Displacement motion prediction of a landing deck for recovery operations of rotary UAVs


Autoria(s): Yang, Xilin
Data(s)

2013

Resumo

This paper proposes a practical prediction procedure for vertical displacement of a Rotarywing Unmanned Aerial Vehicle (RUAV) landing deck in the presence of stochastic sea state disturbances. A proper time series model tending to capture characteristics of the dynamic relationship between an observer and a landing deck is constructed, with model orders determined by a novel principle based on Bayes Information Criterion (BIC) and coefficients identified using the Forgetting Factor Recursive Least Square (FFRLS) method. In addition, a fast-converging online multi-step predictor is developed, which can be implemented more rapidly than the Auto-Regressive (AR) predictor as it requires less memory allocations when updating coefficients. Simulation results demonstrate that the proposed prediction approach exhibits satisfactory prediction performance, making it suitable for integration into ship-helicopter approach and landing guidance systems in consideration of computational capacity of the flight computer.

Identificador

http://eprints.qut.edu.au/62002/

Publicador

Springer

Relação

DOI:10.1007/s12555-011-0157-8

Yang, Xilin (2013) Displacement motion prediction of a landing deck for recovery operations of rotary UAVs. International Journal of Control, Automation and Systems, 11(1), pp. 58-64.

Direitos

Springer

Fonte

Australian Research Centre for Aerospace Automation; School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #Bayes information criterion #Recursive least square #Times series
Tipo

Journal Article