Title :
Neuro-genetic PID autotuning
Author :
Lima, J.M. ; Azevedo, A.B. ; Duarte, N. ; Fonseca, C.M. ; Ruano, A.E. ; Fleming, P.J.
Author_Institution :
Fac. of Sci. & Technol., Univ. of Algarve, Faro, Portugal
Abstract :
A new PID autotuning technique, involving neural networks and genetic algorithms is proposed. The validity of this approach is shown, through the results of several experiments. Special attention is given to the off-line training of one of the auto-tuner models, the criterion networks. Procedures used to obtain good training data are described.
Keywords :
adaptive control; genetic algorithms; neurocontrollers; self-adjusting systems; three-term control; autotuner model; genetic algorithm; neural network; neurogenetic PID autotuning technique; Artificial neural networks; Genetic algorithms; Splines (mathematics); Standards; Training; Tuning; Genetic algorithms; Neural networks; PID autotuning;
Conference_Titel :
Control Conference (ECC), 2001 European
Conference_Location :
Porto
Print_ISBN :
978-3-9524173-6-2
