Finite Set Model Predictive Control Research Articles

Proportional Usage of Low-Level Actions in Model Predictive Control for Six-Phase Electric Drives

Finite Control-Set Model Predictive Control (FCS-MPC) appears as an interesting alternative to regulate multiphase electric drives, thanks to inherent advantages such as its capability to include new restrictions and fast-transient response. Nevertheless, in industrial applications, FCS-MPC is typically discarded to control multiphase motors because the absence of a modulation stage produces a high harmonic content. In this regard, multi-vectorial approaches are an innovative solution to improve the electric drive performance taking advantage of the implicit modulator flexibility of Model Predictive Control (MPC) strategies. This work proposes the definition of a new multi-vectorial set of control actions formed by a couple of adjacent large voltage vectors and a null voltage vector with an adaptative application ratio. The combination of two large voltage vectors provides minimum x-y current injection whereas the application of a null voltage vector reduces the active voltage production. Moreover, the optimum selection of the null voltage vector for each couple of large voltage vectors permits reducing the switching frequency. On the other hand, the active application time for this couple is estimated through an analytic function based on the operating point. This procedure avoids the use of an iterative process to define the duty cycles, hence significatively decreasing the computational burden.

Multilayer Model Predictive Control for a Voltage Mode Digital Power Amplifier

The application of the finite control set model predictive control to cascaded inverters is severely limited by its computational complexity. In this paper, a load observer based multilayer model predictive control is proposed for the voltage mode digital power amplifier employing cascaded full-bridge neutral point clamped inverter, which can avoid the use of load current sensor and greatly reduce the controller computation without affecting its dynamic performance. The discrete mathematical model of the voltage mode digital power amplifier employing cascaded full-bridge neutral point clamped inverter is established with filter inductor current and filter capacitor voltage as state variables. A load current observer is designed based on this to avoid the use of load current observer. Based on the discrete model and the observed load current, the upper layer of the multilayer model predictive control determines the optimal level that minimizes the cost function. The middle layer allocates the optimal level to each submodule in order to achieve capacitor voltage balancing. The lower layer determines the switching state of each submodule in order to reduce switching actions. Finally, the experimental results based on the designed nine-level prototype show that the develop multilayer model predictive control lead to acceptable steady state, dynamic and robust performance, with only 1.37% of the run time of the traditional model predictive control.

Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller

Photovoltaic (PV) power systems are integrated with high penetration levels into the grid. This in turn encourages several modifications for grid codes to sustain grid stability and resilience. Recently, constant power management and regulation is a very common approach, which is used to limit the PV power production. Thus, this article proposes dual-mode power generation algorithm for grid-connected PV systems. The developed system considers the two-stage PV configuration for implementation, where the dual-mode power generation technique is executed within the DC–DC conversion (boost) stage. Most of the techniques adopted for dual-mode power operation employ the conventional perturb and observe method, which is known with unsatisfactory performance at fast-changing atmospheric conditions. Considering this issue, this study suggests a modified maximum power point tracker for power extraction. Furthermore, a new adaptive DC-link controller is developed to improve the DC-link voltage profile at different operating conditions. The adaptive DC-link controller is compared with the traditional PI controller for voltage regulation. The inverter control is accomplished using finite-set model predictive control with two control objectives, namely reference current tracking and switching frequency minimization. The overall control methodology is evaluated at different atmospheric and operating conditions using MATLAB/Simulink software.

An Improved Model Predictive Control Method for Three-Port Soft Open Point

Soft open point (SOP) is a key power electronic device to improve the flexibility and stability of the distribution network and is becoming a research hotspot. The traditional double closed-loop control of SOP has a complex structure, difficult process of parameter design, and poor output power quality. To solve these problems, finite control set model predictive control (FCS-MPC) has been adopted. Since FCS-MPC involves a large amount of calculation and experiences delay in current tracking, an improved FCS-MPC with delay compensation is proposed for three-port SOP in this paper to replace the inner loop current control strategy. Improved model predictive control combines the two-step prediction method based on the voltage vector and vector angle compensation method. The vector method is used to construct a mathematical model and a prediction model of three-port SOP. Based on FCS-MPC, the two-step prediction method that takes voltage as the target is used to compensate for the current delay problem, and the amount of calculation is reduced by converting the control target. Meanwhile, the vector angle compensation method is used to compensate the future reference value. Finally, a simulation model is built in MATLAB/Simulink. The simulation results under steady state and dynamic conditions show that the proposed strategy can effectively improve the current delay and reduce the amount of calculation. Furthermore, it has better current tracking accuracy and faster dynamic response speed.

Multistep Finite Control Set Model Predictive Control of Photovoltaic Power Generation System with Harmonic Compensation

Photovoltaic (PV) power generation is the main aspect of new energy power generation, and it is an important means to achieve the goal of carbon neutrality. When the PV system is connected to the grid, the nonlinear load of the grid will affect the power quality and consume reactive power. This paper proposes a PV power generation grid-connected system to improve power quality, with an active power filter (APF) function. Through the maximum power point tracking (MPPT) method, PV power generation can operate at the maximum power point and play the function of harmonic and reactive power compensation at the load side. To improve the dynamic performance of the grid-connected PV system and harmonic compensation simultaneously, multistep finite control set model predictive control (FCS-MPC) is adopted for the grid-connected module. The whole system does not need additional equipment, as it plays the role of two devices and effectively reduces the input cost. In this paper, the proposed structure and multistep FCS-MPC are verified in MATLAB/Simulink. The results show that the system injects the maximum power into the power grid at the same time when the load changes and compensates the harmonic generated by the nonlinear load of the power grid so that the total harmonic distortion of the power grid can meet the operation standard, and the system has good dynamic performance and steady-state performance.

Improved Virtual Inertia of PMSG-Based Wind Turbines Based on Multi-Objective Model-Predictive Control

In the case of a high penetration rate of wind energy conversion systems, the conventional virtual inertia control of permanent magnet synchronous generators (PMSG) has an insufficient support capability for system frequency, leading to an unstable system frequency and a slower response. Considering the finite control set model predictive control has multi-objective regulation capabilities and efficient tracking capabilities, and an improved multi-objective model-predictive control is proposed in this paper for PMSG-based wind turbines with virtual inertia based on its mathematical model. With the prediction model, the optimal control of the current and the frequency of the PMSG-based wind turbines can be obtained. Since the shaft torque changes rapidly under high virtual inertia, shaft oscillation may occur under this scenario. To address this problem, the electromagnetic torque is set as an additional optimization objective, which effectively suppresses the oscillation. Furthermore, based on accurate short-term wind speed forecasting, a dynamic weight coefficient strategy is proposed, which can reasonably distribute the weight coefficients according to the working conditions. Finally, simulations are carried out on a 2 MW PMSG-based wind turbine platform, and the effectiveness of the proposed control strategies is verified.

A Low Complexity Two Step Predictive Torque and Flux Control Scheme for PMSM Drive

Nowadays, finite control set model predictive control techniques are widely used for variable speed Permanent Magnet Synchronous Motor (PMSM) drive applications due to its simple, intuitive algorithm and easy inclusion of motor objectives. In conventional predictive torque control (PTC) method, both torque and flux are controlled by a cost function optimization, where it introduces weighting factors. The selection and tuning of weighting factors is difficult since it affects torque and flux performance of PMSM drive. In this article, a two-step PTC for PMSM drive is proposed, where the flux control objective is replaced with the reactive torque component. Therefore, optimal torque and flux controlling of PMSM is achieved with similar units for both control objectives. Hence, it eliminates weighting factor tuning problem and reduces the average torque and flux ripples over a two sample instants. Additionally, the reduced voltage vector strategy is proposed, so that increased computational efficiency is achieved. To validate the proposed methodology, simulations and experimental tests are conducted for three phase PMSM drive. The obtained simulation and experimental results justify an improved torque and flux response with reduced computational burden when compared to existing PTC methods.

DSTATCOM implementation using Reduced Switch Single DC Source Cascaded H-bridge Multilevel Inverter

This paper describes the operation of reduced-switch single DC source cascaded H-bridge multilevel inverter (RSDCHBMLI). Compared to conventional multilevel inverters, RSDCHBMLI offers a number of advantages such as lower component count, inherent isolation and requirement of single DC source. The paper proposes application of RSDCHBMLI as DSTATCOM in a weak distribution system. The usage of single DC-link capacitor in this topology eliminates the problem of capacitor voltage balancing in DSTATCOM operation. The DSTATCOM is operated in current controlled mode (CCM) using Finite control set-Model predictive control (FCS-MPC). FCS-MPC is successful in independently performing load compensation in presence of feeder impedance along with maintaining sinusoidal voltages at the point of common coupling (PCC), without the need of any modulator or supplementary control techniques. This paper also explores different control schemes used for maintaining the DC-bus voltage. A current based proportional-integral (PI) DC-bus voltage controller is implemented in this paper, which allows easier calculation of the controller gain parameters. The performance of the current based controller is also compared with conventional power based DC-bus controllers in terms of steady state error and settling time. The results are presented for a 11-kV distribution system with RSDCHBMLI based DSTATCOM simulated in PSCAD/EMTDC environment.

Simulink Implementation of Voltage Stability Improvements Using STATCOM based 5-level Diode Clamped Converter

In this paper, a STATCOM based on Five-level Diode Clamped Multilevel Converter is used to maintain the bus voltage at specific bus bar in a suggested grid under various abnormal conditions like 2-phase to ground fault, load disturbance and source disturbance. The suggested grid consists of a single machine, transmission line and loads. The compensation procedure is carried out and compared between the two suggested control methods, the first method was the traditional control method using Phase Shifted-PWM controller which is used to improve the voltage profile. The Second one was the Finite Set-Model Predictive Controller for improving the voltage profile. The simulation results show that the two methods provided significant improvements of the bus voltage profile. Moreover, the improvement of voltage profile using FS-MPC method is less over shoot and attains a steady state better than the conventional PS-PWM when the system is subjected under many disturbances. The results of the harmonic effect show low values of total harmonic distortion (THD) of supply voltage and current.

A finite set-model predictive control based on FPGA flatform for eleven-level cascaded H-Bridge inverter fed induction motor drive

Model predictive control has been considered as a powerful alternative control method in power converters and electrical drives recently. This paper proposes a novel method for finite control set predictive control algorithm foran induction motor fed by 11-level cascaded H-Bridge converter. To deal with the high computation volume of MPC algorithm applied for CHBconverter, 7-adjacent vectors method is applied for calculating the desired voltage vector which minimizes the cost function. Moreover, by utilizingfield programmable gate array (FPGA) platform with its flexible structure,the total execution time reduces considerably so that the selected voltage vector can be applied immediately without delay compensation. This method improves the dynamic responses and steady-state performance of the system. Finally, experimental results verify the effectiveness of control design

A Simplified Finite Control Set Model Predictive Control for T-Type Three-Level Power Conversion System Based on LCL Filter

Finite control set model predictive control (FCSMPC) is a highly attractive and potential control method for grid-tied converters. However, there are several challenges when employing FCSMPC in an LCL filter-based T-type three-level power conversion system (PCS) for battery energy storage applications. These challenges mainly include the increasing complexity of control algorithm and excessive cost of additional sensors, which deteriorate the performance of PCS and limit the application of FCSMPC. In order to overcome these issues, this paper proposes a simplified FCSMPC algorithm to reduce the computation complexity. Furthermore, full-dimensional state observers are adopted and implemented to estimate the instantaneous values of grid-side current and capacitor voltage for purpose of removing unnecessary electrical sensors. The implementation of proposed FCSMPC algorithm is described step by step in detail. Simulation results are provided as a verification for the correctness of theoretical analysis. Finally, a three-phase T-type three-level PCS prototype rated at 2.30 kVA/110 V is built up. Experimental results extracted from the prototype can verify the effectiveness of the proposed control strategy.

Topology, Modeling and Control Scheme for a new Seven-Level Inverter With Reduced DC-Link Voltage

This paper presents a novel single-source three-phase multilevel converter with voltage boosting capability for medium-voltage photovoltaic applications. This converter consists of different switched-capacitor networks, formed by 1 capacitor and 3 active switches, as a basic switching cell to generate variable dc-link voltage that boosts the input dc-source voltage, producing 2n+1 (n2) voltage levels at the output. It can reduce the dc-link voltage requirements by 50% in comparison to the traditional neutral point clamped (NPC), flying capacitors, active NPC (ANPC), hybrid and hybrid clamped ANPC and cascaded H-bridge topologies, and 75% to advanced ANPC topologies. It can also reduce the number of required switches and capacitors as well as their voltage stresses compared to these state-of-the-art topologies reported in the literature so far. A finite control set model predictive control algorithm is derived to control the converter, which has the capability to control the active and reactive power without distorting the generated grid current quality. The capacitor voltage balancing is inherent in the proposed topology, and thus, there is no need for any additional voltage balancing circuit, which reduces the control complexity. As an example, a 7-level version of the proposed topology is compared to other existing 7-level inverter topologies.

A low‐complexity FS‐MPDPC with extended voltage set for grid‐connected converters

The conventional finite control set model predictive control (FS-MPC) for converter control is a well-studied area, but performance degradation due to the finite candidate vector set is still limiting its practical applications. Extending the voltage vector set using discrete space vector modulation has been proposed as a solution to overcome the limitations, but the brute-force search inherent to FS-MPC increases the computational complexity for a larger voltage set. This paper proposes a technique to alleviate the above issue by avoiding the brute-force search that is being executed in FS-MPC. The technique utilises the basics of direct-power-control theory to cut down the number of candidate voltage vectors applied in each cycle in the optimization problem. In this work, a design example having a voltage vector set of 37 elements is considered, and the proposed technique narrows down the search to eight optimal vectors. The proposed controller is specifically designed for active–reactive power control of a grid-connected converter that interlinks an energy storage system to the grid. The system is modelled in MATLAB Simulink environment and simulations are carried out to analyse the performance in all four active–reactive bidirectional power flow modes. Results validate the performance of the controller, both in steady-state and transient conditions. Further, the reduction in computational complexity due to the proposed algorithm is evaluated. It is observed that the number of computations was reduced approximately by 75% after applying the proposed algorithm for a system with a 37 voltage vector set.

Finite-control-set model predictive control for magnetically coupled wireless power transfer systems

Output voltage control is an important subject in magnetically coupled wireless power transfer (MC-WPT) applications. Conventional control methods for MC-WPT systems use the PI controller. However, this method suffers from three issues: time-consuming tuning work of the PI parameters, increased control complexity due to the needs of the modulator, and poor dynamic performance. To provide an attractive alternative to the PI controller, a novel output voltage regulation method based on finite-control-set model predictive control (FCS-MPC) has been proposed for a MC-WPT system. The proposed method has inherent advantages such as a very intuitive concept, no need for a modulator, and fast dynamic response. Moreover, it can achieve soft switching by constructing pulse-density-modulation-based voltage pulse sequences as the control set. The design and implementation of the proposed controller are discussed in this paper. The proposed control method has been tested on a series-series-compensated MC-WPT system, and experimental results demonstrate the effectiveness of the proposed control method in comparison with PI control methods.

Sequential Phase-Shifted Model Predictive Control for Modular Multilevel Converters

Model predictive control has emerged as a promising approach to govern modular multilevel converters (MMCs), due to its flexibility to include multiple control objectives and simple design process. However, this control scheme presents relevant issues, such as high computational complexity and variable switching frequency. This work proposes a sequential phase-shifted model predictive control (PS-MPC) for MMCs. The key novelty of this proposal lies in the way the predictive control strategy is formulated to fully exploit a phase-shifted pulsewidth modulation technique through an appropriate choice of synchronized average models for each carrier. In this way, the proposed predictive controller obtains independent optimal modulating signals for each carrier in a sequential manner, by solving an optimization problem with reduced computational effort independent of the number of submodules. This sequential optimization allows one to formulate the optimal control problem to achieve multiple control objectives, similarly to the finite-control-set MPC (FCS-MPC). Nevertheless, the MMC governed with the proposed PS-MPC generates an output voltage with fix-spectrum and operates with an even power loss distribution among semiconductors in steady-state, outperforming the standard FCS-MPC strategy. Experimental results are provided to verify the proposed PS-MPC effectiveness when governing a three-phase MMC with four half-bridges per stack.

Efficient FPGA-Based Real-Time Implementation of Model Predictive Control for Single-Phase Direct Matrix Converter

Finite control set model predictive control (FCS-MPC) is an optimal control strategy that solves user-defined objective functions to determine the best control action for the next time interval. Real-time implementations of model predictive control techniques are quite challenging for certain topologies due to computation complexities. In this paper, key aspects of achieving robust, reliable, and efficient field programmable gate arrays (FPGAs) based model predictive control are presented for single-phase direct matrix topology. The effectiveness of FPGA-based model predictive control is validated experimentally using an ALTERA Cyclone IV FPGA. Experimental results show that an effective load current control performance is obtained by taking advantage of pipelining capability of the FPGA device. The tradeoff between control bandwidth, FPGA resources, and hardware utilization is discussed.

Model Predictive Control for Paralleled Uninterruptible Power Supplies with an Additional Inverter Leg for Load-Side Neutral Connection

Uninterruptible Power Supplies (UPS) have been demonstrated to be the key technology in feeding either single- and three-phase loads in a wide range of critical applications, such as high-tier datacenters and medical facilities. To increase the overall system power capacity and resilience, UPS systems are usually connected in parallel. When UPS systems are parallel connected, a circulating current can rise, inhibiting correct system operation. Moreover, having a controlled load power distribution is another fundamental requirement in paralleled UPS systems. However, strategies to ensure these two topics have not been explored to date for UPS systems with a load-side neutral connection. This paper proposes an innovative Finite Control Set Model Predictive Control (FCS-MPC) strategy that ensures circulating current elimination and controlled load power distribution for paralleled UPS systems that use an additional inverter leg for load neutral point connection. Additionally, a system topology based on two parallel-connected UPS systems that can simultaneously supply single- and three-phase critical loads is proposed. Experimental results show the effectiveness and robustness of the proposed control techniques even when different types of loads are connected to the UPS systems.

Carrier-Based Modulated Model Predictive Control Strategy for Three-Phase Two-Level VSIs

The implementation of finite-control-set model predictive control (FCS-MPC) in voltage source inverters (VSIs) can make the system suffer from poor current harmonics performance, which may complicate the design of the required AC filter. To overcome this shortcoming, a carrier-based modulated model predictive control (CB-MMPC) strategy is proposed in this paper. This method enables the utilization of existing PWM modulation techniques with FCS-MPC, where a modulation waveform with zero-sequence signal injection is generated and compared to a triangular carrier wave, while optimizing the selection of the switching states. As it is shown, the studied CB-MMPC strategy not only considerably improves the current total harmonic distortion (THD) but also attains the performance of fast current dynamic response and robustness as the traditional FCS-MPC. Herein, the detailed implementation of the CB-MMPC control strategy is given, while considering its application to the current feedback control loop of a three-phase three-wire two-level VSI modulated at constant switching frequency. Finally, PLECS circuit simulation and a 3-kW VSI prototype are used to verify the superiority and the effectiveness of the presented CB-MMPC strategy. This is also benchmarked to the FCS-MPC and dead-beat based controllers.

Ripple Attenuation for Induction Motor Finite Control Set Model Predictive Torque Control Using Novel Fuzzy Adaptive Techniques

Finite control set model predictive torque control (FCS-MPTC) strategy has been widely used in induction motor (IM) control due to its fast response characteristic. Although the dynamics of the FCS-MPTC method are highly commended, its steady-state performance—ripple deserves attention in the meantime. To improve the steady-state performance of the IM drives, this paper proposes an improved FCS-MPTC strategy, based on a novel fuzzy adaptive speed controller and an adaptive weighting factor, tuning strategy to reduce the speed, torque and flux ripples caused by different factors. Firstly, a discrete predicting plant model (PPM) with a new flux observer is established, laying the ground for achieving an FCS-MPTC algorithm accurately. Secondly, after analyzing the essential factors in establishing a fuzzy adaptive PI controller, with high ripple suppression capacity, an improved three-dimensional controller is designed. Simultaneously, the implementation procedures of the fuzzy adaptive PI controller-based FCS-MPTC are presented. Considering that a weighting factor must be employed in the cost function of an FCS-MPTC method, system ripples increase if the value of the weighting factor is inappropriate. Then, on that basis, a novel fuzzy adaptive theory-based weighting factor tuning strategy is proposed, with the real-time torque and flux performance balanced. Finally, both simulation and hardware-in-loop (HIL) test are conducted on a 1.1 kW IM drive to verify the proposed ripple reduction algorithms.

Model Predictive Control of MPUC7-Based STATCOM Using Autotuned Weighting Factors

A seven-level modified packed U-cell (MPUC7) based static synchronous compensator (MPUC7-STATCOM) with an autotuned finite control-set model predictive control (AFCS-MPC) is introduced in this article. MPUC7-STATCOM is a compact four-quadrant cascaded topology that comprises merely six switches and two isolated dc capacitors. Thus, in comparison with a seven-level cascaded H-bridge (CHB) based STATCOM, not only the proposed configuration has exceptionally reduced active/passive component count, but also MPUC7-STATCOM designed AFCS-MPC control method complexity is attenuated meaningfully. Boost-mode operation and low voltage rating of the components can be also mentioned as the merits of the MPUC7-STATCOM. Using the proposed AFCS-MPC, nonlinearities of the MPUC7 converter have been considered and both capacitors’ voltages are directly regulatable at different desired amounts accurately. Moreover, the weighting factors of the proposed AFCS-MPC are tunable automatically in real-time. Consequently, MPUC7-STATCOM has a desirable dynamic operation and its capacitors’ values are reduced. Provided simulation and experimental results validate the viability of the MPUC7-STATCOM topology and robustness of the designed AFCS-MPC method as well as its steady-state and dynamic operation.