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This work describes the application of the output-error method using the Levenberg-Marquardt optimization algorithm to the Flight Path Reconstruction (FPR) problem, which constitutes an important preliminary step towards the aircraft parameter identification. This method is also applied to obtain the aerodynamic and control derivatives of a regional jet aircraft from flight test data with measurement noise and bias. Experimental results are reported, employing a real jet aircraft, with flight test data acquired by smart probes, inertial sensors (gyrometers and accelerometers) and Global Positioning Systems (GPS) receivers.

In this work, two optimization algorithms are investigated to accomplish the parameter identification of the longitudinal motion of a real aircraft by using the output error method. The first algorithm is the nature-inspired algorithm named the life cycle model, which is a composed strategy based on other heuristics such as genetic algorithms and particle swarm optimization. The second one is the gradient-based technique named Levenberg-Marquardt algorithm, which is a variant of the Gauss-Newton method. Flight test data, performed with a training jet aircraft (Xavante AT-26), were used to feed the output error method. In this context, both optimization algorithms were tested, in solo performance and in a cascade-type approach. Results are reported, aiming to illustrate the success of using the proposed methodology.

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