This paper presents a novel modeling technique that integrates first-principles and system-identification techniques through the use of global optimization methods in the frequency domain. The approach yields real-time high-fidelity linear and non-linear models. The integrated modeling technique has been used to model the Carnegie Mellon University (CMU) Yamaha R-50 autonomous helicopter. Comparisons between predicted responses and flight experiments for hover and cruise flight, in the time and frequency domains, show excellent agreement. The results suggest that the models obtained with the integrated technique are adequate for the design of high-performance control systems and the accurate simulation of complex autonomous missions.
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