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    • 1. 发明专利
    • HYBRID CROW-SEARCH ALGORITHM WITH PARTICLE SWARM OPTIMIZATION IN LOAD FREQUENCY CONTROL (LFC).
    • AU2021105834A4
    • 2021-11-11
    • AU2021105834
    • 2021-08-18
    • BABU NALADI RAMBHAGAT SANJEEV KUMARSAHA ARINDITASAIKIA LALIT CHANDRA
    • BABU NALADI RAMSAIKIA LALIT CHANDRABHAGAT SANJEEV KUMARSAHA ARINDITA
    • G06N3/00G06F1/30
    • A method for hybrid crow-search algorithm with particle swarm optimization (hCA-PSO), comprises of: setting values of flock size, iteration, random number, flight length, awareness probability and memory for the hCA-PSO; assigning a position and memory to crow of the hybrid crow-search algorithm; evaluating fitness using a transfer function of a tilt-integral-derivative with filter (TIDN) controller, wherein if random number is greater than awareness probability, then a new crow position is generated using the crow search algorithm, else a current position is retained; updating assigned memory with the new crow position if current retained position is greater than memory, else the current position is retained in the memory; and obtaining best position of crow with optimum controller parameters if number of interactions is less than maximum value of iterations providing as the setting values. setting values of flock size, iteration, random number, flight length, awareness probability and memory for the hCA-PSO; assigning a position and memory to crow of the hybrid crow-search algorithm; evaluating fitness using a transfer function of a tilt-integral-derivative with filter (TDN) controller, 104 wherein if random number is greater than awareness probability, then a new crow positions generated using the crow search algorithm, else a current position is retained 106 updating assigned memory with the new crow position if current retained position is greater than memory, else the current position is retained in the memory 108 obtaining best position of crow with optimum controller parameters if number of interactions is less than maximum value of iterations providing as the setting values 110 Set values of flock size, iteration, random number (rj) fght length (FL), awareness robability (AP), memory (m) Assign position and memory to crow Fitness evaluation by (4) Generating new o sition Selecting (Xaar+) using () random psition Yes feasibility check No of new position |Update the position rRetain the current with new one (X"'" position (X""') Yes No Update the m emory Retain the |with new position current position lUpdate positions and velocities of all crows according to (I1 nd(2 Noterations