This paper extends our previous open loop aircraft flutter model analysis to more general closed loop case, as closed loop situation is more practical than open loop case. Due to two measured noises in this general closed loop aircraft flutter model analysis, optimal input signal is determined from the aspect of unbiased estimate, i.e., one unbiased nonparametric flutter model only through the collected close loop input-output data. To give the detailed dependence about optimal input signal on nonparametric estimate, we derive one explicit improved form and its statistical analysis. Moreover, to guarantee the equivalence between the unbiased estimate and convergence property, one composite Lyapunov analysis is formulated to consider two different noises, similar to convergent within noise, i.e. robustness.This composite approach allows for a comprehensive assessment of the system’s behavior under the combined influence of these noises, ensuring that the desired estimation properties are maintained despite the uncertainties in the system model, disturbances, and variations in operating conditions.
Finally, one platform is established, and some simulations are done to prove our proposed theoretical results. The main contribution of this paper is to present new ideas about how to improve the accurate identification within the closed loop situation and input-output noises simultaneously. The above is demonstrated with experimental studies cases of the application on an experimental platform of aircraft flutter.