Constrained optimization model for the design of an adaptive (X)over-bar chart

An economic-statistical model is developed for variable parameters (VP) (X) over bar charts in which all design parameters vary adaptively, that is, each of the design parameters (sample size, sampling interval and control-limit width) vary as a function of the most recent process information. The cost function due to controlling the process quality through a VP (X) over bar chart is derived. During the optimization of the cost function, constraints are imposed on the expected times to signal when the process is in and out of control. In this way, required statistical properties can be assured. Through a numerical example, the proposed economic-statistical design approach for VP (X) over bar charts is compared to the economic design for VP (X) over bar charts and to the economic-statistical and economic designs for fixed parameters (FP) (X) over bar charts in terms of the operating cost and the expected times to signal. From this example, it is possible to assess the benefits provided by the proposed model. Varying some input parameters, their effect on the optimal cost and on the optimal values of the design parameters was analysed.

Applying a genetic neuro-model reference adaptive controller in drilling optimization

Motivated by rising drilling operation costs, the oil industry has shown a trend toward real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated with parameters modeling. One of the drillbit performance evaluators, the Rate Of Penetration (ROP), has been used as a drilling control parameter. However, relationships between operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on an auto-regressive with extra input signals, or ARX model and on a Genetic Algorithm (GA) to control the ROP. © [2006] IEEE.

Optimization of multipulse converters with delta and Y-differential connections

This work presents a study regarding the optimization of multipulse converters. A general expression for the connection (Δ or Y) for both 12 and 18-pulses is obtained and describes the output voltages on the secondary windings, depending on the voltage reference from the primary. These generalized expressions allows choosing different ratios between input and output voltages and as result an optimum operation point for the converter can be calculated. Considering Δ-connected converters the optimum point occurs when the magnetic core of the autotransformer processes 18% and 17% of the output power for 12 and 18-pulses, respectively. For Y-connected converters the optimum point occurs when the kVA rating is 13% and 18% for 12 and 18-pulses, respectively. Based on these results magnetic elements can be calculated and designed leading to a great weight and volume reduction and also to lower costs and losses. Finally an analysis is made to improve the kVA rating of the transformers for 12 and 18 pulses converters. © 2009 IEEE.