15. The fuzzy logic controller of claim 14 in which said fuzzifier second means receives said process input signals and said representations of input fuzzy patterns generated by said fuzzifier first means from said process input signals, said fuzzifier second means comprising means for selecting a clearness distribution from said knowledge-base corresponding to each of said input fuzzy patterns, and means for utilizing each said clearness distribution, and the input signal utilized by said fuzzifier first means in generating the representation of the fuzzy pattern which corresponds to said clearness distribution, to generate a representation of a clearness degree.
15. The fuzzy logic controller of claim 14 in which said fuzzifier second means receives said process input signals and said representations of input fuzzy patterns generated by said fuzzifier first means from said process input signals, said fuzzifier second means comprising means for selecting a clearness distribution from said knowledge-base corresponding to each of said input fuzzy patterns, and means for utilizing each said clearness distribution, and the input signal utilized by said fuzzifier first means in generating the representation of the fuzzy pattern which corresponds to said clearness distribution, to generate a representation of a clearness degree. 19. The fuzzy logic controller of claim 15 wherein said means for mapping of said approximate reasoning means comprises means for determining the average value of input clearness degrees represented by said representations of input clearness degrees and for assigning said average value to the control action clearness degree represented by said representation of a control action clearness degree.