Sensor Based System Identification in Real Time for Noise Covariance Deficient Models

System identification methods have extensive application in the aerospace industry’s experimental stability and control studies. Accurate aerodynamic modeling and system identification are necessary because they enable performance evaluation, flight simulation, control system design, fault detection, and model aircraft’s complex non-linear behavior. Various estimation methods yield different levels of accuracies with varying complexity and computational time requirements. The primary motivation of such studies is the accurate quantification of process noise. This research evaluates the performance of two recursive parameter estimation methods, viz.; First is the Fourier Transform Regression (FTR). The second approach describes the Extended version of Recursive Least Square (EFRLS), where E.F. refers to the Extended Forgetting factor. Also, the computational viability of these methods was analyzed for real-time application in aerodynamic parameter estimation for both linear and non-linear systems. While the first method utilizes the frequency domain to evaluate aerodynamic parameters, the second method works when noise covariances are unknown. The performance of both methods was assessed by benchmarking against parameter estimates from established methods like Extended Kalman Filter (EKF), Unscented Kalman Filter (UNKF), and Output Error Method (OEM)

Design & Implementation of an Electric Fixed-wing Hybrid VTOL UAV for Asset Monitoring

Fixed-wing unmanned aerial vehicles (UAVs) offer the best aerodynamic efficiency required for long-distance or high-endurance applications, albeit their runway requirement for take-off and landing in comparison with quadcopters, helicopters, and flapping-wing UAVs that can perform vertical take-off and landing (VTOL). Integrating a multirotor system with a fixed-wing UAV imparts VTOL capabilities without significantly compromising fixed-wing aerodynamic efficiency, endurance, payload capacity or range. Documented system design approaches to address various challenges of such fusion processes are sparse. This research proposes a holistic approach for designing, prototyping, and testing an electric-powered fixed-wing hybrid VTOL UAV. The proposed system design approach augments the standard aircraft design process with additional steps to integrate VTOL capabilities. Separate fixed-wing and multirotor designs were derived from the frozen mission requirements, which were then fused. The process used simulation for modeling and evaluating alternatives for the hybrid UAV created using standard aircraft design equations. We prototyped and instrumented the final design to validate operational capabilities through test flights. Multiple flight trials identified the ideal combination of Lithium-Polymer (Li-Po) batteries for VTOL (8000mAh) and fixed-wing (14000mAh) modes to meet the endurance and range requirements. The redundant power supplies also increased the survivability chances of the hybrid UAV during failures