Double-objective economic statistical design of the VP T-2 control chart: Wald's identity approach

Research has shown that applying the T-2 control chart by using a variable parameters (VP) scheme yields rapid detection of out-of-control states. In this paper, the problem of economic statistical design of the VP T-2 control chart is considered as a double-objective minimization problem with the statistical objective being the adjusted average time to signal and the economic objective being expected cost per hour. We then find the Pareto-optimal designs in which the two objectives are met simultaneously by using a multi-objective genetic algorithm. Through an illustrative example, we show that relatively large benefits can be achieved by applying the VP scheme when compared with usual schemes, and in addition, the multi-objective approach provides the user with designs that are flexible and adaptive.

Despacho ótimo de potências ativa e reativa de sistema elétricos multi-áreas considerando restrições físicas, econômicas e ambientais =: Envronmentally constrained active-reactive optimal power flow-a compromising strategy for economic-emission dispatch and a multi-area paradigm

Pós-graduação em Engenharia Elétrica - FEIS

On the properness of an impulsive control extension of dynamic optimization problems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

On nonlinear dynamics and control of a robotic arm with chaos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

NASH game and mixed H2/H∞ control

In this work a Nonzero-Sum NASH game related to the H2 and H∞ control problems is formulated in the context of convex optimization theory. The variables of the game are limiting bounds for the H2 and H∞ norms, and the final controller is obtained as an equilibrium solution, which minimizes the `sensitivity of each norm' with respect to the other. The state feedback problem is considered and illustrated by numerical examples.

Nonlinear state estimation and control for chaos suppression in MEMS resonator

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Manipulation of follicle development to ensure optimal oocyte quality and conception rates in cattle

Over the last several decades, a number of therapies have been developed that manipulate ovarian follicle growth to improve oocyte quality and conception rates in cattle. Various strategies have been proposed to improve the responses to reproductive biotechnologies following timed artificial insemination (TAI), superovulation (SOV) or ovum pickup (OPU) programmes. During TAI protocols, final follicular growth and size of the ovulatory follicle are key factors that may significantly influence oocyte quality, ovulation, the uterine environment and consequently pregnancy outcomes. Progesterone concentrations during SOV protocols influence follicular growth, oocyte quality and embryo quality; therefore, several adjustments to SOV protocols have been proposed depending on the animal category and breed. In addition, the success of in vitro embryo production is directly related to the number and quality of cumulus oocyte complexes harvested by OPU. Control of follicle development has a significant impact on the OPU outcome. This article discusses a number of key points related to the manipulation of ovarian follicular growth to maximize oocyte quality and improve conception rates following TAI and embryo transfer of in vivo-and in vitro-derived embryos in cattle.

Imperceptible electrical noise attenuates isometric plantar flexion force fluctuations with correlated reductions in postural sway

Optimal levels of noise stimulation have been shown to enhance the detection and transmission of neural signals thereby improving the performance of sensory and motor systems. The first series of experiments in the present study aimed to investigate whether subsensory electrical noise stimulation applied over the triceps surae (TS) in seated subjects decreases torque variability during a force-matching task of isometric plantar flexion and whether the same electrical noise stimulation decreases postural sway during quiet stance. Correlation tests were applied to investigate whether the noise-induced postural sway decrease is linearly predicted by the noise-induced torque variability decrease. A second series of experiments was conducted to investigate whether there are differences in torque variability between conditions in which the subsensory electrical noise is applied only to the TS, only to the tibialis anterior (TA) and to both TS and TA, during the force-matching task with seated subjects. Noise stimulation applied over the TS muscles caused a significant reduction in force variability during the maintained isometric force paradigm and also decreased postural oscillations during quiet stance. Moreover, there was a significant correlation between the reduction in force fluctuation and the decrease in postural sway with the electrical noise stimulation. This last result indicates that changes in plantar flexion force variability in response to a given subsensory random stimulation of the TS may provide an estimate of the variations in postural sway caused by the same subsensory stimulation of the TS. We suggest that the decreases in force variability and postural sway found here are due to stochastic resonance that causes an improved transmission of proprioceptive information. In the second series of experiments, the reduction in force variability found when noise was applied to the TA muscle alone did not reach statistical significance, suggesting that TS proprioception gives a better feedback to reduce force fluctuation in isometric plantar flexion conditions.

A New Control Architecture for Robust Controllers in Rear Electric Traction Passenger HEVs

It is well known that control systems are the core of electronic differential systems (EDSs) in electric vehicles (EVs)/hybrid HEVs (HEVs). However, conventional closed-loop control architectures do not completely match the needed ability to reject noises/disturbances, especially regarding the input acceleration signal incoming from the driver's commands, which makes the EDS (in this case) ineffective. Due to this, in this paper, a novel EDS control architecture is proposed to offer a new approach for the traction system that can be used with a great variety of controllers (e. g., classic, artificial intelligence (AI)-based, and modern/robust theory). In addition to this, a modified proportional-integral derivative (PID) controller, an AI-based neuro-fuzzy controller, and a robust optimal H-infinity controller were designed and evaluated to observe and evaluate the versatility of the novel architecture. Kinematic and dynamic models of the vehicle are briefly introduced. Then, simulated and experimental results were presented and discussed. A Hybrid Electric Vehicle in Low Scale (HELVIS)-Sim simulation environment was employed to the preliminary analysis of the proposed EDS architecture. Later, the EDS itself was embedded in a dSpace 1103 high-performance interface board so that real-time control of the rear wheels of the HELVIS platform was successfully achieved.

The Future REvascularization Evaluation in patients with Diabetes mellitus: Optimal management of Multivessel disease (FREEDOM) trial: Clinical and angiographic profile at study entry

Background The optimal revascularization strategy for diabetic patients with multivessel coronary artery disease (MVD) remains uncertain for lack of an adequately powered, randomized trial. The FREEDOM trial was designed to compare contemporary coronary artery bypass grafting (CABG) to percutaneous coronary intervention (PCI) with drug-eluting stents in diabetic patients with MVD against a background of optimal medical therapy. Methods A total of 1,900 diabetic participants with MVD were randomized to PCI or CABG worldwide from April 2005 to March 2010. FREEDOM is a superiority trial with a mean follow-up of 4.37 years (minimum 2 years) and 80% power to detect a 27.0% relative reduction. We present the baseline characteristics of patients screened and randomized, and provide a comparison with other MVD trials involving diabetic patients. Results The randomized cohort was 63.1 +/- 9.1 years old and 29% female, with a median diabetes duration of 10.2 +/- 8.9 years. Most (83%) had 3-vessel disease and on average took 5.5 +/- 1.7 vascular medications, with 32% on insulin therapy. Nearly all had hypertension and/or dyslipidemia, and 26% had a prior myocardial infarction. Mean hemoglobin A1c was 7.8 +/- 1.7 mg/dL, 29% had low-density lipoprotein <70 mg/dL, and mean systolic blood pressure was 134 +/- 20 mm Hg. The mean SYNTAX score was 26.2 with a symmetric distribution. FREEDOM trial participants have baseline characteristics similar to those of contemporary multivessel and diabetes trial cohorts. Conclusions The FREEDOM trial has successfully recruited a high-risk diabetic MVD cohort. Follow-up efforts include aggressive monitoring to optimize background risk factor control. FREEDOM will contribute significantly to the PCI versus CABG debate in diabetic patients with MVD. (Am Heart J 2012;164:591-9.)

SINGULARLY PERTURBED DISCOUNTED MARKOV CONTROL PROCESSES IN A GENERAL STATE SPACE

This paper studies the asymptotic optimality of discrete-time Markov decision processes (MDPs) with general state space and action space and having weak and strong interactions. By using a similar approach as developed by Liu, Zhang, and Yin [Appl. Math. Optim., 44 (2001), pp. 105-129], the idea in this paper is to consider an MDP with general state and action spaces and to reduce the dimension of the state space by considering an averaged model. This formulation is often described by introducing a small parameter epsilon > 0 in the definition of the transition kernel, leading to a singularly perturbed Markov model with two time scales. Our objective is twofold. First it is shown that the value function of the control problem for the perturbed system converges to the value function of a limit averaged control problem as epsilon goes to zero. In the second part of the paper, it is proved that a feedback control policy for the original control problem defined by using an optimal feedback policy for the limit problem is asymptotically optimal. Our work extends existing results of the literature in the following two directions: the underlying MDP is defined on general state and action spaces and we do not impose strong conditions on the recurrence structure of the MDP such as Doeblin's condition.

OPTIMIZATION AND CONTROL OF A CONTINUOUS POLYMERIZATION REACTOR

This work studies the optimization and control of a styrene polymerization reactor. The proposed strategy deals with the case where, because of market conditions and equipment deterioration, the optimal operating point of the continuous reactor is modified significantly along the operation time and the control system has to search for this optimum point, besides keeping the reactor system stable at any possible point. The approach considered here consists of three layers: the Real Time Optimization (RTO), the Model Predictive Control (MPC) and a Target Calculation (TC) that coordinates the communication between the two other layers and guarantees the stability of the whole structure. The proposed algorithm is simulated with the phenomenological model of a styrene polymerization reactor, which has been widely used as a benchmark for process control. The complete optimization structure for the styrene process including disturbances rejection is developed. The simulation results show the robustness of the proposed strategy and the capability to deal with disturbances while the economic objective is optimized.

PERFORMANCE EVALUATION OF RESOURCE-AWARE BUSINESS PROCESSES USING STOCHASTIC AUTOMATA NETWORKS

In this work, we study the performance evaluation of resource-aware business process models. We define a new framework that allows the generation of analytical models for performance evaluation from business process models annotated with resource management information. This framework is composed of a new notation that allows the specification of resource management constraints and a method to convert a business process specification and its resource constraints into Stochastic Automata Networks (SANs). We show that the analysis of the generated SAN model provides several performance indices, such as average throughput of the system, average waiting time, average queues size, and utilization rate of resources. Using the BP2SAN tool - our implementation of the proposed framework - and a SAN solver (such as the PEPS tool) we show through a simple use-case how a business specialist with no skills in stochastic modeling can easily obtain performance indices that, in turn, can help to identify bottlenecks on the model, to perform workload characterization, to define the provisioning of resources, and to study other performance related aspects of the business process.

Cost effectiveness of OptiMal® rapid diagnostic test for malaria in remote areas of the Amazon Region, Brazil

Abstract Background In areas with limited structure in place for microscopy diagnosis, rapid diagnostic tests (RDT) have been demonstrated to be effective. Method The cost-effectiveness of the Optimal® and thick smear microscopy was estimated and compared. Data were collected on remote areas of 12 municipalities in the Brazilian Amazon. Data sources included the National Malaria Control Programme of the Ministry of Health, the National Healthcare System reimbursement table, hospitalization records, primary data collected from the municipalities, and scientific literature. The perspective was that of the Brazilian public health system, the analytical horizon was from the start of fever until the diagnostic results provided to patient and the temporal reference was that of year 2006. The results were expressed in costs per adequately diagnosed cases in 2006 U.S. dollars. Sensitivity analysis was performed considering key model parameters. Results In the case base scenario, considering 92% and 95% sensitivity for thick smear microscopy to Plasmodium falciparum and Plasmodium vivax, respectively, and 100% specificity for both species, thick smear microscopy is more costly and more effective, with an incremental cost estimated at US$549.9 per adequately diagnosed case. In sensitivity analysis, when sensitivity and specificity of microscopy for P. vivax were 0.90 and 0.98, respectively, and when its sensitivity for P. falciparum was 0.83, the RDT was more cost-effective than microscopy. Conclusion Microscopy is more cost-effective than OptiMal® in these remote areas if high accuracy of microscopy is maintained in the field. Decision regarding use of rapid tests for diagnosis of malaria in these areas depends on current microscopy accuracy in the field.

A Robust Structural PGN Model for Control of Cell-Cycle Progression Stabilized by Negative Feedbacks

The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a probabilistic genetic network (PGN) to construct a hypothetical model with a dynamical behavior displaying the degree of robustness typical of the biological cell cycle. The structure of our PGN model was inspired in well-established biological facts such as the existence of integrator subsystems, negative and positive feedback loops, and redundant signaling pathways. Our model represents genes interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model does not perform as well as our PGN model, even upon moderate noise conditions. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle.