Neuro fuzzy optimal transmission control for automobile with variable loads

An optimal transmission controller for an automobile with variable loads is designed and tested by using a transmission system (Isuzu NAVi-5) which consists of actuators and sensors beside 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 an optimal transmission controller. The automobile loads are estimated from the signals of the status sensors by fuzzy logic. The vehicle operator´s intention is inferred by fuzzy logic using the information from the automobile status sensors on which the operator´s intention is reflected. Then, these are fed into a neural network. An experienced driver (a lot of data) teaches the neural network an optimal gear shift scheduling such that a vehicle operator feels comfortable even when the automobile loads change (for example when an automobile is traveling up and down hill)