Bio inspired technique for controlling angle of attack of aircraft

<p>This paper deals with the design of a proportional–integral (PI) controller for controlling the angle of attack of flight control system. For the first time teaching learning-based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed PI controller. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the PI controller. The superiority of proposed approach is demonstrated by comparing the results with that of the conventional methods like genetic algorithm (GA) and particle swarm optimization (PSO). It is observed that TLBO optimized PI controller gives better dynamic performance in terms of settling time, overshoot, and undershoot as compared to GA and PSO based PI controllers. The various performance indices like mean square error (MSE), integral absolute error (IAE), and integral time absolute error (ITAE) are improved by using the TLBO soft computing techniques. Further, robustness of the system is studied by varying all the system parameters from −50% to +50% in step of 25%. Analysis also reveals that TLBO optimized PI controller gains are quite robust and need not be reset for wide variation in system parameters.</p>

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Publication Details

Journal
IAES International Journal of Artificial Intelligence
Published
2024-10-08
DOI
https://doi.org/10.11591/ijai.v13.i4.pp4206-4216
Primary Topic
Advanced Control Systems Design
Type
article
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article

Bio inspired technique for controlling angle of attack of aircraft

Subhakanta Bal, Sudarshan Swain, Partha Sarathi Khuntia
IAES International Journal of Artificial Intelligence
Advanced Control Systems Design
article

Bio inspired technique for controlling angle of attack of aircraft

Subhakanta Bal, Sudarshan Swain, Partha Sarathi Khuntia
article en

Abstract

<p>This paper deals with the design of a proportional–integral (PI) controller for controlling the angle of attack of flight control system. For the first time teaching learning-based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed PI controller. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the PI controller. The superiority of proposed approach is demonstrated by comparing the results with that of the conventional methods like genetic algorithm (GA) and particle swarm optimization (PSO). It is observed that TLBO optimized PI controller gives better dynamic performance in terms of settling time, overshoot, and undershoot as compared to GA and PSO based PI controllers. The various performance indices like mean square error (MSE), integral absolute error (IAE), and integral time absolute error (ITAE) are improved by using the TLBO soft computing techniques. Further, robustness of the system is studied by varying all the system parameters from −50% to +50% in step of 25%. Analysis also reveals that TLBO optimized PI controller gains are quite robust and need not be reset for wide variation in system parameters.</p>

IAES International Journal of Artificial IntelligenceVol. 13(4)
Biju Patnaik University of Technology (IN), Nalanda University (IN), Institute of Science and Technology
Openalex Percentile: Top 80%
Advanced Control Systems Design
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Bio inspired technique for controlling angle of attack of aircraft — Subhakanta Bal, Sudarshan Swain, et al. · IAES International Journal of Artificial Intelligence (2024) | TGRS Research Map | TGRS