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Results for “optimal control”

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At least 91 records · Page 5Linked to original sources

PubMed2006

Optimal control design of constant amplitude phase-modulated pulses: application to calibration-free broadband excitation.

An optimal control algorithm for generating purely phase-modulated pulses is derived. The methodology is applied to obtain broadband excitation with unprecedented tolerance to RF inhomogeneity. Design criteria were transformation of Iz-->Ix over resonance offsets of +/-25 kHz for constant RF amplitude anywhere in the range 10-20 kHz, with a pulse length of 1 ms. Simulations transform Iz to greater than 0.99 Ix over the targetted ranges of resonance offset and RF variability. Phase deviations in the final magnetization are less than 2-3 degrees over almost the entire range, with sporadic deviations of 6-9 degrees at a few offsets for the lowest RF (10 kHz) in the optimized range. Experimental performance of the new pulse is in excellent agreement with the simulations, and the robustness of the excitation pulse and a derived refocusing pulse are demonstrated by insertion into conventional HSQC and HMBC-type experiments.

Journal Article↗

PubMed1983

[Biologic systems and optimal control].

A lot of biological systems can be modeled by mathematical relations. Furthermore, existence of regulations and optimizations lead to optimal control systems. In this paper we want to describe with simple examples some difficulties and advantages of such systemic approaches.

Hormones↗

PubMed2000

Dynamic optimal control of homeostasis: an integrative system approach for modeling of the central nitrogen metabolism in Saccharomyces cerevisiae.

The theory of dynamic optimal metabolic control (DOMC), as developed by Giuseppin and Van Riel (Metab. Eng., 2000), is applied to model the central nitrogen metabolism (CNM) in Saccharomyces cerevisiae. The CNM represents a typical system encountered in advanced metabolic engineering. The CNM is the source of the cellular amino acids and proteins, including flavors and potentially valuable biomolecules; therefore, it is also of industrial interest. In the DOMC approach the cell is regarded as an optimally controlled system. Given the metabolic genotype, the cell faces a control problem to maintain an optimal flux distribution in a changing environment. The regulation is based on strategies and balances feedback control of homeostasis and feedforward regulation for adaptation. The DOMC approach is an integrative, holistic approach, not based on mechanistic descriptions and (therefore) not biased by the variation present in biochemical and molecular biological data. It is an effective tool to structure the rapidly increasing amount of data on the function of genes and pathways. The DOMC model is used successfully to predict the responses of pulses of ammonia and glutamine to nitrogen-limited continuous cultures of a wild-type strain and a glutamine synthetase-negative mutant. The simulation results are validated with experimental data.

Homeostasis↗

PubMed1998

On the optimal control of behaviour: a stochastic perspective.

Evolution is a closed stochastic optimisation process driven by the interaction between behaviour and environment towards local maxima in fitness. It is inferred that nervous systems are selected to provide optimal control of behaviour (the 'assumption of optimality'), such that for some behaviours, the expectation of future hazards to survival are minimised. This is illustrated by goal-directed saccades in which minimising total flight-time of primary and secondary movements provides a better fit to observations than simply minimising the error of the primary movement. This optimisation is extended to intra-movement trajectories, where low-bandwidth (smooth) velocity profiles provide a more satisfactory description of observations than simple bang-bang control. Since minimum-time behaviours cannot be controlled by error feedback, it is concluded that the cerebellum must be executing a real-time unreferenced optimisation process. This requires explorative as well as exploitative behaviour. Stochastic gradient descent is discussed as a possible means by which the cerebellum may optimise behaviour.

Behavior↗

PubMed2006

Effective Hamiltonians by optimal control: solid-state NMR double-quantum planar and isotropic dipolar recoupling.

We report the use of optimal control algorithms for tailoring the effective Hamiltonians in nuclear magnetic resonance (NMR) spectroscopy through sophisticated radio-frequency (rf) pulse irradiation. Specifically, we address dipolar recoupling in solid-state NMR of powder samples for which case pulse sequences offering evolution under planar double-quantum and isotropic mixing dipolar coupling Hamiltonians are designed. The pulse sequences are constructed numerically to cope with a range of experimental conditions such as inhomogeneous rf fields, spread of chemical shifts, the intrinsic orientation dependencies of powder samples, and sample spinning. While the vast majority of previous dipolar recoupling sequences are operating through planar double-or zero-quantum effective Hamiltonians, we present here not only improved variants of such experiments but also for the first time homonuclear isotropic mixing sequences which transfers all I(x), I(y), and I(z) polarizations from one spin to the same operators on another spin simultaneously and with equal efficiency. This property may be exploited to increase the signal-to-noise ratio of two-dimensional experiments by a factor of square root 2 compared to conventional solid-state methods otherwise showing the same efficiency. The sequences are tested numerically and experimentally for a powder of (13)C(alpha),(13)C(beta)-L-alanine and demonstrate substantial sensitivity gains over previous dipolar recoupling experiments.

Algorithms↗

PubMed2002

Quantum computing by an optimal control algorithm for unitary transformations.

Quantum computation is based on implementing selected unitary transformations representing algorithms. A generalized optimal control theory is used to find the driving field that generates a prespecified unitary transformation. The approach is independent of the physical implementation of the quantum computer and it is illustrated for one and two qubit gates in model molecular systems, where only part of the Hilbert space is used for computation.

Journal Article↗

PubMed2005

Optimal control of coupled spin dynamics: design of NMR pulse sequences by gradient ascent algorithms.

In this paper, we introduce optimal control algorithm for the design of pulse sequences in NMR spectroscopy. This methodology is used for designing pulse sequences that maximize the coherence transfer between coupled spins in a given specified time, minimize the relaxation effects in a given coherence transfer step or minimize the time required to produce a given unitary propagator, as desired. The application of these pulse engineering methods to design pulse sequences that are robust to experimentally important parameter variations, such as chemical shift dispersion or radiofrequency (rf) variations due to imperfections such as rf inhomogeneity is also explained.

Algorithms↗

PubMed2006

Design and control optimization of microclimate liquid cooling systems underneath protective clothing.

The use of protective clothing, whether in space suits, hazardous waste disposal, or sporting equipment, generally increases the risk of heat stress and hyperthermia by impairing the capacity for evaporative heat exchange from the body to the environment. To date the most efficient method of microclimate cooling underneath protective clothing has been via conductive heat exchange from circulating cooling fluid next to the skin. In order to make the use of liquid microclimate cooling systems ((LQ)MCSs) as portable and practical as possible, the physiological and biomedical engineering design goals should be towards maximizing the efficiency of cooling to maintain thermal comfort/neutrality with the least cooling possible to minimize coolant and power requirements. Meeting these conditions is an extremely complex task that requires designing for a plethora of different factors. The optimal fitting of the (LQ)MCSs, along with placement and design of tubing and control of cooling, appear to be key avenues towards maximizing efficiency of heat exchange. We review the history and major design constraints of (LQ)MCSs, the basic principles of human thermoregulation underneath protective clothing, and explore potential areas of research into tubing/fabric technology, coolant distribution, and control optimization that may enhance the efficiency of (LQ)MCSs.

Cold Temperature↗

PubMed2000

Optimal control of molecular motion: design, implementation, and inversion.

This paper reviews recent theoretical and experimental developments aimed at controlling molecular motion using tailored laser fields. Emphasis is given to seeking optimal designs for the laser controls and optimal implementation of the controls in the laboratory. Optimization on both counts provides a rigorous, flexible, and physically attractive means for obtaining the best possible control over molecular motion under any specified conditions. The theoretical design and laboratory implementation of control are best effected by a closed-loop process that draws on observations of the evolving molecular sample to steer it toward the desired target. Going beyond control, similar closed-loop laboratory learning concepts may lead to automated molecular monitors for inversion to systematically identify details of molecular Hamiltonians.

Chemistry, Physical↗

PubMed2006

Event-driven time-optimal control for a class of discontinuous bioreactors.

Discontinuous bioreactors may be further optimized for processing inhibitory substrates using a convenient fed-batch mode. To do so the filling rate must be controlled in such a way as to push the reaction rate to its maximum value, by increasing the substrate concentration just up to the point where inhibition begins. However, an exact optimal controller requires measuring several variables (e.g., substrate concentrations in the feed and in the tank) and also good model knowledge (e.g., yield and kinetic parameters), requirements rarely satisfied in real applications. An environmentally important case, that exemplifies all these handicaps, is toxicant wastewater treatment. There the lack of online practical pollutant sensors may allow unforeseen high shock loads to be fed to the bioreactor, causing biomass inhibition that slows down the treatment process and, in extreme cases, even renders the biological process useless. In this work an event-driven time-optimal control (ED-TOC) is proposed to circumvent these limitations. We show how to detect a "there is inhibition" event by using some computable function of the available measurements. This event drives the ED-TOC to stop the filling. Later, by detecting the symmetric event, "there is no inhibition," the ED-TOC may restart the filling. A fill-react cycling then maintains the process safely hovering near its maximum reaction rate, allowing a robust and practically time-optimal operation of the bioreactor. An experimental study case of a wastewater treatment process application is presented. There the dissolved oxygen concentration was used to detect the events needed to drive the controller.

Biomass↗

PubMed1997

Feedback control of unsupported standing in paraplegia--part I: optimal control approach.

This is the first of a pair of papers which describe an investigation into the feasibility of providing artificial balance to paraplegics using electrical stimulation of the paralyzed muscles. By bracing the body above the shanks, only stimulation of the plantarflexors is necessary. This arrangement prevents any influence from the intact neuromuscular system above the spinal cord lesion. In this paper, we extend the design of the controllers to a nested-loop LQG (linear quadratic Gaussian) stimulation controller which has ankle moment feedback (inner loops) and inverted pendulum angle feedback (outer loop). Each control loop is tuned by two parameters, the control weighting and an observer rise-time, which together determine the behavior. The nested structure was chosen because it is robust, despite changes in the muscle properties (fatigue) and interference from spasticity.

Biofeedback, Psychology↗

PubMed2006

Sustainable ecosystem management using optimal control theory: part 1 (deterministic systems).

The concept of sustainability, an abstract one by its nature, has been given a mathematical representation through the use of Fisher information as a measure. It is used to propose the sustainability hypotheses for dynamical systems, which has paved the way to achieve sustainable development through externally enforced control schemes. For natural systems, this refers to the task of ecosystem management, which is complicated due the lack of clear objectives. This work attempts to incorporate the idea of sustainability in ecosystem management. The natural regulation of ecosystems suggests two possible control options, top-down control and bottom-up control. A comparison of these two control philosophies is made on generic food chain models using the objectives derived from the sustainability hypotheses. Optimal control theory is used to derive the control profiles to handle the complex nature of the models and the objectives. The results indicate a strong relationship between the hypotheses and the dynamic behavior of the models, supporting the use of Fisher information as a measure. As regards to ecosystem management, it has been observed that top-down control is more aggressive but can result in instability, while bottom-up control is guaranteed to give a stable and improved dynamic response. The results also indicate that bottom-up control is a better option to affect shifts in the dynamic regimes of a system, which may be required to recover the system from a natural disaster like the hurricane Katrina.

Animals↗

PubMed2004

Optimizing control of simulated moving beds--linear isotherm.

A new optimization based adaptive control strategy for simulated moving beds (SMBs) is proposed. A linearized reduced order model, which accounts for the periodic nature of the SMB process, is used for online optimization and control. The manipulated variables are the four inlet flow rates, the outputs are the raffinate and extract concentrations. Concentration measurements at the raffinate and extract outlets are used as the feedback information. The state estimate from the periodic Kalman filter is used for the prediction of the outlet concentrations over a chosen horizon. Predicted outlet concentrations are the basis for the calculation of the optimal input adjustments, which maximize the productivity and minimize the desorbent consumption subject to constraints on product purities. The realization of this concept is discussed and the implementation on a virtual eight column SMB platform is assessed, in the case of binary linear systems. For a whole series of typical plant disturbances it is shown that the proposed approach is effective in minimizing off-spec products and in achieving optimal SMB operation, also in the case where there are significant model uncertainties.

Models, Theoretical↗

PubMed2004

Quantum optimally controlled transition landscapes.

A large number of experimental studies and simulations show that it is surprisingly easy to find excellent quality control over broad classes of quantum systems. We now prove that for controllable quantum systems with no constraints placed on the controls, the only allowed extrema of the transition probability landscape correspond to perfect control or no control. Under these conditions, no suboptimal local extrema exist as traps that would impede the search for an optimal control. The identified landscape structure is universal for all controllable quantum systems of the same dimension when seeking to maximize the same transition probability, regardless of the detailed nature of the system Hamiltonian. The presence of weak control field noise or environmental decoherence is shown to preserve the general structure of the control landscape, but at lower resolution.

Journal Article↗

PubMed1993

[Unequal genetic contributions of parents to offsprings and their optimal control].

Due to the joint effects of natural and artificial selection, the proportions of genetic materials originating from different parents may vary in the gene pool of offsprings, and this creates a problem of unequal genetic contributions of parents to offsprings. It is shown that unequal genetic contribution substantially affects the genetic gain via realized selection differential and effective population size, and brings error to the empirical prediction formulae of selection response: R = i.sigma P.h2. The aim of breeding should be to select the genetically superior individuals and then to make more genetic contributions of better parents to offspring gene pool. However, the latter aspect has been ignored in theoretical study as well as in certain breeding practice. To deal with the problem, a method which takes maximizing genetic advance as general objective and considers some breeding restrictions, is suggested to control the percentage of genetic contributions. A numerical example from egg-type chicken breeding is used to demonstrate the effects of optimal control of unequal genetic contributions. The result indicates that at the same level of effective population size, the realized selection response for different traits under the optimal pattern of unequal genetic contributions could be 34.27-216.57% higher than that under the actual unequal pattern.

Animals↗

PubMed2004

DMLC leaf-pair optimal control of IMRT delivery for a moving rigid target.

In dynamic multileaf collimation (DMLC), pairs of servo-controlled leaves sweep across the target to deliver the modulated radiation intensity map while the beam is on continuously. The mathematical model for dynamic, optimal control of a single leaf pair has been developed for the case of a rigid target, translating parallel to the leaf trajectories. This mathematical model ensures delivery of the modulated intensity map while minimizing beam-on time. Numerical solutions of the model are presented here for optimal IMRT delivery for stationary and oscillating targets, together with a discussion of the results. Comparisons between solutions for stationary and mobile targets, as well as comparisons between optimal and suboptimal algorithms, are provided. These comparisons allow us to estimate potential gains in the effectiveness of DMLC IMRT delivery when it is based on optimal algorithms.

Algorithms↗

PubMedDate not supplied

A primer on dynamic optimization and optimal control in pharmacoeconomics.

Pharmacoeconomic analyses employ a wide range of techniques and methods to help societies allocate scarce health-care resources wisely, fairly, and efficiently. Techniques such as dynamic optimization and optimal control, however, have yet to be exploited by this field. Although control theory has a long history in mathematical biology and disease management, its application to economic costs in these disciplines has not yet been explored. Pharmacoeconomics therefore may offer a particularly promising starting point because of the emphasis this field places on the economic perspective. Although challenges may exist to implementing these techniques in practice (at least in some settings), there will nevertheless be value to considering the dynamic perspective these techniques offer, which requires thinking more critically about the optimal allocation of scare health-care resources over time. Therefore, our article serves as a primer to introduce this dynamic perspective from an economic standpoint within the context of two examples of treating of hyperlipidemia.

Cost Control↗

PubMed2005

Optimizing control of simulated moving beds--experimental implementation.

The operation of simulated moving beds (SMBs) at their optimal operating conditions is difficult and not robust. Therefore, it is common practice to operate SMB units far from their economic optimum in order to tolerate uncertainties in the system and minimize the effect of disturbances. Recently, we have proposed an on-line optimization based SMB control scheme that allows to exploit the full economic potential of SMB technology. The goal of this work is two-fold. Firstly, to experimentally evaluate and demonstrate the capability of the controller to optimize and operate the SMB units, thus delivering the products with maximum productivity and minimum solvent consumption. Secondly, to show the suitability of the controller even using a minimum of system information, thus making the detailed isotherm measurements redundant and saving time in the separation design phase. This paper reports and discusses the first experimental implementation of the control concept on a high purity separation of nucleosides (uridine, guanosine) with an eight-column four-section SMB where the species to be separated are retained on the source 30RPC stationary phase according to a linear isotherm.

Chromatography, Liquid↗