• Energy Research

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.

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.

This paper presents a controller design process for an aircraft tracking problem when not all states are available. In the study, a nonlinear-transport aircraft simulation model was used and identified through Maximum Likelihood Principle and Extended Kalman Filter. The obtained mathematical model was used to design a Linear–Quadratic Regulator (LQR) with optimal weighting matrices when not all states are measured. The nonlinear aircraft simulation model with LQR controller tracking abilities were analyzed for multiple experiments with various noise levels. It was shown that the designed controller is robust and allows for accurate trajectory tracking. It was found that, in ideal atmospheric conditions, the tracking errors are small, even for unmeasured variables. In wind presence, the tracking errors were proportional to the wind velocity and acceptable for small and moderate disturbances. When turbulence was present in the experiment, state variable oscillations occurred that were proportional to the turbulence intensity and acceptable for small and moderate disturbances.

This paper presents a controller design process for an aircraft tracking problem when not all states are available. In the study, a nonlinear-transport aircraft simulation model was used and identified through Maximum Likelihood Principle and Extended Kalman Filter. The obtained mathematical model was used to design a Linear–Quadratic Regulator (LQR) with optimal weighting matrices when not all states are measured. The nonlinear aircraft simulation model with LQR controller tracking abilities were analyzed for multiple experiments with various noise levels. It was shown that the designed controller is robust and allows for accurate trajectory tracking. It was found that, in ideal atmospheric conditions, the tracking errors are small, even for unmeasured variables. In wind presence, the tracking errors were proportional to the wind velocity and acceptable for small and moderate disturbances. When turbulence was present in the experiment, state variable oscillations occurred that were proportional to the turbulence intensity and acceptable for small and moderate disturbances.

Thrust vector control (TVC) might be used to control aircraft at large altitudes and in post-stall conditions when aerodynamic control surfaces are ineffective. This study demonstrated that the implementation of the TVC on high-speed aircraft is a reasonable solution and might be an alternative when compared to the complicated reaction control system or large aerodynamic control surfaces. The numerical flight dynamics model of the X-15 experimental aircraft was developed and implemented in MATLAB/Simulink and then used to investigate the proposed solution. The obtained results indicate that the aircraft, equipped with full 3D thrust vectoring and two independent horizontal stabilizers to control the roll angle, was able to achieve flight along the path that was defined by a set of waypoints. This paper also highlights the potential benefits and challenges of using TVC as a control method for aircraft. The results of this study contribute to the growing body of research on aircraft control and simulation. Future work can explore the use of TVC for other aircraft with unique configurations and low maneuverability features.

Thrust vector control (TVC) might be used to control aircraft at large altitudes and in post-stall conditions when aerodynamic control surfaces are ineffective. This study demonstrated that the implementation of the TVC on high-speed aircraft is a reasonable solution and might be an alternative when compared to the complicated reaction control system or large aerodynamic control surfaces. The numerical flight dynamics model of the X-15 experimental aircraft was developed and implemented in MATLAB/Simulink and then used to investigate the proposed solution. The obtained results indicate that the aircraft, equipped with full 3D thrust vectoring and two independent horizontal stabilizers to control the roll angle, was able to achieve flight along the path that was defined by a set of waypoints. This paper also highlights the potential benefits and challenges of using TVC as a control method for aircraft. The results of this study contribute to the growing body of research on aircraft control and simulation. Future work can explore the use of TVC for other aircraft with unique configurations and low maneuverability features.