Experimental Validation of Total Energy Control System for UAVs

Pedro Jimenez,Daniel Agudelo,Piotr Lichota,Krzysztof Rogowski

doi:10.3390/en13010014

Abstract

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.

Highlights

Present-day unmanned aircraft systems (UASs) play an important role in daily life
For systems with higher nonlinearities, another approach such as the linear parameter varying (LPV) formulation established by Chadli [1,2] should be used, as it directly includes nonlinearities in Takagi-Sugeno (T-S) fuzzy model problem formulation, whereas the extended Kalman filter (EKF) is a linearization of the Kalman filter
Results validating the theory of Total Energy Control System (TECS) and EKF algorithms through flight tests are presented

Summary

Introduction

Present-day unmanned aircraft systems (UASs) play an important role in daily life. These systems perform functions in aerial photography, surveillance, reconnaissance, search and rescue, and atmospheric data acquisition, among others. To perform a specific mission efficiently and precisely, systems must be able to adjust proportional, integral and derivative (PID) controllers through algorithms such as the EKF (extended Kalman filter) and TECS (Total Energy Control System), which allows determination of aircraft attitude and altitude, longitudinal control, and velocity to adjust through auto-tuned controllers. The main purpose of this paper is to establish a methodology that describes how the dynamic model of an unmanned aerial vehicle (UAV) can be validated to determine the actual control parameters in order to decrease the required time to tune the on-board controllers.

Objectives

Results

Conclusion