A simple current control strategy for a four-leg indirect matrix converter

In this paper the experimental validation of a predictive current control strategy for a four-leg indirect matrix converter is presented. The four-leg indirect matrix converter can supply energy to an unbalanced three-phase load whilst providing a path for the zero sequence load. The predictive current control technique is based on the optimal selection among the valid switching states of the converter by evaluating a cost function, resulting in a simple approach without the necessity for modulators. Furthermore, zero dc-link current commutation is achieved by synchronizing the state changes in the input stage with the application of a zero voltage space vector in the inverter stage. Simulation results are presented and the strategy is experimentally validated using a laboratory prototype

To develop an efficient variable speed compressor motor system

This research presents a proposed new method of improving the energy efficiency of a Variable Speed Drive (VSD) for induction motors. The principles of VSD are reviewed with emphasis on the efficiency and power losses associated with the operation of the variable speed compressor motor drive, particularly at low speed operation.The efficiency of induction motor when operated at rated speed and load torque is high. However at low load operation, application of the induction motor at rated flux will cause the iron losses to increase excessively, hence its efficiency will reduce dramatically. To improve this efficiency, it is essential to obtain the flux level that minimizes the total motor losses. This technique is known as an efficiency or energy optimization control method. In practice, typical of the compressor load does not require high dynamic response, therefore improvement of the efficiency optimization control that is proposed in this research is based on scalar control model.In this research, development of a new neural network controller for efficiency optimization control is proposed. The controller is designed to generate both voltage and frequency reference signals imultaneously. To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. The simulation of the proposed controller for variable speed compressor is presented. The results obtained clearly show that the efficiency at low speed is significant increased. Besides that the speed of the motor can be maintained. Furthermore, the controller is also robust to the motor parameters variation. The simulation results are also verified by experiment

Induction Motors

AC motors play a major role in modern industrial applications. Squirrel-cage induction motors (SCIMs) are probably the most frequently used when compared to other AC motors because of their low cost, ruggedness, and low maintenance. The material presented in this book is organized into four sections, covering the applications and structural properties of induction motors (IMs), fault detection and diagnostics, control strategies, and the more recently developed topology based on the multiphase (more than three phases) induction motors. This material should be of specific interest to engineers and researchers who are engaged in the modeling, design, and implementation of control algorithms applied to induction motors and, more generally, to readers broadly interested in nonlinear control, health condition monitoring, and fault diagnosis

New control structure for high voltage fields

In electrostatic painting, a high voltage is applied to the paint, attracting the paint particles toward a grounded work object, drastically increasing the efficiency of the painting process. However, combining high voltage and highly flammable paint is a potential hazard that is reduced by an automatic fire extinguishing system and strict controller limits defined by safety standards. The thesis investigates alternative controller strategies attempting to improve the performance of ABB's high-voltage control system. The dynamics of electrostatic gas discharge, or corona discharge, is studied to estimate the relation between the applied voltage and the corona current passing through the electrostatic field. However, given the data available for the real-time system, the estimation problem is concluded to be structurally unidentifiable, resulting in the estimators not converging to the actual state of the system. Despite that, a simple estimator is utilized in a current limiting controller. This controller is activated when the system leaves its normal working area. Simulation results indicate that this controller can decrease the amount of unnecessary safety-related stops and reduce the reaction time for actual safety-hazard incidents. Furthermore, a data-driven approach is selected to model and create a controller for the system generating the high-voltage output. The model of the dynamics of the high-voltage system is created using neural networks and open-loop high-resolution data collected with a self-developed data acquisition program. Then, the estimated model is used in a reinforcement learning environment to create a theoretically optimal controller valid for the entire nonlinear workspace. Due to limited computational resources, and errors in the data, the thesis presents a lower-resolution proof of concept for both the neural network model and controller. Additionally, the thesis presents a basis of knowledge on ABB's electrostatic painting system, featuring recommendations and suggestions for future work.In electrostatic painting, a high voltage is applied to the paint, attracting the paint particles toward a grounded work object, drastically increasing the efficiency of the painting process. However, combining high voltage and highly flammable paint is a potential hazard that is reduced by an automatic fire extinguishing system and strict controller limits defined by safety standards. The thesis investigates alternative controller strategies attempting to improve the performance of ABB's high-voltage control system. The dynamics of electrostatic gas discharge, or corona discharge, is studied to estimate the relation between the applied voltage and the corona current passing through the electrostatic field. However, given the data available for the real-time system, the estimation problem is concluded to be structurally unidentifiable, resulting in the estimators not converging to the actual state of the system. Despite that, a simple estimator is utilized in a current limiting controller. This controller is activated when the system leaves its normal working area. Simulation results indicate that this controller can decrease the amount of unnecessary safety-related stops and reduce the reaction time for actual safety-hazard incidents. Furthermore, a data-driven approach is selected to model and create a controller for the system generating the high-voltage output. The model of the dynamics of the high-voltage system is created using neural networks and open-loop high-resolution data collected with a self-developed data acquisition program. Then, the estimated model is used in a reinforcement learning environment to create a theoretically optimal controller valid for the entire nonlinear workspace. Due to limited computational resources, and errors in the data, the thesis presents a lower-resolution proof of concept for both the neural network model and controller. Additionally, the thesis presents a basis of knowledge on ABB's electrostatic painting system, featuring recommendations and suggestions for future work

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

Nonlinear adaptive control for robust wide speed range operation of IPMSM drives

Various applications, including robotics, spindle drives, machine tools, etc. rely on accurate, reliable controllers to deliver the required drive performance. With recent advances in magnetic materials and semiconductor technology, machines such as the permanent magnet synchronous machine (PMSM) family of ac drives have seen a rise in popularity, owing to the high power density, efficiency and relative longevity as compared to conventional ac motors. In particular, interior permanent magnet synchronous machines (IPMSM) are characterized by all the features of the PMSM family, with the additional possibility of improved efficiency due to rotor construction, making them ideal for critical applications with high performance demands. Notably, despite the advantageous aspects of PMSM motors in general, control of this class of ac machines is complex if full performance potential is to be realized. In order to achieve optimal efficiency while permitting wide speed range operation, it is crucial to design controllers that are capable of delivering this high performance. Due to the nonlinearity of magnetic flux distribution during operation, the parameters of the PMSM may vary significantly. Thus, a high performance controller must be capable of optimizing efficiency while maintaining excellent response characteristics from set-point or loading variations. As a result of the nonlinear flux distribution caused by rotor/stator magnetic field interactions, direct control of PMSM in the stator reference frame is not possible as the level of mathematical complexity renders it infeasible. Expression of the PMSM stator variables in the rotating rotor reference frame permits the effective decoupling of machine variables into velocity and torque control components. This is roughly analogous to separately excited direct current (DC) motors, where control of the rotor speed (field magnetization) and shaft torque (armature current) are decoupled as a function of the design. Analysis of the PMSM model in the rotating reference frame shows that the “d” and “q” axis currents are principally responsible for indirect air gap flux control and developed shaft torque, respectively. Traditional linear type control techniques based on proportional-integral-derivative (PID) controllers are able to achieve moderate success in controlling the PMSM family. The performance achieved is however typically within a narrow operational band and without the ability to adapt to parametric variation or optimize efficiency. This restriction makes PID type controllers non-ideal for more demanding applications that require highly accurate control and high efficiency regardless of load, temperature, machine age or operating environment. Therefore, this thesis presents a robust nonlinear control algorithm utilizing an adaptive back-stepping technique with flux control for optimizing developed torque and improved operational range. Further, global asymptotic stability of the proposed controller is assured through Lyapunov’s stability criterion in conjuncture with criterion supported by Barbalat’s lemma. The proposed control algorithm ensures that the machine operates at precise command speeds, coping with system uncertainties and disturbances, while reducing losses and enabling operation over a wide speed range. Simulation of the proposed system is carried out in MATLAB/Simulink, as well as in a cosimulation environment utilizing MATLAB/Simulink and PSIM. The first scenario implements an ideal mathematical system model with the controller in Simulink; whereas the second scenario uses PSIM to host the dynamic system model, with MATLAB/Simulink hosting the controller. This co-simulation permits rapid, accurate system analysis, by employing more accurate software models for switching elements, synchronous machine and any reactive elements not reflected in the basic mathematical model. Simulation results from both methods indicate excellent performance and robust operation, with excellent disturbance rejection. Real-time implementation of the system is realized utilizing the DS1104 digital signal processor (DSP) in conjuncture with an IPMSM commutated by a three-phase two-level insulated gate bipolar transistor (IGBT) inverter, with a direct current (DC) generator as dynamic load. Performance of the proposed controller have been verified through experimental implementation for a range of operating conditions

Energy Shaping Control for Stabilization of Interconnected Voltage Source Converters in Weakly-Connected AC Microgrid Systems

With the ubiquitous installations of renewable energy resources such as solar and wind, for decentralized power applications across the United States, microgrids are being viewed as an avenue for achieving this goal. Various independent system operators and regional transmission operators such as Southwest Power Pool (SPP), Midcontinent System Operator (MISO), PJM Interconnection and Electric Reliability Council of Texas (ERCOT) manage the transmission and generation systems that host the distributed energy resources (DERs). Voltage source converters typically interconnect the DERs to the utility system and used in High voltage dc (HVDC) systems for transmitting power throughout the United States. A microgrid configuration is built at the 13.8kV 4.75MVA National Center for Reliable Energy Transmission (NCREPT) testing facility for performing grid-connected and islanded operation of interconnected voltage source converters. The interconnected voltage source converters consist of a variable voltage variable frequency (VVVF) drive, which powers a regenerative (REGEN) load bench acting as a distributed energy resource emulator. Due to the weak-grid interface in islanded mode testing, a voltage instability occurs on the VVVF dc link voltage causing the system to collapse. This dissertation presents a new stability theorem for stabilizing interconnected voltage source converters in microgrid systems with weak-grid interfaces. The new stability theorem is derived using the concepts of Dirac composition in Port-Hamiltonian systems, passivity in physical systems, eigenvalue analysis and robust analysis based on the edge theorem for parametric uncertainty. The novel stability theorem aims to prove that all members of the classes of voltage source converter-based microgrid systems can be stabilized using an energy-shaping control methodology. The proposed theorems and stability analysis justifies the development of the Modified Interconnection and Damping Assignment Passivity-Based Control (Modified IDA-PBC) method to be utilized in stabilizing the microgrid configuration at NCREPT for mitigating system instabilities. The system is simulated in MATLAB/SimulinkTM using the Simpower toolbox to observe the system’s performance of the designed controller in comparison to the decoupled proportional intergral controller. The simulation results verify that the Modified-IDA-PBC is a viable option for dc bus voltage control of interconnected voltage source converters in microgrid systems

AVERAGE-VALUE MODELING OF HYSTERESIS CURRENT CONTROL IN POWER ELECTRONICS

Hysteresis current control has been widely used in power electronics with the advantages of fast dynamic response under parameter, line and load variation and ensured stability. However, a main disadvantage of hysteresis current control is the uncertain and varying switching frequency which makes it difficult to form an average-value model. The changing switching frequency and unspecified switching duty cycle make conventional average-value models based on PWM control difficult to apply directly to converters that are controlled by hysteresis current control. In this work, a new method for average-value modeling of hysteresis current control in boost converters, three-phase inverters, and brushless dc motor drives is proposed. It incorporates a slew-rate limitation on the inductor current that occurs naturally in the circuit during large system transients. This new method is compared with existing methods in terms of simulation run time and rms error. The performance is evaluated based on a variety of scenarios, and the simulation results are compared with the results of detailed models. The simulation results show that the proposed model represents the detailed model well and is faster and more accurate than existing methods. The slew-rate limitation model of hysteresis current control accurately captures the salient detail of converter performance while maintaining the computational efficiency of average-value models. Validations in hardware are also presented