A Comparative Analysis of Intelligent and PID Controllers for an Aircraft Pitch Control System

Zakarya Mohammed Motea, Herman Wahid, Junaid Zahid, Swan Htet Lwin, Abbas Musa Hassan


Aircraft pitch control system is one example of nonlinear complex systems which requires feedback control. Fuzzy logic controllers (FLC) have emerged as intelligent method in controlling such system by utilizing fuzzy logic principle. This paper presents a comparative analysis for the performance of proportional-derivative-integral (PID) controller and fuzzy logic controller in controlling the aircraft pitch angle. The input is the elevator deflection angle and the output is the pitch angle of the aircraft. For the fuzzy controller, it is governed by five membership functions and seventeen rules which were tuned repeatedly according to the actual output of the controller corresponding to the customized set point. The procedures of the PID and the FLC design are discussed in methodology section. In general, both PID and FLC perform within the design requirements. However, FLC outperforms PID in three design parameters namely the settling time, the percentage of overshoot and the steady state error, with improvements of 12%, 98% and 97%, respectively.


Aircraft; Fuzzy logic controller; PID controller; Pitch control.

Article Metrics

Abstract view : 729 times
PDF - 286 times

Full Text:



Axes / Control Surfaces - Principles of flight, Aeronautics Research Mission Directorate, National Aeronautics and Space Administration (NASA), 2010.

P. Kumar and S. Narayan, Optimal design of robust FOPID for the aircraft pitch control system using multi-objective GA, 2016 IEEE Students' Conference on Electrical, Electronics and Computer Science, Bhopal, India, 2016, pp. 1–6.

Vishal and J. Ohri, GA tuned LQR and PID controller for aircraft pitch control, 2014 IEEE 6th India International Conference on Power Electronics, Kurukshetra, India, 2014, pp. 1–6.

R. Zaeri, A. Ghanbarzadeh, B. Attaran and Z. Zaeri, Fuzzy logic controller based pitch control of aircraft tuned with bees algorithm, The 2nd International Conference on Control, Instrumentation and Automation, Shiraz, Iran, 2011, pp. 705–710.

D. We, H. Xiong and J. Fu, Aircraft autopilot pitch control based on fuzzy active disturbance rejection control, 2015 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration, Wuhan, China, 2015, pp. 144–147.

I. N. Ibrahim and M. A. Al Akkad, Exploiting an intelligent fuzzy-PID system in nonlinear aircraft pitch control, 2016 International Siberian Conference on Control and Communications, Moscow, Russia, 2016, pp. 1–7.

C. C. Lee, Fuzzy logic in control systems: fuzzy logic controller, IEEE Transactions on Systems, Man, and Cybernetics, 20(2), 404-418, 1990.

E. H. Mamdani, Application of fuzzy logic to approximate reasoning using linguistic synthesis, IEEE Transactions on Computers, 26(20), 1182–1191, 1977.

N. Wahid and M. F. Rahmat, Pitch control system using LQR and fuzzy logic controller, 2010 IEEE Symposium on Industrial Electronics and Applications, Penang, Malaysia, 2010, pp. 389–394.

Vishal and J. Ohri, GA tuned LQR and PID controller for aircraft pitch control, 2014 IEEE 6th India International Conference on Power Electronics, Kurukshetra, India, 2014, pp. 1–6.

P. Kumar and J. Raheja, Optimal design of robust FOPID for the flight control system using multi-objective differential evolution, 2015 2nd International Conference on Recent Advances in Engineering & Computational Sciences, Chandigarh, India, 2015, pp. 1–4.

N. Wahid and N. Hassan, Self-tuning fuzzy PID controller design for aircraft pitch control, 2012 Third International Conference on Intelligent Systems Modelling and Simulation, Kota Kinabalu, Malaysia, 2012, pp. 19–24.

University of Michigan, Aircraft pitch: system modeling, Control Tutorials for Matlab Simulink, 2018. Available online at: http://ctms.engin.umich.edu/CTMS/index.php.


  • There are currently no refbacks.