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Algorithms
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Algorithms for PID Controller 2021
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Algorithms for PID Controller 2021

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".

Deadline for manuscript submissions: closed (1 April 2022) | Viewed by 26548

Special Issue Editors

Prof. Dr. Ramiro Barbosa

E-Mail Website
Guest Editor
Institute of Engineering of Porto, Rua Dr. António Bernardino de Almeida, 431, 4249-015 Porto, Portugal
Interests: control; simulation; optimization; fractional calculus; evolutionary algorithms; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Isabel Jesus

E-Mail Website
Guest Editor
Department of Electrical Engineering, Institute of Engineering-Polytechnic of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, 4249-015 Porto, Portugal
Interests: photovoltaic systems; fractional order control systems; fuzzy control systems; evolutionary algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

To date, the PID controller is the most commonly used control algorithm in industry applications. Since its first developments, the PID algorithm has gone hand in hand with the evolution of science and engineering, and new methods and applications have been introduced over time. Advances in recent decades provided by the area of fractional-order control, and more recently by artificial intelligence techniques, have given rise to a refreshing boost to PID control.

This Special Issue aims to present the most recent developments in the theory and applications of PID controllers. The focus is on reporting theoretical and applied research results in control structures, optimization techniques, metaheuristic algorithms, tuning methods, digital implementations, and applications of the PID algorithm, among others, and in the use of current techniques of artificial intelligence such as machine learning, deep learning, and reinforcement learning.

Prof. Dr. Ramiro S. Barbosa
Prof. Dr. Isabel Jesus
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 submissions that pass pre-check are 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. Algorithms is an international peer-reviewed open access monthly 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 1600 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

  • Fractional-order PID controller
  • Fuzzy PID controller
  • Neural PID controller
  • Fuzzy logic
  • Fractional-order control
  • Predictive control
  • Optimization
  • Neural networks
  • Metaheuristic algorithms
  • Neural-fuzzy algorithms
  • Evolutionary algorithms
  • Machine learning
  • Deep learning
  • Digital implementation
  • Reinforcement learning
  • Artificial intelligence

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Published Papers (7 papers)

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Editorial

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2 pages, 172 KiB  
Editorial
Special Issue on Algorithms for PID Controllers 2021
by Ramiro S. Barbosa and Isabel S. Jesus
Algorithms 2023, 16(1), 35; https://doi.org/10.3390/a16010035 - 6 Jan 2023
Cited by 2 | Viewed by 2578
Abstract
The PID is the most common type of algorithm used in control system applications [...] Full article
(This article belongs to the Special Issue Algorithms for PID Controller 2021)

Research

Jump to: Editorial

18 pages, 15693 KiB  
Article
Modeling and Control of IPMC-Based Artificial Eukaryotic Flagellum Swimming Robot: Distributed Actuation
by José Emilio Traver, Cristina Nuevo-Gallardo, Paloma Rodríguez, Inés Tejado and Blas M. Vinagre
Algorithms 2022, 15(6), 181; https://doi.org/10.3390/a15060181 - 25 May 2022
Cited by 8 | Viewed by 2320
Abstract
Ionic polymer-metal composites (IPMCs) are electrically driven materials that undergo bending deformations in the presence of relatively low external voltages, exhibiting a great potential as actuators in applications in soft robotics, microrobotics, and bioengineering, among others. This paper presents an artificial eukaryotic flagellum [...] Read more.
Ionic polymer-metal composites (IPMCs) are electrically driven materials that undergo bending deformations in the presence of relatively low external voltages, exhibiting a great potential as actuators in applications in soft robotics, microrobotics, and bioengineering, among others. This paper presents an artificial eukaryotic flagellum (AEF) swimming robot made up of IPMC segments for the study of planar wave generation for robot propulsion by single and distributed actuation, i.e., considering the first flagellum link as an actuator or all of them, respectively. The robot comprises three independent and electrically isolated actuators, manufactured over the same 10 mm long IPMC sheet. For control purposes, a dynamic model of the robot is firstly obtained through its frequency response, acquired by experimentally measuring the flagellum tip deflection thanks to an optical laser meter. In particular, two structures are considered for such a model, consisting of a non-integer order integrator in series with a resonant system of both non-integer and integer order. Secondly, the identified models are analyzed and it is concluded that the tip displacement of each actuator or any IPMC point is characterized by the same dynamics, which remains unchanged through the link with mere variations of the gain for low-frequency applications. Based on these results, a controller robust to gain variations is tuned to control link deflection regardless of link length and enabling the implementation of a distributed actuation with the same controller design. Finally, the deflection of each link is analyzed to determine whether an AEF swimming robot based on IPMC is capable of generating a planar wave motion by distributed actuation. Full article
(This article belongs to the Special Issue Algorithms for PID Controller 2021)
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14 pages, 495 KiB  
Article
Containment Control of First-Order Multi-Agent Systems under PI Coordination Protocol
by Mingyang Huang, Chenglin Liu and Liang Shan
Algorithms 2021, 14(7), 209; https://doi.org/10.3390/a14070209 - 14 Jul 2021
Cited by 2 | Viewed by 2351
Abstract
This paper investigates the containment control problem of discrete-time first-order multi-agent system composed of multiple leaders and followers, and we propose a proportional-integral (PI) coordination control protocol. Assume that each follower has a directed path to one leader, and we consider several cases [...] Read more.
This paper investigates the containment control problem of discrete-time first-order multi-agent system composed of multiple leaders and followers, and we propose a proportional-integral (PI) coordination control protocol. Assume that each follower has a directed path to one leader, and we consider several cases according to different topologies composed of the followers. Under the general directed topology that has a spanning tree, the frequency-domain analysis method is used to obtain the sufficient convergence condition for the followers achieving the containment-rendezvous that all the followers reach an agreement value in the convex hull formed by the leaders. Specially, a less conservative sufficient condition is obtained for the followers under symmetric and connected topology. Furthermore, it is proved that our proposed protocol drives the followers with unconnected topology to converge to the convex hull of the leaders. Numerical examples show the correctness of the theoretical results. Full article
(This article belongs to the Special Issue Algorithms for PID Controller 2021)
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17 pages, 5639 KiB  
Article
Optimal Coronavirus Optimization Algorithm Based PID Controller for High Performance Brushless DC Motor
by Mohamed A. Shamseldin
Algorithms 2021, 14(7), 193; https://doi.org/10.3390/a14070193 - 25 Jun 2021
Cited by 23 | Viewed by 4085
Abstract
This paper presents an efficient coronavirus optimization algorithm (CVOA) to find the optimal values of the PID controller to track a preselected reference speed of a brushless DC (BLDC) motor under several types of disturbances. This work simulates how the coronavirus (COVID-19) spreads [...] Read more.
This paper presents an efficient coronavirus optimization algorithm (CVOA) to find the optimal values of the PID controller to track a preselected reference speed of a brushless DC (BLDC) motor under several types of disturbances. This work simulates how the coronavirus (COVID-19) spreads and infects healthy people. The initial values of PID controller parameters consider the zero patient, who infects new patients (other values of PID controller parameters). The model aims to simulate as accurately as possible the coronavirus activity. The CVOA has two major advantages compared to other similar strategies. First, the CVOA parameters are already adjusted according to disease statistics to prevent designers from initializing them with arbitrary values. Second, the approach has the ability to finish after several iterations where the infected population initially grows at an exponential rate. The proposed CVOA was investigated with well-known optimization techniques such as the genetic algorithm (GA) and Harmony Search (HS) optimization. A multi-objective function was used to allow the designer to select the desired rise time, the desired settling time, the desired overshoot, and the desired steady-state error. Several tests were performed to investigate the obtained proper values of PID controller parameters. In the first test, the BLDC motor was exposed to sudden load at a steady speed. In the second test, the continuous sinusoidal load was applied to the rotor of the BLDC motor. In the third test, different operating points of reference speed were selected to the rotor of the BLDC motor. The results proved that the CVOA-based PID controller has the best performance among the techniques. In the first test, the CVOA-based PID controller has a minimum rise time (0.0042 s), minimum settling time (0.0079 s), and acceptable overshoot (0.0511%). In the second test, the CVOA-based PID controller has the minimum deviation about the reference speed (±4 RPM). In the third test, the CVOA-based PID controller can accurately track the reference speed among other techniques. Full article
(This article belongs to the Special Issue Algorithms for PID Controller 2021)
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24 pages, 2522 KiB  
Article
Optimised Tuning of a PID-Based Flight Controller for a Medium-Scale Rotorcraft
by Lindokuhle J. Mpanza and Jimoh Olarewaju Pedro
Algorithms 2021, 14(6), 178; https://doi.org/10.3390/a14060178 - 3 Jun 2021
Cited by 9 | Viewed by 3869
Abstract
This paper presents the parameter optimisation of the flight control system of a singlerotor medium-scale rotorcraft. The six degrees-of-freedom (DOF) nonlinear mathematical model of the rotorcraft is developed. This model is then used to develop proportional–integral–derivative (PID)-based controllers. Since the majority of PID [...] Read more.
This paper presents the parameter optimisation of the flight control system of a singlerotor medium-scale rotorcraft. The six degrees-of-freedom (DOF) nonlinear mathematical model of the rotorcraft is developed. This model is then used to develop proportional–integral–derivative (PID)-based controllers. Since the majority of PID controllers installed in industry are poorly tuned, this paper presents a comparison of the optimised tuning of the flight controller parameters using particle swarm optimisation (PSO), genetic algorithm (GA), ant colony optimisation (ACO) and cuckoo search (CS) optimisation algorithms. The aim is to find the best PID parameters that minimise the specified objective function. Two trim conditions are investigated, i.e., hover and 10 m/s forward flight. The four algorithms performed better than manual tuning of the PID controllers. It was found, through numerical simulation, that the ACO algorithm converges the fastest and finds the best gains for the selected objective function in hover trim conditions. However, for 10 m/s forward flight trim, the GA algorithm was found to be the best. Both the tuned flight controllers managed to reject a gust wind of up to 5 m/s in the lateral axis in hover and in forward flight. Full article
(This article belongs to the Special Issue Algorithms for PID Controller 2021)
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14 pages, 2458 KiB  
Article
A PID Parameter Tuning Method Based on the Improved QUATRE Algorithm
by Zhuo-Qiang Zhao, Shi-Jian Liu and Jeng-Shyang Pan
Algorithms 2021, 14(6), 173; https://doi.org/10.3390/a14060173 - 31 May 2021
Cited by 11 | Viewed by 3358
Abstract
The PID (proportional–integral–derivative) controller is the most widely used control method in modern engineering control because it has the characteristics of a simple algorithm structure and easy implementation. The traditional PID controller, in the face of complex control objects, has been unable to [...] Read more.
The PID (proportional–integral–derivative) controller is the most widely used control method in modern engineering control because it has the characteristics of a simple algorithm structure and easy implementation. The traditional PID controller, in the face of complex control objects, has been unable to meet the expected requirements. The emergence of the intelligent algorithm makes intelligent control widely usable. The Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is a new evolutionary algorithm. Compared with other intelligent algorithms, the QUATRE algorithm has a strong global search ability. To improve the accuracy of the algorithm, the adaptive mechanism of online adjusting control parameters was introduced and the linear population reduction strategy was adopted to improve the performance of the algorithm. The standard QUATRE algorithm, particle swarm optimization algorithm and improved QUATRE algorithm were tested by the test function. The experimental results verify the advantages of the improved QUATRE algorithm. The improved QUATRE algorithm was combined with PID parameters, and the simulation results were compared with the PID parameter tuning method based on the particle swarm optimization algorithm and standard QUATRE algorithm. From the experimental results, the control effect of the improved QUATRE algorithm is more effective. Full article
(This article belongs to the Special Issue Algorithms for PID Controller 2021)
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19 pages, 1377 KiB  
Article
Analysis of a Traditional and a Fuzzy Logic Enhanced Perturb and Observe Algorithm for the MPPT of a Photovoltaic System
by Diogo Remoaldo and Isabel Jesus
Algorithms 2021, 14(1), 24; https://doi.org/10.3390/a14010024 - 14 Jan 2021
Cited by 32 | Viewed by 4732
Abstract
This paper presents the results obtained for the maximum power point tracking (MPPT) technique applied to a photovoltaic (PV) system, composed of five solar panels in series using two different methodologies. First, we considered a traditional Perturb and Observe (P&O) algorithm and in [...] Read more.
This paper presents the results obtained for the maximum power point tracking (MPPT) technique applied to a photovoltaic (PV) system, composed of five solar panels in series using two different methodologies. First, we considered a traditional Perturb and Observe (P&O) algorithm and in a second stage we applied a Fuzzy Logic Controller (FLC) that uses fuzzy logic concepts to improve the traditional P&O; both were implemented in a boost converter. The main aim of this paper is to study if an artificial intelligence (AI) based MPPT method, can be more efficient, stable and adaptable than a traditional MPPT method, in varying environment conditions, namely solar irradiation and/or environment temperature and also to analyze their behaviour in steady state conditions. The proposed FLC with a rule base collection of 25 rules outperformed the controller using the traditional P&O algorithm due to its adaptative step size, enabling the FLC to adapt the PV system faster to changing environment conditions, guessing the correct maximum power point (MPP) faster and achieving lower oscillations in steady state conditions, leading to higher generated energy due to lower losses both in steady state and dynamic environment conditions. The simulations in this study were performed using MATLAB (Version 2018)/Simulink. Full article
(This article belongs to the Special Issue Algorithms for PID Controller 2021)
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