PID CONTROLLER DESIGN FOR DECENTRALIZED TITO PROCESS USING MODIFIED DIFFERENTIAL EVOLUTION ALGORITHM

2021 ◽  
Vol 49 (3) ◽  
Author(s):  
Jailsingh Bhookya ◽  
Ravi Kumar Jatoth
Keyword(s):  
Differential Evolution ◽  
Pid Controller ◽  
Controller Design ◽  
Differential Evolution Algorithm ◽  
Pid Controller Design ◽  
Evolution Algorithm

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.

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