Browsing by Subject "Uncertainty modeling"

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    Synthesis and validation of flight control for UAV.
    (2009-11) Paw, Yew Chai
    Unmanned Aerial Vehicles (UAVs) are widely used worldwide for a board range of civil and military applications. There continues to be a growing demand for reliable and low cost UAV systems. This is especially true for small-size mini UAV systems where majority of systems are still deployed as prototypes due to their lack of reliability. Improvement in the modeling, testing and flight control for the small UAVs would increase their reliability during autonomous flight. The traditional approach used in manned aircraft and large UAV system synthesizing, implementing and validating the flight control system to achieve desired objectives is time consuming and resource intensive. This thesis aims to provide an integrated framework with systematic procedures to synthesize and validate flight controllers. This will help in the certification of UAV system and provide rapid development cycle from simulation to real system flight testing. The effectiveness of the approach is demonstrated by applying the developed framework on a small UAV system that was developed at the University of Minnesota. The thesis is divided into four main parts. The first part is mathematical modeling of the UAV nonlinear simulation model using first principle theory. Flight test system identification technique is used to extract model and model uncertainty parameters to update the nonlinear simulation model. The nonlinear simulation model developed must be able to simulate the actual UAV flight dynamics accurately for real-time simulation and robust control design purposes. Therefore it is important to include model uncertainties into the nonlinear simulation model developed, especially in small UAV system where its dynamics is less well understood than the full-size aircraft. The second part of the work provides the approach and procedures for uncertainty modeling into the nonlinear simulation model such that realization of linear uncertain model is possible. The third part of work describes the flight control design and architecture used in the UAV autopilot system. Classical and model-based control synthesis approaches are presented for roll angle tracking controller to demonstrate the controller synthesis approaches and practical controller implementation issues on the embedded flight computer system. The last part of work blends in all the previous works into the integrated framework for testing and validation of the synthesized controllers. This involves software-in-the-loop, processor-in-the-loop and flight testing of the synthesized controllers using the integrated framework developed.