Tuning of Optimal Classical and Fractional Order PID Parameters forAutomatic Generation Control Based on the Bacterial Swarm Optimization (original) (raw)
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Owing to the superior transient and steady-state performance of the fractional-order proportional-integral-derivative (FOPID) controller over its conventional counterpart, this paper exploited its application in an automatic voltage regulator (AVR) system. Since the FOPID controller contains two more control parameters (µ and λ ) as compared to the conventional PID controller, its tuning process was comparatively more complex. Thus, the intelligence of one of the most recently developed metaheuristic algorithms, called the salp swarm optimization algorithm (SSA), was utilized to select the optimized parameters of the FOPID controller in order to achieve the optimal dynamic response and enhanced stability of the studied AVR system. To validate the effectiveness of the proposed method, its performance was compared with that of the recently used tuning methods for the same system configuration and operating conditions. Furthermore, a stability analysis was carried out using pole-zero a...
Fractional Order Fuzzy PID Controller for Automatic Generation Control of Power Systems
ECTI Transactions on Electrical Engineering, Electronics, and Communications, 2021
In this study, a Hybrid Adaptive Differential Evolution and Pattern Search (hADE-PS) tuned Fractional Order Fuzzy PID (FOFPID) structure is suggested for AGC of power systems. At first, a non-reheat type two-area thermal system is considered and the improvement of the proposed approach over Bacteria Foraging Optimization Algorithm (BFOA), Teaching Learning Based Optimization (TLBO), Jaya Algorithm (JA), Genetic Algorithm (GA) and Hybrid BFOA and Particle Swarm Optimization Algorithm (hBFOA-PSO) for the identical test systems has been demonstrated. The analysis was then extended to interconnected thermal power system of reheat type and two-area six-unit system. The results are compared with Firefly Algorithm (FA), Symbiotic Organism Search Algorithm (SOSA) and Artificial Bee colony (ABC) for second test system and TLBO, Hybrid Stochastic Fractal Search and Local Unimodal Sampling (hSFS-LUS), ADE and hADE-PS tuned PID for third test system. Finally, robustness of the suggested control...
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DESIGN OF FRACTIONAL ORDER PID CONTROLLER BASED PARTICLE SWARM
Fractional order PID (FOPID) controller is a special kind of PID controller whose derivative and integral order are fractional rather than integer which has five parameters to be tuned. This paper presents study of the implementation of tuning method and performance enhancement of the closed loop system by use of the fractional order PID (PI λ D μ) controller utilizing a MATLAB/Simulink. The tuning methods for these type controllers have many mixed tools of the available optimization methods and update artificial optimization methods in the design. In this paper particle swarm optimization has been implemented to design FOPID controller in which the unknown parameters are determined minimizing a given integral of time weighted absolute error (ITAE). The main specification of this paper is that the all five parameters of (PI λ D μ) have been found directly without spreading the steps. It has been shown that the response and performance of the closed loop system with FOPID controller is much better than integer order PID controller for the same system and with better robustness.
Electrical Engineering & Electromechanics, 2020
This paper investigates the use of fractional order Proportional, Integral and Derivative (FOPID) controllers for the frequency and power regulation in a microgrid power system. The proposed microgrid system composes of renewable energy resources such as solar and wind generators, diesel engine generators as a secondary source to support the principle generators, and along with different energy storage devices like fuel cell, battery and flywheel. Due to the intermittent nature of integrated renewable energy like wind turbine and photovoltaic generators, which depend on the weather conditions and climate change this affects the microgrid stability by considered fluctuation in frequency and power deviations which can be improved using the selected controller. The fractional-order controller has five parameters in comparison with the classical PID controller, and that makes it more flexible and robust against the microgrid perturbation. The Fractional Order PID controller parameters are optimized using a new optimization technique called Krill Herd which selected as a suitable optimization method in comparison with other techniques like Particle Swarm Optimization. The results show better performance of this system using the fractional order PID controller-based Krill Herd algorithm by eliminates the fluctuations in frequency and power deviation in comparison with the classical PID controller. The obtained results are compared with the fractional order PID controller optimized using Particle Swarm Optimization. The proposed system is simulated under nominal conditions and using the disconnecting of storage devices like battery and Flywheel system in order to test the robustness of the proposed methods and the obtained results are compared. References 18, figures 8.
An Optimal Fractional Order Controller for an AVR System Using Particle Swarm Optimization Algorithm
Conference on Power Engineering Large Engineering Systems, 2007
Application of fractional order PID (FOPID) controller to an automatic voltage regulator (AVR) is presented and studied in this paper. An FOPID is a PID whose derivative and integral orders are fractional numbers rather than integers. Design stage of such a controller consists of determining five parameters. This paper employs particle swarm optimization (PSO) algorithm to carry out the aforementioned
Comparison Between PID and FOPID Controllers Based on Particle Swarm Optimization
The intelligent optimization method for designing Fractional Order ( PIλDδ ) controller (FOPID) based on Particle Swarm Optimization (PSO) is used in this paper . The Fractional Order ( PIλDδ ) controller (FOPID) same as conventional PID controller but integral order (λ) and derivative order (δ) are fractional. The new and good performance extension for FOPID can be provided by Fractional calculus because of the flexibility order of fractional calculus. The Fractional Order ( PIλDδ ) controller (FOPID) and conventional PID controller are applied to the three problems (stable, unstable and non-minimum phase systems). The parameters of FOPID comprise proportionality constant, integral constant, derivative constant, integral order (λ) and derivative order (δ). The design of ( PIλDδ ) controller needs to optimize five parameters while the design of conventional PID controller needs only three parameters to optimize. Therefore, the task of designing FOPID controller is more challenger th...
Evaluations of Optimum Value of PID Controller Gains Using Hybrid Bacterial Swarm Optimization
In the control system problems it is challenging to find the PID parameters in the initial stage, and there fine tuning during the system run condition. In this paper we have test the application of hybrid bacterial foraging and particle swarm optimization algorithm named as bacterial swarm optimization BSO) based PID parameter tuning of close loop controller. The objective is dependent on globally minimal error squared error integral criteria of the step response of second order and higher order plants cascaded with PID controller by our proposed method. In this algorithm parameters are found by evolutionary methods with consideration of the globally optimal solution for control applications. The Kp, Ki and Kd gains are calculated by the PSO and (BSO) methods for plants with all the poles of the transfer function located in the left half of the s-plane. The performance of both algorithms is analyzed on transfer functions of a second order and higher order plants.