A Temperature Controlled System for Car Air Condition Based on Neuro-fuzzy

Neural networks are good at recognizing patterns, but they are not good at explaining how they reach their decisions, while fuzzy logic systems, which can reason with imprecise information, are good at explaining their decisions but they cannot automatically acquire the rules they use to make those decisions. These limitations have been a central driving force behind the creation of intelligent hybrid systems where two or more techniques are combined in a manner that overcomes individual techniques. Based on these theory, we propose an automated neuro-fuzzy system approach for controlling car air condition temperature. Simulation shows that its control performance and stability was found to be improved significantly and even superior to the optimized PID controller and optimized conventional fuzzy controller. The system temperature was controlled with desired performance.