Special Issue "Control and Soft Computing"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 April 2020.

Special Issue Editors

Prof. Dr. Rui Araújo
E-Mail Website
Guest Editor
Institute of Systems and Robotics (ISR-UC), Department of Electrical and Computer Engineering (DEEC-UC), University of Coimbra, 3004-531 Coimbra, Portugal
Interests: computational intelligence; intelligent control; fuzzy systems; neural networks; estimation; control; robotics; mobile robotics and intelligent vehicles; real-time systems
Dr. Jérôme Mendes
E-Mail Website
Guest Editor
Institute of Systems and Robotics, University of Coimbra, 3004-531 Coimbra, Portugal
Interests: computational intelligence; intelligent control; fault detection/diagnosis; evolving systems
Dr. Francisco A. A. Souza
E-Mail Website
Guest Editor
1. Institute of Systems and Robotics, University of Coimbra, 3004-531 Coimbra, Portugal
2. Oncontrol Technologies, LDA, 3004-531 Coimbra, Portugal
Interests: applied machine learning; industrial systems; process control

Special Issue Information

Dear Colleagues,

Recent advances in control and soft computing systems have brought new levels of real-life applications in a wide range of areas, including control of industrial systems, internet of things (IoT), cyber-physical systems, smart grids, power and energy systems, biomedical engineering, and so on. The complexity and amount of data underlying the industrial processes have increased during the recent years, mainly with the advent of the industry 4.0 paradigm, thus requiring advanced strategies to cope with them. Soft computing techniques, as opposed to traditional computing, have been demonstrated to be a useful tool to translate the data and complexity of modern industrial systems into useful information, which can be, for example, used to help to process control and optimization, and process understanding.

This Special Issue intends to disseminate the recent developments on the topics of process control and soft computing, with an emphasis on, but not limited to, industrial systems. This being a multidisciplinary Special Issue, papers that have as main topic advanced techniques for control and soft computing algorithms are welcome, as well applications on:

  • Modern control in the various industries;
  • Computational intelligence methodologies for intelligent control and identification;
  • Failure detection and predictive maintenance;
  • Automatic decision making;
  • Soft/virtual sensors;
  • Internet of things (IoT);
  • Cyber-physical systems;
  • Smart grids;
  • Intelligent robotics;
  • Human–robot interaction;
  • Power and energy systems;
  • Smart manufacturing;
  • Biomedical engineering.

Prof. Dr. Rui Araújo
Dr. Jérôme Mendes
Dr. Francisco A. A. Souza
Guest Editors

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. Applied Sciences 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 1500 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

  • Adaptive control
  • Distributed control
  • Networked control
  • Intelligent and AI based control (fuzzy systems, neural networks, evolutionary)
  • Optimization and robust control
  • Fault detection and control
  • Biologically inspired evolutionary algorithms
  • Fuzzy systems and neural networks
  • Evolving/iterative/self-organizing soft computing algorithms
  • Machine learning
  • Autonomous systems
  • Intelligent decision systems
  • Reinforcement and deep-learning
  • Clustering algorithms
  • Modeling
  • Soft sensors
  • Smart manufacturing and Industry 4.0
  • Robotics

Published Papers (4 papers)

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Research

Open AccessArticle
Physics-Based Vehicle Simulation Using PD Servo
Appl. Sci. 2019, 9(22), 4949; https://doi.org/10.3390/app9224949 - 17 Nov 2019
Abstract
In this paper, we introduce a novel system for physics-based vehicle simulation from input trajectory. The proposed system approximates the physical movements of a real vehicle using a proportional derivative (PD) servo which estimates proper torques for wheels and controls a vehicle’s acceleration [...] Read more.
In this paper, we introduce a novel system for physics-based vehicle simulation from input trajectory. The proposed system approximates the physical movements of a real vehicle using a proportional derivative (PD) servo which estimates proper torques for wheels and controls a vehicle’s acceleration based on the conditions of the given trajectory. To avoid expensive simulation calculation, the input trajectory is segmented and compared to the optimized trajectories stored in a path library. Based on the similarity of the curve shape between the input and simulated trajectories, an iterative search method is introduced to generate a physically derivable trajectory for convincing simulation results. For an interaction with other objects in the virtual environment, the surface of the vehicle is subdivided into several parts and deformed individually from external forces. As demonstrated in the experimental results, the proposed system can create diverse traffic scenes with multiple vehicles in a fully automated way. Full article
(This article belongs to the Special Issue Control and Soft Computing)
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Open AccessArticle
Research on Optimal Landing Trajectory Planning Method between an UAV and a Moving Vessel
Appl. Sci. 2019, 9(18), 3708; https://doi.org/10.3390/app9183708 - 06 Sep 2019
Abstract
The location, velocity, and flight path angle of an autonomous unmanned aerial vehicle (UAV) landing on a moving vessel are key factors for an optimal landing trajectory. To tackle this challenge, this paper proposes a method for calculating the optimal approach landing trajectory [...] Read more.
The location, velocity, and flight path angle of an autonomous unmanned aerial vehicle (UAV) landing on a moving vessel are key factors for an optimal landing trajectory. To tackle this challenge, this paper proposes a method for calculating the optimal approach landing trajectory between an UAV and a small vessel. A numerical approach (iterative method) is used to calculate the optimal approach landing trajectory, and the initial lead is introduced in the calculation process of the UAV trajectory for the inclination and heading angle for accuracy improvement, so that the UAV can track and calculate the optimal landing trajectory with high precision. Compared with the variational method, the proposed method can calculate an optimal turning direction angle for the UAV during the landing. Simulation experiments verify the effectiveness of the proposed algorithm and give optimal initialization values. Full article
(This article belongs to the Special Issue Control and Soft Computing)
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Open AccessArticle
Adaptive Backstepping Fractional Fuzzy Sliding Mode Control of Active Power Filter
Appl. Sci. 2019, 9(16), 3383; https://doi.org/10.3390/app9163383 - 16 Aug 2019
Cited by 1
Abstract
An adaptive fractional-order fuzzy control method for a three-phase active power filter (APF) using a backstepping and sliding mode controller is developed for the purpose of compensating harmonic current and stabilizing the DC voltage quickly. The dynamic model of APF is changed to [...] Read more.
An adaptive fractional-order fuzzy control method for a three-phase active power filter (APF) using a backstepping and sliding mode controller is developed for the purpose of compensating harmonic current and stabilizing the DC voltage quickly. The dynamic model of APF is changed to an analogical cascade system for the convenience of the backstepping strategy. Then a fractional-order sliding mode surface is designed and a fuzzy controller is proposed to approximate the unknown term in the controller, where parameters can be adjusted online. The simulation experiments are conducted and investigated using MATLAB/SIMULINK software package to verify the advantage of the proposed controller. Furthermore, the comparison study between the fractional-order controller and integer-order one is also conducted in order to demonstrate the better performance of the proposed controller in total harmonic distortion (THD), a significant index to evaluate the current quality in the smart grid. Full article
(This article belongs to the Special Issue Control and Soft Computing)
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Open AccessArticle
Pursuer’s Control Strategy for Orbital Pursuit-Evasion-Defense Game with Continuous Low Thrust Propulsion
Appl. Sci. 2019, 9(15), 3190; https://doi.org/10.3390/app9153190 - 05 Aug 2019
Abstract
This paper studies the orbital pursuit-evasion-defense problem with the continuous low thrust propulsion. A control strategy for the pursuer is proposed based on the fuzzy comprehensive evaluation and the differential game. First, the system is described by the Lawden’s equations, and simplified by [...] Read more.
This paper studies the orbital pursuit-evasion-defense problem with the continuous low thrust propulsion. A control strategy for the pursuer is proposed based on the fuzzy comprehensive evaluation and the differential game. First, the system is described by the Lawden’s equations, and simplified by introducing the relative state variables and the zero effort miss (ZEM) variables. Then, the objective function of the pursuer is designed based on the fuzzy comprehensive evaluation, and the analytical necessary conditions for the optimal control strategy are presented. Finally, a hybrid method combining the multi-objective genetic algorithm and the multiple shooting method is proposed to obtain the solution of the orbital pursuit-evasion-defense problem. The simulation results show that the proposed control strategy can handle the orbital pursuit-evasion-defense problem effectively. Full article
(This article belongs to the Special Issue Control and Soft Computing)
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