Implementation of neural network-based real-time process control on IBM Zero Instruction Set Computer (ZISC-036)
Kurosh Madani, Gilles Mercier, Abdennasser Chebira, Sebastian Duchesne · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
Most of applications on neural adaptive process control are developed on back-propagation or CMAC algorithms. We present here a new approach based on a derivative of Radial Basis Function Network: The Restricted Coulomb Energy (RCE) for a parallel implementation of adaptive process control. The RCE network has been implemented on a single board based on the Zero Instruction Set Computer (ZISC-036) neural processor of IBM. The network learning consists on identification of a real second order process (DC motor with position sensor). We expose the learning and generalization phases of network, then we give simulation and experimental results.