Switched Polytopic Controller Applied on a Positive Reconfigurable Power Electronic Converter

The reconfigurable power electronic converters (RPECs) are a new generation of systems, which modify their physical configuration in terms of a desired input or output operation characteristic. This kind of converters is very attractive in terms of versatility, compactness, and robustness. They have been proposed in areas such as illumination, transport electrification (TE), eenewable energy (RE), smart grids and the internet of things (IoT). However, the resulting converters operate in switched variable operation-regions, rather than over single operation points. As a result, there is a complexity increment on the modeling and control stage such that traditional techniques are no longer valid. In order to overcome these challenges, this paper proposes a kind of switched polytopic controller (SPC) suitable to stabilize an RPEC. Modeling, control, numerical and practical results are reported. To this end, a 400 W positive synchronous bi-directional buck/boost converter is used as a testbed. It is also shown, that the proposed converter and robust controller accomplish a compact, modular and reliable design during different working configuration, operation points and load changes

Fractional-Order Approximation and Synthesis of a PID Controller for a Buck Converter

In this paper, the approximation of a fractional-order PIDcontroller is proposed to control a DC–DC converter. The synthesis and tuning process of the non-integer PID controller is described step by step. A biquadratic approximation is used to produce a flat phase response in a band-limited frequency spectrum. The proposed method takes into consideration both robustness and desired closed-loop characteristics, keeping the tuning process simple. The transfer function of the fractional-order PID controller and its time domain representation are described and analyzed. The step response of the fractional-order PID approximation shows a faster and stable regulation capacity. The comparison between typical PID controllers and the non-integer PID controller is provided to quantify the regulation speed introduced by the fractional-order PID approximation. Numerical simulations are provided to corroborate the effectiveness of the non-integer PID controller

Switched Polytopic Controller Applied on a Positive Reconfigurable Power Electronic Converter

The reconfigurable power electronic converters (RPECs) are a new generation of systems, which modify their physical configuration in terms of a desired input or output operation characteristic. This kind of converters is very attractive in terms of versatility, compactness, and robustness. They have been proposed in areas such as illumination, transport electrification (TE), eenewable energy (RE), smart grids and the internet of things (IoT). However, the resulting converters operate in switched variable operation-regions, rather than over single operation points. As a result, there is a complexity increment on the modeling and control stage such that traditional techniques are no longer valid. In order to overcome these challenges, this paper proposes a kind of switched polytopic controller (SPC) suitable to stabilize an RPEC. Modeling, control, numerical and practical results are reported. To this end, a 400 W positive synchronous bi-directional buck/boost converter is used as a testbed. It is also shown, that the proposed converter and robust controller accomplish a compact, modular and reliable design during different working configuration, operation points and load changes

A Comparison of Integrated Filtering and Prediction Methods for Smart Grids

The intelligent use of green and renewable energies requires reliable and preferably anticipated information regarding their availability and the behavior of meteorological variables in a scenario of natural intermittency. Examples of this are the smart grids, which can incorporate, among others, a charging system for electric vehicles and modern and predictive management techniques. However, some issues associated with such procedures are data captured by sensors and transducers with noise in their signals and low information repeatability under the same reading conditions. To tackle such problems, numerous filtering and data fitting techniques and various prediction methods have been developed, but an appropriate selection can be cumbersome. Also, some filtering techniques, such as RANdom SAmple Consensus (RANSAC) appear not to have been used in prediction scenarios for smart grids, to the authors’ knowledge. In this regard, this paper aims to present a comparison in terms of average error, determination coefficient, and cross validation that can be expected under prediction schemes as Multiple Linear Regression, Vector Support Machines and a Multilayer Perceptron Regression Neural Network (MLPRNN), with filtering/scaling methods such as Maximum and Minimum, L2 Norm, Standard Scale, and RANSAC. Cross validation allows to flag problems like overfitting or selection bias, and this comparison is another novelty for smart grid scenarios, to the authors’ knowledge. Although many combinations were analyzed, RANSAC, with L2 Norm filtering and an MLPRNN for prediction, generate the best results. RANSAC algorithm with L2 Norm is a novelty for filtering and predicting in smart grids, and through an MLPRNN, the R2 error can be reduced to 0.8843, the MSE to 0.8960, and the cross validation accuracy can be increased to 0.44 (±0.2)