Finite control set model predictive control-a powerful control algorithm for grid-connected power converters

© 2016 IEEE. This paper presents a detailed description of Finite Control Set Model Predictive Control applied to power converters. Some key features related to this methodology are presented and compared with model predictive control based space vector modulation methods. The basic models, principles, control diagrams, and simulation results are presented to provide a comparison between them. The analysis is performed on a three-phase/ two-level voltage source inverter, which is one of the most common converter topologies used in industry. Among the conclusions are the feasibility and great potential of Finite Control Set Model Predictive Control due to the advanced signal-processing capability, particularly for power systems with a reduced number of switching states and more complicated principles

Investigation of direct matrix converter working as a versatile converter (AC/AC, AC/DC, DC/AC, DC/DC conversion) with predictive control

© 2017 IEEE. The three-phase direct matrix converter has been researched exclusively as a direct AC/AC converter, being a competitive alternative to the conventional AC/DC/AC converter. Other possibilities of the matrix converter such as AC/DC, DC/AC and DC/DC conversion still remain unexplored. This paper firstly explores these possibilities and puts forward a concept of the versatile converter. With one matrix converter, different conversion purposes can be accomplished as required. The matrix converter based conversion has some advantages compared with other converters. Model predictive control (MPC) is applied in this work to control the matrix converter to perform the required conversion goals. A generalized model is obtained for all types of conversion in this work. With MPC, different objectives and constraints can be easily included in the control scheme. In addition, the observers are used to reduce the number of voltage and current sensors. Simulation results verify the effectiveness and feasibility of AC/DC, DC/AC and DC/DC conversion with the matrix converter

Comprehensive study of finite control set model predictive control algorithms for power converter control in microgrids

© 2020 Institution of Engineering and Technology. All rights reserved. Advances in power electronics and digital control open a new horizon in the control of power converters. Particularly, model predictive control has been developed for control applications in industrial electronics and power systems. This study presents a comprehensive study on recent achievements of model predictive control algorithms to overcome the challenges in the real-time implementation of power converter control, which is the lowest level control of hierarchical control in microgrids. The study shows that most of these alternate solutions can enhance system reliability, stability, and efficiency. The control platform devices for the real-time implementation of these algorithms are compared. The related issues are discussed and classified, respectively. Finally, a summary is provided, leading to some further research questions and future work

A hysteretic multiscale formulation for nonlinear dynamic analysis of composite materials

This article has been made available through the Brunel Open Access Publishing Fund.A new multiscale finite element formulation is presented for nonlinear dynamic analysis of heterogeneous structures. The proposed multiscale approach utilizes the hysteretic finite element method to model the microstructure. Using the proposed computational scheme, the micro-basis functions, that are used to map the microdisplacement components to the coarse mesh, are only evaluated once and remain constant throughout the analysis procedure. This is accomplished by treating inelasticity at the micro-elemental level through properly defined hysteretic evolution equations. Two types of imposed boundary conditions are considered for the derivation of the multiscale basis functions, namely the linear and periodic boundary conditions. The validity of the proposed formulation as well as its computational efficiency are verified through illustrative numerical experiments

Involvement of the Glycogen Synthase Kinase-3 Signaling Pathway in TBI Pathology and Neurocognitive Outcome

BACKGROUND: Traumatic brain injury (TBI) sets in motion cascades of biochemical changes that result in delayed cell death and altered neuronal architecture. Studies have demonstrated that inhibition of glycogen synthase kinase-3 (GSK-3) effectively reduces apoptosis following a number of stimuli. The Wnt family of proteins, and growth factors are two major factors that regulate GSK-3 activity. In the absence of stimuli, GSK-3 is constitutively active and is complexed with Axin, adenomatous polyposis coli (APC), and casein kinase Iα (CK1α) and phosphorylates ß-Catenin leading to its degradation. Binding of Wnt to Frizzled receptors causes the translocation of GSK-3 to the plasma membrane, where it phosphorylates and inactivates the Frizzled co-receptor lipoprotein-related protein 6 (LRP6). Furthermore, the translocation of GSK-3 reduces ß-Catenin phosphorylation and degradation, leading to ß-Catenin accumulation and gene expression. Growth factors activate Akt, which in turn inhibits GSK-3 activity by direct phosphorylation, leading to a reduction in apoptosis. METHODOLOGY/PRINCIPAL FINDINGS: Using a rodent model, we found that TBI caused a rapid, but transient, increase in LRP6 phosphorylation that is followed by a modest decrease in ß-Catenin phosphorylation. Phospho-GSK-3β immunoreactivity was found to increase three days post injury, a time point at which increased Akt activity following TBI has been observed. Lithium influences several neurochemical cascades, including inhibiting GSK-3. When the efficacy of daily lithium was assessed, reduced hippocampal neuronal cell loss and learning and memory improvements were observed. These influences were partially mimicked by administration of the GSK-3-selective inhibitor SB-216763, as this drug resulted in improved motor function, but only a modest improvement in memory retention and no overt neuroprotection. CONCLUSION/SIGNIFICANCE: Taken together, our findings suggest that selective inhibition of GSK-3 may offer partial cognitive improvement. As a broad spectrum inhibitor of GSK-3, lithium offers neuroprotection and robust cognitive improvement, supporting its clinical testing as a treatment for TBI

Fuzzy-based self-tuning model predictive direct power control of grid-connected multilevel converters

© 2017 IEEE. This paper proposes a self-tuning model predictive direct power control (MPDPC) strategy for power flow control and power quality improvement in grid-connected power converters. At each sampling instant, a fuzzy logic controller is used to determine online the best weighting factor values for a given operating point. These values are then used to solve the multi-objective optimal control problem associated to the MPDPC. The optimal solution that minimizes the multi-objective cost function is chosen as the input (power switch state). The proposed method is examined through a case study and verified numerically via MAT LAB SIMULINK. A comparative study is conducted to demonstrate the effective performance of this approach. As a result of the proposed weighting factor online tuning, an improved performance in terms of total harmonic distortion and average switching frequency is attained when compared with fixed weighting factors

Time-delayed model predictive direct power control for vehicle to grid and grid to vehicle applications

© 2017 IEEE. This paper presents a time-delayed model predictive control for power converters used in vehicle to grid and grid to vehicle systems. Finite-based model predictive control has proven to be an alternate digital control method for power converters. However, there are some real-time implementation issues, including specifically time delay, that have to be addressed in order to achieve the system reliability and stability as well as better performance. The proposed method compensates the delay time arising from measuring, calculating, and applying the optimal control sequence in the digital processor. In this way, the delay time is considered in the system input and optimal switching states are applied to the converter once they are available. The proposed method is studied through two benchmarks and verified numerically via MATLAB/Simulink