Patricio Cortes

Predictive Control in Power Electronics and Drives

Predictive control is a very wide class of controllers that have found rather recent application in the control of power converters. Research on this topic has been increased in the last years due to the possibilities of todays microprocessors used for the control. This paper presents the application of different predictive control methods to power electronics and drives. A simple classification of the most important types of predictive control is introduced, and each one of them is explained including some application examples. Predictive control presents several advantages that make it suitable for the control of power converters and drives. The different control schemes and applications presented in this paper illustrate the effectiveness and flexibility of predictive control.

Predictive Current Control of a Voltage Source Inverter

This paper presents a predictive current control method and its application to a voltage source inverter. The method uses a discrete-time model of the system to predict the future value of the load current for all possible voltage vectors generated by the inverter. The voltage vector which minimizes a quality function is selected. The quality function used in this work evaluates the current error at the next sampling time. The performance of the proposed predictive control method is compared with hysteresis and pulsewidth modulation control. The results show that the predictive method controls very effectively the load current and performs very well compared with the classical solutions

Model Predictive Control—A Simple and Powerful Method to Control Power Converters

This paper presents a detailed description of finite control set model predictive control (FCS-MPC) applied to power converters. Several key aspects related to this methodology are, in depth, presented and compared with traditional power converter control techniques, such as linear controllers with pulsewidth-modulation-based methods. The basic concepts, operating principles, control diagrams, and results are used to provide a comparison between the different control strategies. The analysis is performed on a traditional three-phase voltage source inverter, used as a simple and comprehensive reference frame. However, additional topologies and power systems are addressed to highlight differences, potentialities, and challenges of FCS-MPC. Among the conclusions are the feasibility and great potential of FCS-MPC due to present-day signal-processing capabilities, particularly for power systems with a reduced number of switching states and more complex operating principles, such as matrix converters. In addition, the possibility to address different or additional control objectives easily in a single cost function enables a simple, flexible, and improved performance controller for power-conversion systems.

Predictive Control of a Three-Phase Neutral-Point-Clamped Inverter

A new predictive strategy for current control of a three-phase neutral-point-clamped inverter is presented. The algorithm is based on a model of the system. From that model, the behavior of the system is predicted for each possible switching state of the inverter. The state that minimizes a given quality function is selected to be applied during the next sampling interval. Several compositions of are proposed, including terms dedicated to achieve reference tracking, balance in the dc link, and reduction of the switching frequency. In comparison to an established control method, the strategy presents a remarkable performance. The proposed method achieves comparable reference tracking with lower switching frequency per semiconductor and similar transient behavior. The main advantage of the method is that it does not require any kind of linear controller or modulation technique, achieving a different approach to control a power converter.

Delay Compensation in Model Predictive Current Control of a Three-Phase Inverter

When control schemes based on finite control set model predictive control are experimentally implemented, a large amount of calculations is required, introducing a considerable time delay in the actuation. This delay can deteriorate the performance of the system if not considered in the design of the controller. In this paper, the problem is described, and the solution to this issue is clearly explained using a three-phase inverter as an example. Experimental results to validate this solution are shown.

Predictive Control of Power Converters and Electrical Drives: Rodriguez/Predictive Control of Power Converters and Electrical Drives

The book starts with an introduction to the subject before the first chapter on classical control methods for power converters and drives. This covers classical converter control methods and classical electrical drives control methods. The next chapter on Model predictive control first looks at predictive control methods for power converters and drives and presents the basic principles of MPC. It then looks at MPC for power electronics and drives. The third chapter is on predictive control applied to power converters. It discusses: control of a three-phase inverter; control of a neutral point clamped inverter; control of an active front end rectifier, and; control of a matrix converter. In the middle of the book there is Chapter four Predictive control applied to motor drives. This section analyses predictive torque control of industrial machines and predictive control of permanent magnet synchronous motors. Design and implementation issues of model predictive control is the subject of the final chapter. The following topics are described in detail: cost function selection; weighting factors design; delay compensation; effect of model errors, and prediction of future references. While there are hundreds of books teaching control of electrical energy using pulse width modulation, this will be the very first book published in this new topic.

Direct Power Control of an AFE Using Predictive Control

This paper presents a new control scheme for an active front-end rectifier using model-based predictive control. The control strategy minimizes a cost function, which represents the desired behavior of the converter. Future values of currents and power are predicted using a discrete-time model. The active and reactive powers are directly controlled by selecting the optimal switching state. The main advantages of this method are that there is no need of linear current controllers, coordinates transformations or modulators. The rectifier operates with sinusoidal input currents and unity power factor. Simulation and experimental results are presented to verify the performance of the proposed power control scheme.

Predictive Torque Control of Induction Machines Based on State-Space Models

In this paper, we present a predictive control algorithm that uses a state-space model. Based on classical control theory, an exact discrete-time model of an induction machine with time-varying components is developed improving the accuracy of state prediction. A torque and stator flux magnitude control algorithm evaluates a cost function for each switching state available in a two-level inverter. The voltage vector with the lowest torque and stator flux magnitude errors is selected to be applied in the next sampling interval. A high degree of flexibility is obtained with the proposed control technique due to the online optimization algorithm, where system nonlinearities and restrictions can be included. Experimental results for a 4-kW induction machine are presented to validate the proposed state-space model and control algorithm.

Model Predictive Control of an Inverter With Output

The use of an inverter with an output LC filter allows for generation of output sinusoidal voltages with low harmonic distortion, suitable for uninterruptible power supply systems. However, the controller design becomes more difficult. This paper presents a new and simple control scheme using predictive control for a two-level converter. The controller uses the model of the system to predict, on each sampling interval, the behavior of the output voltage for each possible switching state. Then, a cost function is used as a criterion for selecting the switching state that will be applied during the next sampling interval. In addition, an observer is used for load-current estimation, enhancing the behavior of the proposed controller without increasing the number of current sensors. Experimental results under linear and nonlinear load conditions, with a 5.5-kW prototype, are presented, verifying the feasibility and good performance of the proposed control scheme.

LC

This paper presents a model predictive current control algorithm that is suitable for multilevel converters and its application to a three-phase cascaded H-bridge inverter. This control method uses a discrete-time model of the system to predict the future value of the current for all voltage vectors, and selects the vector which minimizes a cost function. Due to the large number of voltage vectors available in a multilevel inverter, a large number of calculations are needed, making difficult the implementation of this control in a standard control platform. A modified control strategy that considerably reduces the amount of calculations without affecting the systems performance is proposed. Experimental results for five- and nine-level inverters validate the proposed control algorithm.