Optimal Fractional-Order PI Control Design for a Variable Speed PMSG-Based Wind Turbine

© 2021 IIETA. . This is an open access article distributed under the Creative Commons Attribution License, to view a copy of the license, see: https://creativecommons.org/licenses/by/4.0/This paper focusses on the design of optimal control strategies for a variable-speed wind energy system based on Permanent Magnet Synchronous Generator (PMSG). The fractional order PI controller, denoted PIλ, is an extension of the classical PI controller, which provides greater flexibility, better performance and robustness, however the tuning of the controller parameters is challenging. In this work, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) provide approximate solutions to various problems and form a good optimization. In our system, they are used to have the PI regulator parameters and tune the parameters of the proposed controllers. The proposed controllers have been applied as maximum power point (MPPT) controllers for the wind turbine and to regulate the PMGS currents under variable weather conditions and. The results show that, among all these controllers, the fractional order PI controller optimized by the PSO leads to better performance in terms of the transient response characteristics such overshoot, rise time and settling time.Peer reviewedFinal Published versio

DE-based tuning of PIλDμ controllers

A new method that relies on evolutionary computation concepts is proposed in this paper to tune the parameters of fractional order PIlambdaDmu controllers, in which the orders of the integral and derivative parts, lambda and mu, respectively, are fractional. The main advantage of the fractional order controllers is that the increase in the number of parameters in the controller allows an increase in the number of control specifications that can be met. A Differential Evolution (DE) algorithm is proposed to make the controlled system fulfill different design specifications in time and frequency domains. This method is based on the minimization of a fitness function. Experiments have been carried out in simulation and in a real DC motor platform. The results illustrate the effectiveness of this method.Publicad

Intelligent position control for intelligent Pneumatic actuator with ball-beam (IPABB) system

A pneumatic actuator system is considered extremely nonlinear, making accurate position control of this actuator difficult to obtain. In this article, a novel cascade fractional-order PID (CFOPID) controller for the intelligent pneumatic actuator (IPA) positioning system utilizing particle swarm optimization (PSO) is presented. The pneumatic system was modeled using the system identification (SI) technique. To demonstrate the effectiveness of the CFOPID controller, a comparison to the FOPID controller is performed based on the rise, settling, and peak times, peak overshoot, and integral of square error (ISE). From the results obtained, the proposed CFOPID controller provides superior control over the FOPID controller. For the application of the position controller, the proposed system incorporates an intelligent pneumatic actuated ball and beam (IPABB) system. The mathematical model of the system was developed and validated through a simulation utilizing a PID (outer loop) and CFOPID controller (inner loop). The suggested controller’s accuracy and robustness have been studied by a comparative examination of the results obtained utilizing the proposed and other prior controllers on the same system. The results indicate that the intelligent pneumatic actuator, when coupled with a CFOPID controller, is capable of controlling the positioning of the ball and beam system

Satisfactory optimization design for fractional order PID controller

Copyright © 2019 ASME. This paper presents a new parameters optimization approach for fractional order PID controllers, which uses a satisfactory optimization model. To fulfill different design performance specfications and constrains of systems, the application of multi-criterion satisfactory optimization to fractional control systems is considered. At the same time, the performance of fractional control systems controlled by fractional order controller and integer order controller is discussed. The simulation illustrates the effectiveness of the proposed method and the superiority of the fractional order controller in both time domain and frequency domain

Rotational speed control of multirotor UAV's propulsion unit based on fractional-order PI controller

In this paper the synthesis of a rotational speed closed-loop control system based on a fractional-order proportional-integral (FOPI) controller is presented. In particular, it is proposed the use of the SCoMR-FOPI procedure as the controller tuning method for an unmanned aerial vehicle’s propulsion unit. In this framework, both the Hermite-Biehler and Pontryagin theorems are used to predefine a stability region for the controller. Several simulations were conducted in order to try to answer the questions – is the FOPI controller good enough to be an alternative to more complex FOPID controllers? In what circumstances can it be advantageous over the ubiquitous PID? How robust this fractional-order controller is regarding the parametric uncertainty of considered propulsion unit model?info:eu-repo/semantics/publishedVersio

Fractional control of heat diffusion systems

The concept of differentiation and integration to non-integer order has its origins in the seventeen century. However, only in the second-half of the twenty century appeared the first applications related to the area of control theory. In this paper we consider the study of a heat diffusion system based on the application of the fractional calculus concepts. In this perspective, several control methodologies are investigated and compared. Simulations are presented assessing the performance of the proposed fractional-order algorithms