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Neural Network Controller for Two-Degree-Freedom Helicopter Control System. Project Summary For emergency services, one of the fittest candidates is two-degree-freedom (2-DOF) helicopter.

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  1. Neural Network Controller for Two-Degree-Freedom Helicopter Control System Project Summary • For emergency services, one of the fittest candidates is two-degree-freedom (2-DOF) helicopter. • Helicopter is inherently complicated unstable and nonlinear dynamic system under a significant influence of disturbances and parameter perturbations. The system has to be stabilized using a feedback controller. • Automatic control features of 2-DOF helicopter are usually approximated by linear quadratic regulator (LQR) controller, which is not efficient due to its linear feature. • A control system that adapts the nonlinear dynamics of various flight regimes as they occur has the potential to achieve superior performance. Towards this aim artificial intelligence e.g., Neural Network (NN) based system is on-demand. • This Research presents the nonlinear control of 2-DOF helicopter using an efficient artificial NN controller. It is developed using back propagation, feed forward NN model to control helicopter’s motors and consequently pitch and yaw angles using MATLAB software. • The practical implementation into the existing 2-DOF Helicopter gives precise results for the changes in the pitch and yaw angles(~ 33% pitch and 69% yaw improvement compared to LQR) followed by increased stability and safety in controlling the helicopter. • This may be useful in controlling helicopters precisely whenever complicated maneuvers needed to conduct by pilots. Project Development Flow Quanser2-DOF Helicopter (Left) and Dynamics of 2-DOF Helicopter (Right) • SIMULINK Block Diagram for The Closed-loop Helicopter Controller System STUDENT PHOTO Simple System Block Diagram Performance Results Pitch & Yaw Response for controller comparison • Left-Up: NN controller Pitch Response • Left-Down: NN controller Yaw Response • Right-Up: GUI for NN test & validation of data • Right-Down: NN Best-fit plot • Just-Down: NN Performance / Efficiency • Conclusions • The proposed controller exhibits good tracking performance for an unstable helicopter system. • Increased stability and safety in controlling the helicopter remotely for emergency / rescue services. • Useful in controlling helicopters precisely whenever complicated maneuvers needed to conduct by pilots. Name: Matric No.: Supervisor: Department of Electric and Electronic Engineering Faculty of Engineering UniversitiPutra Malaysia, 43400 UPM Serdang, Selangor, Malaysia. Tel: +603 – 8946 4449 E-Mail: ribhan@eng.upm.edu.my Department of Electric and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia. E-Mail:

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