.39; P fascial closure. Timing of attempted closure plays a significant role in attaining delayed primary fascial closure, highlighting the importance of early re-exploration.
Optimal control of suspended sediment distribution model of Talaga lake
Ratianingsih, R.; Resnawati, Azim, Mardlijah, Widodo, B.
2017-08-01
Talaga Lake is one of several lakes in Central Sulawesi that potentially to be managed in multi purposes scheme because of its characteristic. The scheme is addressed not only due to the lake maintenance because of its sediment but also due to the Algae farming for its biodiesel fuel. This paper governs a suspended sediment distribution model of Talaga lake. The model is derived from the two dimensional hydrodynamic shallow water equations of the mass and momentum conservation law of sediment transport. An order reduction of the model gives six equations of hyperbolic systems of the depth, two dimension directional velocities and sediment concentration while the bed elevation as the second order of turbulent diffusion and dispersion are neglected. The system is discreted and linearized such that could be solved numerically by box-Keller method for some initial and boundary condition. The solutions shows that the downstream velocity is play a role in transversal direction of stream function flow. The downstream accumulated sediment indicate that the suspended sediment and its changing should be controlled by optimizing the downstream velocity and transversal suspended sediment changing due to the ideal algae growth need.
Function-valued adaptive dynamics and optimal control theory.
Parvinen, Kalle; Heino, Mikko; Dieckmann, Ulf
2013-09-01
In this article we further develop the theory of adaptive dynamics of function-valued traits. Previous work has concentrated on models for which invasion fitness can be written as an integral in which the integrand for each argument value is a function of the strategy value at that argument value only. For this type of models of direct effect, singular strategies can be found using the calculus of variations, with singular strategies needing to satisfy Euler's equation with environmental feedback. In a broader, more mechanistically oriented class of models, the function-valued strategy affects a process described by differential equations, and fitness can be expressed as an integral in which the integrand for each argument value depends both on the strategy and on process variables at that argument value. In general, the calculus of variations cannot help analyzing this much broader class of models. Here we explain how to find singular strategies in this class of process-mediated models using optimal control theory. In particular, we show that singular strategies need to satisfy Pontryagin's maximum principle with environmental feedback. We demonstrate the utility of this approach by studying the evolution of strategies determining seasonal flowering schedules.