Abstract

This paper presents the development of an optimal flight control system for a small-scale Unmanned Aerial Vehicle (UAV) helicopter. Complex and highly coupled dynamics of the helicopter naturally complicates the modeling process and the controller design. In this work, the comprehensive nonlinear model of the helicopter system is derived from the first-principles modeling and its parameters are verified with system identification approaches. The derived nonlinear model is with modest level of complexity and the high-fidelity linearized model is adequate for flight control system design. Helicopter is a high-dimensional and inherently unstable system. It demands accurate and efficient control algorithms to stabilize the attitude of the helicopter. Full-state feedback control is utilized in the controller design. However, onboard sensors can provide only partial states information for feedback. The unmeasured states are estimated by means of a reduced-order observer. Linear Quadratic Regulator (LQR) methodology and integral state augmentation are adopted in order to achieve the desired performance of the control system. The simulation results indicate the developed control system is competent and efficient enough to control the UAV helicopter.

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