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  • New methods for PID autotuning
    Publication . Ruano, Antonio; Lima, João
    In this paper a recent approach for PID autotuning, involving neural networks, is ferther developed. To make this approach adaptive, optimal PID values must be known on-line. In this paper neural network models of tuning criteria, together with the use of genetic algorithms, are proposed to solve this problem.
  • Neuro-genetic PID autotuning: time invariant case
    Publication . Lima, João; Ruano, Antonio
    The Proportional, Integral and Derivative (PID) controllers are widely used in induxtrial applications. Their popularity comes from their robust performance and also from their functional simplicity.
  • Neuro-genetic Pid autotuning
    Publication . Lima, João; Azevedo, Ana Beatriz da Piedade de; Duarte, N. M.; Fonseca, C. M.; Ruano, Antonio; Fleming, P. J.
    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.