Process economic improvement subject to safety, operational and environmental constraints is an ultimate goal of using on-line process optimization and control techniques. The dynamic nature of present-day market conditions motivates the consideration of process dynamics within the economic optimization calculation. Two key paradigms for implementing real-time dynamic economic optimization are a dynamic real-time optimization (DRTO) and regulatory MPC two-layer architecture, and a single-level economic model predictive control (EMPC) con figuration. In the two-layer architecture, the economically optimal set-point trajectories computed in an upper DRTO layer are provided to the MPC layer, while in the single-layer EMPC con figuration the economics are incorporated within the MPC objective function. There are limited studies on a systematic performance comparison between these two approaches. Furthermore, these studies do not simultaneously consider the economic, disturbance rejection and computational performance criteria. Thus, it may not be clear under what conditions one particular method is preferable over the other. These reasons motivate a more comprehensive comparison between the two paradigms, with both open and closed-loop predictions considered in the DRTO calculations. In order to conduct this comparison, we utilize two process case studies for the economic analysis and performance comparison of on-line optimization systems. The first case study is a process involving two stirred-tank reactors in-series with an intermediate mixing point, and the second case study is a linear multi-input single-output (MISO) system. These processes are represented using a fi rst principles model in the form of differential-algebraic equations (DAEs) system for the first case study and a simplified linear model of a polymerization reactor for the second case study problem. Both of the case study processes include constraints associated with input variables, safety considerations, and output quality. In these case study problems, the objective of optimal process operation is net profit improvement. The following performance evaluation criteria are considered in this study: (I) optimal value of the economic objective function, (II) average run time (ART) over a same operating time interval, (III) cumulative output constraint violation (COCV) for each constraint. The update time of the single-layer approach is selected to be equal to that of the control layer in the two-layer formulations, while the update time of the economic layer in the two-layer formulation is bigger than that of the single-layer approach. The nonlinear programing (NLP) problems which result in the single-layer and two-layer formulations and the quadratic programing problem which corresponds to the MPC formulation are solved using the fmincon and quadprog optimization solvers in MATLAB. Performance assessment of the single-layer and two-layer formulations is evaluated in the presence of a variety of unknown disturbance scenarios for the first case study problem. The effect of a dynamic transition in the product quality is considered in the performance comparison of the single-layer and two-layer methods in the second case-study problem. The first case study problem results show that for all unknown disturbance scenarios, the economic performance of the single-layer approach is slightly higher than that of the two layer formulations. However, the average computation times for the DRTO-MPC two-layer formulations are at least one order of magnitude lower than that of the EMPC formulation. Also, comparison results of the COCV for the EMPC formulation for different sizes of update time intervals could justify the necessity of the MPC control layer to reduce the COCV for the economic optimization problems with update times larger than that of the MPC control layer. A similar computational advantage of the OL- and CL-DRTO-MPC over the EMPC is observed for the second case study problem. In particular, it is shown that increasing the economic horizon length in the EMPC formulation to a sufficiently large value may result a higher economic improvement. However, the increase in economic optimization horizon would increase the resulting NLP problem size. The computational burden could limit the use of the EMPC formulation with larger economic optimization horizons in real-time applications. The ART of the dual-layer methods is at least two orders of magnitude lower than that of the EMPC methods with an appropriate horizon length. The CL-DRTO-MPC economic performance is slightly less than that of the EMPC formulation with the same economic optimization horizon. In conclusion, the performance comparison on the basis of multiple criteria in this study demonstrates that the economic performance criterion is not necessarily the only important metric, and the operational constraint limitations and the optimization problem solution time could have an important impact on the selection of the most suitable real-time optimization approach. / Thesis / Master of Applied Science (MASc)

Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2007.

Type 1 Diabetes is a dangerous and life-long disease for which its prevalence is global. Research has shown that tight glycaemic control of this disease significantly reduces the risks of developing several life threatening diabetic complications. The Ets-Insulin-Bolus Calculator (EIBC), inspired by the Ets concept (Equivalent Teaspoon Sugar), was primarily designed to assist type I diabetics in improving their blood glucose control. The EIBC has shown to improve the average blood glucose level of type 1 diabetics. The need for this study however is to determine whether the ET!3C promotes tighter glycaemic control for type 1 diabetics based on a more-in-depth numerical analysis. With the use of the latest technology in blood glucose monitoring, the CGMS from Medtronic, mathematical models expressing and rating blood glucose control have been proposed and derived in this study. A clinical trial with type 1 diabetics has also been conducted. The use of the models together with the clinical trial results have shown that the EIBC does in fact promote tighter glycaemic control for type 1 diabetics. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2007.

Type 1 Diabetes is a dangerous and life-long disease for which its prevalence is global. Research has shown that tight glycaemic control of this disease significantly reduces the risks of developing several life threatening diabetic complications. The Ets-Insulin-Bolus Calculator (EIBC), inspired by the Ets concept (Equivalent Teaspoon Sugar), was primarily designed to assist type I diabetics in improving their blood glucose control. The EIBC has shown to improve the average blood glucose level of type 1 diabetics. The need for this study however is to determine whether the ET!3C promotes tighter glycaemic control for type 1 diabetics based on a more-in-depth numerical analysis. With the use of the latest technology in blood glucose monitoring, the CGMS from Medtronic, mathematical models expressing and rating blood glucose control have been proposed and derived in this study. A clinical trial with type 1 diabetics has also been conducted. The use of the models together with the clinical trial results have shown that the EIBC does in fact promote tighter glycaemic control for type 1 diabetics. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2007.

This thesis addresses several synthesis and optimization issues for embedded control systems. Examples of such systems are automotive and avionics systems in which physical processes are controlled by embedded computers through sensor and actuator interfaces. The execution of multiple control applications, spanning several computation and communication components, leads to a complex temporal behavior that affects control quality. The relationship between system timing and control quality is a key issue to consider across the control design and computer implementation phases in an integrated manner. We present such an integrated framework for scheduling, controller synthesis, and quality optimization for distributed embedded control systems. At runtime, an embedded control system may need to adapt to environmental changes that affect its workload and computational capacity. Examples of such changes, which inherently increase the design complexity, are mode changes, component failures, and resource usages of the running control applications. For these three cases, we present trade-offs among control quality, resource usage, and the time complexity of design and runtime algorithms for embedded control systems. The solutions proposed in this thesis have been validated by extensive experiments. The experimental results demonstrate the efficiency and importance of the presented techniques.

[pt] Os gráficos de controle estão entre as ferramentas indispensáveis para monitorar o desempenho de um processo em várias indústrias. Quando estimativas de parâmetros são necessárias para projetar esses gráficos, seu desempenho é afetado devido aos erros de estimação. Para resolver esse problema, no passado, pesquisadores avaliavam o desempenho desses métodos em termos do valor esperado do número médio de amostras até um alarme falso condicionado às estimativas dos parâmetros (denotado por 𝐶𝐴𝑅𝐿0). No entanto, esta solução não considera a grande variabilidade do 𝐶𝐴𝑅𝐿0 entre usuários. Então, recentemente, surgiu a ideia de medir o desempenho dos gráficos de controle usando a probabilidade de o 𝐶𝐴𝑅𝐿0 ser maior do que um valor especificado – que deve estar próximo do desejado nominal. Isso é chamado de Exceedance Probability Criterion (EPC). Para aplicar o EPC, a função de distribuição acumulada (c.d.f.) do 𝐶𝐴𝑅𝐿0 é necessária. No entanto, para um dos gráficos de controle mais utilizados, o gráfico Xbarra, também conhecido como gráfico x (sob a suposição de distribuição normal), a expressão matemática da c.d.f. não está disponível na literatura. Como contribuição nesse sentido, o presente trabalho apresenta a derivação exata da expressão matemática da c.d.f. do 𝐶𝐴𝑅𝐿0 para três possíveis casos de estimação de parâmetros: (1) quando a média e o desvio-padrão são desconhecidos, (2) quando apenas a média é desconhecida e (3) quando apenas o desvio-padrão é desconhecido. Assim, foi possível calcular o número mínimo de amostras iniciais, m, que garantem um desempenho desejada do gráfico em termos de EPC. Esses resultados mostram que m pode assumir valores consideravelmente grandes (como, por exemplo, 3.000 amostras). Como solução, duas novas equações são derivadas aqui para ajustar os limites de controle garantindo assim um desempenho desejado para qualquer valor de m. A vantagem dessas equações é que uma delas fornece resultados exatos enquanto a outra dispensa avançados softwares de computador para os cálculos. Um estudo adicional sobre o impacto desses ajustes no desempenho fora de controle (OOC) fornece tabelas que ajudam na decisão do melhor tradeoff entre quantidade adequada de dados e desempenhos IC e OOC preferenciais do gráfico. Recomendações práticas para uso desses resultados são aqui também fornecidas. / [en] Control charts are among the indispensable tools for monitoring process performance in various industries. When parameter estimation is needed to design these charts, their performance is affected due to parameter estimation errors. To overcome this problem, in the past, researchers have evaluated the performance of control charts and designed them in terms of the expectation of the realized in-control (IC) average run length (𝐶𝐴𝑅𝐿0). But, as pointed recently, this solution does not account for what is known as the practitioner-to-practitioner variability (i.e., the variability of 𝐶𝐴𝑅𝐿0). So, a recent idea emerged where control chart performance is measured by the probability of the 𝐶𝐴𝑅𝐿0 being greater than a specified value - which must be close to the nominal desired one. This is called the Exceedance Probability Criterion (EPC). To apply the EPC, the cumulative distribution function (c.d.f.) of the 𝐶𝐴𝑅𝐿0 is required. However, for the most well-known control chart, named the two-sided Shewhart Xbar (or simply X) Chart (under normality assumption), the mathematical c.d.f. expression of the 𝐶𝐴𝑅𝐿0 is not available in the literature. As a contribution in this respect, the present work presents the derivation of the exact c.d.f. expression of the 𝐶𝐴𝑅𝐿0 for three cases of parameters estimation: (1) when both the process mean and standard deviation are unknown, (2) when only the mean is unknown and (3) when only the standard deviation is unknown. Using these key results, it was possible to calculate the exact minimum number of initial (Phase I) samples (m) that guarantees a desired in-control performance in terms of the EPC. These results show that m can be prohibitively large (such as 3.000 samples). As a solution to this problem, two new equations are derived here to adjust the control limits to guarantee a desired in-control performance in terms of the EPC for any given value of m. The advantage of these equations (compared to the existing adjustments methods) is that one provides exact results and the other one does not require too many computational resources to perform the calculations. A further study about the impact of these adjustments on the out-of-control (OOC) performance provides useful tables to decide the appropriate amount of data and the adjustments that corresponds to a user preferred tradeoff between the IC and OOC performances of the chart. Practical recommendations for using these findings are also provided in this research work.

Grid-connected inverters have wide application in the field of distributed generation and power quality. As the power level demanded by these applications increase, the design and performance evaluation of these converters become important. In the present work, a 50 kVA three-phase back-to-back connected inverter with output LCL filter is built to study design and performance evaluation aspects of grid-connected inverters. The first part of the work explores the split-capacitor resistive-inductive (SC-RL) passive damping scheme for the output LCL filter of a three-phase grid-connected inverter. The low losses in the SC-RL scheme makes it suitable for high power applications. The SCRL damped LCL filter is modelled using state space approach. Using this model, the power loss and damping are analysed. A method for component selection that minimizes the power loss in the damping resistors while keeping the system well damped is proposed. Analytical results show the losses to be in the range of 0.05-0.1% and the quality factor to be in the range of 2.0-2.5. These results are validated experimentally. In the second part of the work, a test method to evaluate the thermal performance of the semi-conductor devices of a three-phase grid-connected inverter is proposed. The method eliminates the need for high power sources, loads or any additional power converters for circulation of power. Only energy corresponding to the losses is consumed. The capability of the method to evaluate the thermal performance of the DC bus capacitors and the output filter components is also explored. The method can be used with different inverter configurations -three-wire or four-wire and for different PWM techniques. The method has been experimentally validated at a power level of 24kVA. In the third part of the work, the back-to-back connected inverter is programmed as a hardware grid simulator. The hardware grid simulator emulates the real-time grid and helps create grid disturbances often observed at the point of common coupling in an ac low voltage grid. A novel disturbance generation algorithm has been developed, analysed and implemented in digital controller using finite state machine model for control of the grid simulator. A wide range of disturbance conditions can be created using the developed algorithm. Experimental tests have been done on a linear purely resistive load, a non-linear diode-bridge load and a current-controlled inverter load to validate the programmed features of the grid simulator.