A single-neuron PID adaptive multicontroller scheme based on RBFNN

Abstract

In order to improve the control performance of the multicontroller proposed by Guo and Jutan (Canadian Journal of Chemical Engineering, 79, 817-22, 2001), a single-neuron PID multicontroller scheme based on a radial base function neural network (RBFNN) is proposed in this paper. This scheme has four controllers, specifically a set-point controller, two load controllers and a proportional controller. These controllers may be designed independently to achieve good control performance for both set-point tracking and load rejection. In particular, the set-point controller and the load controller have been chosen as single-neuron PID controllers. The model parameters and the parameters of the two single-neuron PID controller are updated in real time. For simplicity, the feedforward controller can be chosen as a unity gain proportional controller. It guarantees physical realizability and provides complete compensation for measurable disturbance. The simulation results show that the single-neuron PID adaptive multicontroller scheme based on RBFNN is very effective and the controller is of relatively strong robustness.

Keywords

load rejection multicontroller RBFNN set-point tracking single neuron

References

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