摘要
Purpose-In recent times,fuzzy logic is gaining more and more attention,and this is because of the capability of understanding the functioning of the system as per human knowledge-based system.The main contribution of the work is dynamically adapting the important parameters throughout the execution of the flower pollination algorithm(FPA)using concepts of fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.Design/methodology/approach-The fuzzy logic-based parameter adaptation in the FPA is proposed.In addition,type2 fuzzy logic is used to design fuzzy inference system for dynamic parameter adaptation in metaheuristics,which can help in eliminating uncertainty and hence offers an attractive improvement in dynamic parameter adaption in metaheuristic method,and,in reality,the effectiveness of the interval type2 fuzzy inference system(IT2 FIS)has shown to provide improved results as matched to type-1 fuzzy inference system(T1 FIS)in some latest work.Findings-One case study is considered for testing the proposed approach in a fault tolerant control problem without faults and with partial loss of effectiveness of main actuator fault with abrupt and incipient nature.For comparison between the type-1 fuzzy FPA and interval type-2 fuzzy FPA is presented using statitical analysis which validates the advantages of the interval type2 fuzzy FPA.The statistical Z-test is presented for comparison of efficiency between two fuzzy variants of the FPA optimization method.Originality/value-The main contribution of the work is a dynamical adaptation of the important parameters throughout the execution of the flower pollination optimization algorithm using concepts of type2 fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.
