Editorial

3 pages, 168 KiB

Open AccessEditorial

Preface to “Model Predictive Control and Optimization for Cyber-Physical Systems”

by Denis Sidorov

Mathematics 2023, 11(4), 1004; https://doi.org/10.3390/math11041004 - 16 Feb 2023

Cited by 3 | Viewed by 955

The concept of cyber-physical systems (CPSs) in electrical, civil and mechanical engineering is closely related to Smart Grids and Smart Cities, based on advanced computing technologies used for monitoring, control and communication [...] Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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13 pages, 5031 KiB

Open AccessArticle

Implementation of Voltage Sag Relative Location and Fault Type Identification Algorithm Using Real-Time Distribution System Data

by Yunus Yalman, Tayfun Uyanık, Adnan Tan, Kamil Çağatay Bayındır, Yacine Terriche, Chun-Lien Su and Josep M. Guerrero

Mathematics 2022, 10(19), 3537; https://doi.org/10.3390/math10193537 - 28 Sep 2022

Cited by 3 | Viewed by 1119

Abstract

One of the common power quality (PQ) problems in transmission and distribution systems is the voltage sag that affects the sensitive loads. Losses and problems caused by the voltage sag in the power system can be reduced by correctly determining the relative location [...] Read more.

One of the common power quality (PQ) problems in transmission and distribution systems is the voltage sag that affects the sensitive loads. Losses and problems caused by the voltage sag in the power system can be reduced by correctly determining the relative location of the voltage sag. This paper proposes a novel algorithm to classify voltage sag relative location and fault type, which is the main root cause of voltage sag, based on the actual voltage and current data before and during the voltage sag. The performance of the algorithm is investigated by performing a numerical simulation utilizing MATLAB/Simulink. Moreover, the proposed algorithm is integrated into the power quality monitoring system (PQMS) of the real distribution system and tested. The results show that the performance of the proposed method is satisfactory. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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24 pages, 7882 KiB

Open AccessArticle

An Improvement of Model Predictive for Aircraft Longitudinal Flight Control Based on Intelligent Technique

by Mohamed El-Sayed M. Essa, Mahmoud Elsisi, Mohamed Saleh Elsayed, Mohamed Fawzy Ahmed and Ahmed M. Elshafeey

Mathematics 2022, 10(19), 3510; https://doi.org/10.3390/math10193510 - 26 Sep 2022

Cited by 9 | Viewed by 1749

Abstract

This paper introduces a new intelligent tuning for the model predictive control (MPC) based on an effective intelligent algorithm named the bat-inspired algorithm (BIA) for the aircraft longitudinal flight. The tuning of MPC horizon parameters represents the main challenge to adjust the system [...] Read more.

This paper introduces a new intelligent tuning for the model predictive control (MPC) based on an effective intelligent algorithm named the bat-inspired algorithm (BIA) for the aircraft longitudinal flight. The tuning of MPC horizon parameters represents the main challenge to adjust the system performance. So, the BIA algorithm is intended to overcome the tuning issue of MPC parameters due to conventional methods, such as trial and error or designer experience. The BIA is adopted to explore the best parameters of MPC based on the minimization of various time domain objective functions. The suggested aircraft model takes into account the aircraft dynamics and constraints. The nonlinear dynamics of aircraft, gust disturbance, parameters uncertainty and environment variations are considered the main issues against the control of aircraft to provide a good flight performance. The nonlinear autoregressive moving average (NARMA-L2) controller and proportional integral (PI) controller are suggested for aircraft control in order to evaluate the effectiveness of the proposed MPC based on BIA. The proposed MPC based on BIA and suggested controllers are evaluated against various criteria and functions to prove the effectiveness of MPC based on BIA. The results confirm that the accomplishment of the suggested BIA-based MPC is outstanding to the NARMA-L2 and traditional PI controllers according to the cross-correlation criteria, integral time absolute error (ITAE), system overshoot, response settling time, and system robustness. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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23 pages, 8274 KiB

Open AccessArticle

Continuous-Control-Set Model Predictive Control for Three-Level DC–DC Converter with Unbalanced Loads in Bipolar Electric Vehicle Charging Stations

by Muhammad Sadiq, Carlos Alfaro Aragon, Yacine Terriche, Syed Wajahat Ali, Chun-Lien Su, Ľuboš Buzna, Mahmoud Elsisi and Chung-Hong Lee

Mathematics 2022, 10(19), 3444; https://doi.org/10.3390/math10193444 - 22 Sep 2022

Cited by 16 | Viewed by 1613

Abstract

Zero-emission transportation is currently a public priority, especially in big cities. For this reason, the use of electric vehicles (EVs) is receiving much attention. To facilitate the adoption of EVs, a proper charging infrastructure together with energy management is essential. This article proposes [...] Read more.

Zero-emission transportation is currently a public priority, especially in big cities. For this reason, the use of electric vehicles (EVs) is receiving much attention. To facilitate the adoption of EVs, a proper charging infrastructure together with energy management is essential. This article proposes a design guideline for a direct current (DC) charging station with bipolar properties. A bipolar system can convert a two-wire system into three wires in a microgrid system with a neutral line. The configuration of the bipolar system supports different loads; therefore, the unbalanced operation is inherent to the system. The proposed bipolar DC charging station (CS) has a three-level balancing converter that reduces the step-down effort chargers. Moreover, this paper proposes the continuous-control-set model predictive control (CCS-MPC)-based balancing strategy that allows the handling of different output loads while keeping the neutral-line voltage efficiently regulated with improved dynamic performance compared to a traditional controller. Stability and parameter robustness analyses are also performed for the control parameter selection. To ensure the performance of the proposed method, both simulation and experimental results are presented and compared with those obtained from the traditional methods. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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19 pages, 7237 KiB

Open AccessArticle

Digital Twin Formation Method for Distributed Generation Plants of Cyber–Physical Power Supply Systems

by Yuri Bulatov, Andrey Kryukov, Andrey Batuhtin, Konstantin Suslov, Ksenia Korotkova and Denis Sidorov

Mathematics 2022, 10(16), 2886; https://doi.org/10.3390/math10162886 - 12 Aug 2022

Cited by 4 | Viewed by 1321

Abstract

The purpose of the study presented in the article was to develop a method for the formation of digital twins for distributed generation plants operating as part of cyber–physical power supply systems. A method of forming a digital twin for a system for [...] Read more.

The purpose of the study presented in the article was to develop a method for the formation of digital twins for distributed generation plants operating as part of cyber–physical power supply systems. A method of forming a digital twin for a system for automatic regulation of the voltage and rotor speed of a synchronous generator is considered. The structure of a digital twin is presented in the form of a multiply connected model using experimental data. The possibility of using a fuzzy inference system, artificial neural networks, and a genetic algorithm for solving the problem is shown. As a result of the research, neuro-fuzzy models of the elements of the distributed generation plant were obtained, which are an integral part of the digital twin. Based on the simulation results, the following conclusions were drawn: the proposed method for constructing an optimized fuzzy model gives acceptable results when compared with experimental data and shows practical applicability in constructing a digital twin. In the future, in order to simplify the model, it is necessary to solve the problem of optimizing the number of rules in the fuzzy inference system. It is also advisable to direct further research to the formation of a complete hierarchical fuzzy system that connects all elements of the digital twin. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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15 pages, 1522 KiB

Open AccessArticle

An Approach to Assessing Spatial Coherence of Current and Voltage Signals in Electrical Networks

by Pavel Ilyushin, Aleksandr Kulikov, Konstantin Suslov and Sergey Filippov

Mathematics 2022, 10(10), 1768; https://doi.org/10.3390/math10101768 - 22 May 2022

Cited by 2 | Viewed by 1135

Abstract

In the context of energy industry decentralization, electrical networks encounter deviations of power quality indices (PQI), including violations of the sinusoidality of current and voltage signals, which increase errors in the joint digital processing of spatially separated signals in digital devices. This paper [...] Read more.

In the context of energy industry decentralization, electrical networks encounter deviations of power quality indices (PQI), including violations of the sinusoidality of current and voltage signals, which increase errors in the joint digital processing of spatially separated signals in digital devices. This paper addresses specific features of using the concept of spatial coherence in the measurement and digital processing of current and voltage signals. Methods for assessing the coherence of current and voltage signals during synchronized measurements are considered for the case of PQI deviation. The example of a double-ended transmission line fault location (hereafter, DTLFL) demonstrates that the lower the cross-correlation coefficient, the higher the error and the lower the accuracy of calculating the distance to the fault site. The nature of the influence of spatial coherence violations on errors in DTLFL depends on the expression used to calculate the distance to the fault point. The application of a normalized cross-correlation coefficient for finding errors in the digital processing of current and voltage signals, in the case of spatial coherence violation, was substantiated. The influence of interharmonics and noise on errors in DTLFL, in the case of violations of spatial coherence of signals, was investigated. The magnitude of distortions and error in estimating the current and voltage amplitude depends on the ratio between the amplitudes and phases of the fundamental and distorting interharmonics. Filtration of the original and decimated signals based on the discrete Fourier transform eliminates the noise components of the power frequency harmonics. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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18 pages, 553 KiB

Open AccessArticle

Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA

by Luis Fernando Grisales-Noreña, Oscar Danilo Montoya, Ricardo Alberto Hincapié-Isaza, Mauricio Granada Echeverri and Alberto-Jesus Perea-Moreno

Mathematics 2021, 9(16), 1913; https://doi.org/10.3390/math9161913 - 11 Aug 2021

Cited by 11 | Viewed by 1403

Abstract

In this paper, we propose a master–slave methodology to address the problem of optimal integration (location and sizing) of Distributed Generators (DGs) in Direct Current (DC) networks. This proposed methodology employs a parallel version of the Population-Based Incremental Learning (PPBIL) optimization method in [...] Read more.

In this paper, we propose a master–slave methodology to address the problem of optimal integration (location and sizing) of Distributed Generators (DGs) in Direct Current (DC) networks. This proposed methodology employs a parallel version of the Population-Based Incremental Learning (PPBIL) optimization method in the master stage to solve the location problem and the Vortex Search Algorithm (VSA) in the slave stage to solve the sizing problem. In addition, it uses the reduction of power losses as the objective function, considering all the constraints associated with the technical conditions specific to DGs and DC networks. To validate its effectiveness and robustness, we use as comparison methods, different solution methodologies that have been reported in the specialized literature, as well as two test systems (the 21 and 69-bus test systems). All simulations were performed in MATLAB. According to the results, the proposed hybrid (PPBIL–VSA) methodology provides the best trade-off between quality of the solution and processing times and exhibits an adequate repeatability every time it is executed. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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17 pages, 933 KiB

Open AccessArticle

Adaptive Fault Estimation for Hyperbolic PDEs

by Yuan Yuan, Xiaodong Xu and Stevan Dubljevic

Mathematics 2021, 9(14), 1613; https://doi.org/10.3390/math9141613 - 08 Jul 2021

Cited by 2 | Viewed by 1682

Abstract

The new adaptive fault estimation scheme is proposed for a class of hyperbolic partial differential equations in this paper. The multiplicative actuator and sensor faults are considered. There are two cases that require special consideration: (1). only one type of fault (actuator or [...] Read more.

The new adaptive fault estimation scheme is proposed for a class of hyperbolic partial differential equations in this paper. The multiplicative actuator and sensor faults are considered. There are two cases that require special consideration: (1). only one type of fault (actuator or sensor) occurs; (2). two types of faults occurred simultaneously. To solve the problem of fault estimation, three challenges need to be solved: (1). No prior information of fault type is known; (2). Unknown faults are always coupled with state and input; (3). Only one boundary measurement is available. The original plant is converted to Observer canonical form. Two filters are proposed and novel adaptive laws are developed to estimate unknown fault parameters. With the help of the proposed update laws, the true state of the faulty plant can be estimated by the proposed observers composed of two filters. By selecting a suitable Lyapunov function, it is proved that under unknown external disturbance, the estimation errors of state parameters and fault parameters decay to arbitrarily small value. Finally, the validity of the proposed observer and adaptive laws is verified by numerical simulation. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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16 pages, 3896 KiB

Open AccessArticle

A Control Method for IPMSM Based on Active Disturbance Rejection Control and Model Predictive Control

by Fang Liu, Haotian Li, Ling Liu, Runmin Zou and Kangzhi Liu

Mathematics 2021, 9(7), 760; https://doi.org/10.3390/math9070760 - 01 Apr 2021

Cited by 9 | Viewed by 2370

Abstract

In this paper, the speed tracking problem of the interior permanent magnet synchronous motor (IPMSM) of an electric vehicle is studied. A cascade speed control strategy based on active disturbance rejection control (ADRC) and a current control strategy based on improved duty cycle [...] Read more.

In this paper, the speed tracking problem of the interior permanent magnet synchronous motor (IPMSM) of an electric vehicle is studied. A cascade speed control strategy based on active disturbance rejection control (ADRC) and a current control strategy based on improved duty cycle finite control set model predictive control (FCSMPC) are proposed, both of which can reduce torque ripple and current ripple as well as the computational burden. First of all, in the linearization process, some nonlinear terms are added into the control signal for voltage compensation, which can reduce the order of the prediction model. Then, the dq-axis currents are selected by maximum torque per ampere (MTPA). Six virtual vectors are employed to FCSMPC, and a novel way to calculate the duty cycle is adopted. Finally, the simulation results show the validity and superiority of the proposed method. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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17 pages, 839 KiB

Open AccessArticle

A Valid Dynamical Control on the Reverse Osmosis System Using the CESTAC Method

by Samad Noeiaghdam, Denis Sidorov, Alyona Zamyshlyaeva, Aleksandr Tynda and Aliona Dreglea

Mathematics 2021, 9(1), 48; https://doi.org/10.3390/math9010048 - 28 Dec 2020

Cited by 14 | Viewed by 1905

Abstract

The aim of this study is to present a novel method to find the optimal solution of the reverse osmosis (RO) system. We apply the Sinc integration rule with single exponential (SE) and double exponential (DE) decays to find the approximate solution of [...] Read more.

The aim of this study is to present a novel method to find the optimal solution of the reverse osmosis (RO) system. We apply the Sinc integration rule with single exponential (SE) and double exponential (DE) decays to find the approximate solution of the RO. Moreover, we introduce the stochastic arithmetic (SA), the CESTAC method (Controle et Estimation Stochastique des Arrondis de Calculs) and the CADNA (Control of Accuracy and Debugging for Numerical Applications) library instead of the mathematical methods based on the floating point arithmetic (FPA). Applying this technique, we would be able to find the optimal approximation, the optimal error and the optimal iteration of the method. The main theorems are proved to support the method analytically. Based on these theorems, we can apply a new stopping condition in the numerical procedure instead of the traditional absolute error. These theorems show that the number of common significant digits (NCSDs) of exact and approximate solutions are almost equal to the NCSDs of two successive approximations. The numerical results are obtained for both SE and DE Sinc integration rules based on the FPA and the SA. Moreover, the number of iterations for various

ε

are computed in the FPA. Clearly, the DE case is more accurate and faster than the SE for finding the optimal approximation, the optimal error and the optimal iteration of the RO system. Full article

(This article belongs to the Special Issue Model Predictive Control and Optimization for Cyber-Physical Systems)

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