http://ieeexplore.ieee.org/iel5/5610941/5624686/05624745.pdf

Power electronics

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 today's 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 Control in Power Electronics and Drives

This paper addresses to some of the latest contributions on the application of Finite Control Set Model Predictive Control (FCS-MPC) in Power Electronics. In FCS-MPC , the switching states are directly applied to the power converter, without the need of an additional modulation stage. The paper shows how the use of FCS-MPC provides a simple and efficient computational realization for different control objectives in Power Electronics. Some applications of this technology in drives, active filters, power conditioning, distributed generation and renewable energy are covered. Finally, attention is paid to the discussion of new trends in this technology and to the identification of open questions and future research topics.

State of the Art of Finite Control Set Model Predictive Control in Power Electronics

Model predictive control (MPC) is a very attractive solution for controlling power electronic converters. The aim of this paper is to present and discuss the latest developments in MPC for power converters and drives, describing the current state of this control strategy and analyzing the new trends and challenges it presents when applied to power electronic systems. The paper revisits the operating principle of MPC and identifies three key elements in the MPC strategies, namely the prediction model, the cost function, and the optimization algorithm. This paper summarizes the most recent research concerning these elements, providing details about the different solutions proposed by the academic and industrial communities.

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Model Predictive Control for Power Converters and Drives: Advances and Trends

The authors discuss high-voltage power conversion. Conventional series connection and three-level voltage source inverter techniques are reviewed and compared. A novel versatile multilevel commutation cell is introduced: it is shown that this topology is safer and more simple to control, and delivers purer output waveforms. The authors show how this technique can be applied to either choppers or voltage-source inverters and generalized to any number of switches.<<ETX>>

Multi-level conversion : high voltage choppers and voltage-source inverters

This paper focuses on direct torque control (DTC) for three-phase AC electric drives. A novel model predictive control scheme is proposed that keeps the motor torque, the stator flux, and (if present) the inverter's neutral point potential within given hysteresis bounds while minimizing the switching frequency of the inverter. Based on an internal model of the drive, the controller predicts several future switch transitions, extrapolates the output trajectories, and chooses the sequence of inverter switch positions (voltage vectors) that minimizes the switching frequency. The advantages of the proposed controller are twofold. First, as underlined by the experimental results in the second part of this paper, it yields a superior performance with respect to the industrial state of the art. Specifically, the switching frequency is reduced by up to 50% while the torque and flux are kept more accurately within their bounds. Moreover, the fast dynamic torque response is inherited from standard DTC. Second, the scheme is applicable to a large class of (three-phase) AC electric machines driven by inverters.

Model Predictive Direct Torque Control—Part I: Concept, Algorithm, and Analysis

For direct model predictive control with reference tracking of the converter current, we derive an efficient optimization algorithm that allows us to solve the control problem for very long prediction horizons. This is achieved by adapting sphere decoding principles to the underlying optimization problem. The proposed algorithm requires only few computations and directly provides the optimal switch positions. Since the computational burden of our algorithm is effectively independent of the number of converter output levels, the concept is particularly suitable for multi-level topologies with a large number of voltage levels. Our method is illustrated for the case of a variable speed drive system with a three-level voltage source converter.

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Multistep Finite Control Set Model Predictive Control for Power Electronics

Direct model predictive control (MPC) with reference tracking, also referred to as finite control set MPC (FCS-MPC), has gained significant attention in recent years, mainly from the academic community. Thanks to its applicability to a wide range of power electronic systems, it is considered a promising control method for such systems. However, to simplify the design, researchers frequently make choices that—often unknowingly—reduce the system performance. In this article, we discuss and analyze the factors that affect the closed-loop performance of FCS-MPC. Based on these findings, design guidelines are provided that help to maximize the system performance. To highlight the performance benefits, two case studies will be considered: the first one consists of a two-level converter and an induction machine, whereas the second one adds an $LC$ filter between the converter and the machine.

Guidelines for the Design of Finite Control Set Model Predictive Controllers

The performance of direct model predictive control (MPC) with reference tracking and long prediction horizons is evaluated through simulations, using the current control problem of a variable speed drive system with a voltage source inverter as an illustrative example. A modified sphere decoding algorithm is used to efficiently solve the optimization problem underlying MPC for long horizons. For a horizon of five and a three-level inverter, for example, the computational burden is reduced by four orders of magnitude, compared to the standard exhaustive search approach. This paper illustrates the performance gains that are achievable by using prediction horizons larger than one. Specifically, for long prediction horizons and a low switching frequency, the total harmonic distortion of the current is significantly lower than for space vector modulation, making direct MPC with long horizons an attractive and computationally viable control scheme.

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Performance of Multistep Finite Control Set Model Predictive Control for Power Electronics

This paper presents a model predictive control (MPC) approach for dc-dc boost converters. A discrete-time switched nonlinear (hybrid) model of the converter is derived, which captures both the continuous and the discontinuous conduction mode. The controller synthesis is achieved by formulating an objective function that is to be minimized subject to the model dynamics. The proposed MPC strategy, utilized as a voltage-mode controller, achieves regulation of the output voltage to its reference, without requiring a subsequent current control loop. Furthermore, a state estimation scheme is implemented that addresses load uncertainties and model mismatches. Simulation and experimental results are provided to demonstrate the merits of the proposed control methodology, which include a fast transient response and a high degree of robustness.

Tobias Geyer

Papers

Model Predictive Direct Torque Control—Part I: Concept, Algorithm, and Analysis

Multistep Finite Control Set Model Predictive Control for Power Electronics

Guidelines for the Design of Finite Control Set Model Predictive Controllers

Performance of Multistep Finite Control Set Model Predictive Control for Power Electronics

Direct Voltage Control of DC–DC Boost Converters Using Enumeration-Based Model Predictive Control