Nonlinear control via fuzzy linguistic control
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This paper presents an analytic formulation of a class of fuzzy logic control algorithms that is meant to capture the essential nonlinearit(ies) of a given fuzzy control scheme. This formulation is based on using the characteristic functions of the rule set's constituent fuzzy subsets as interpolating functions to shape a nonlinear function that maps the process error, and its rate of change or cumulative sum, into the appropriate control action. We will discuss the implications of the proposed approach and its usage in establishing conditions for stability of fuzzy control systems, and in explaining how fuzzy control algorithms function as they do.
