This letter presents a novel indirect learning architecture which uses
a single neural network in implementation. The new architecture gener
ates the error signal required in training the controller network by a
n innovative design using a memory element and few switches. The new c
ontroller needs only half the number of neurons and connection weights
in comparison with the original indirect learning architecture. Also
given are the simulation results in controlling a nonlinear plant.