Fuzzy Logic and NeuroFuzzy Technologies in Appliances

Fuzzy Logic is an innovative technology that enables the implementation of ‘intelligent’ functions in embedded systems. One of its advantages is, that even complicated functions and adaptive control loops can be implemented with the limited resources of low-cost 8 bit microcontrollers. We will discuss development methodologies, tools used, and code speed/size requirements of three case studies. The first case study shows how an existing product is enhanced with new, intelligent functions. In home air conditioners, the enhancement of the thermostat by fuzzy logic control techniques allows for a better adaptation to the requirements of the user. This results in a higher comfort level. Also, detection of low load situations yields energy savings. The second case study covers the replacement of sensors with fuzzy logic state estimatiors. In the example of a central heating system control, a $35 outdoor temperature sensor and its installation were replaced. Comparisons show that the fuzzy logic solution better adapts to high and low heat demand periods, thus yielding higher comfort and energy savings at the same time. The presented system is now in production in Germany (350,000 units per year). The third case study focusses on the automated generation of fuzzy logic systems or parts thereof. For laundry load detection in washing machines, neural-fuzzy technologies are employed that set up a fuzzy logic system using experimental data. The results of washing experiments, evaluated by experts, form this data base. The introduction of the resulting fuzzy logic laundry load detector saves an average 20% water and energy. The presented system is now in production in Germany (400,000 units per year). The following discussion assumes the reader is familiar with basic fuzzy logic design principles. For a comprehensive hands-on course on practical fuzzy logic design, refer to [14].