Advances in Fractional-Order PID Controllers

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Engineering".

Deadline for manuscript submissions: closed (12 December 2022) | Viewed by 10145

Special Issue Editor


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Guest Editor
Department of Cybernetics, University of West Bohemia, 301 00 Pilsen, Czech Republic
Interests: automatic control; fractional control; embedded systems; robotics; process control; fractional-order systems; Kalman filtering; MATLAB simulation; system modeling; mechatronics; industrial automation; robotics.
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Special Issue Information

Dear Colleagues,

Fractional calculus was introduced as a pure mathematical concept by Leibnitz in the 17th century, but the idea of fractional order control has been known since the end of 19th century. Nevertheless, it was not until Podlubny’s seminal paper which introduced the concept of fractional-order PID controllers that interest began to grow exponentially in the field. In recent decades, there has been a growing number of research works related to fractional control systems and specifically fractional-order PID controllers. These controllers can provide more flexibility in control loop shaping, namely in the frequency domain, and there is a clear physical interpretation of all their parameters. However, a predominant problem remains regarding their cost-effective industrial implementation, and researchers are looking for an “ideal fractional-order PID controller building block”. Indeed, research is ongoing in fractional-order PID design and optimization tools and special math libraries for numerical simulation. Based on the latest developments in embedded HW, novel architectures for fractional controller implementation have emerged, e.g., based on FPGAs. 

Contributions should fit the scope of the journal Fractal and Fractional, and topics of interest include (but are not limited to):

  • Fractional-order PID controllers
  • Fractional-order PID controller optimization
  • Fractional-order PID controller tuning and autotuning
  • Fractional-order PID controller implementation (continuous and discrete)
  • Fractional-order PID controller industrialization
  • Advanced HW architectures for fractional-order PID controllers (e.g., FPGA-based)
  • Interactive design tools and SW libraries for fractional-order PID controllers
  • Analogue implementation of fraction-order PID controllers
  • Robust fractional-order control
  • Stability of fractional-order control systems
  • New application domain for fractional control and fractional PID control
  • Control oriented fractional calculus and theory
  • Fractional-order control systems
  • Numerical simulation of fractional-order control systems
  • System identification for fractional-order control
  • Fractional order control performance assessment

Dr. Martin Čech
Guest Editor

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Keywords

  • fractional-order PID controller
  • fuzzy PID controller
  • neural PID controller
  • fractional-order control
  • stability analysis
  • optimization
  • neural networks

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Published Papers (4 papers)

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Research

22 pages, 6980 KiB  
Article
Modified FOPID Controller for Frequency Regulation of a Hybrid Interconnected System of Conventional and Renewable Energy Sources
by Amil Daraz, Suheel Abdullah Malik, Abdul Basit, Sheraz Aslam and Guoqiang Zhang
Fractal Fract. 2023, 7(1), 89; https://doi.org/10.3390/fractalfract7010089 - 13 Jan 2023
Cited by 41 | Viewed by 2983
Abstract
In this article, a fractional-order proportional-integral-differential (FOPID) controller and its modified structure, called a MFOPID controller, are presented. To guarantee optimal system performance, the gains of the proposed FOPID and MFOPID controllers are well-tuned, employing the Jellyfish Search Optimizer (JSO), a novel and [...] Read more.
In this article, a fractional-order proportional-integral-differential (FOPID) controller and its modified structure, called a MFOPID controller, are presented. To guarantee optimal system performance, the gains of the proposed FOPID and MFOPID controllers are well-tuned, employing the Jellyfish Search Optimizer (JSO), a novel and highly effective bioinspired metaheuristic approach. The proposed controllers are assessed in a hybrid system with two domains, where each domain contains a hybrid of conventional (gas, reheat, and hydro) and renewable generation sources (solar and wind). For a more realistic analysis, the presented system model includes practical limitations with nonlinear characteristics, such as governor dead zone/band (GDZ/GDB), boiler dynamics, generation rate limitation/constraint (GRL/GRC), system uncertainties, communication time delay (CTD), and load changes. The suggested methodology outperforms some newly developed heuristic techniques, including fitness-dependent optimizer (FDO), sine-cosine algorithm (SCA), and firefly algorithm (FA), for the interconnected power system (PS) of two regions with multiple generating units. Furthermore, the proposed MFOPID controller is compared with JSO-tuned PID/FOPID and PI controllers to ascertain its superiority. The results signify that the presented control method and its parametric optimization significantly outperforms the other control strategies with respect to minimum undershoot and peak overshoot, settling times, and ITSE in the system’s dynamic response. The sensitivity analysis outcomes imply that the proposed JSO-MFOPID control method is very reliable and can effectively stabilize the load frequency and interconnection line in a multi-area network with interconnected PS. Full article
(This article belongs to the Special Issue Advances in Fractional-Order PID Controllers)
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23 pages, 9366 KiB  
Article
Optimal PID Controllers for AVR Systems Using Hybrid Simulated Annealing and Gorilla Troops Optimization
by Sultan Alghamdi, Hatem F. Sindi, Muhyaddin Rawa, Abdullah A. Alhussainy, Martin Calasan, Mihailo Micev, Ziad M. Ali and Shady H. E. Abdel Aleem
Fractal Fract. 2022, 6(11), 682; https://doi.org/10.3390/fractalfract6110682 - 18 Nov 2022
Cited by 19 | Viewed by 2114
Abstract
In the literature, all investigations dealing with regulator design in the AVR loop observe the AVR system as a single input single output (SISO) system, where the input is the generator reference voltage, while the output is the generator voltage. Besides, the regulator [...] Read more.
In the literature, all investigations dealing with regulator design in the AVR loop observe the AVR system as a single input single output (SISO) system, where the input is the generator reference voltage, while the output is the generator voltage. Besides, the regulator parameters are determined by analyzing the terminal generator voltage response for a step change from zero to the rated value of the generator voltage reference. Unlike literature approaches, in this study, tuning of the AVR controllers is conducted while modeling the AVR system as a double input single output (DISO) system, where the inputs are the setpoint of the generator voltage and the step disturbance on the excitation voltage, while the output is the generator voltage. The transfer functions of the generator voltage dependence on the generator voltage reference value and the excitation voltage change were derived in the developed DISO-AVR model. A novel objective function for estimating DISO-AVR regulator parameters is proposed. Also, a novel metaheuristic algorithm named hybrid simulated annealing and gorilla troops optimization is employed to solve the optimization problem. Many literature approaches are compared using different regulator structures and practical limitations. Furthermore, the experimental results of 120 MVA synchronous generators in HPP Piva (Montenegro) are presented to show the drawbacks of the literature approaches that observe generator setpoint voltage change from zero to the rated value. Based on the presented results, the proposed procedure is efficient and strongly applicable in practice. Full article
(This article belongs to the Special Issue Advances in Fractional-Order PID Controllers)
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16 pages, 5102 KiB  
Article
A Fractional-Order On-Line Self Optimizing Control Framework and a Benchmark Control System Accelerated Using Fractional-Order Stochasticity
by Jairo Viola and YangQuan Chen
Fractal Fract. 2022, 6(10), 549; https://doi.org/10.3390/fractalfract6100549 - 28 Sep 2022
Cited by 4 | Viewed by 2170
Abstract
This paper presents a design and evaluation of a fractional-order self optimizing control (FOSOC) architecture for process control. It is based on a real-time derivative-free optimization layer that adjusts the parameters of a discrete-time fractional-order proportional integral (FOPI) controller according to an economic [...] Read more.
This paper presents a design and evaluation of a fractional-order self optimizing control (FOSOC) architecture for process control. It is based on a real-time derivative-free optimization layer that adjusts the parameters of a discrete-time fractional-order proportional integral (FOPI) controller according to an economic cost function. A simulation benchmark is designed to assess the performance of the FOSOC controller based on a first order plus dead time system. Similarly, an acceleration mechanism is proposed for the fractional-order self optimizing control framework employing fractional-order Gaussian noise with long-range dependence given by the Hurst exponent. The obtained results show that the FOSOC controller can improve the system closed-loop response under different operating conditions and reduce the convergence time of the real-time derivative-free optimization algorithm by using fractional-order stochasticity. Full article
(This article belongs to the Special Issue Advances in Fractional-Order PID Controllers)
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16 pages, 1234 KiB  
Article
FOPI/FOPID Tuning Rule Based on a Fractional Order Model for the Process
by Helber Meneses, Orlando Arrieta, Fabrizio Padula, Antonio Visioli and Ramon Vilanova
Fractal Fract. 2022, 6(9), 478; https://doi.org/10.3390/fractalfract6090478 - 29 Aug 2022
Cited by 10 | Viewed by 1820
Abstract
This paper deals with the design of a control system based on fractional order models and fractional order proportional-integral-derivative (FOPID) controllers and fractional-order proportional-integral (FOPI) controllers. The controller design takes into account the trade-off between robustness and performance as well as the trade-off [...] Read more.
This paper deals with the design of a control system based on fractional order models and fractional order proportional-integral-derivative (FOPID) controllers and fractional-order proportional-integral (FOPI) controllers. The controller design takes into account the trade-off between robustness and performance as well as the trade-off between the load disturbance rejection and set-point tracking tasks. The fractional order process model is able to represent an extensive range of dynamics, including over-damped and oscillatory behaviors and this simplifies the process modelling. The tuning of the FOPID and FOPI controllers is achieved by using an optimization, as a first step, and in a second step, several fitting functions were used to capture the behavior of the optimal parameters of the controllers. In this way, a new set of tuning rules called FOMCoRoT (Fractional Order Model and Controllers Robust Tuning) is obtained for both FOPID and FOPI controllers. Simulation examples show the effectiveness of the proposed control strategy based on fractional calculus. Full article
(This article belongs to the Special Issue Advances in Fractional-Order PID Controllers)
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