Modeling And Design Of Nano Scale Cmos Controller Using Adaptive Neuro-Fuzzy For Speed Control Of Dc Shunt Motor

Abstract

The main aim of this work is to control the speed of the DC shunt motor by using a nano scale Complimentary Metallic oxide Field Effect Transistor (CMOS) inverter with Adaptive Neuro-Fuzzy based method for optimal parameter selection. The speed of the DC shunt motor can be varied by varying armature voltage with field current constant and varying the field current with armature voltage constant. It is found that the speed is said to increase with increase in armature voltage for which the graph is a linear in case of armature controlled method. Whereas for the field control method the speed is said to increase with decrease in field current with armature voltage to be constant. The stated condition is cross verified by plotting the graphs for conventional and proposed nano scale CMOS inverter with ANFIS optimization scheme. A novel technique for modeling and devising a nano scale CMOS circuit using adaptive neuro-fuzzy network for controlling and tuning the switching characteristics of the circuit so that it is symmetric with equal values of rise time and fall time with equal output for propagation delay during low to high and high to low outputs. This control over the CMOS switching characteristics using ANFIS controller offers an effective speed control for DC shunt motors. The designed scheme for 45nm process technology is simulated using MATLAB. The results for nano scale CMOS inverter with ANFIS optimization scheme proved to be accurate with an accuracy of 97.5% to 100% which is compared with experimentation results obtained in laboratory using conventional speed control techniques like field and armature control methods.