Repository logo
 

Search Results

Now showing 1 - 7 of 7
  • A neural network PID autotuner
    Publication . Ruano, Antonio; Lima, João; Mamat, R.; Fleming, P. J.
    Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. Their popularity comes from their rebust performance and also from their functional simplicity. Whether because the plant is time-varying, or because of components ageing, these controllers need to be regularly retuned.
  • Comparison of alternative approaches to neural network PID autotuning
    Publication . Ruano, Antonio; Lima, João; Mamat, R.; Fleming, P. J.
    In this paper, a scheme for the automatic tuning of PID controllers on-line, with the assistance of trained neural networks, is proposed. The alternative approaches are presented and compared.
  • On-line adaptation of neural network
    Publication . Lima, João; Ruano, Antonio
    The Proportional Integral and Devirative (PID) controller autotuning is an important problem, both in practical and theoretical terms. The autotuning procedure must take place in real-time, and therefore the corresponding optimisation procedure must also be executed in real-time and without disturbing on-line control.
  • 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.
  • Um modelo em simulink para sintonia automática de controladores PID usando redes neuronais
    Publication . Lima, João; Ruano, Antonio; Mamat, R.; Fleming, P. J.
    The PID controllers are widely used in industry. Whether because the plant is time-varying, or because of components ageing, these controllers need to be regularly retuned. During the last years, several methods have been proposed for PID autotuning.
  • Automatic tuning of PID controllers using a neuro-genetic system
    Publication . Ruano, Antonio; Lima, João; Azevedo, Ana Beatriz da Piedade de; Duarte, N. M.; Fleming, P. J.
    Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller turning problems. In this paper we propose to combine its joint use, by exploiting the nonlinear mapping capabilites of neural networks to model objective functions, and to use them to supply their values to a genetic algorithm which performs on-line minimization.
  • A novel technique for controller tuning
    Publication . Ruano, Antonio; Lima, João; Azevedo, Ana Beatriz da Piedade de; Duarte, N. M.; Fleming, P. J.
    Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller tuning problems. In this paper we purpose to combine its joint use, by exploiting the nonlinear mapping capabilities of neural networks to model objective functions, and use them to supply their values to a genetic algorithm which performs on-line minimization. Simulation results show that this is a valid approach, offering desired properties for on-line use such as a dramatic reduction in computation time and avoiding the need of perturbing the closed-loop operation.