Neuro fuzzy transmission control for automobile with variable loads

A transmission controller for an automobile with variable loads is designed and tested by using a transmission system (Isuzu NAVi-5) consisting of actuators and sensors besides gears, a throttle, and a clutch. This system engages and disengages the clutch and gears up and down automatically. In other words, a manual gear-shift system is automated. As neuro and fuzzy approaches are promising methods to interface between a vehicle operator and an automobile, they are used to design a transmission controller. Automobile loads are estimated from the signals of status sensors by fuzzy logic. Vehicle driver´s intention is inferred by fuzzy logic using the information from automobile status sensors on which driver´s intention is reflected. These are then fed into a neural network. An experienced driver (much data) teachers the neural network an optimal gear-shift scheduling such that a vehicle operator feels comfortable even when automobile loads change (for example when an automobile is traveling up and down hill)