Open AccessObjective functions modification of GA optimized PID controller for brushed DC motor
Author(s) -
A. A. M. Zahir,
S. S. N. Alhady,
Aeizaal Azman A. Wahab,
Musyaffa' Ahmad
Publication year - 2020
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v10i3.pp2426-2433
Subject(s) - settling time , overshoot (microwave communication) , control theory (sociology) , pid controller , mean squared error , computer science , approximation error , rise time , steady state (chemistry) , genetic algorithm , step response , algorithm , mathematics , statistics , temperature control , artificial intelligence , control engineering , voltage , machine learning , control (management) , telecommunications , engineering , chemistry , electrical engineering
PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteria show improvement in all performance parameter after being modified. All of the error criteria produce 0% overshoot, 29.51%-39.44% shorter rise time, 21.11%-42.98% better settling time, 10% to 53.76% reduction in steady state error. The performance of modified objective function in minimizing the error signal is reduced. It can be concluded that modification of objective function by adding performance parameter into consideration could improve the performance of rise time, settling time, overshoot percentage, and steady state error