Optimal Fuzzy Precompensated TID controller for Nonlinear Dynamical Systems | ||||
Menoufia Journal of Electronic Engineering Research | ||||
Volume 33, Issue 2, July 2024, Page 1-8 PDF (743.62 K) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/mjeer.2024.242642.1084 | ||||
View on SCiNiTO | ||||
Authors | ||||
Hossam Khalil 1; Osama Elshazly2; Omar Shaheen3 | ||||
1Industrial Electronics and Control Engineering, Faculty of Electronic Engineering, Menofia University Mechatronics Engineering Department, Faculty of Engineering, 6 October University, | ||||
2Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering, Menoufia University Mechatronics Engineering Department, High Institute of Engineering and Technology (HIET) | ||||
3Industrial Electronics and Control Engineering, Faculty of Electronic Engineering, Menofia University Electrical Engineering Department, Faculty of Engineering, 6 October University, | ||||
Abstract | ||||
An efficient fuzzy precompensated tilt integral derivative (FP-TID) controller is introduced for controlling nonlinear systems in the present work. The proposed control system structure combines two controlling modules; fuzzy logic control (FLC) and TID controller. This combination merges the benefits of fuzzy logic system and TID controller in terms of control system design. Consequently, it provides a high degree of flexibility to face disturbances and parameter uncertainty which affect the system performance. The scaling factors of fuzzy precompensator and TID controller parameters are optimized using the Grey Wolf Optimizer and the optimum range for those parameters is specified with minimizing an integral time absolute error (ITAE) fitness function. The applicability and superiority of the presented FP-TID controller based on GWO is evaluated through simulation of nonlinear continuous stirred tank reactor and its results are compared with other control techniques. Simulation tasks exhibit that the FP-TID presents a high superiority response for system disturbance and uncertainties compared to the other techniques. | ||||
Keywords | ||||
TID controller; Fuzzy precompensator; Grey Wolf Optimizer; Uncertain nonlinear systems | ||||
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