Using the Cross-Entropy Method for Control Optimization: A Case Study of See-and-Avoid on Unmanned Aerial Vehicles

Olivares-Mendez, Miguel A.; Fu, Changhong; Kannan, Somasundar; Voos, Holger y Campoy Cervera, Pascual (2014). Using the Cross-Entropy Method for Control Optimization: A Case Study of See-and-Avoid on Unmanned Aerial Vehicles. En: "2014 22nd Mediterranean Conference on Control and Automation (MED)", 16-19 June, 2014, Palermo, Italy. ISBN 978-1-4799-5901-3. pp. 1183-1189.

Descripción

Título: Using the Cross-Entropy Method for Control Optimization: A Case Study of See-and-Avoid on Unmanned Aerial Vehicles
Autor/es:
  • Olivares-Mendez, Miguel A.
  • Fu, Changhong
  • Kannan, Somasundar
  • Voos, Holger
  • Campoy Cervera, Pascual
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 2014 22nd Mediterranean Conference on Control and Automation (MED)
Fechas del Evento: 16-19 June, 2014
Lugar del Evento: Palermo, Italy
Título del Libro: 2014 22nd Mediterranean Conference on Control and Automation (MED)
Fecha: 2014
ISBN: 978-1-4799-5901-3
Materias:
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Automática, Ingeniería Electrónica e Informática Industrial [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

This paper presents an adaptation of the Cross-Entropy (CE) method to optimize fuzzy logic controllers. The CE is a recently developed optimization method based on a general Monte-Carlo approach to combinatorial and continuous multi-extremal optimization and importance sampling. This work shows the application of this optimization method to optimize the inputs gains, the location and size of the different membership functions' sets of each variable, as well as the weight of each rule from the rule's base of a fuzzy logic controller (FLC). The control system approach presented in this work was designed to command the orientation of an unmanned aerial vehicle (UAV) to modify its trajectory for avoiding collisions. An onboard looking forward camera was used to sense the environment of the UAV. The information extracted by the image processing algorithm is the only input of the fuzzy control approach to avoid the collision with a predefined object. Real tests with a quadrotor have been done to corroborate the improved behavior of the optimized controllers at different stages of the optimization process.

Más información

ID de Registro: 37651
Identificador DC: http://oa.upm.es/37651/
Identificador OAI: oai:oa.upm.es:37651
URL Oficial: http://www1.unipa.it/med14/
Depositado por: Memoria Investigacion
Depositado el: 09 Sep 2015 16:22
Ultima Modificación: 14 Sep 2015 14:50
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