Abstract
For linear systems and nonlinear systems, classic controllers such as PID have been widely used in industrial control processes and in flight control systems because of their simple structure and robust performance in a wide range of operating conditions. Several numerical approaches such as Fuzzy Logic Controller (FLC) algorithm and evolutionary algorithms have been used for the optimum design of PID controllers. In this paper Fuzzy PID controller is developed to improve the performance for a pitch control of aircraft system. The controller is designed based on the dynamic modeling of system begins with a derivation of suitable mathematical model to describe the longitudinal motion of an aircraft. Mamdani-type-Fuzzy Logic Controller is used to tune each parameter of Proportional-integral-derivative (PID) controller by selecting appropriate fuzzy rules through simulations. The simulation results show that Fuzzy Logic Controller tuned by PID algorithm is better performance and more robust than the classical type algorithm for aircraft pitch control.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bryan, G.H., Williams, W.E.: The longitudinal stability of aerial gliders. Proc. R. Soc. Lond. A 73, 110–116 (1904)
Tobak, Murray, Schiff, Lewis B.: On the formulation of the aerodynamic characteristics in aircraft dynamics. NACA TR Report-456 (1976)
Goman, M.G, Stolyarov, G.I, Tyrtyshnikov, S.L, Usoltsev, S.P, Khrabrov, A.N,: Mathematical description of aircraft longitudinal aerodynamic characteristics at high angles of attack accounting for dynamic effects of separated flow. TsAGI Preprint No. 9 (1990)
Wang, Q., Stengel, R.F.: Robust nonlinear flight control of a high-performance aircraft. IEEE Trans. Control Syst. Technol. 13(1), 15–26 (2005)
Snell, A., Stout, P.: Robust longitudinal control design using dynamic inversion and quantitative feedback theory. J. Guidance Navig. Control 20(5), 933–940 (1997)
Bossert, D.E.: Design of robust quantitative feedback theory controllers for pitch attitude hold systems. J. Guidance Navig. Control, 17(1), 217–219 (1994)
Fujimoro, A., Tsunetomo, H.: Gain-scheduled control using fuzzy logic and its application to flight control. J. Guidance Navig. Control 22(1), 175–177 (1999)
Anderson, John: Introduction to Flight, 4th edn. McGraw-Hill, New York (2000)
Etkin, Bernard, Reid, Lloyd D.: Dynamics of Flight; Stability and Control, 3rd edn. John Wiley and Sons, New York (1998)
Nelson, R.C.: Flight Stability and Automatic Control, 2nd edn, McGraw-Hill, New York (1998)
MacDonald, R.A., Garelick, M., Grady, J.O.: Linearized mathematical models for DeHAvilland Canada ‘Buffalo and Twin Otter’ STOL Transport, U.S. Department of Transportation, Transportation Systems Centre Reports No. DOTR-TSC-FAA-72-8, (1971)
Schmidt, L.V.: Introduction to Aircraft Flight Dynamics, AIAA Education Series, (1998)
Chen, F.C., Khalil, H.K.: Two-time-scale longitudinal control of airplanes using singular perturbation. AIAA J. Guidance Navig. Control 13(6), 952–960 (1990)
Sivanandam, S.N., Deepa, S.N.: Control System Engineering using MATLAB. VIKAS Publishing company Ltd, New Delhi, India (2007)
Alfaro, V.M., Vilanova, R., Arrieta O.: Two-degree-of-freedom PI/PID tuning approach for smooth control on cascade control systems. In: Proceedings of the 47th IEEE Conference on Decision and Control Cancun, Mexico 9–11 Dec (2008)
Ang, K.H., LI, C.G, Yun.: PID control system analysis, design, and technology. In: IEEE Transactions on Control Systems Technology, vol. 13(4) (2005)
Yurkevich, V.D.: Advances in PID control. InTec, (2011). ISBN 978-953-307-267-8
Myint, M., Oo, H.K., Naing, Z.M., Myint, Y.M.: PID controller for stability of Piper Cherokee’s pitch displacement using MATLAB. In: International Conference on Sustainable Development: Issues and prospects for the GMS, China (2008)
Zhou, X., Wang, Z., Wang, H.: Design of series leading correction PID controller. In: IEEE International Conference, (2009)
Chen, G., Pham, T.T.: Introduction to Fuzzy Systems, Chapman and Hall/CRC Applied Mathematics and Nonlinear Science Series, (2006)
Wahid, N., Rahmat, M.F., Jusoff, K.: Comparative assesment using LQR and fuzzy logic controller for a pitch control system. Eur. J. Sci. Res. 42(2), 184–194 (2010)
Lee, C.C.: Fuzzy logic in control system: fuzzy logic controller I. IEEE Trans. Syst. Man Cybern. 20, 404–418 (1990)
Lee, C.C.: Fuzzy logic in control system: fuzzy logic controller II. IEEE Trans. Syst. Man Cybern. 20, 419–435 (1990)
Jianwen, C., Zhanjun, H., Jingcun, S., Changjian, P.: Simulation of fuzzy self-tuning PID control based on simulink. Appl. Mech. Mater. 52–54, 1644–1649 (2011)
Vick. A., Cohen, K.: Longitudinal stability augmentation using a fuzzy logic based PID controller. 28th North American Fuzzy Information Processing Society Annual Conference, USA (2009)
Shanchez, E.N., Bacerra, H.M., Verez, C.M.: Combining fuzzy, PID and regulation for an autonomous mini helicopter. Int. J. Inf. Sci. pp. 1999–2022 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer India
About this paper
Cite this paper
Deepa, S.N., Sudha, G. (2014). A Design of Longitudinal Control of an Aircraft Using a Fuzzy Logic Based PID Controller. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 258. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1771-8_49
Download citation
DOI: https://doi.org/10.1007/978-81-322-1771-8_49
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-1770-1
Online ISBN: 978-81-322-1771-8
eBook Packages: EngineeringEngineering (R0)