PUBLICATIONS

A robust adaptive speed sensorless induction motor direct torque control (DTC) using a neural network (NN) is presented in this

paper. The inherent lumped uncertainties of the induction motor DTC system such as parametric uncertainty, external load

disturbance and unmodeled dynamics are approximated by the NN. An additional robust control term is introduced to compensate

for the reconstruction error. A control law and adaptive laws for the weights in the NN, as well as the bounding constant of the

lumped uncertainties are established so that the whole closed-loop system is stable in the sense of Lyapunov. The effect of the

speed estimation error is analyzed, and the stability proof of the control system is also proved. Experimental results as well as

computer simulations are presented to show the validity and efficiency of the proposed system.