Exploration of different parameter selection in fuzzy control applications on microcontroller

Abstract

In this paper, we explore memory usage and speed of execution when developing fuzzy applications on a microcontroller. To develop a fuzzy system, various parameters need to be select. Different parameters result in different degrees of accuracy and give different memory cost and execution time. In the experiments, we consider two typical controllers: fuzzy fan control and fuzzy pendulum. We target at PIC18F8722 microcontroller. We implement the example various fuzzy APIs in C for the microcontroller for testing the characteristics of typical fuzzy programs. We explore the tradeoff between the memory cost, and speed. The results show that using table lookup for fuzzy set approach is faster than the calculation. Max-min inference is not always faster than max-product operation. The code size for the example fuzzy program is around 20-30K. The number of instructions increases when we use complex fuzzy inference operation and defuzzification. The data size is increased linearly when the size of fuzzy sets grows.