In this paper, optimal linear control techniques are utilised to control a radio-controlled helicopter (30 size) in the AeroSIMRC simulation environment. A grey-box time-domain system identification method is used to estimate a linear state space model that operates in hover mode. Identifying the unknown parameters in the model is highly dependent on the initial values and the input data. The model is divided into subsystems to make estimation possible. The identified state space model shows a good measure of fit compared to the simulator's flight data. A linear quadratic controller forms the inner-loop, and an optimised PID outer-loop generates attitude commands from a given inertial position trajectory. An observer estimates the unmeasured states such as blade flapping. The controller is developed in Simulink ® with a plug-in written for the AeroSIMRC flight simulator. The plug-in enables Simulink ® to control the simulator through a User Datagram Protocol interface for the purpose of model and controller validation. The proposed methodology facilitates a low cost test environment for new flight control algorithms. The simulation results show that the controller keeps the helicopter stable in the presence of considerable environmental disturbances and plant uncertainties.
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