Rule based approximate reasoning for intelligent control

Fuzzy logic control is being increasingly applied to solve control problems in areas where system complexity, development time and cost are the major issues. In the absence of a system mathematical model, a fuzzy system model is described which is analogous to a human operator's behavior, based on approximate reasoning bound by a minimum set of rules. A set of linguistic fuzzy control rules are set up which are conditional linguistic statements which establish the relationships between the inputs and the outputs. The motor speed is controlled by controlling the armature voltage Va. This technique is used by the author as a fundamental basis for the fuzzy controller synthesis. To comply with the torque demand requirements, the armature current and field currents are maintained at a constant level for motor speeds less than the base speed and the speed is controlled by varying the armature voltage. The field current can be varied to control the speed by maintaining the armature voltage at a constant level for motor speeds higher than the base speed. But, field current is not varied here, since speed control is below the base speed. The armature is supplied with different voltages with the shunt field of the motor permanently connected to a constant exciting voltage. The main supply is AC which is converted to DC by using a bridge circuit. Silicon controlled rectifiers (SCR) are used to vary the mean voltage supplied to the DC motor by firing the SCR's at varying angles of the input sine wave. The speed of the motor is more or less proportional to the varying supply voltages.