Genetic Algorithm-Optimized PID Controller for Better Performance of PV System

2016 ◽  
Author(s):  
Roshdy Abdelrassoul ◽  
Yosra Ali ◽  
Mohamed Saad Zaghloul
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Pv System

scholarly journals Genetic Algorithm-Optimized PID Controller for better Performance of PV System

2016 ◽  
Vol 5 (9) ◽  
pp. 55-60 ◽  
Author(s):  
Roshdy Abdelrassoul ◽  
Yosra Ali ◽  
Mohamed Saad
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Pv System

scholarly journals Data-Driven Tuning of PID Controlled Piezoelectric Ultrasonic Motor

Actuators ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 148
Author(s):  
Sarah Makarem ◽  
Bülent Delibas ◽  
Burhanettin Koc
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Good Alternative ◽  
Data Driven ◽  
Grid Search ◽  
Single Source ◽  
Dual Frequency ◽  
Dual Source ◽  
Stage System ◽  
Piezoelectric Ultrasonic Motor

Ultrasonic motors employ resonance to amplify the vibrations of piezoelectric actuator, offering precise positioning and relatively long travel distances and making them ideal for robotic, optical, metrology and medical applications. As operating in resonance and force transfer through friction lead to nonlinear characteristics like creep and hysteresis, it is difficult to apply model-based control, so data-driven control offers a good alternative. Data-driven techniques are used here for iterative feedback tuning of a proportional integral derivative (PID) controller parameters and comparing between different motor driving techniques, single source and dual source dual frequency (DSDF). The controller and stage system used are both produced by the company Physik Instrumente GmbH, where a PID controller is tuned with the help of four search methods: grid search, Luus–Jaakola method, genetic algorithm, and a new hybrid method developed that combines elements of grid search and Luus–Jaakola method. The latter method was found to be quick to converge and produced consistent result, similar to the Luus–Jaakola method. Genetic Algorithm was much slower and produced sub optimal results. The grid search has also proven the DSDF driving method to be robust, less parameter dependent, and produces far less integral position error than the single source driving method.

PSO-Based Tunning of PID Controller for Speed Control of DC Motor

2014 ◽  
Vol 7 (3) ◽  
pp. 65-79
Author(s):  
Ibrahem S. Fatah
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Pid Controller ◽  
Dc Motor ◽  
Proportional Integral Derivative ◽  
Stable Convergence ◽  
Swarm Optimization ◽  
Tuning Parameters ◽  
Pid Controller Tuning ◽  
Rising Time

In this paper, a Proportional-Integral-Derivative (PID) controller of DC motor is designed by using particle swarm optimization (PSO) strategy for formative optimal PID controller tuning parameters. The proposed approach has superior feature, including easy implementation, stable convergence characteristics and very good computational performances efficiency. The DC Motor Scheduling PID-PSO controller is modeled in MATLAB environment. Comparing with conventional PID controller using Genetic Algorithm, the planned method is more proficient in improving the speed loop response stability, the steady state error is reduced, the rising time is perfected and the change of the required input do not affect the performances of driving motor with no overtaking.

scholarly journals Optimization and comparative analysis of PID and FOPID controller for BLDC motor

2019 ◽  
Vol 8 (3) ◽  
pp. 174
Author(s):  
P. Vimala ◽  
C. R. Balamurugan ◽  
A. Subramanian ◽  
T. Vishwanath
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Input Signal ◽  
Pid Controller ◽  
Input Voltage ◽  
Bldc Motor ◽  
Phase Inverter ◽  
Three Phase ◽  
The Stability ◽  
Three Phase Inverter

The FOPID and PID controller are designed to control the speed of <br /> the BLDC motor. The parameters , , , λ and µ of these controller are optimized based on genetic algorithm. The optimized coefficients keep in track with zero error signals. The output of the controller is given to the variable dc source which varies the input voltage to the three phase inverter depending on the input signal. The three phase inverter gives the voltage to the BLDC motor which enhances the stability of the system. <br /> The effectiveness of the controller is demonstrated by simulation.

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