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Results for “optimal control”

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At least 127 records · Page 7Linked to original sources

PubMed1999

Optimal control of walking with functional electrical stimulation: a computer simulation study.

Bipedal locomotion was simulated to generate a pattern of activating muscles for walking using electrical stimulation in persons with spinal cord injury (SCI) or stroke. The simulation presented in this study starts from a model of the body determined with user-specific parameters, individualized with respect to the lengths, masses, inertia, muscle and joint properties. The trajectory used for simulation was recorded from an able-bodied subject while walking with ankle-foot orthoses. A discrete mathematical model and dynamic programming were used to determine the optimal control. A cost function was selected as the sum of the squares of the tracking errors from the desired trajectories, and the weighted sum of the squares of agonist and antagonist activations of the muscle groups acting around the hip and knee joints. The aim of the simulation was to study plausible trajectories keeping in mind the limitations imposed by the spinal cord injury or stroke (e.g., spasticity, decreased range of movements in some joints, limited strength of paralyzed, externally activated muscles). If the muscles were capable of generating the movements required and the trajectory was achieved, then the simulation provided two kinds of information: 1) timing of the onset and offset of muscle activations with respect to the various gait events and 2) patterns of activation with respect to the maximum activation. These results are important for synthesizing a rule-based controller.

Algorithms↗

PubMed1996

Optimal control problems arising in cell-cycle-specific cancer chemotherapy.

We explore mathematical properties of models of cancer chemotherapy including cell-cycle dependence. Using the mathematical methods of control theory, we demonstrate two assertions of interest for the biomedical community: 1 Periodic chemotherapy protocols are close to the optimum for a wide class of models and have additional favourable properties. 2 Two possible approaches, (a) to minimize the final count of malignant cells and the cumulative effect of the drug on normal cells, or (b) to maximize the final count of normal cells and the cumulative effect of the drug on malignant cells, lead to similar principles of optimization. From the mathematical viewpoint, the paper provides a catalogue of simplest mathematical models of cell-cycle dependent chemotherapy. They can be classified based on the number of compartments and types of drug action modelled. In all these models the optimal controls are complicated by the singular and periodic trajectories and multiple solutions. However, efficient numerical methods have been developed. In simpler cases, it is also possible to provide an exhaustive classification of solutions. We also discuss developments in estimation of cell cycle parameters and cell-cycle dependent drug action.

Cell Compartmentation↗

PubMedDate not supplied

Optimal control of intermittent normal conduction in a tachycardia-dependent right bundle branch block.

Tachycardia-dependent right bundle branch block (RBBB) with atrial fibrillation in a patient under digitalis therapy is presented, in which supernormal phase of intraventricular conduction was well-documented. The development of long intervals terminated by a normally conducted beat was attributed to the occurrence of concealed atrio-ventricular (A-V) conduction of the atrial fibrillation impulse during the supernormal phase. The ventricular interval caused by a normally conducted beat (xs) in the interval of 1.01-1.63 s was transformable into a vector differential equation dy/dx = In (x + a) + 1, where parameter a = 0, 0.04, 0.08, 0.16, and 0.24. This is piecewise continuous and integrable. The function in (x + 0.04) + 1 was considered to give the solution of the problem of optimal control, which is equivalent to the problem of finding Green's function of the region, i.e. to solving the Dirichlet problem. The solution curves, given by y = (x + a) in (x + a) + 1, can be interpreted as distributions. There were structurally stable vector field points on a differentiable manifold, i.e, attractors. In general, the modelling may be applicable to tachycardia-dependent RBBB.

Aged↗

PubMed2005

Obtaining optimal control in mild asthma: theory and practice.

BACKGROUND: Studies have shown that asthma severity is easily under-estimated and as a result, patients may be under-treated with reduced asthma control. OBJECTIVE: This study, performed in the General Practice Research Database (GPRD), investigates asthma control in patients treated as intermittent asthmatics (short-acting beta agonist (SABA) alone), or persistent asthmatics (additional inhaled cortico-steroid (ICS), no other medication). METHODS: Patients (0-45 years) diagnosed with asthma between 1 January 1995 and 31 December 2001 taking > or =2 scripts for SABA (SABA only group) or > or =3 scripts for ICS (ICS group) in the first six months following diagnosis were selected. Factors associated with drug prescriptions were assessed. RESULTS: SABA script rates were 3.6 and 5.1 per year in the SABA and ICS group respectively, i.e. >1 dose/day. 10.5% of SABA group and 13.4% of ICS group used oral steroids. Within the SABA group, 37% were stepped up to ICS, the time to first ICS script being significantly associated with prior hospitalization (RR 2.26, CI 1.65-3.10) and atopy (RR 1.47, CI 1.33-1.63). A higher rate of oral steroid use was significantly associated with using ICS, being female, adult and smoking. Smokers and atopic individuals had increased risk of obtaining an earlier script for oral steroid (RR 1.32, CI 1.10-1.59 and RR 1.28, CI 1.10-1.49, respectively). CONCLUSIONS: Asthma control was sub-optimal in a substantial proportion of patients using relatively high doses of SABA, or SABA and ICS from the outset of asthma treatment in general practice. Being female, atopic, a smoker and prior hospitalization were all associated with lack of asthma control and could guide physicians in treatment prescribing.

Administration, Inhalation↗

PubMed1997

Optimal control of the chemotherapy of HIV.

Using an existing ordinary differential equation model which describes the interaction of the immune system with the human immunodeficiency virus (HIV), we introduce chemotherapy in an early treatment setting through a dynamic treatment and then solve for an optimal chemotherapy strategy. The control represents the percentage of effect the chemotherapy has on the viral production. Using an objective function based on a combination of maximizing benefits based on T cell counts and minimizing the systemic cost of chemotherapy (based on high drug dose/strength), we solve for the optimal control in the optimality system composed of four ordinary differential equations and four adjoint ordinary differential equations.

Anti-HIV Agents↗

PubMedDate not supplied

Optimal control mode of a biochemical feedback system.

An optimal feedback system for constant-value control of biochemical reaction system was investigated by computer simulations. A feedback system containing a cyclic enzyme system where two enzyme types share a substrate in a cyclic manner, was found to be the most reliable one. This feedback system has a capability to keep the stationary value of the end product at a desired level against not only exogenous substrate supply but also endogenous parametric disturbances. The cyclic enzyme system installed as a control element of this feedback system played the role of comparator in this feedback system. The control mode of this feedback system was in good agreement with that of a system established by means of optimization technique based on the maximum principle. Also bang - bang control could be performed in this biochemical feedback system as well as in electrical one.

Enzymes↗

PubMed1991

Voltage polarity relay--optimal control of electrochemical urea oxidation.

Voltage polarity relay (VPR) is shown to optimize the urea oxidation rate and urea current utilization under constant current conditions in direct electrochemical urea oxidation. Direct electrochemical urea oxidation is characterized by reversible deactivation of the working electrode due to oxidation products remaining on the surface and the requirement that the working electrode potential remain below about 1.1 V relative to Ag/AgCl in order to prevent undesirable secondary electrochemical oxidations. The VPR method monitors the potential of the working electrode relative to a suitable reference and changes system polarity when the upper potential set limit is reached. Thus, what was the working electrode becomes the counter electrode and vice versa. Since urea oxidation products are desorbed from the counter electrode when its potential drops below about -0.6 V relative to Ag/AgCl, alternating electrode functions between working and counter provides cyclic electrode regeneration and continuous urea oxidation. VPR is believed to optimize constant current control for any electrochemical system that exhibits behavior similar to direct electrochemical urea oxidation.

Electrochemistry↗

PubMed2006

Optimal control of type 1 diabetes mellitus in youth receiving intensive treatment.

OBJECTIVE: To investigate the impact of factors that might interfere with optimal glycemic control in youth with type 1 diabetes mellitus (T1DM) in the current era of intensive management, including the interplay of race/ethnicity and socioeconomic status (SES) on HbA1c levels. STUDY DESIGN: This study comprised a database review of all patients under age 18 years with T1DM for at least 6 months duration. Sex, age, race/ethnicity, duration of diabetes, mode of insulin administration (pump vs injection), body mass index, SES, and HbA1c level were recorded at each patient's most recent visit between January and September 2003. RESULTS: Mean HbA1c level for the 455 patients was 7.6% +/- 1.4%; only 31% of patients failed to meet the therapeutic goal of < 8.0%. Multiple linear regression analysis identified female sex (P = .02), older age (P = .001), longer duration of diabetes (P < .001), injection therapy (P < .001), and lower SES (P = .001) as significantly associated with higher HbA1c level. After adjustment for SES, race/ethnicity was not a determinant of HbA1c level. CONCLUSIONS: Low SES had a greater association with poor metabolic control than did race/ethnicity, which was not associated with differences in HbA1c level after controlling for SES. Most children were able to attain glycemic targets at least as good as the Diabetes Control and Complications Trial recommendations in a large clinical practice.

Child↗

PubMed1992

Optimal control of tumor size used to maximize survival time when cells are resistant to chemotherapy.

The high failure rates encountered in the chemotherapy of some cancers suggest that drug resistance is a common phenomenon. In the current study, the tumor burden during therapy is used to slow the growth of the drug-resistant cells, thereby maximizing the survival time of the host. Three types of tumor growth model are investigated--Gompertz, logistic, and exponential. For each model, feedback controls are constructed that specify the optimal tumor mass as a function of the size of the resistant subpopulation. For exponential and logistic tumor growth, the tumor burden during therapy is shown to have little impact upon survival time. When the tumor is in Gompertz growth, therapies maintaining a large tumor burden double and sometimes triple the survival time under aggressive therapies. Aggressive therapies aim for a rapid reduction in the sensitive cell subpopulation. These conclusions are not dependent upon the values of the model constants that determine the mass of resistant cells. Since treatments maintaining a high tumor burden are optimal for Gompertz tumor growth and close to optimal for exponential and logistic tumor growth, it may no longer be necessary to know the growth characteristics of a tumor to schedule anticancer drugs.

Animals↗

PubMed2005

DMLC leaf-pair optimal control for mobile, deforming target.

Existing algorithms of dynamic control of independent pairs of leaves allow optimal DMLC delivery of IMRT to rigid targets translating parallel to leaf trajectories. However, in numerous cases of radiotherapy treatments simplifying assumptions of rigid-like motions of targets and surrounding tissues are clearly not satisfied. Therefore algorithms have to be developed that allow one to control MLC so that predetermined intensities are delivered to various points in targets that experience compression and expansion at the time of irradiation. Moreover, it is desirable for such algorithms to ensure that delivery of modulated intensity map will be done with minimal expense of monitor units. Derivation of the algorithm that optimizes the DMLC IMRT to mobile, deforming target is presented in this paper. [To illustrate the general algorithm two representative examples of DMLC IMRT delivery to deforming targets are presented in full detail.] Finally, similarities and differences between solutions for immobile targets, for moving, rigid targets and for moving, deforming targets are discussed.

Algorithms↗

PubMed2000

Metabolic modeling of Saccharomyces cerevisiae using the optimal control of homeostasis: a cybernetic model definition.

A model is presented to describe the observed behavior of microorganisms that aim at metabolic homeostasis while growing and adapting to their environment in an optimal way. The cellular metabolism is seen as a network with a multiple controller system with both feedback and feedforward control, i.e., a model based on a dynamic optimal metabolic control. The dynamic network consists of aggregated pathways, each having a control setpoint for the metabolic states at a given growth rate. This set of strategies of the cell forms a true cybernetic model with a minimal number of assumptions. The cellular strategies and constraints were derived from metabolic flux analysis using an identified, biochemically relevant, stoichiometry matrix derived from experimental data on the cellular composition of continuous cultures of Saccharomyces cerevisiae. Based on these data a cybernetic model was developed to study its dynamic behavior. The growth rate of the cell is determined by the structural compounds and fluxes of compounds related to central metabolism. In contrast to many other cybernetic models, the minimal model does not consist of any assumed internal kinetic parameters or interactions. This necessitates the use of a stepwise integration with an optimization of the fluxes at every time interval. Some examples of the behavior of this model are given with respect to steady states and pulse responses. This model is very suitable for describing semiquantitatively dynamics of global cellular metabolism and may form a useful framework for including structured and more detailed kinetic models.

Cybernetics↗

PubMed1992

An optimal controller for an electric ventricular-assist device: theory, implementation, and testing.

This paper addresses the development and testing of an optimal position feedback controller for the Penn State electric ventricular-assist device (EVAD). The control law is designed to minimize the expected value of the EVAD's power consumption for a targeted patient population. The closed-loop control law is implemented on an Intel 8096 microprocessor and in vitro test runs show that this controller improves the EVAD's efficiency by 15-21%, when compared with the performance of the currently used feedforward control scheme.

Computers↗

PubMed1996

Optimal control algorithm for pneumatic ventricular assist devices: its application to automatic control and monitoring of ventricular assist devices.

We developed a control and monitoring unit for pneumatic ventricular assist devices (VADs), which provides optimal fill and empty control and real-time evaluation of pump performance. The flow signal of the inflow cannula is integrated every beat to yield pump filling volume per pump diastole. The ejection signal is triggered when pump filling reaches a preset level. The instantaneous mean flow of each beat (stroke volume/cycle length) is compared with the previous beat, and the threshold level is readjusted to optimize flow. This feedback loop is repeated every beat, and pump filling is immediately adjusted to yield maximum pump flow. Simultaneously the mean flow of every 10 beats is compared with that of the previous 10 beats; then, the ejection time is readjusted to optimize flow. Initial clinical application of this unit supports its effectiveness and reliability.

Aged↗

PubMedDate not supplied

Genetic algorithm in the control optimization.

Genetic algorithm (GA) represents an exploratory search mathematical technique, which uses statistical methods of selection. They are named blind search technique as they usually operate without knowledge of the task domain. GA is inspired from the evolutionary features of biological systems. The natural individual selection of offspring that are better adapted will resist in time (3). The pioneer worker in this field was John Holland and the University of Michigan staff from 1975. The beginning study was in natural adaptive process explanation and continues with computed artificial systems developing that exploit the evolution natural principles. A GA technique was applied for a controller parameter optimization that regulates the mean blood pressure. The intelligent system adjusts the anesthetic agent in order to maintain the pressure constant with small variations from a desired set value. This is usually necessary for anesthesia control (mathematical model from 11, 12). Such a system was developed and tested using computer simulations. This paper describes some aspects about the GA mathematical method and finally the results of the controller implementation are presented.

Algorithms↗

PubMed2006

Cooperating or fighting with decoherence in the optimal control of quantum dynamics.

This paper explores the use of laboratory closed-loop learning control to either fight or cooperate with decoherence in the optimal manipulation of quantum dynamics. Simulations of the processes are performed in a Lindblad formulation on multilevel quantum systems strongly interacting with the environment without spontaneous emission. When seeking a high control yield it is possible to find fields that successfully fight with decoherence while attaining a good quality yield. When seeking modest control yields, fields can be found which are optimally shaped to cooperate with decoherence and thereby drive the dynamics more efficiently. In the latter regime when the control field and the decoherence strength are both weak, a theoretical foundation is established to describe how they cooperate with each other. In general, the results indicate that the population transfer objectives can be effectively met by appropriately either fighting or cooperating with decoherence.

Journal Article↗

PubMed2004

Isotope selective ionization by optimal control using shaped femtosecond laser pulses.

We report on selective optimization of different isotopes in an ionization process by means of spectrally broad shaped fs-laser pulses. This is demonstrated for (39,39)K2 and (39,41)K2 by applying evolution strategies in a feedback loop, whereby a surprisingly high enhancement of one isotope versus the other and vice versa is achieved (total factor approximately 140). Information about the dynamics on the involved vibrational states is extracted from the optimal pulse shapes, which provides a new spectroscopical approach of yielding distinct frequency pattern on fs-time scales. The method should, in principle, be feasible for all molecules.

Journal Article↗

PubMed2026

Optimizing Control Definitions in Opioid Use Disorder Genetic Research Using Electronic Health Records.

Amidst the opioid crisis, understanding the genetic basis of opioid use disorder (OUD) is crucial for identifying biological mechanisms and intervention points. However, genome-wide association studies (GWASs) have been hampered by inadequate sample sizes and often the use of control populations not assessed for prior opioid exposure. Because opioid exposure is a prerequisite for the development of OUD, consideration of exposure history in controls is important. Electronic health record data (EHR) paired with genomic information allow a broader sampling of patients with OUD and exposed controls. We leveraged data across two healthcare systems to evaluate the impact of using controls not screened for opioid exposure ('generic') versus minimally opioid-exposed control ('exposed'). First, at the phenotypic level, we conducted phenome-wide association studies (PheWAS) to compare the medical comorbidity profiles of OUD cases when using generic versus exposed controls. While PheWAS results for OUD-related comorbidities were more pronounced when using the generic group, 83% of the disease associations were overlapping and of similar effect sizes. Second, at the genetic level, we conducted GWAS (cases vs. generic; cases vs. exposed) and assessed differences in genetic correlations and degrees of phenotypic misclassification. Genetic results were concordant across control groups based on heritability (generic: 0.16 ± 0.07 vs. 0.10 ± 0.07), associations with the coding OPRM1 variant rs1799971 (pgeneric = 8.83E-03 vs. pexposed = 1.83E-02) and genetic correlations with prior OUD GWAS (rg-generic = 0.83 ± 0.26 vs. rg-exposed = 0.78 ± 0.27). Although GWASs were limited by sample size (Ngeneric = 6269, Nexposed = 6365), compared to an independent OUD GWAS (N = 425 944), the dilution value for the two GWAS was not different from 1, suggesting no major impact of phenotypic misclassification. This study represents the first effort to enhance OUD genetic research through optimization of control definitions using EHR data. Generic controls ascertained within the US health systems, where exposure to prescription opioids is high, offer a practical alternative for genetic studies of OUD.

Humans↗

PubMed1976

Optimal control of artificial aeration in river networks.

Under suitable conditions, artificial in situ aeration is an appropriate and economical method of alleviating water pollution. Regional planning for the control of water pollution can properly consider the use of artificial aeration on a river network in conjunction with other pollution abatement techniques. Application of optimization methods can yield significant savings in the aeration energy consumption required to produce a given level of impact on a polluted river network. The confluence of two rivers, each receiving effluent discharges and subject to artificial aeration control, is first investigated. It is shown that the optimal feedback aeration strategy in one branch of the river system not only depends on measurements of the water quality in that branch, but also on the water quality measurements in the second branch. With these results as the foundation, the optimal aeration control strategy is then determined for a generalized river network modeled as a graphical tree. Various properties of the optimal aeration policy are illustrated by computational examples.

Air↗