Alternative control methods for DC–DC converters: An application to a four‐level three‐cell DC–DC converter
Identifieur interne : 000004 ( Istex/Curation ); précédent : 000003; suivant : 000005Alternative control methods for DC–DC converters: An application to a four‐level three‐cell DC–DC converter
Auteurs : Diego Patino [France, Colombie] ; Mihai Bâja [France] ; Pierre Riedinger [France] ; Hervé Cormerais [France] ; Jean Buisson [France] ; Claude Iung [France]Source :
- International Journal of Robust and Nonlinear Control [ 1049-8923 ] ; 2011-07-10.
English descriptors
- Teeft :
- Activation functions, Alternative control methods, American control conference, Average model, Average value, Basic concepts, Benchmark, Boolean, Boolean control, Buck converter, Buisson, Capacitor, Capacitor voltages, Constraint, Control block, Control laws, Control methods, Control objective, Control problem, Control problems, Control scheme, Control values, Converter, Copyright, Cormerais, Design phase, Discrete time implementation, Dspace, Energetic principles, Equilibrium point, Experimental results, Feedback, Hamiltonian, Hybrid, Hybrid systems, Ieee, Ieee conference, Ieee power electronics specialists conference, Ieee transactions, Industrial applications, Industrial electronics, International journal, John wiley sons, Limit cycle, Load variations, Lyapunov, Lyapunov function, Matrix, Meynard, Mode control, Mode sequence, Modeling, Morari, Multicell converters, Multilevel, Multilevel converter, Multilevel converters, Necessary conditions, Neural network, Nonlinear, Nonlinear control, Optimal control, Optimal control approach, Optimal control problem, Optimal limit cycle, Optimal policy, Optimal solutions, Optimal trajectories, Optimization, Optimization problem, Papafotiou, Patino, Power converters, Power electronics, Predictive, Predictive approach, Predictive approaches, Predictive control, Problem order, Quadratic criterion, Real time implementation, Reference values, Robust, Robustness, Sample time, Sampling frequency, Sampling time, Simulation results, Singular arcs, Singular trajectories, Stabilization, Stabilization approach, Stabilization method, State feedback, State feedback control, State space, Steady state, Time sequence, Trajectory.
Abstract
This paper proposes three synthesis methods for controlling power converters. The three control strategies yield state feedback control laws that are easy to implement. The first method is a stabilization approach, based on energetic principles and the notion of Lyapunov function. The second is an optimal control approach based on the minimum principle. The third is a neural predictive approach which uses model predictive control to track a given optimal stable limit cycle. This method allows a proper control of the waveform. Except for the predictive approach, system stability for the methods is guaranteed by construction. The four‐level three‐cell DC–DC converter is used as a benchmark to test these strategies. Simulation and experimental results show that the methods have a good performance even with load perturbations. Copyright © 2010 John Wiley & Sons, Ltd.
Url:
DOI: 10.1002/rnc.1651
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when="2011-07-10">2011-07-10</date></imprint><idno type="ISSN">1049-8923</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1049-8923</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="Teeft" xml:lang="en"><term>Activation functions</term><term>Alternative control methods</term><term>American control conference</term><term>Average model</term><term>Average value</term><term>Basic concepts</term><term>Benchmark</term><term>Boolean</term><term>Boolean control</term><term>Buck converter</term><term>Buisson</term><term>Capacitor</term><term>Capacitor voltages</term><term>Constraint</term><term>Control block</term><term>Control laws</term><term>Control methods</term><term>Control objective</term><term>Control problem</term><term>Control problems</term><term>Control scheme</term><term>Control values</term><term>Converter</term><term>Copyright</term><term>Cormerais</term><term>Design phase</term><term>Discrete time implementation</term><term>Dspace</term><term>Energetic principles</term><term>Equilibrium point</term><term>Experimental results</term><term>Feedback</term><term>Hamiltonian</term><term>Hybrid</term><term>Hybrid systems</term><term>Ieee</term><term>Ieee conference</term><term>Ieee power electronics specialists conference</term><term>Ieee transactions</term><term>Industrial applications</term><term>Industrial electronics</term><term>International journal</term><term>John wiley sons</term><term>Limit cycle</term><term>Load variations</term><term>Lyapunov</term><term>Lyapunov function</term><term>Matrix</term><term>Meynard</term><term>Mode control</term><term>Mode sequence</term><term>Modeling</term><term>Morari</term><term>Multicell converters</term><term>Multilevel</term><term>Multilevel converter</term><term>Multilevel converters</term><term>Necessary conditions</term><term>Neural network</term><term>Nonlinear</term><term>Nonlinear control</term><term>Optimal control</term><term>Optimal control approach</term><term>Optimal control problem</term><term>Optimal limit cycle</term><term>Optimal policy</term><term>Optimal solutions</term><term>Optimal trajectories</term><term>Optimization</term><term>Optimization problem</term><term>Papafotiou</term><term>Patino</term><term>Power converters</term><term>Power electronics</term><term>Predictive</term><term>Predictive approach</term><term>Predictive approaches</term><term>Predictive control</term><term>Problem order</term><term>Quadratic criterion</term><term>Real time implementation</term><term>Reference values</term><term>Robust</term><term>Robustness</term><term>Sample time</term><term>Sampling frequency</term><term>Sampling time</term><term>Simulation results</term><term>Singular arcs</term><term>Singular trajectories</term><term>Stabilization</term><term>Stabilization approach</term><term>Stabilization method</term><term>State feedback</term><term>State feedback control</term><term>State space</term><term>Steady state</term><term>Time sequence</term><term>Trajectory</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This paper proposes three synthesis methods for controlling power converters. The three control strategies yield state feedback control laws that are easy to implement. The first method is a stabilization approach, based on energetic principles and the notion of Lyapunov function. The second is an optimal control approach based on the minimum principle. The third is a neural predictive approach which uses model predictive control to track a given optimal stable limit cycle. This method allows a proper control of the waveform. Except for the predictive approach, system stability for the methods is guaranteed by construction. The four‐level three‐cell DC–DC converter is used as a benchmark to test these strategies. Simulation and experimental results show that the methods have a good performance even with load perturbations. Copyright © 2010 John Wiley & Sons, Ltd.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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