This paper presents an analysis of a Total Energy Control System (TECS) introduced by Lambregts to control unmanned aerial vehicle (UAV) velocity and altitude by using the total energy distribution. Furthermore, an extended Kalman filter (EKF) approach was used to predict aircraft response in terms of angular rates and linear acceleration during a test flight campaign. From both approaches, state equations were obtained to model the aircraft using Matlab-Simulink. From an aerodynamic study, airplane characteristics were obtained in terms of non-dimensional derivatives and compared to those obtained from the experimental methods. It was determined that TECS approach was very accurate; however, disturbance errors could be decreased by adjusting some model parameters. On the other hand, it was difficult to obtain a real estimation from the EKF method due to the presence of turbulence during flight and the relatively low inertia of the scale model. Dynamic characteristics were validated using a low-cost inertial sensor that cab be easily integrated in UAV platforms. The gathered data can be used to predict model characteristics by integrating the information into flight simulators for future design development.

In this study, a numerical procedure for designing an aircraft system-identification maneuver with simultaneous flight-control deflections is described. The elevator, aileron, and rudder multistep excitations that maximize the D-optimality criterion were found by a genetic algorithm. Like for any dynamic system, this input-design process would require determining optimal time-dependent functions resulting in infinite-dimensional optimization. To limit the search-space dimensions, the switching points of the inputs were selected on the basis of the discrete wavelet transform. In the investigation, the design was compared with the maneuvers that used harmonically related multisines and typical multistep inputs (3-2-1-1 on elevator, 1-2-1 on aileron, rudder doublet) for simultaneous flight-control deflections. The case of typical excitations applied one at a time was examined as well. Through simulations, it was found that the maneuvers with simultaneous flight-control deflections that were based on the D-optimality criterion or harmonically related multisine signals are better in terms of accuracy, aircraft response, and resulting $G$ force than the designs based on the typical excitations.

In this paper, the full tracking problem in aircraft system identification and control is presented. Time domain output error method with maximum likelihood principle was used to perform system identification. The linear quadratic regulator (LQR)-based approach has been used for solving aviation full tracking problems in aviation. It has been shown that the generalized nonlinear LQR control is able to handle such problems even in case of inaccurate measurements and in the presence of moderate disturbances provided that the model of an aircraft is properly identified.

Designing a reconfiguration system for an aircraft requires a good mathematical model of the object. An accurate model describing the aircraft dynamics can be obtained from system identification. In this case, special maneuvers for parameter estimation must be designed, as the reconfiguration algorithm may require to use flight controls separately, even if they usually work in pairs. The simultaneous multi-axis multi-step input design for reconfigurable fixed-wing aircraft system identification is presented in this paper. D-optimality criterion and genetic algorithm were used to design the flight controls deflections. The aircraft model was excited with those inputs and its outputs were recorded. These data were used to estimate stability and control derivatives by using the maximum likelihood principle. Visual match between registered and identified outputs as well as relative standard deviations were used to validate the outcomes. The system was also excited with simultaneous multisine inputs and its stability and control derivatives were estimated with the same approach as earlier in order to assess the multi-step design.