Search

Complex energy systems can effectively integrate renewable energy sources such as wind and solar power into the information network and coordinate the operation of renewable energy sources to ensure its reliability. In the voltage source converter-based high voltage direct current system, the traditional vector control strategy faces some challenges, such as difficulty in PI parameters tuning and multiobjective optimizations. To overcome these issues, a finite control set model predictive control-based advanced control strategy is proposed. Based on the discrete mathematical model of the grid-side voltage source converter, the proposed strategy optimizes a value function with errors of current magnitudes to predict switching status of the grid-side converter. Moreover, the abilities of the system in resisting disturbances and fault recovery are enhanced by compensating delay and introducing weight coefficients. The complex energy system in which the wind power is delivered by the voltage source converter-based high voltage direct current system is modeled by Simulink and simulation results show that the proposed strategy is superior to the tradition PI control strategy under various situations, such as wind power fluctuation and fault occurrences.

Thesis in the scope of the PhD in Electrical and Computer Engineering, specialization in Energy, presented to the Faculty of Sciences and Technology of the University of Coimbra. Nowadays, several types of electric motors are utilized in industrial applications, namely induction motors (IMs), permanent magnet synchronous motors (PMSMs) and synchronous reluctance motors (SynRMs). Owing to the high cost of PMSMs and due to the rotor losses of IMs, SynRMs can be considered an ideal choice for some applications. These motors have a simple structure, are robust, and have a low cost due to the absence of permanent magnets or windings in the rotor. To exploit the advantages of SynRM drives, an adequate control strategy is essential. In recent times, due to the development of fast and cheap microprocessors and FPGAs, the category of control strategies known as finite control set model predictive control (FCS-MPC) has attracted significant attention in both academia and industry. FCS-MPC has as main advantages, an intuitive and simple implementation, very fast dynamic response and the ability to tackle several constraints in a straightforward manner. Due to these advantages, it can be considered an ideal alternative to field-oriented control (FOC) and direct torque control (DTC) in high performance motor drives. In spite of its advantages, FCS-MPC has been barely proposed for the control of SynRM drives, especially if we consider that some applications require the drive system to operate in the full speed range. This thesis proposes three different FCS-MPC control strategies for high-performance SynRM drives. The first two control strategies combine the concepts of active flux and torque control in order to operate the SynRM in the constant torque region. The first control strategy, baptized as predictive active flux and torque control (PAFTC), regulates the active flux and the electromagnetic torque of the SynRM in an independent manner. It follows the standard implementation steps of FCS-MPC, namely by predicting the values of the state variables for all possible switching states of the inverter, and by using a cost function with a weighting factor which needs to be tuned. A second control approach, known as simplified PAFTC (S-PAFTC), is a simplified version of the PAFTC in the sense that the predictions of the state variables are replaced by the calculation of an equivalent reference voltage, performed only once in a sampling period. This procedure leads to a smaller computational time, when the control strategy is implemented in a digital control platform, and to the use of a cost function without any weighting factor, overcoming one of the challenging tasks in classical FCS-MPC strategies which is the choice of the optimal value(s) for the weighting factor(s). The simulation and experimental results obtained with these control strategies demonstrate the very good steady-state and dynamic response of the SynRM drive in the constant torque region. With the aim to safely operate the SynRM drive in the full speed range, while ensuring at the same time the exploitation of all its potentialities and limits, including its operation with optimal efficiency, a third control strategy, known as predictive load angle and stator flux control (PLASFC), is proposed for SynRM drives. The PLASFC, implemented in a stator flux reference frame, regulates the stator flux and the load angle of the SynRM in an independent manner. While the stator flux regulation is straightforward, the torque is regulated indirectly by controlling the load angle, bringing benefits in terms of a smooth transition between the different motor operating regions. Similarly to the S-PAFTC strategy, an equivalent reference voltage is calculated instead of predicting the values of the motor state variables for all possible switching states of the inverter, and the cost function does not include any weighting factor. In the PLASFC strategy, the SynRM is easily operated in the full speed range: constant torque region (including zero speed), constant power region and constant load angle region, the last two being part of what is usually known as field-weakening (FW) region. With this control strategy, the voltage, current and load angle limits are easily exploited by simple mathematical relations and saturation blocks. In addition, a loss minimization algorithm is developed and incorporated in this control strategy thus allowing to operate the SynRM with minimum copper losses for a given load torque. Furthermore, to improve the performance of the control system, some parameters namely the motor apparent inductances, are estimated online. Several simulation and experimental results presented demonstrate the excellent steady-state and dynamic performance of the SynRM drive when operating with the PLASFC strategy, thus clearly demonstrating the benefits of using FCS-MPC strategies in the field of electric drives in general and SynRM drives in particular. Atualmente, diversos tipos de motores elétricos são utilizados em aplicações industriais, nomeadamente os motores de indução (IMs), os motores síncronos de ímanes permanentes (PMSMs) e os motores síncronos de relutância (SynRMs). Devido ao elevado custo dos PMSMs e às elevadas perdas no rotor dos motores de indução, os SynRMs podem ser considerados a escolha ideal para algumas aplicações. Estes motores possuem uma estrutura simples, são robustos e têm um baixo custo de fabrico devido à ausência de ímanes permanentes ou enrolamentos no rotor. De modo a explorar toda as vantagens dos acionamentos baseados em SynRMs, é essencial uma estratégia de controlo adequada. Recentemente, em virtude do desenvolvimento de microprocessadores e FPGAs mais rápidos e económicos, a categoria de controlo conhecida como controlo preditivo baseado em modelos de estados finitos (FCS-MPC) tem despertado um especial interesse no mundo académico e na indústria. O FCS-MPC tem várias vantagens, tais como uma implementação simples e intuitiva, uma rápida resposta dinâmica e a possibilidade de considerar várias restrições de uma forma direta. Devido a estas vantagens, o FCS-MPC pode ser considerado uma alternativa ideal ao controlo por orientação de campo (FOC) e ao controlo direto de binário (DTC) em acionamentos de alto desempenho. Apesar das suas vantagens, o FCS-MPC ainda tem sido pouco utilizado no controlo de acionamentos baseados em SynRMs, especialmente se considerar que algumas aplicações necessitam que o acionamento opere em toda a gama de velocidades. Esta dissertação propõe três estratégias de controlo FCS-MPC para acionamentos de alto desempenho baseados num SynRM. As duas primeiras estratégias de controlo combinam os conceitos do fluxo ativo e do controlo de binário, de modo a operar o SynRM na região de binário constante. A primeira estratégia, denominada controlo preditivo do fluxo ativo e de binário (PAFTC), regula o fluxo ativo e o binário eletromagnético do SynRM de forma independente. A estratégia PAFTC segue a estrutura padrão do FCS-MPC, uma vez que prevê os valores futuros das variáveis de estado para todos os estados de comutação possíveis do inversor, e utiliza uma função de custo com um peso que necessita de ser sintonizado. Uma segunda abordagem de controlo, denominada PAFTC simplificado (S-PAFTC), é uma versão simplificada do PAFTC uma vez que o cálculo das predições das variáveis de estado é substituído pelo cálculo das tensões de referência equivalentes, realizado apenas uma vez num período de amostragem. Esta estratégia de controlo possui um tempo de execução menor, quando implementada numa plataforma de controlo digital e, faz uso de uma função custo sem qualquer peso, ultrapassando um grande desafio das estratégias FCS-MPC clássicas, que é a escolha do(s) valor(es) ótimo(s) para o(s) peso(s). Os resultados de simulação e experimentais obtidos com estas estratégias de controlo mostram excelente desempenho do acionamento baseado no SynRM na região de binário constante, tanto em regime permanente como em regime dinâmico. Com o objetivo de operar o acionamento baseado no SynRM de forma segura em toda a gama de velocidades, e ao mesmo tempo assegurar que todas as suas potencialidades e limites são explorados, incluindo uma operação com eficiência ótima, uma terceira estratégia de controlo, conhecida como controlo preditivo do ângulo de carga e fluxo estatórico (PLASFC), é proposta para acionamentos baseados em SynRMs. A estratégia de controlo PLASFC, implementada no referencial do fluxo estatórico, controla o fluxo estatórico e o ângulo de carga do SynRM de forma independente. Enquanto que a regulação do fluxo estatórico é direta, a regulação do binário é realizado de forma indireta através do controlo do ângulo de carga, o que conduz a uma transição suave entre as diferentes regiões de operação do motor. Tal como na estratégia S-PAFTC, as tensões de referência equivalentes são calculadas ao invés de prever os valores futuros das variáveis de estado do motor para todas os estados de comutação do inversor possíveis, e a função custo não inclui qualquer peso. Na estratégia PLASFC, o SynRM é facilmente operado em toda a gama de velocidades: região de binário constante (incluindo a velocidade zero), região de potência constante e região de ângulo de carga constante, sendo que as últimas duas regiões pertencem à região normalmente designada por região de campo enfraquecido (FW). Com esta estratégia de controlo, os limites de tensão, corrente e ângulo de carga são facilmente explorados através de relações matemáticas simples e blocos de saturação. Adicionalmente, um algoritmo de minimização de perdas é desenvolvido e incorporado nesta estratégia de controlo, permitindo que o SynRM opere com perdas no cobre mínimas para um dado binário de carga. Além disso, para melhorar o desempenho do sistema de controlo, alguns parâmetros tais como as indutâncias aparentes do motor são estimadas em tempo real. Por fim, são apresentados múltiplos resultados de simulação e experimentais que demonstram um excelente desempenho do acionamento baseado no SynRM quando operado através da estratégia PLASFC tanto em regime permanente quanto em regime dinâmico, demonstrando claramente os benefícios da utilização das estratégias FCS-MPC no campo dos acionamentos elétricos em geral e, particularmente, nos acionamentos baseados em SynRMs.

This paper presents a predictive controller that simultaneously controls the position, speed and the current of PMSM. The controller is based on finite control set model predictive control approach. Motion profile generator is used for the generation of reference signals. Signals generated there enter into the controller and act as feedforward signals that are evaluated inside of a cost function with other predictions. Measured position is used as a feedback and the speed and load torque are estimated by Kalman filter. The control is formulated in the dq coordinate frame. Simulation results show that the performance of the proposed position controller is significantly improved by using the proposed feedforward terms in the cost function when comparing to the cost function without these terms. The controller with improved cost function was also experimentally verified with Texas Instruments DSP.

This paper presents a finite control set model predictive control (FCS-MPC) based shunt active harmonic filter (SAHF) for power quality improvement. A detailed mathematical model of a SAHF is considered and used with the FCS-MPC algorithm for future prediction. The reference currents required for harmonic mitigation and reactive power compensation are generated using p-q theory. The two step ahead reference values required for compensating calculation delay in the FCS-MPC algorithm are obtained by using vector angle method. The simulation results present the compensation capabilities of the proposed SAHF and its control. The performance of the proposed system is evaluated for steady state and transient conditions. The influence of model parameter errors on the performance of the controller is analyzed by considering the total harmonic distortion (THD) of the source current and the absolute reference tracking error of the filter current as a measure to evaluate its robustness.

This paper proposes an improved model predictive control based on novel error correction between reference and predicted current. The proposed control strategy introduces novel error correction between reference and predicted current to improve robustness and steady-state performance of the system. The control coefficient is computed by the error between the kth instant and the (k-1)th instant without trial, and its range is limited by the Lyapunov stability theorem. Moreover, it modifies the control law of the conventional finite control set model predictive control to reduce the computational burden. The encouraging performances are tested under a single-phase voltage source rectifier. The simulated and experimental results demonstrate that the proposed control strategy not only offers good robustness but also leads to better steady-state performance while retaining fast dynamic response.

Due to its fault tolerance, a multiphase brushless direct current (BLDC) motor can meet high reliability demand for application in electric vehicles. The voltage-source inverter (VSI) supplying the motor is subjected to open circuit faults. Therefore, it is necessary to design a fault-tolerant (FT) control algorithm with an embedded fault diagnosis (FD) block. In this paper, finite control set-model predictive control (FCS-MPC) is developed to implement the fault-tolerant control algorithm of a five-phase BLDC motor. The developed control method is fast, simple, and flexible. A FD method based on available information from the control block is proposed; this method is simple, robust to common transients in motor and able to localize multiple open circuit faults. The proposed FD and FT control algorithm are embedded in a five-phase BLDC motor drive. In order to validate the theory presented, simulation and experimental results are conducted on a five-phase two-level VSI supplying a five-phase BLDC motor.

This paper proposes the Finite control set Model Predictive Control (FCS-MPC) with delay compensation for three-phase threelevel T-Type NPC inverter (T-Type NPC) of grid-connected photovoltaic systems (PV). The proposed FCS-MPC controls the objectives: current tracking control, DC-link capacitor voltage balance, the reduction of switching frequency to ensure issues of the power quality and improve the efficiency of grid-connected of PV system. The cost function of the proposed FCS-MPC uses the 27 possible switching states generated by TType NPC, the optimal switching state is selected in each sampling time that minimizes the cost function. The proposed FCS-MPC has also proposed the delay compensation with two-step prediction horizon at time k+2 to reduce the total harmonic distortion (THD) of the grid current. The proposed FCS-MPC is verified by using Matlab/Simulink.

In power electronics, the $\ell _1$ -norm (instead of the squared $\ell _2$ -norm) is often used in the objective function of model predictive controllers (MPCs) with reference tracking. Although the $\ell _1$ -norm is preferred for its computational simplicity, it might lead to a performance deterioration and closed-loop instability. This paper analyzes the root cause for this and discusses the benefits of using the $\ell _2$ -norm instead. Given the theoretical nature of this paper, a power electronics-oriented case study is employed to visualize and exemplify—through examples and simulations—the mathematical concepts and arguments presented. To this end, a variable speed drive system with a three-level voltage-source inverter serves as an illustrative example to clearly demonstrate the effectiveness of using the $\ell _2$ -norm.

The paper introduces an examination of finite control set model predictive current control for five-leg voltage source inverter. A Matlab/Simulink model for the of finite control set model predictive current control based on cost function reduction, with load current limitation as a new control algorithm approach. The algorithm chooses one from 32 switching states that produce least error between the desired currents and the predicted currents; the algorithm applies the selected switching control signals as a command to the inverter switches. The proposed algorithm also excludes any switching state that gives currents above the desired values. Subsequently the system response is improved with the reduction of overshoots and deviations from reference. The robustness of the model is tested by applying balanced reference currents with unbalanced load, and a step change in reference currents.

Model predictive control (MPC) has emerged as a promising control technique for power electronic applications due to its own features, mainly, handling of multi-variables, constraints, fast dynamic response. Among the MPC families, finite control set MPC has become one of the most popular strategies since it takes the switching nature of the power converter. The switches or voltage levels can be directly incorporated in the control formulation as manipulable control-inputs, and thus, no modulator is required. An optimal control problem is formulated using a cost function that forecasts the future system behavior over a finite prediction horizon. The standard optimization process to obtain the optimal control-input is the exhaustive search algorithm (ESA). To date, most of the research is limited to horizon one only (single-step MPC). Recently, it has been shown that increasing horizon length greater than one (multistep MPC), has significant benefits in the steady-state performance when compared to single-step MPCs. However, it poses a high computational burden, and thus, its practical implementation becomes challenging. The aim of this thesis is to study the use of multistep MPC for power electronics systems and electrical drives. The focus is on technical and theoretical issues regarding the optimization process that considers a computationally efficient optimizer namely sphere decoding algorithm (SDA). Moreover, a suitable MPC formulation which includes the full steady-state information (e.g., currents and voltages) is adopted, which is, in fact, a formal MPC approach used in control theory. Special attention is given to a crucial and so far unsolved computational issue faced by the SDA during the transient operation of the system. If not properly addressed, it may have a detrimental effect on the system operation. To solve this issue, an efficient preconditioning approach to the SDA is proposed that exploits the quadratic formulation of the optimal control problem. The outcome of this research is evidence of the potential for multistep MPC in power electronics systems and electrical drives. The theoretical and practical proposals in this thesis allow the multistep MPC to govern power converters and electrical drives over the whole operating conditions of the system with a fast dynamic response, reduced harmonic distortion, and higher efficiency, which enables it as a viable and attractive control alternative for power electronics applications.

Esse artigo propoe o estudo do controle preditivo baseado em modelo de conjunto de acoes de controle finito applicado a um processo nao baseado em eventos. Uma fundamentacao teorica e fornecida, apresentando os pros e contras da tecnica de controle. Algumas melhorias a estrategia convencional sao propostas, como variacao dinâmica do conjunto. Resultados de simulacao sao apresentados para corroborar a teoria desenvolvida.

The model predictive control is a set of algorithms which uses the dynamical model of controlled system to predict the future systems responses. Nowadays, the nonlinear finite control set model predictive control (FCS-MPC) is a popular technique for control of induction motor drives. The FCS-MPC enables accurate and high-dynamic control of the induction motor currents, rotational speed, torque etc. with respect to system constraints (e.g. urrent/voltage limitations). The main drawbacks of FCS-MPC algorithms are their computational requirements which reduce FCS-MPC prediction horizon and its applications. Our paper is focused on the FPGA accelerator of FCS-MPC of induction motor extended by the three phase inverter model with dead-times and voltage drops. These inverter nonlinear effects play important role especially in nonnominal drive conditions (e.g. low speeds).

This paper proposes an error-voltage based open-switch fault diagnosis strategy for matrix converter (MC). A finite control set model predictive control (FCS-MPC) method is used to operate the MC. The MC system performances under normal operation and under a single open-switch fault operation are analyzed. A fault diagnosis strategy has also been implemented in two steps. First, the faulty phase is detected and identified based on a comparison of the reference and estimated output line-to-line voltages. Then, the faulty switch is located by considering the switching states of the faulty phase. The proposed fault diagnosis method is able to locate the faulty switch accurately and quickly without additional voltage sensors. Simulation and experimental results are presented to demonstrate the feasibility and effectiveness of the proposed strategy

This work presents a new Finite Control Set Model Predictive Control (FCS-MPC) strategy based on an input reference tracking. The control structure admits a closed-loop representation featuring a linear dynamic and a perturbation term. Thus, the stability and the design process can be carried out by means of standard control methods. Besides, it reduces the computational burden because the minimization process does not consider the output predictions. In this work, the linear dynamic is included by designing an integral state-feedback linear controller. In addition, an offline optimization is proposed to find the optimal input which is applied in the next sampling instant. Finally, the results show that the proposed approach can lead to unbiased reference tracking even under severe parameters mismatch.

Finite Control Set Model Predictive Control (FCS-MPC) allows to deal with non-linearities of the system and obtain a fast dynamic response. Therefore FCS-MPC is a good alternative to govern complex power converters or when fast transient operation is required. A problem about the implementation of FCS-MPC is the computational cost, which is bigger for multilevel converters. This paper proposed a new method to implement FCS-MPC reducing the necessary iterations in a 3-phase 4-level Flying Capacitor converter. Simulation results show that the proposed FCS-MPC strategy produces an effective control of the load current, while keeping balanced capacitor voltages with lower necessary iterations.

© 2017 IEEE. The finite-control-set model predictive direct torque control (FCS-MPDTC) is a novel and promising control scheme for permanent magnet synchronous motors (PMSMs). An important feature of FCS-MPDTC is that the eight possible voltage space vectors or switching combinations of the power converters are directly taken into account as the control input of the system. Due to the considerable torque and flux ripples, to improve the performance of FCS-MPDTC, this paper presents an extended set of twenty modulated voltage space vectors with fixed duty ratio. To mitigate the computational burden caused by increased number of voltage space vectors, a pre-selective scheme is designed for the proposed FCS-MPDTC to filter out the impractical voltage vectors instead of evaluating all twenty voltage space vectors. The drive system efficiency of conventional direct torque control (DTC), conventional FCS-MPDTC and proposed method are investigated. A stator current minimisation scheme is also proposed to further increase the system efficiency.

This paper proposes a new Maximum Power Point Tracking (MPPT) method based on the concept of Finite Control Set Model Predictive Control (FCS-MPC) for Photovoltaic (PV) applications. The proposed method uses the measured PV current and power data from previous steps to predict the power in the next step correspondent to various possible switching configurations of the power converter. Then it applies the switching configuration which results in increase in the produced power by the PV array. Simulation results are provided to verify operation of the proposed method and compare it with the traditional Perturb and Observe (P&O) method.

Model predictive control (MPC) method with finite control set needs calculations according to the total number of voltage vectors made by multi-level converters. This operating principle of the MPC tends dramatically to increase the computational load and number of calculations when the level of cascaded H-bridge (CHB) inverters is increased. A new MPC algorithm is proposed in this paper for decreasing the number of calculation in multi-level CHB inverters, in which only three voltage vectors are evaluated to determine optimal vectors regardless of the level of CHB inverters. As a result, the proposed MPC method needs fewer calculations and decreases the computational load compared to the conventional MPC method for CHB inverters, without affecting the performance and dynamic response of 5-level CHB inverter.

This paper proposes a computationally efficient model predictive control strategy for quasi-Z source inverter. Unlike the classical finite control set model predictive control method, besides the a...

The article presents a general framework valid for the high-frequency excitation-based position observer for low-speed sensorless control of synchronous reluctance machines. A finite-control-set model-predictive-control technique is proposed accordingly, exploiting the switching current ripple for the position estimation. The position error due to cross saturation is inherently accounted for. The proposed scheme is integrated with an adaptive projection vector for position error estimation for high speeds region through a simple fusion structure for a smooth transition. The performance of the proposed technique is validated on a 1.1-kW synchronous reluctance motor test bench.

This paper presents an evaluation of Finite Control Set-Model Predictive Control (FCS-MPC) performance for dynamic resources provisioning. Realization of a shared-resources environment is experimented in software system network by virtualization technique. Control parameter regulates the resources provisioning among the users to guarantee the achievement of performance metrics in the network. The objective preferences are maintained in relative term by manipulating a finite set of operating points as the control states. Moreover, an optimization procedure is implemented based on receding horizon prediction of MPC in a feedback control scheme. Further investigation is conducted to examine the performance of optimal FCS and constrained FCS for dynamic system management. The experimental results demonstrate that constrained FCS system provides a better response stability than the optimal FCS. Correspondingly, the range and quantity of input states are significantly influential to the flow of control action. A wider range and longer control state sequence yields to a smoother control signal stream.

In this paper, finite control set model predictive current control strategy for five-phase permanent magnet synchronous motor is analysed. At first, virtual voltage vectors are adopted to avoid including all the 32 voltage vectors of five-phase inverter into the control set. Besides, under different rotor speed, estimated voltage vector is predicted in advance so that a new online updated adaptive control set can be established with proper voltage amplitude and only three vectors. Consequently, current ripples and computational burden can be much reduced. At last, experimental results are presented and indicate the performance improvement of the proposed control strategy.

In this paper a method to control the output current of a three-phase grid connected two- level converter is presented. The current control approach is a finite control set model predictive control with sphere decoding. Sphere decoding algorithm gives a computationally efficient solution of the problem for long horizons. The goal of the control algorithm is to minimize the grid current tracking error and switching frequency. These goals are met with the choice of the appropriate cost function. Simulations are carried out in order to investigate the proposed current control approach. The influence of control parameters on the control objectives is investigated through simulations.

Optimizacijski problem modelskog prediktivnog upravljanja strujom frekvencijskog pretvarača formuliran je u obliku problema najmanjih kvadrata s cjelobrojnim rješenjem. Korištenjem sphere decoding načela izveden je efikasan algoritam za određivanje optimalne upravljačke akcije. Nadalje, kako bi se računska složenost dodatno smanjila, koristi se algoritam redukcije koji preoblikuje prostor traženja rješenja u kojem se nalazi cjelobrojno rješenje optimizacijskog problema. Navedeni algoritmi su pokazani na modelu dvorazinskog trofaznog pretvarača spojenog na naponsku mrežu. For direct model predictive control with reference tracking of the converter current, the optimization problem is formulated as an integer least-squares problem. Sphere decoding principles are adapted to this optimization problem and an efficient algorithm for computing optimal switch positions is derived. Furthermore, in order to reduce the computational effort even more, a reduction algorithm is added as a preprocessing stage to reshape the search space in which the integer solution lies. Three-phase grid connected converter serves as an illustrative example to demonstrate the effectiveness of the proposed algorithms.

The study presents the direct flux and current vector control of an induction motor (IM) drive, which is a relatively newer and promising control strategy, through the use of model predictive control (MPC) techniques. The results highlight that the fast flux control nature of direct flux control strategy is further enhanced by MPC. Predictive control is applied in two of its variants, namely the finite control set and modulated MPC, and the advantages and limitations of the two are underlined. This work also highlights, through experimental results, the importance of prioritising the flux part of the cost function which is particularly significant in the case of an IM drive. The performance of the MPC-based approach is compared with the proportional-integral controller, which also prioritises the flux control loop, under various operating regions of the drive such as in the flux-weakening regime. Simulations show the performance expected with different control strategies which is then verified through experiments.

This paper proposes a finite control set model predictive current control (FCS-MPCC) with grey prediction for surface mounted PMSM drives. The basic FCS-MPCC is combined with grey prediction to improve the dynamic performance current control. Grey system takes into account both certain and uncertain information in real system, and use the rolling optimal grey sequence to predict the control current for cost function. The performance is demonstrated in both simulation and experiment. The results illustrate that FCS-MPCC with grey prediction expresses a good current response under the load disturbance and good performance under different parameter variations. Meanwhile the steady-state performance of current can be assured.

In this paper, a simplified direct finite-control-set model predictive control with DC-Link voltage dynamic reference design is proposed for active front-end rectifiers without requiring additional external control loops. Specifically, a desired voltage vector which only requires three explorations is directly selected by using a single cost function. Meanwhile, the proposed method can accurately perform the direct finite-control-set model predictive control without overshoot by applying the dynamic reference design through the mathematical calculations. Simulation results are presented to demonstrate the efficacy of the proposed method.

This paper presents the power converters topology and the corresponding control systems of a three-phase regenerative grid simulator. The proposed system consists in three identical single-phase units, each one consisting in two H-bridge power converters sharing a common dc-bus. The mathematical model of the two converters is developed and based on them, a finite control set model predictive control strategy was developed for the grid simulator. Simulation results demonstrate the very good dynamic performance of the developed grid simulator under all operating conditions and for all types of loads, as well as the adequacy of predictive control algorithms for the application in question.

POWER ELECTRONICS AND DRIVES; ISSN 2451-0262

In this paper, an improved direct finite-control-set model predictive control with delay compensation and simplified computational approach is proposed for active front-end rectifiers. Specifically, an active voltage vector which only requires one exploration is directly selected and applied to avoid the exhaustive exploration for testing all feasible voltage vectors during one switching period. Meanwhile, a delay compensation method is presented. The control delay caused by the calculation effort can be compensated. The performance of the proposed method can be improved. Simulation results are presented to demonstrate the efficacy of the proposed method.

This paper presents a new speed Finite Control Set Model Predictive Control (FCS-MPC) algorithm which has been applied to a Permanent Magnet Synchronous Motor (PMSM) driven by a Matrix Converter (MC). This method replaces the classical cascaded control scheme with a single control law that controls the motor currents and speed. Additionally, unlike classical MC modulation methods, the method allows direct control of the MC input currents. The performance of the proposed work has been verified by simulation studies and experimental results.

This paper presents the evaluation of different types of digital filter in Finite Control Set Model Predictive Control (FCS-MPC), in order to control the injected current spectrum of a power converter, and fix it to a narrow band around an arbitrary switching frequency. In FCS-MPC, a cost function in which there are included system variables to be controlled, is minimized. With the use of a current error filter, the current spectrum can also be controlled. Simulations are presented to show the obtained results.

This text focuses on advanced torque control of permanent magnet synchronous motor drives. A novel modular structure is introduced to simplify the design and implementation of Model Predictive Control (MPC). The layout consists of the control and the control framework. The dynamic control is the novel virtual flux controller, which is used to reach desired reference values, and the state observer, which is used to reduce effects of non-modeled system properties. The control framework consists of static mappings to simplify the control problem. Besides the alpha-beta and d-q transformations, a reference generation procedure is used to generate state references based on optimality criteria. Also, the actuation scheme is part of the control framework and defines the available input set and the resulting control properties. The first method actuates directly switch states, i.e. voltage vectors, which yield an integer set named Finite Control Set (FCS). The other method actuates duty cycles via modulation, which yield the Convex Control Set (CCS). A stability analysis is carried out for both, CCS-MPC and FCS-MPC. MPC is called stable, if it is feasible and convergent, which can be ensured using the main MPC stability theorem. However, stringent computation requirements make it difficult to apply the theorem in practice. Thus, the Lyapunov based MPC approach is applied to the motor drive, which provides stability guarantees independent of the prediction horizon. A stability constraint based on control Lyapunov functions (CLF) ensures convergence to the origin and the resulting optimal control problem is shown to be feasible for all time. In other words, a control input can be found at each sampling instant, which satisfies all constraints and yields a stable closed-loop system. The properties of CCS-MPC are derived using a nonlinear controller and the constrained closed-loop system is shown to be stable in the sense of Lyapunov. The stability properties of FCS-MPC are more complex due to the integer input set. Using set-theoretical methods, it is shown that a sufficiently large control error can be steered towards the origin. In other words, the proposed FCS-MPC is shown to be set stable, i.e. the control error is guaranteed to converge to a well-defined neighborhood of the origin. MPC requires that a Constrained Finite Time Optimal Control (CFTOC) problem is solved at each sampling time. Small sampling periods and limited computation capabilities of embedded hardware require the CFTOC to be sufficiently simple, which is achieved using the virtual flux model in the static reference frame. The problem size is contained using a sufficiently small prediction horizon and efficient algorithms are necessary to provide a result within a sampling period. The CFTOC of the proposed CCS-MPC is a (convex) linear or quadratic programming problem, which can be solved using existing efficient algorithms. To provide a minimal approach, an efficient algorithm is introduced to solve the one-step-ahead prediction CFTOC analytically. FCS-MPC results in a mixed integer programming problem and is therefore more difficult to solve with standard numerical methods. In practice, the CFTOC is solved by enumeration, which is combined with branch-and-bound, i.e. branch-and-cut, techniques to improve the computational efficiency. The control algorithms have been developed on a Software-in-the-Loop (SiL) platform based on Matlab/Simulink and the code is implemented without modification on an experimental test-bench. The evaluation confirms the design and implementation of CCS-MPC and FCS-MPC and shows good results in dynamic and steady-state operation. The two MPC approaches have complimentary properties, which can be used to target different applications. CCS-MPC achieves a constant switching frequency and is a promising alternative to proportional-integral (PI) vector control. The concept can be combined with different modulation schemes, e.g. the Symmetric Space Vector Modulation (SSVM) and the Discontinuous Space Vector Modulation (DSVM) are used in this text. FCS-MPC takes the inverter switching into account and achieves an approximately constant switching ripple but a variable switching frequency. The concept is most profitably applied to systems where a high sampling frequency compared to the switching frequency is desired, e.g. high power or servo drives. Moreover, FCS-MPC lacks Pulse Width Modulation (PWM) harmonics in its current spectrum. Consequently, it is advantageous in terms of acoustic noise since emphasized tones are missing. However, the distinguished PWM harmonics of CCS-MPC are simpler to filter. In summary, it can be said that the work on advanced torque control of permanent magnet synchronous motor drives has produced an innovative strategy. The introduction of a new structure has significantly simplified the model predictive control problem, the concept of stability in particular. Moreover, this structure results in the implementation of simple algorithms, which can be computed efficiently.

This paper introduces a modified Finite Control Set Model Predictive Control scheme (FCS-MPC) for a Permanent Magnet Synchronous Machine (PMSM). This paper is to investigate the idea of interpolation to obtain an extra six virtual switching vectors, in addition to the original 8 physical switching vectors existed for the controlling functions, and as a result, there are total twelve active vectors available for the evaluation of the cost function in the FCS-MPC. Simulation results and spectrum analysis of the proposed approach demonstrate the improvement over the conventional FCS-MPC.

In this paper, the problem of the stabilization of a discrete-time linear system subject to a fixed and uniformly quantized control set is considered. It is well known that, working with quantized inputs, the states of the system (except for a negligible set of initial conditions) cannot reach asymptotically the equilibrium point. Our aim is then to find an invariant and attractive neighborhood of the equilibrium and provide with a controller which steers the system into it. We construct a continuous and increasing family of invariant sets including one which is, in a specific sense, minimal. The invariance and attractivity properties of such sets are revised in the finite control set case: we propose a family of controllers taking on a finite number of values and ensuring the system convergence to the minimal invariant set. Some consequences of our technique axe underlined with particular regard to the usage of model predictive control tools. In the last section an example which shows the effectiveness of our results is presented.

In this paper we consider the problem of controllability for a discrete linear control system xk+1 = Axk + Buk, uk ∈ U, where (A, B) is controllable and U is a finite set. We prove the existence of a finite set U ensuring density for the reachable set from the origin under the necessary assumptions that the pair (A, B) is controllable and A has eigenvalues with modulus greater than or equal to 1. In the case of A only invertible we obtain density on compact sets. We also provide uniformity results with respect to the matrix A and the initial condition. In the one-dimensional case the matrix A reduces to a scalar λ and for λ andgt; 1 the reachable set R(0, U) from the origin is R(0, U)(λ) = {∑j=0n ujλj uj ∈ U, n ∈ N} When 0 andlt; λ andlt; 1 and U = {0, 1, 3}, the closure of this set is the subject of investigation of the well-known {0, 1, 3}-problem. It turns out that the nondensity of R(0, Ũ(λ))(λ) for the finite set of integers Ũ(λ) = {0, ±1, ..., ±[λ]} is related to special classes of algebraic integers. In particular if λ is a Pisot number, then the set is nowhere dense in R for any finite control set U of rationals.