M-FRHC based Rule Reduction for FLC
What is it about?
To deploy a real time fuzzy logic controller, it is important to have active rule reduction. However, existing active rule reduction processes compromises between accuracy and execution time which cannot be varied. In this paper a novel active rule reduction process is developed where the optimization between execution time and accuracy can be varied online.
Why is it important?
Fuzzy logic controllers can model human knowledge. Thus non-linear and critical control problems are easy to counter with this technique. However, they are computationally quite expensive and they are difficult to tackle large inputs as the number of rules exponentially increases with linear increase in inputs. This paper provides solution to this problem with the introduction of M-FRHC rule reduction algorithm.