Is. Ahn et Jh. Lan, IMPLEMENTATION OF A NEURAL-NETWORK CONTROLLER AND ESTIMATOR USING A DIGITAL SIGNAL-PROCESSING CHIP, Mathematical and computer modelling, 21(1-2), 1995, pp. 133-141
In this paper, artificial neural networks with error backpropagation a
re considered for the control of linear and nonlinear dynamics. A neur
al network estimator and controller is constructed and trained off-lin
e to learn the dynamic behavior and satisfactory control. The neural n
etwork estimator generates estimates of the plant output and also prov
ides the plant Jacobian for the neural network controller. For real-ti
me control purpose, the neural network estimator and controller is imp
lemented in assembly language using a Motorola DSP56001 digital signal
processing chip. The time to convergence can be shortened by utilizin
g the computational speed of the chip. The nonlinear activation functi
on of the neural network is approximated and stored as a look-up table
. Simulation results between the DSP and C language versions agree wel
l without any noticeable degradations.