scholarly journals FPGA Implementation of PID Controller for the Stabilization of a DC-DC “Buck” Converter

10.5772/39083 ◽  
2012 ◽  
Author(s):  
Eric William ◽  
Jesus Linares-Flores ◽  
Enrique Guzman-Ramirez ◽  
Hebertt Sira-Ramirez
Keyword(s):  
Pid Controller ◽  
Fpga Implementation ◽  
Buck Converter

scholarly journals Swarm-Inspired Algorithms to Optimize a Nonlinear Gaussian Adaptive PID Controller

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3385
Author(s):  
Erickson Puchta ◽  
Priscilla Bassetto ◽  
Lucas Biuk ◽  
Marco Itaborahy Filho ◽  
Attilio Converti ◽  
...  
Keyword(s):  
Pid Controller ◽  
Optimization Algorithms ◽  
Optimization Methods ◽  
Buck Converter ◽  
Algebraic Solution ◽  
Nonlinear Load ◽  
Bee Colony ◽  
Arduous Task ◽  
Whale Optimization

This work deals with metaheuristic optimization algorithms to derive the best parameters for the Gaussian Adaptive PID controller. This controller represents a multimodal problem, where several distinct solutions can achieve similar best performances, and metaheuristics optimization algorithms can behave differently during the optimization process. Finding the correct proportionality between the parameters is an arduous task that often does not have an algebraic solution. The Gaussian functions of each control action have three parameters, resulting in a total of nine parameters to be defined. In this work, we investigate three bio-inspired optimization methods dealing with this problem: Particle Swarm Optimization (PSO), the Artificial Bee Colony (ABC) algorithm, and the Whale Optimization Algorithm (WOA). The computational results considering the Buck converter with a resistive and a nonlinear load as a case study demonstrated that the methods were capable of solving the task. The results are presented and compared, and PSO achieved the best results.

scholarly journals Optimal Fractional PID Controller for Buck Converter Using Cohort Intelligent Algorithm

2021 ◽  
Vol 4 (3) ◽  
pp. 50
Author(s):  
Preeti Warrier ◽  
Pritesh Shah
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Power Converters ◽  
Buck Converter ◽  
Optimization Techniques ◽  
Superior Performance ◽  
Computational Time ◽  
Optimization Approach ◽  
Response Characteristics ◽  
Fractional Order Controller

The control of power converters is difficult due to their non-linear nature and, hence, the quest for smart and efficient controllers is continuous and ongoing. Fractional-order controllers have demonstrated superior performance in power electronic systems in recent years. However, it is a challenge to attain optimal parameters of the fractional-order controller for such types of systems. This article describes the optimal design of a fractional order PID (FOPID) controller for a buck converter using the cohort intelligence (CI) optimization approach. The CI is an artificial intelligence-based socio-inspired meta-heuristic algorithm, which has been inspired by the behavior of a group of candidates called a cohort. The FOPID controller parameters are designed for the minimization of various performance indices, with more emphasis on the integral squared error (ISE) performance index. The FOPID controller shows faster transient and dynamic response characteristics in comparison to the conventional PID controller. Comparison of the proposed method with different optimization techniques like the GA, PSO, ABC, and SA shows good results in lesser computational time. Hence the CI method can be effectively used for the optimal tuning of FOPID controllers, as it gives comparable results to other optimization algorithms at a much faster rate. Such controllers can be optimized for multiple objectives and used in the control of various power converters giving rise to more efficient systems catering to the Industry 4.0 standards.

scholarly journals FPGA–implementation of PID-controller by differential evolution optimization

2018 ◽  
Vol 8 (1) ◽  
pp. 395-402
Author(s):  
Mika Hanhila ◽  
Timo Mantere ◽  
Jarmo T. Alander
Keyword(s):  
Differential Evolution ◽  
Pid Controller ◽  
Differential Evolution Algorithm ◽  
Fpga Implementation ◽  
Solution Convergence ◽  
Fitness Value ◽  
Mutation Operation ◽  
Self Adaptation ◽  
Evolution Algorithm

Abstract We will describe an FPGA implementation of PID-controller that uses differential evolution to optimize the coefficients of the PID controller, which has been implemented in VHDL. The original differential evolution algorithm was improved by ranking based mutation operation and self-adaptation of mutation and crossover parameters. Ranking-based mutation operation improves the quality of solution, convergence rate and success of optimization. Due to the self-adaptive control parameters, the user does not have to estimate the mutation and crossover rates. Optimization have been performed by calculating for each generation fitness value by means of trial parameters. The final optimal parameters are selected based on the minimum fitness.

scholarly journals Design and FPGA Implementation of Immune-PID Controller Based on BBO Algorithm for Heart Rate Regulation

2021 ◽  
Vol 14 (2) ◽  
pp. 432-440
Author(s):  
Eman Mohsin ◽  
◽  
Tariq Tashan ◽  
Ekhlas Karam ◽  
◽  
...  
Keyword(s):  
Heart Rate ◽  
Pid Controller ◽  
Fpga Implementation ◽  
Rate Regulation ◽  
Heart Rate Regulation

scholarly journals Modified Elman Neural-PID Controller Design for DC-DC Buck Converter System Based on Dolphin Echolocation Optimization

2018 ◽  
Vol 14 (3) ◽  
pp. 129-140
Author(s):  
Khulood E. Dagher
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Load Resistance ◽  
Buck Converter ◽  
Minimum Problem ◽  
Portable Devices ◽  
Elman Neural Network ◽  
Pid Controller Design ◽  
On Line ◽  
Local Minimum Problem

This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performance and achieve the desired output. In addition, there is a minimization for the tracking voltage error to zero value of the Buck converter output, especially when changing a load resistance by 10%.

scholarly journals Fractional-Order Approximation and Synthesis of a PID Controller for a Buck Converter

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 629 ◽  
Author(s):  
Allan G. Soriano-Sánchez ◽  
Martín A. Rodríguez-Licea ◽  
Francisco J. Pérez-Pinal ◽  
José A. Vázquez-López
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Order Approximation ◽  
Buck Converter ◽  
Step Response ◽  
Pid Controllers ◽  
Limited Frequency ◽  
Tuning Process ◽  
Band Limited ◽  
Fractional Order Pid

In this paper, the approximation of a fractional-order PIDcontroller is proposed to control a DC–DC converter. The synthesis and tuning process of the non-integer PID controller is described step by step. A biquadratic approximation is used to produce a flat phase response in a band-limited frequency spectrum. The proposed method takes into consideration both robustness and desired closed-loop characteristics, keeping the tuning process simple. The transfer function of the fractional-order PID controller and its time domain representation are described and analyzed. The step response of the fractional-order PID approximation shows a faster and stable regulation capacity. The comparison between typical PID controllers and the non-integer PID controller is provided to quantify the regulation speed introduced by the fractional-order PID approximation. Numerical simulations are provided to corroborate the effectiveness of the non-integer PID controller.

Improvement of Buck Converter Performance Using Artificial Bee Colony Optimized-PID Controller

2015 ◽  
pp. 304-310 ◽  
Author(s):  
Yusuf Sonmez ◽  
Ozcan Ayyildiz ◽  
H. Tolga Kahraman ◽  
Ugur Guvenc ◽  
Serhat Duman
Keyword(s):  
Pid Controller ◽  
Artificial Bee Colony ◽  
Buck Converter ◽  
Bee Colony

Design and Realization of Stand-Alone Digital Fractional Order PID Controller for Buck Converter Fed DC Motor

2016 ◽  
Vol 35 (6) ◽  
pp. 2189-2211 ◽  
Author(s):  
Swapnil Khubalkar ◽  
Amit Chopade ◽  
Anjali Junghare ◽  
Mohan Aware ◽  
Shantanu Das
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Dc Motor ◽  
Buck Converter ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller
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