9e4a63e1-93fe-4dcb-82b0-09e05412abd020211127090212572naun:naunmdt@crossref.orgMDT DepositInternational Journal of Mathematics and Computers in Simulation1998-015910.46300/9102http://www.naun.org/cms.action?id=2826329202132920211510.46300/9102.2021.15https://www.naun.org/cms.action?id=23312Intelligent Pitch Controller Identification and DesignAmirTorabiFaculty of Electrical Engineering,Khorasan University ,Mashhad,IranAmin AdineAhariFaculty of Electrical Engineering,Khorasan University ,Mashhad,IranAliKarsazFaculty of Electrical Engineering,Khorasan University ,Mashhad,IranSeyyed HossinKazemiFaculty of Electrical Engineering,Khorasan University ,Mashhad,IranThis paper exhibits a comparative assessmentbased on time response specification performance between modern and classical controller for a pitch control system of an aircraft system. The dynamic modeling of pitch control system is considered on the design of an autopilot that controls the pitch angle It starts with a derivation of a suitable mathematical model to describe the dynamics of an aircraft. For getting close to actual conditionsthe white noise disturbance is applied to the system.In this paper it is assumed that the modelpitch control systemis not available. So using the identification system and Box-Jenkins model estimator we identify the pitch control system System’s identification is a procedure for accurately characterizing the dynamic response behavior of a complete aircraft, of a subsystem, or of an individual component from measureddata.To study the effectiveness of the controllers, the LQR Controller and PID Controller and fuzzy controller is developed for controlling the pitch angle of an aircraft system. Simulation results for the response of pitch controller are presented instep’s response. Finally, the performances of pitch control systems are investigated and analyzed based on common criteria of step’s response in order to identify which control strategy delivers better performance with respect to the desired pitch angle. It is found from simulation, that the fuzzy controller gives the best performance compared to PID and LQR controller.112720211127202113414025https://www.naun.org/main/NAUN/mcs/2021/a502002-025(2021).pdf10.46300/9102.2021.15.25https://www.naun.org/main/NAUN/mcs/2021/a502002-025(2021).pdfN. Wahid, N. Hassan,M.F. Rahmat“Application of Intelligent Controller in Feed-back Control Loop for Aircraft Pitch Control”, Australian Journal of Basic and Applied Scien-ces2011 10.1139/tcsme-2009-0034J.K. Shiau and D.M. Ma, “An Autopilot Design for the Longitudinal Dynamics of a Low Speed Experimental UAV using Two Time Scale Cascade Decomposition”, Transaction of the Canadian Society for Mechanical Engineering, Vol 33, No 3, 2009. M. Myint, H.K. Oo, Z.M. 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