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An important drawback in the application of model-based predictive controllers for multiphase systems is the relatively high harmonic content. Harmonics arise due to the fixed sampling-time nature and the absence of modulation methods in the control technique. Recent research works have proposed different procedures to overcome this disadvantage at the expense of increasing the complexity of the controller and, in most cases, the computational requirements. There are, however, natural ways to face this harmonic generation that have been barely explored in the scientific literature. These alternatives include the use of variable sampling times or the application of the observer theory, whose utility has been stated without excessively increasing the computational cost of the controller. This paper presents the basis of both methodologies, analyzing their interest as natural alternatives to mitigate the generation of harmonic components in modern electrical drives when using predictive controllers. A five-phase induction machine is used as a case example to experimentally validate the study and draw conclusions.

An important drawback in the application of model-based predictive controllers for multiphase systems is the relatively high harmonic content. Harmonics arise due to the fixed sampling-time nature and the absence of modulation methods in the control technique. Recent research works have proposed different procedures to overcome this disadvantage at the expense of increasing the complexity of the controller and, in most cases, the computational requirements. There are, however, natural ways to face this harmonic generation that have been barely explored in the scientific literature. These alternatives include the use of variable sampling times or the application of the observer theory, whose utility has been stated without excessively increasing the computational cost of the controller. This paper presents the basis of both methodologies, analyzing their interest as natural alternatives to mitigate the generation of harmonic components in modern electrical drives when using predictive controllers. A five-phase induction machine is used as a case example to experimentally validate the study and draw conclusions.

An important drawback in the application of model-based predictive controllers for multiphase systems is the relatively high harmonic content. Harmonics arise due to the fixed sampling-time nature and the absence of modulation methods in the control technique. Recent research works have proposed different procedures to overcome this disadvantage at the expense of increasing the complexity of the controller and, in most cases, the computational requirements. There are, however, natural ways to face this harmonic generation that have been barely explored in the scientific literature. These alternatives include the use of variable sampling times or the application of the observer theory, whose utility has been stated without excessively increasing the computational cost of the controller. This paper presents the basis of both methodologies, analyzing their interest as natural alternatives to mitigate the generation of harmonic components in modern electrical drives when using predictive controllers. A five-phase induction machine is used as a case example to experimentally validate the study and draw conclusions.

An important drawback in the application of model-based predictive controllers for multiphase systems is the relatively high harmonic content. Harmonics arise due to the fixed sampling-time nature and the absence of modulation methods in the control technique. Recent research works have proposed different procedures to overcome this disadvantage at the expense of increasing the complexity of the controller and, in most cases, the computational requirements. There are, however, natural ways to face this harmonic generation that have been barely explored in the scientific literature. These alternatives include the use of variable sampling times or the application of the observer theory, whose utility has been stated without excessively increasing the computational cost of the controller. This paper presents the basis of both methodologies, analyzing their interest as natural alternatives to mitigate the generation of harmonic components in modern electrical drives when using predictive controllers. A five-phase induction machine is used as a case example to experimentally validate the study and draw conclusions.

The usual Shewhart control chart efficiently detects large shifts in the mean of a quality characteristic and has been extensively studied in the literature. Most proposed alternatives to the Shewhart chart aim to improve either the signal performance for smaller mean shifts or reduce the sampling effort required to detect a larger shift. Measurement error has been shown in the literature to result in reduced power to detect process shifts. The combination of multiple measurements and two-stage sampling is considered here as a strategy for both regaining power lost due to measurement error and specifically tuning the charts for shifts of a particular size. It is shown that both the average total sample size and the average run length are improved relative to the standard Shewhart control chart under the same measurement error conditions. Chart designs are recommended to achieve particular control objectives.

This thesis presents a method for the design of a predictive controller with variable step sizes.Predictive methods such as receding horizon control (or model predictive control) use aa fixed sampling frequency when updating the inputs. In the proposed method, the switchingtimes are incorporated into an optimization problem, thus resulting in anadaptive step-size control process. The controller with variable timesteps is shown to require less tuning and to reduce the number of expensive model evaluations.An alternate solution approach had to be developed to accommodate the new problem formulation.The controller's stability is proven in a context that does not require terminal cost or constraints.The thesis presents examples that compare the performance of the variable switching time controllerwith the receding horizon method with a fixed step size. This research opens many roads for futureextension of the theoretical work and practical applications of the controller., Doctor of Science (PhD)

The usual Shewhart control chart efficiently detects large shifts in the mean of a quality characteristic and has been extensively studied in the literature. Most proposed alternatives to the Shewhart chart aim to improve either the signal performance for smaller mean shifts or reduce the sampling effort required to detect a larger shift. Measurement error has been shown in the literature to result in reduced power to detect process shifts. The combination of multiple measurements and two-stage sampling is considered here as a strategy for both regaining power lost due to measurement error and specifically tuning the charts for shifts of a particular size. It is shown that both the average total sample size and the average run length are improved relative to the standard Shewhart control chart under the same measurement error conditions. Chart designs are recommended to achieve particular control objectives.