Prior information driven design of fuzzy logic controllers with application to the overhead crane control

The single-input-rule-modules (SIRMs) connected fuzzy reasoning method is an efficient way to reduce the number of fuzzy rules in the rule-based fuzzy controllers. However, there still exist fuzzy rule generation problems in the design process of the SIRMs connected fuzzy logic controllers (SIRMFLCs). To tackle this problem, this paper presents a prior information driven method for constructing the SIRMFLCs, including both type-2 and type-1 cases. Here, prior information means the requirements that the controllers must meet, e.g. continuity, symmetry and monotonicity of the controllers. To encode such prior information into the SIRMFLCs, the parameter conditions or constraints are provided. To show the effectiveness of the proposed method, applications to the stabilization control of the overhead crane system is given. Through utilizing the prior information to constrain the structures and parameters of fuzzy rules, the proposed strategy can reduce the blindness in the initialization of fuzzy rules and can generate the single input rule modules systematically.