Journal
AUTOMATION IN CONSTRUCTION
Volume 23, Issue -, Pages 55-63Publisher
ELSEVIER
DOI: 10.1016/j.autcon.2011.12.005
Keywords
Hybrid evolutionary algorithm; Recurrent neural network; Tower crane; Underactuated system; Nonlinear system control
Ask authors/readers for more resources
This paper is concerned with the control of an underactuated three-dimensional tower crane system using a recurrent neural network (RNN) which is evolved by an evolutionary algorithm. In order to improve the performance in evolving the RNN, a hybrid evolutionary algorithm (HEA) which utilizes the operators of a constricted particle swarm optimization (PSO) and a binary-coded genetic algorithm (GA) is proposed. Simulation results show that the proposed HEA has superior performance in a comparison with the canonical algorithms and that the control system works effectively. (C) 2011 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available