Abstract:

Aiming at the issue that quantum genetic algorithm is not suitable for continuons function optimization, an improved quantum genetic algorithm is proposed. This algorithm directly compares the quantum chromosomes with the current best solution to determine the rotating angle of the rotating gate. Every individual in population evolves with different rates to complete local search and global search simultaneously. Mutation operation is used to prevent the premature convergence. After analyzing the algorithm and its global convergence, this algorithm is applied to solve the function extremum and to optimize the PID controller parameters, and it is compared with the standard genetic algorithm and the quantum genetic algorithm. Experimental results illustrate that the proposed algorithm has better performance.