A self-tuning neuromorphic controller: application to the crane problem
1998; Elsevier BV; Volume: 6; Issue: 12 Linguagem: Inglês
10.1016/s0967-0661(98)00121-x
ISSN1873-6939
AutoresL. Moreno, Leopoldo Sánchez, Juan Albino Méndez Pérez, Santiago Torres, A. Hamilton, G.N. Marichal,
Tópico(s)Neural Networks and Applications
ResumoThis paper is concerned with the design and application of a self-tuning controller, aided by means of neural network s (NN). The structure of the controller is based on the use of neural networks as an implicit self-tuner for the controller. The aim o f this approach is to take advantage of the learning properties of the neural networks to increase the performance of the self-tuning. The a pplication of this technique is performed on an overhead crane. The control objective is to suppress undesirable oscillations during op eration of the crane. First, some simulations were carried out, as well as a comparison with a standard self-tuning method, that demon strate the advantages of this method. After this, a real-time implementation on a scale prototype of a crane was done to verify th e applicability of the method.
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