Saturday, July 25, 2020

Power Converters and AC Electrical Drives with Linear Neural Networks by Maurizio Cirrincione, Marcello Pucci and Gianpaolo Vitale

 Download Power Converters and AC Electrical Drives with Linear Neural Networks by Maurizio Cirrincione, Marcello Pucci and Gianpaolo Vitale


Contents of Power Converters and AC Electrical Drives 

1. Review of Basic Concepts: Space-Vector Analysis

Part I Power Converters

1. Pulsewidth Modulation of Voltage Source Inverters
2. Power Quality

Part II Electrical Drives

1. Dynamic and Steady-State Models of the Induction Machine
2. Control Techniques of Induction Machine Drives
3. Sensorless Control of Induction Machine Drives
4. Permanent Magnet Synchronous Motor Drives

Part III Neural-Based Orthogonal Regression

1. Neural-Based Orthogonal Regression

Part IV Selected Applications

1. Least-Squares and Neural Identification of Electrical Machines
2. Neural-Enhanced Single-Phase DG Systems with APF Capability
3. Neural Sensorless Control of AC Drives

Preface of Power Converters and AC Electrical Drives 

A.recent trend for the development of.these disciplines is.the.application.of.artificial intelligence. (AI). tools,. such. as. expert systems. (ES),. artificial neural networks. (ANN),. fuzzy logic systems.(FLS),.genetic algorithms.(GA),.and,.more.recently,.multi-agent systems.(MAS)..These. tools.have.been.proven.to.be.able.to.boost.the.performance.of.these.systems.in.real-world. and.industrial.applications.thanks.to.features.such.as.“learning,”.“self-organization,”.and. “self-adaptation.”With.particular.regard.to.ANNs.for.nonlinear.function.approximation,.in.power.electronics.and.electr cal.drives.applications,.they.are.used.for.control.and.identification,.such. as.the.multilayer.perceptron.(MLP).or.the.radial.basis.function.(RBF)..Another.kind.of. neuron.that.has.also.been.applied.recently.is.linear.neurons.(ADALINE),.whose.simplicity. has.given.surprisingly.good.results. On. the. other. hand,. the. detailed. unified. mathematical. treatment. of. space-vectors. has. made. it. possible. to. embed. the. theory. of. linear. neural. networks,. resulting   improvements,.both.theoretical.and.experimental,.of.classical.approaches.in.electrical.drives.and. power.electronics..This.standpoint.is.the.goal.of.the.book:.to.present.in.a.systematic.way.
the.classical.theory.based.on.space-vectors.in.identification,.control.of.electrical.drives.and.
of.power.converters,.and.the.improvements.that.can.be.attained.when.using.linear.neural.
networks.
With.this.outlook,.this.book.is.divided.into.four.parts:
•. Part.I.deals.specifically.with.voltage.source.inverters.(VSI).and.their.control.
•. Part.II.deals.with.AC.electrical.drive.control,.with.particular.attention.to.induction.
and.permanent.magnet.synchronous.motor.drives.
•. Part.III.deals.with.theoretical.aspects.of.linear.neural.networks.
•. Part. IV. deals. with. specific. applications. of. linear. neural. networks. to. electrical.
drives.and.power.quality.

Outline of the Book
Chapter.1.presents.the.theory.of.space-vectors.and.instantaneous.power..This.chapter.is.
fundamental.for.understanding.the.rest.of.the.book.
Chapter.2.describes.the.open-loop.and.closed-loop.control.of.voltage.source.inverters..
With.regard.to.open-loop.techniques.it.also.explains.the.different.kinds.of.pulsewidth.
modulation.(PWM).strategies,.and.with.regard.to.closed-loop.techniques.it.analyzes.both.
current.and.power.control.of.VSIs..Voltage-oriented.control.(VOC).and.direct.power.control.(DPC).are.also.presented..Chapter.3.explains.the.fundamentals.of.power.quality;.parallel.active.filters.(PAFs).and.series.active.filters.(SAFs),.with.reference.to.their.operating.
principle.and.control.strategies,.are.investigated..Passive.and.hybrid.filter.configurations.
are.also.analyzed.
Chapter.4.deals.with.induction.machine.(IM).static.and.dynamic.space-vector.models..
The.dynamic.model.of.the.IM,.including.saturation.effects,.is.shown..Finally,.the.spacevector.dynamic.model.of.the.IM,.including.rotor.and.stator.slotting.effects,.is.described..
Chapter.5.describes,.first,.scalar.control.strategies.of.IM.drives.with.impressed.voltages.
and. currents.. It. then. derives. field-oriented. control. (FOC). strategies,. with. reference. to.
rotor,. stator,. and. magnetizing. flux. linkage. orientations.. Related. flux. models. are. also.
presented.. Finally,. direct. torque. control. (DTC). strategies. are. presented,. particularly.
the.classic.switching.table.(ST).DTC,.the.space-vector.modulation.(SVM).DTC,.and.the.
electromagnetically. compatible. (DTC).. The. so-called. direct. self-control. (DSC). is. also.
described..Chapter.6.covers.sensorless.control.of.IM.drives,.with.particular.reference.to.
both.model-based.and.anisotropy-based.techniques..With.regard.to.model-based.techniques,.the.following.estimators/observers.are.described:.open-loop.speed.estimators,.
model. reference. adaptive. systems. (MRAS),. full-order. Luenberger. adaptive. observer.
(FOLO),.full-order.sliding-mode.observer,.reduced-order.adaptive.observer.(ROO),.and,.
finally,.the.extended.Kalman.filter..With.reference.to.anisotropy-based.techniques,.the.
following.methodologies.have.been.described:.revolving.Carrier.techniques,.pulsating.
carrier.techniques,.and.high-frequency.excitation.techniques..Chapter.7.derives.the.permanent. magnet. synchronous. motor. space-vector. model.. Field-oriented. control. (FOC).
with. both. impressed. voltage. and. currents. is. described.. Various. control. strategies. are.
presented. to. maximize. the. electromagnetic. torque. production. or. the. drive. efficiency..
The.DTC.of.the.PMSM.is.also.presented..Finally,.both.anisotropy-.and.model-based.sensorless.techniques.are.explained.
Chapter.8.deals.with.the.theory.of.linear.neural.networks,.particularly.the.neural.EXIN.
family..Starting.from.the.adaptive.linear.neuron.(ADALINE).structure,.it.presents.more.
recent.and.performing.linear.neural.networks:.the.TLS.EXIN.neuron,.the.Ge-TLS.EXIN.
neuron,.the.MCA.EXIN.neuron,.and,.finally,.the.MCA.EXIN.+.neuron.
Chapter.9.covers,.first,.the.sensitivity.analysis.of.the.classic.flux.models.of.IM.drives.
versus.parameter.variations..It.then.presents.some.on-line.parameter.estimation.techniques. of. IMs. by. the. least-squares. (LS). technique,. including. both. unconstrained. and.
constrained.estimations..Finally,.it.shows.the.neural.self-.commissioning.of.IM.drives..
Chapter.10.deals.with.the.application.of.neural.adaptive.filtering.to.distributed.generation.(DG).and.active.power.filter.(APF).systems..The.ADALINE.design.criteria.for.the.
fundamental.frequency.extraction.and.the.harmonic.load.current.compensation.are.presented..The.stability.issues.of.the.entire.system.are.included..Experimental.verification. of.the.neural.approach.is.presented.in.comparison.with.classic.approaches..Chapter.11.
presents.some.applications.of.LS-based.techniques.to.speed.estimation.of.IMs..In.partic
ular,.the.following.neural-based.observers.are.presented.and.discussed:.the.MCA.EXIN.
+.MRAS.observer,.the.TLS.EXIN.full-order.Luenberger.adaptive.observer,.and,.finally,.
the.reduced.order.adaptive.observer..The.general.approach.of.this.book.is.presenting.ini
tially.the.theoretical.background.of.each.subject.immediately.followed.by.a.set.of.simu
lations.of.experimental.results.supporting.the.analytical.part..It.is.the.authors’.opinion.
that.the.presence.of.many.results.should.help.the.reader.in.understanding.better.the.
treated.theoretical.aspects.

How to Use This Book
This. book. can. be. used. in. different. ways,. depending. on. the. background. of. the. reader..
Instructors.for.undergraduate.students.can.use.Chapters.1,.2,.4,.5,.and.7.for.a.one-semester.
course.in.power.electronics.and.electrical.drives..Postgraduate.and.PhD.students.could.
also.cover.Chapters.3.and.6..Researchers.involved.in.applications.of.ANNs.to.power.elec
tronics.and.drives.would.find.it.more.interesting.to.go.through.Chapters.9.through.11..
Theoreticians.will.find.a.comprehensive.coverage.of.linear.neural.networks.in.Chapter.8..
Figure.P.1.suggests.different.paths.for.reading.this.book.
Chapter.1.should.be.read.first,.since.it.provides.the.basic.tools..The.power.electronics.path.
consists.of.Chapters.2,.3,.and.10..The.IM.drives.path.includes.Chapters.4.through.6.and 11.
(electrical.machine.approach).or,.alternatively,.Chapters.2,.5,.6,.and.11.(power.converter.
approach)..The.PMSM.drives.path.includes.Chapters.2.and.7.(or.directly.Chapter 7)..The.
IM.identification.path.includes.Chapters.4.and.9..Finally,.the.ANN.path.includes.Chapters.
8.through.11.

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