Special Issue "Intelligent Control for Future Systems"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A8: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: 20 April 2022.

Special Issue Editor

Prof. Dr. Eduard Petlenkov
E-Mail Website
Guest Editor
Department of Computer Systems, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia
Interests: control; identification; dynamic systems; intelligent control; computational intelligence; data-driven control; artificial neural networks; fuzzy systems; fractional order systems; industry 4.0

Special Issue Information

Dear Colleagues,

We are organizing a Special Issue that may be of interest to you and would like cordially to invite you to submit a manuscript for consideration and possible publication. The issue is titled "Intelligent Control for Future Systems".

One of the main challenges of future control systems will be data-driven control design for rapidly changing environments that will be able to increase efficiency and reduce energy consumption, emissions, and pollution. Data-driven control algorithms lying on the border between control theory, machine learning, and data science have the largest impact on the future of humanity. This Special Issue focuses on novel methods for automated analysis, modelling, and design of the most efficient control systems for complex processes, methods that can significantly simplify implementation of advanced control techniques in the industry, increase their efficiency, and enable industrial control systems to acquire knowledge and learn from constantly growing data sets.

The Special Issue on “Intelligent Control for Future Systems” is aiming to focus on intelligent and data-driven control techniques and their potential applications.

Prof. Dr. Eduard Petlenkov
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent control
  • computational intelligence for modelling and control
  • applications of intelligent control
  • data-driven control
  • control of complex processes
  • nonlinear control systems
  • fractional order systems

Published Papers (14 papers)

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Research

Article
Structural and Parametric Optimization of S-CO2 Thermal Power Plants with a Pulverized Coal-Fired Boiler Operating in Russia
Energies 2021, 14(21), 7136; https://doi.org/10.3390/en14217136 - 01 Nov 2021
Viewed by 234
Abstract
The Rankine cycle is widely used for electricity production. Significant weight and size characteristics of the power equipment working on superheated steam are the main disadvantages of such power plants. The transition to supercritical carbon dioxide (S-CO2) working fluid is a [...] Read more.
The Rankine cycle is widely used for electricity production. Significant weight and size characteristics of the power equipment working on superheated steam are the main disadvantages of such power plants. The transition to supercritical carbon dioxide (S-CO2) working fluid is a promising way to achieve a significant reduction in equipment metal consumption and to increase energy efficiency. This paper presents the results of thermodynamic analysis of S-CO2 thermal power plants (TPPs) utilizing the heat of combustion products of an energy boiler. It was found that the net efficiency of the developed S-CO2 TPP with a pulverized coal-fired boiler reached 49.2% at an initial temperature of 780 °C, which was 2% higher compared to the efficiency level of steam turbine power plants (STPPs) at a similar turbine inlet temperature. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
A Method for Assessing the Stability of Digital Automatic Control Systems (ACS) with Discrete Elements. Hypothesis and Simulation Results
Energies 2021, 14(20), 6561; https://doi.org/10.3390/en14206561 - 12 Oct 2021
Viewed by 529
Abstract
The article presents a new approach to the analysis of the stability of automatic systems with discrete links. In almost all modern automatic control systems (ACS), there are links that break signals in time. These are power controlled switches—transistors or thyristors operating in [...] Read more.
The article presents a new approach to the analysis of the stability of automatic systems with discrete links. In almost all modern automatic control systems (ACS), there are links that break signals in time. These are power controlled switches—transistors or thyristors operating in a pulsed mode and digital links in regulators. Time discretization significantly affects the stability of processes in the automatic control system. The theoretical analysis of such systems is rather complicated and requires a significant change in engineering approaches to analysis. With the improvement of digital controllers and a significant increase in their performance, this problem has practically been forgotten. However, its mathematical “content” has not changed since the 1980s when discreteness began to play a major role in hindering the transition to digital automatic control systems. In this paper, we propose a new approach that consists of interpreting the sampling operation by a link with the proposed frequency characteristic, which determines the suppression of input high-frequency signals. This link greatly simplifies engineering calculations and demonstrates the new capabilities of sampling systems. These possibilities include the rational distribution of digitalization resources—the number of bits and the sampling interval between the regulator channels, depending on the frequency range of the efficiency of these channels. We verify and confirm our theoretical statements through simulations and show how this approach makes it possible to formulate new principles of construction of seemingly well-known controllers—PID (Proportional Integral Differential) controllers and variable structure systems (VSS). Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Intelligent Control System Architecture for Phosphorus Production from Apatite-Nepheline Ore Waste
Energies 2021, 14(20), 6469; https://doi.org/10.3390/en14206469 - 09 Oct 2021
Viewed by 463
Abstract
This paper proposes multilevel architecture for an intelligent control system for the complex chemical energy technological process of yellow phosphorus production from apatite-nepheline ore processing waste. The research revealed that, when controlling this process, one has to deal with large amounts of multiformat [...] Read more.
This paper proposes multilevel architecture for an intelligent control system for the complex chemical energy technological process of yellow phosphorus production from apatite-nepheline ore processing waste. The research revealed that, when controlling this process, one has to deal with large amounts of multiformat and polymodal information, and control goals differ at different levels not only in effectiveness criteria, but also in the structuredness of the level problems. On this basis, it is proposed that intelligent methods be used for the implementation of information processes and control goals at individual levels and the whole system. The artificial intelligence methods underlying the informational model of a control system offer solutions to problems of analyzing control processes at different hierarchy levels, namely the initial level of sensing devices, the levels of programmable logic controllers, dispatching of control and production processes, enterprise management and strategic planning. Besides, the intelligent control system architecture includes analytical and simulation models of processes occurring in the multistage procedure of ore waste processing by a plant consisting of a granulating machine, a conveyor-type multichambercalcining machine, and an ore thermal furnace. The architecture of information support for the control system comprises a knowledge-based inference block intended for implementing the self-refinement of neural network and simulation models. Fuzzy logic methods are proposed for constructing this block. The paper considers the deployment of control algorithms for a phosphorus production system using the Matlab software environment on the basis of a modern complex system development paradigm known as the model-oriented design concept. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Observer Design for a Variable Moment of Inertia System
Energies 2021, 14(18), 5850; https://doi.org/10.3390/en14185850 - 15 Sep 2021
Viewed by 425
Abstract
Variable moment of inertia systems are common, and a popular laboratory system of this type is the “ball-and-beam”. Such systems are, however, nonlinear and often unstable. Efficient control requires full state information (or at least partial velocities), which are generally difficult to measure. [...] Read more.
Variable moment of inertia systems are common, and a popular laboratory system of this type is the “ball-and-beam”. Such systems are, however, nonlinear and often unstable. Efficient control requires full state information (or at least partial velocities), which are generally difficult to measure. That is why the design of state observers is a relevant problem. In this paper, a new design of an observer is proposed. This new nonlinear observer uses partial output injection and the circle criterion to ensure semiglobal stability. Moreover, we present a complete modeling of the system and systematic testing of the observer in comparison to a baseline in the form of a linear observer. The results show that the designed observer outperforms its linear counterpart and does not impede control. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Energy System Monitoring Based on Fuzzy Cognitive Modeling and Dynamic Clustering
Energies 2021, 14(18), 5848; https://doi.org/10.3390/en14185848 - 15 Sep 2021
Viewed by 490
Abstract
A feature of energy systems (ESs) is the diversity of objects, as well as the variety and manifold of the interconnections between them. A method for monitoring ESs clusters is proposed based on the combined use of a fuzzy cognitive approach and dynamic [...] Read more.
A feature of energy systems (ESs) is the diversity of objects, as well as the variety and manifold of the interconnections between them. A method for monitoring ESs clusters is proposed based on the combined use of a fuzzy cognitive approach and dynamic clustering. A fuzzy cognitive approach allows one to represent the interdependencies between ESs objects in the form of fuzzy impact relations, the analysis results of which are used to substantiate indicators for fuzzy clustering of ESs objects and to analyze the stability of clusters and ESs. Dynamic clustering methods are used to monitor the cluster structure of ESs, namely, to assess the drift of cluster centers, to determine the disappearance or emergence of new clusters, and to unite or separate clusters of ESs. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Traffic Noise Modelling Using Land Use Regression Model Based on Machine Learning, Statistical Regression and GIS
Energies 2021, 14(16), 5095; https://doi.org/10.3390/en14165095 - 18 Aug 2021
Viewed by 490
Abstract
This study estimates the equivalent continuous sound pressure level (Leq) during peak daily periods (‘rush hour’) along the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia, using a land use regression (LUR) model based on machine learning, statistical regression, and [...] Read more.
This study estimates the equivalent continuous sound pressure level (Leq) during peak daily periods (‘rush hour’) along the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia, using a land use regression (LUR) model based on machine learning, statistical regression, and geographical information systems (GIS). The research utilises two types of soft computing methods including machine learning (i.e., decision tree, random frost algorithms) and statistical regression (i.e., linear regression, support vector regression algorithms) to determine the best approach to create a prediction Leq map at the NKVE in Shah Alam, Malaysia. The selection of the best algorithm is accomplished by considering correlation, correlation coefficient, mean-absolute-error, mean-square-error, root-mean-square-error, and mean absolute percentage error. Traffic noise level was monitored using three sound level meters (TES 52A), and a traffic tally was done to analyse the traffic flow. Wind speed was gauged using a wind speed meter. The study relied on a variety of noise predictors including wind speed, digital elevation model, land use type (specifically, if it was residential, industrial, or natural reserve), residential density, road type (expressway, primary, and secondary) and traffic noise average (Leq). The above parameters were fed as inputs into the LUR model. Additional noise influencing factors such as traffic lights, intersections, road toll gates, gas stations, and public transportation infrastructures (bus stop and bus line) are also considered in this study. The models utilised parameters derived from LiDAR (Light Detection and Ranging) data, and various GIS (Geographical Information Systems) layers were extracted to produce the prediction maps. The results highlighted the superior performances by the machine learning (random forest) models compared to the statistical regression-based models. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
The Model of Support for the Decision-Making Process, While Organizing Dredging Works in the Ports
Energies 2021, 14(9), 2706; https://doi.org/10.3390/en14092706 - 09 May 2021
Cited by 1 | Viewed by 539
Abstract
The aim of the research was to create a decision-making model, which would be able to support planning, organizing and conducting the dredging works in the port area. The proposed solution is a multiple element system which enables to verify, in a comprehensive [...] Read more.
The aim of the research was to create a decision-making model, which would be able to support planning, organizing and conducting the dredging works in the port area. The proposed solution is a multiple element system which enables to verify, in a comprehensive way, the majority of the aspects determining the quality and the time of dredging enterprise realization. The paper presents an original approach to the decision-making process during the organization of dredging works, using the computer program. In order to achieve the main goal of the study, the conditions of dredging works were considered. Furthermore, the factors that have an influence on the schedule of the project were evaluated and algorithms, as well as process organization schemes, were developed. If it is not enough, the decision models corresponding to the discussed issue were analysed and the computer program was created. And last but not the least, the proposed project and equipment were verified using a simulation model. While creating this model, the method of multiple criteria AHP (Analytic Hierarchy Process) decision support was used. Moreover, the mass service model with the priority queue regulations, the expert study, and statistical analysis of the traffic flow, were provided. The model was developed in reliance to multiple criteria studies, based on the opinions of multinational experts. These enabled to adjust each element of the system in accordance with various locations. As a result of the research, the following thesis has been proven, that detailed analysis of the conditions of dredging works and taking into account the received conclusions enables to reduce the costs and shorten the time of dredging projects realizations. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Virtual State Feedback Reference Tuning and Value Iteration Reinforcement Learning for Unknown Observable Systems Control
Energies 2021, 14(4), 1006; https://doi.org/10.3390/en14041006 - 15 Feb 2021
Cited by 6 | Viewed by 895
Abstract
In this paper, a novel Virtual State-feedback Reference Feedback Tuning (VSFRT) and Approximate Iterative Value Iteration Reinforcement Learning (AI-VIRL) are applied for learning linear reference model output (LRMO) tracking control of observable systems with unknown dynamics. For the observable system, a new state [...] Read more.
In this paper, a novel Virtual State-feedback Reference Feedback Tuning (VSFRT) and Approximate Iterative Value Iteration Reinforcement Learning (AI-VIRL) are applied for learning linear reference model output (LRMO) tracking control of observable systems with unknown dynamics. For the observable system, a new state representation in terms of input/output (IO) data is derived. Consequently, the Virtual State Feedback Tuning (VRFT)-based solution is redefined to accommodate virtual state feedback control, leading to an original stability-certified Virtual State-Feedback Reference Tuning (VSFRT) concept. Both VSFRT and AI-VIRL use neural networks controllers. We find that AI-VIRL is significantly more computationally demanding and more sensitive to the exploration settings, while leading to inferior LRMO tracking performance when compared to VSFRT. It is not helped either by transfer learning the VSFRT control as initialization for AI-VIRL. State dimensionality reduction using machine learning techniques such as principal component analysis and autoencoders does not improve on the best learned tracking performance however it trades off the learning complexity. Surprisingly, unlike AI-VIRL, the VSFRT control is one-shot (non-iterative) and learns stabilizing controllers even in poorly, open-loop explored environments, proving to be superior in learning LRMO tracking control. Validation on two nonlinear coupled multivariable complex systems serves as a comprehensive case study. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
Energies 2021, 14(2), 420; https://doi.org/10.3390/en14020420 - 13 Jan 2021
Cited by 1 | Viewed by 641
Abstract
Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning [...] Read more.
Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning control into MACS. Specifically, learning feedforward control (LFFC) is implemented as a pattern for incorporation in MACS. The major novelty of this work is that the feedback control part is realized in a real-time periodic MACS, while the LFFC algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS. As a result, a MACS-based LFFC design method has been developed. A second-order B-spline neural network (BSN) is used as a function approximator for LFFC whose input-output mapping can be adapted during control and is intended to become equal to the inverse model of the plant. To provide real-time features for the MACS-based LFFC system, the open robot control software (OROCOS) has been employed as development and runtime environment. A case study using a simulated linear motor in the presence of nonlinear cogging and friction force as well as mass variations is used to illustrate the proposed method. A MACS-based LFFC system has been designed and implemented for the simulated plant. The system consists of a setpoint generator, a feedback controller, and a time-index LFFC that can learn on-line. Simulation results have demonstrated the applicability of the design method. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Influence of Variable Damping Coefficient on Efficiency of TMD with Inerter
Energies 2020, 13(23), 6175; https://doi.org/10.3390/en13236175 - 24 Nov 2020
Cited by 1 | Viewed by 543
Abstract
In this paper, we study the dynamics of a two-degree freedom system consisting of the main body and tuned mass damper with inerter (TMDI). We add the dash-pot with variable damping coefficient to TMDI to study the overall efficiency of the device. We [...] Read more.
In this paper, we study the dynamics of a two-degree freedom system consisting of the main body and tuned mass damper with inerter (TMDI). We add the dash-pot with variable damping coefficient to TMDI to study the overall efficiency of the device. We investigate different types of the non-linear characteristic of the dash-pot. We investigate devices in which damping coefficient change according to the relative displacement or the relative velocity between the damped mass and tuned mass damper. We also include in the investigation of different types of control functions. We show the two-parameter diagrams presenting the main body’s maximum amplitude versus the frequency of excitation of the damped body and different control parameter. We show how the application of a non-linear damper lets us control the main system’s oscillation amplitude. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Particular Methods of Simultaneous Collection of Personal Mobility Research Data from Several Points
Energies 2020, 13(22), 6053; https://doi.org/10.3390/en13226053 - 19 Nov 2020
Viewed by 474
Abstract
Until three or four decades ago, humanity was no longer constrained by the depletion of certain natural resources (especially energy) and the intensified degradation of the natural environment. The consequences of these major crises—such as the economic, financial, and social upheaval of the [...] Read more.
Until three or four decades ago, humanity was no longer constrained by the depletion of certain natural resources (especially energy) and the intensified degradation of the natural environment. The consequences of these major crises—such as the economic, financial, and social upheaval of the world, dramatic climate change, and the entry of politics into a Brownian sarabande—necessitate the transition of civilization to another viable formula. Adequate, timely, and sustainable solutions are being sought, from the subsistence ones to those of economic efficiency. Thus, the mobility revolution is credited as one of the most important levers of change. Starting from the reality that most cars in traffic are not occupied at their maximum capacity, some ideas have already been advanced and even put into practice—“inspired”—which would improve the efficiency in this regard. For example, the reduction in the number of seats in cars and, correspondingly, the considerable reduction in the dimensions of cars are already found in the design of mini-cars and the correlation of identical interests of the self-movement of several people and the integration of this coincidence in a single concurrent mobility formula is already functional through the ride sharing system. Along with intelligent mobility management and the transition to electric and autonomous mobility, streamlining the occupancy of moving cars is seen as a great potential of the mobility revolution. Within the limits of the methodology of data collection in economic statistics, this study proposes a complex technique associated with a convincing tactic of empirical measurement of specific indices of urban traffic issues. The special method is characterized by the simultaneity and plurality of observation points followed by the correlation of the values obtained from the measurement thus performed, with the results from the video recordings taken at the same time. This method will increase the methodological accuracy of data collection in economic statistics. By advancing this method, this study aims to capture the occupancy rates of people in urban vehicle traffic, in different cities, using a combined method. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
Energy and Resource Efficiency in Apatite-Nepheline Ore Waste Processing Using the Digital Twin Approach
Energies 2020, 13(21), 5829; https://doi.org/10.3390/en13215829 - 08 Nov 2020
Cited by 1 | Viewed by 896
Abstract
The paper presents a structure of the digital environment as an integral part of the “digital twin” technology, and stipulates the research to be carried out towards an energy and recourse efficiency technology assessment of phosphorus production from apatite-nepheline ore waste. The problem [...] Read more.
The paper presents a structure of the digital environment as an integral part of the “digital twin” technology, and stipulates the research to be carried out towards an energy and recourse efficiency technology assessment of phosphorus production from apatite-nepheline ore waste. The problem with their processing is acute in the regions of the Russian Arctic shelf, where a large number of mining and processing plants are concentrated; therefore, the study and creation of energy-efficient systems for ore waste disposal is an urgent scientific problem. The subject of the study is the infoware for monitoring phosphorus production. The applied study methods are based on systems theory and system analysis, technical cybernetics, machine learning technologies as well as numerical experiments. The usage of “digital twin” elements to increase the energy and resource efficiency of phosphorus production is determined by the desire to minimize the costs of production modernization by introducing advanced algorithms and computer architectures. The algorithmic part of the proposed tools for energy and resource efficiency optimization is based on the deep neural network apparatus and a previously developed mathematical description of the thermophysical, thermodynamic, chemical, and hydrodynamic processes occurring in the phosphorus production system. The ensemble application of deep neural networks allows for multichannel control over the phosphorus technology process and the implementation of continuous additional training for the networks during the technological system operation, creating a high-precision digital copy, which is used to determine control actions and optimize energy and resource consumption. Algorithmic and software elements are developed for the digital environment, and the results of simulation experiments are presented. The main contribution of the conducted research consists of the proposed structure for technological information processing to optimize the phosphorus production system according to the criteria of energy and resource efficiency, as well as the developed software that implements the optimization parameters of this system. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
A New Virtual Synchronous Generator Design Based on the SMES System for Frequency Stability of Low-Inertia Power Grids
Energies 2020, 13(21), 5641; https://doi.org/10.3390/en13215641 - 28 Oct 2020
Cited by 10 | Viewed by 1109
Abstract
In light of the challenges of integrating more renewable energy sources (RESs) into the utility grid, the virtual synchronous generator (VSG) will become an indispensable configuration of modern power systems. RESs are gradually replacing the conventional synchronous generators that are responsible for supplying [...] Read more.
In light of the challenges of integrating more renewable energy sources (RESs) into the utility grid, the virtual synchronous generator (VSG) will become an indispensable configuration of modern power systems. RESs are gradually replacing the conventional synchronous generators that are responsible for supplying the utility grid with the inertia damping properties, thus renewable power grids are more vulnerable to disruption than traditional power grids. Therefore, the VSG is presented to mimic the behavior of a real synchronous generator in the power grid through the virtual rotor concept (i.e., which emulates the properties of inertia and damping) and virtual primary and secondary controls (i.e., which emulate the conventional frequency control loops). However, inadequate imitation of the inertia power owing to the low and short-term power of the energy storage systems (ESSs) may cause system instability and fail dramatically. To overcome this issue, this paper proposes a VSG based on superconducting magnetic energy storage (SMES) technology to emulate the needed inertia power in a short time and thus stabilizing the system frequency at different disturbances. The proposed VSG based on SMES is applied to improve the frequency stability of a real hybrid power grid, Egyptian Power System (EPS), with high renewables penetration levels, nonlinearities, and uncertainties. The performance superiority of the proposed VSG-based SMES is validated by comparing it with the traditional VSG approach based on battery ESSs. The simulation results demonstrated that the proposed VSG based on the SMES system could significantly promote ultra-low-inertia renewable power systems for several contingencies. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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Article
A Fuzzy-PID Scheme for Low Speed Control of a Vehicle While Going on a Downhill Road
Energies 2020, 13(11), 2795; https://doi.org/10.3390/en13112795 - 01 Jun 2020
Cited by 1 | Viewed by 760
Abstract
We explored a vehicle hill descent control (HDC) system based on an electronic stability program (ESP) and applied this system to brake cars. The experimental results reveal that our system can effectively reduce the workload of a driver during a downhill journey. In [...] Read more.
We explored a vehicle hill descent control (HDC) system based on an electronic stability program (ESP) and applied this system to brake cars. The experimental results reveal that our system can effectively reduce the workload of a driver during a downhill journey. In the first phase of our work, the control strategy of the HDC system based on fuzzy-PID (Proportion Integral Differential) was built by MATLAB/Simulink. Then, the co-simulation based on MATLAB/Simulink, CarSim and AMESim was carried out. Finally, a real vehicle test was conducted to further verify the feasibility of the strategy. A series of simulation experiments and real vehicle tests show that the HDC system can assist the driver to control the vehicle while driving downhill at low speed, thus effectively improving the safety of the vehicle and reducing the workload of driver. Full article
(This article belongs to the Special Issue Intelligent Control for Future Systems)
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