Intelligent Control for Electric Power Systems and Electric Vehicles

Cover
Half Title
Title Page
Copyright Page
Dedication
Contents
Foreword
Preface
About the authors
Acknowledgment
Chapter 1: Nonlinear optimal control and Lie algebra-based control
	1.1. Control based on approximate linearization
		1.1.1. Overview of the optimal control concept
		1.1.2. Design of an H-infinity nonlinear optimal controller
		1.1.3. Optimal state estimation with the H-infinity Kalman Filter
	1.2. Global linearization-based control concepts
		1.2.1. Foundations of global linearization-based control
		1.2.2. Elaborating on input-output linearization
		1.2.3. Input-state linearization
		1.2.4. Stages in the implementation of input-state linearization
		1.2.5. Input-output and input-state linearization for MIMO systems
		1.2.6. Dynamic extension
Chapter 2: Differential flatness theory and flatness-based control methods
	2.1. Global linearization-based control with the use of differential flatness theory
		2.1.1. The background of differential flatness theory
		2.1.2. Differential flatness for finite dimensional systems
		2.1.3. Equivalence and differential flatness
		2.1.4. Differential flatness and trajectory planning
		2.1.5. Differential flatness, feedback control and equivalence
		2.1.6. Flatness-based control for systems with uncertainties
		2.1.7. Classification of types of differentially flat systems
	2.2. Flatness-based control in successive loops
		2.2.1. Decomposition into cascading differentially flat subsystems
		2.2.2. Tracking error for multi-loop flatness-based control
		2.2.3. Comparison to backstepping control for nonlinear systems
Chapter 3: Control of DC and PMBLDC electric motors
	3.1. Control of DC motors through a DC-DC converter
		3.1.1. Outline
		3.1.2. Dynamics of DC-DC converter and motor
		3.1.3. Differential flatness properties of the DC-DC converter
		3.1.4. Flatness-based control in successive loops
		3.1.5. Stability proof
		3.1.6. Multi-loop flatness-based control for converters
		3.1.7. Simulation tests
	3.2. Control of Permanent Magnet Brushless DC motors
		3.2.1. Dynamic model of the PMBLDC motor
		3.2.2. The nonlinear H-infinity control
		3.2.3. Lyapunov stability analysis
		3.2.4. Differential flatness of the PMBLDC motor
		3.2.5. Sliding-mode control for PMBLDC motors
		3.2.6. Simulation tests
Chapter 4: Control of VSI-fed three-phase and multi-phase PMSMs
	4.1. Nonlinear optimal control of 3-phase VSI-PMSM
		4.1.1. Outline
		4.1.2. Dynamic model of the VSI-PMSM system
		4.1.3. Approximate linearization of the VSI-PMSM dynamics
		4.1.4. Stabilizing feedback control
		4.1.5. Lyapunov stability analysis
		4.1.6. Simulation tests
	4.2. Nonlinear optimal control of 6-phase VSI-PMSM
		4.2.1. Outline
		4.2.2. Dynamic model of the VSI-fed six-phase PMSM
		4.2.3. Differential flatness of the VSI-fed six-phase PMSM
		4.2.4. Linearization of the 6-phase VSI-fed PMSM
		4.2.5. Lyapunov stability analysis
		4.2.6. Simulation tests
Chapter 5: Control of energy conversion chains based on distributed PMSMs
	5.1. Control of wind-turbine and PMSM-based electric power unit
		5.1.1. Outline
		5.1.2. Dynamic model of the twin turbine power generation unit
		5.1.3. Differential flatness of the wind power unit
		5.1.4. Linearization of the twin-turbine wind power unit
		5.1.5. Design of an H-infinity nonlinear feedback controller
		5.1.6. The nonlinear H-infinity control
		5.1.7. Lyapunov stability analysis
		5.1.8. Simulation tests
	5.2. Control of a PMSM-driven gas-compression Unit
		5.2.1. Outline
		5.2.2. Dynamics of PMSM-actuated gas-compressors
		5.2.3. Differential flatness of the PMSM gas compressor
		5.2.4. Dynamics of connected PMSM gas-compressors
		5.2.5. Linearization of the connected gas-compressors
		5.2.6. Differential flatness of the interconnected gas-compressors
		5.2.7. Design of an H-infinity nonlinear feedback controller
		5.2.8. Lyapunov stability analysis
		5.2.9. Simulation tests
Chapter 6: Control of energy conversion chains based on Induction Machines
	6.1. Control of the VSI-fed three-phase induction motor
		6.1.1. Outline
		6.1.2. Dynamic model of the induction motor
		6.1.3. Dynamic model of the three-phase voltage source inverter
		6.1.4. Dynamic model of the VSI-fed induction motor
		6.1.5. Linearization and control of the VSI-fed induction motor
		6.1.6. Lyapunov stability analysis
		6.1.7. Simulation tests
	6.2. Control of an induction motor-driven gas compressor
		6.2.1. Outline
		6.2.2. Dynamics of the IM-driven gas-compressor
		6.2.3. Differential flatness of the IM-driven gas-compressor
		6.2.4. Linearization of the IM-driven gas compressor
		6.2.5. Design of an H-infinity nonlinear feedback controller
		6.2.6. Lyapunov stability analysis
		6.2.7. Simulation tests
Chapter 7: Control of multi-phase machines in gas processing and power units
	7.1. Control of gas-compressors actuated by 5-phase PMSMs
		7.1.1. Outline
		7.1.2. Dynamics of gas-compressor driven by 5-phase IM
		7.1.3. Differential flatness of gas-compressor with 5-phase IM
		7.1.4. Linearization of gas-compressor with 5-phase IM
		7.1.5. Design of an H-infinity nonlinear feedback controller
		7.1.6. Lyapunov stability analysis
		7.1.7. Simulation tests
	7.2. Control of 6-phase IM in renewable energy units
		7.2.1. Introduction
		7.2.2. Dynamic model of the 6-phase dual star induction generator
		7.2.3. Differential flatness of the 6-phase DSIG
		7.2.4. Linearization of the 6-phase DSIG
		7.2.5. The nonlinear H-infinity control
		7.2.6. Lyapunov stability analysis
		7.2.7. Simulation tests
Chapter 8: Control of spherical PM motors and switched reluctance motors
	8.1. Control of spherical permanent magnet synchronous motors
		8.1.1. Outline
		8.1.2. Dynamic model of the permanent magnet spherical motor
		8.1.3. Linearization of the PM spherical motor
		8.1.4. Nonlinear optimal controller and stability properties
		8.1.5. Flatness-based control implemented in successive loops
		8.1.6. Simulation tests
		8.1.7. Multi-loop flatness-based control of spherical motors
	8.2. Control of switched reluctance motors for electric traction
		8.2.1. Outline
		8.2.2. Dynamic model of the Switched Reluctance machine
		8.2.3. Linearization for the switched reluctance machine
		8.2.4. Design of an H-infinity nonlinear feedback controller
		8.2.5. The nonlinear H-infinity control
		8.2.6. Lyapunov stability analysis
		8.2.7. Simulation tests
	8.3. Adaptive control for switched reluctance motors
		8.3.1. Outline
		8.3.2. Canonical form of the switched reluctance motor
		8.3.3. Adaptive fuzzy control of the SRM using output feedback
		8.3.4. Lyapunov stability analysis
		8.3.5. Simulation tests
Chapter 9: Control of traction and powertrains in EVs and HEVs
	9.1. Control of multi-phase motors in the EV traction system
		9.1.1. Outline
		9.1.2. Dynamic model of the five-phase induction motor
		9.1.3. Differential flatness of the five-phase IM
		9.1.4. Linearization of the five-phase IM
		9.1.5. The nonlinear H-infinity control
		9.1.6. Lyapunov stability analysis
		9.1.7. Simulation tests
	9.2. Control of HEV power chains
		9.2.1. Outline
		9.2.2. Dynamic model of the HEV power supply / traction system
		9.2.3. Linearization of HEV powertrains
		9.2.4. Design of an H-infinity nonlinear feedback controller
		9.2.5. Lyapunov stability analysis
		9.2.6. Differential flatness properties of the HEV’s powertrain
		9.2.7. Simulation tests
Chapter 10: Control of renewable power units and heat management units
	10.1. Control of residential microgrids
		10.1.1. Outline
		10.1.2. Dynamic model of the hybrid residential microgrid
		10.1.3. Linearization of residential microgrids
		10.1.4. Lyapunov stability analysis
		10.1.5. Differential flatness of residential microgrids
		10.1.6. Simulation tests
	10.2. Control of heat pumps in electric vehicles
		10.2.1. Outline
		10.2.2. Dynamic model of the heat pump
		10.2.3. Nonlinear optimal control for EV heat pumps
		10.2.4. Stability proof
		10.2.5. Simulation tests
Epilogue
Glossary
References
Index