Title: Fuzzy autonym MFs to improve complex grid network security by fuzzy implication PSO algorithm for dealing of islanding ADCS mode
Authors: K. Harinadha Reddy; S. Govinda Raju
Addresses: Department of Electrical and Electronics Engineering, Lakireddy Bali Reddy College of Engineering (A), Mylavaram, Krishna Dt, A.P., India ' Department of Electrical and Electronics Engineering, J.N.T. University, Kakinada, East Godavari district, A.P., India
Abstract: The network system with bigger number of and connectivity computing nodes during the operation is a big challenge. Fuzzy based inference system is elaborately presented with variable weighted random parameter of particle swarm optimisation (PSO), cognitive and social terms. The main content of this paper is that of data handling and concentrated in elaborating the modelling to complete this task for abnormal disturbance conditional state (ADCS) mode. For application point of view, grid network with non-conventional energy systems like distribution generators and micro grids is considered to manage and treatment data in practical environment. This paper presents up to date fuzzy memberships (FMFs) and are obtained at every sampling interval. Also, control vector from fuzzy system are used to modify PSO algorithm for essential analysis and identification and differentiation of data on user required satisfy level. This paper presents auto updating FMFs, i.e., autonym fuzzy memberships (AFMFs) and proposed fuzzy implication PSO (FIM-PSO) for analysis and hence identification of ADCS mode.
Keywords: fuzzy inference system; fuzzy memberships; FMFs; particle swarm optimisation; PSO; personal best data sets; PBDS; global best data sets; GBDS; abnormal disturbance conditional state mode; ADCS.
International Journal of Systems, Control and Communications, 2018 Vol.9 No.3, pp.230 - 254
Received: 16 Mar 2017
Accepted: 17 Nov 2017
Published online: 01 Jun 2018 *