Data Driven Model Estimation for Aerial Vehicles: A Perspective Analysis

Abstract

Unmanned Aerial Vehicles (UAVs) are important tool for various applications, including enhancing target detection accuracy in various surface-to-air and air-to-air missions. To ensure mission success of these UAVs, a robust control system is needed, which further requires well-characterized dynamic system model. This paper aims to present a consolidated framework for the estimation of an experimental UAV utilizing flight data. An elaborate estimation mechanism is proposed utilizing various model structures, such as Autoregressive Exogenous (ARX), Autoregressive Moving Average exogenous (ARMAX), Box Jenkin’s (BJ), Output Error (OE), and state-space and non-linear Autoregressive Exogenous. A perspective analysis and comparison are made to identify the salient aspects of each model structure. Model configuration with best characteristics is then identified based upon model quality parameters such as residual analysis, final prediction error, and fit percentages. Extensive validation to evaluate the performance of the developed model is then performed utilizing the flight dynamics data collected. Results indicate the model’s viability as the model can accurately predict the system performance at a wide range of operating conditions. Through this, to the best of our knowledge, we present for the first time a model prediction analysis, which utilizes comprehensive flight dynamics data instead of simulation work.

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

“…3) Trajectory Formation: Collaborative trajectory formation enables multiple UAVs to find the optimal path from the starting point to the target point. It is one of the emerging areas of research in UAV systems as collaborative path planning minimizes localization cost, improves maneuver decisions, and helps in collision avoidance [109]- [111]. In the existing literature, various collaborative trajectory formation techniques exist.…”

Multi-Agent Variational Approach for Robotics: A Bio-Inspired Perspective

“…The main challenge in this field is to coordinate the actions of multiple robots so that they can work together effectively and efficiently [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ]. In order to solve this problem, researchers often use optimization algorithms, which are mathematical methods that find the best solution to a given problem based on specific objectives and constraints [ 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ]. Using a group of autonomous mobile robots can have a number of benefits, including increased effectiveness, dependability, and robustness when conducting tasks such as exploration, surveillance, and inspection to acquire information [ 29 ].…”

Desenvolvimento De Um Sistema Experimental Para Obtenção De Dados Característicos Do Motor E Da Bateria Utilizados Em Vants Para Aplicação De Técnicas De Identificação De Sistemas

“…Belge et al (2020) obtém uma estimativa da resposta do sistema dinâmico lateral de um VANT usando conjuntos de dados de entrada-saída empíricos utilizando os modelos paramétricos ARX, ARMAX e OE. Fatima et al (2022) elaborou mecanismo de estimativa utilizando várias estruturas de modelo, como ARX, ARMAX, BJ e OE para um VANT experimental utilizando dados de voo.…”