Diagnosis of individual cell frequencies in a coupled cavity chain by genetic algorithms

Genetic algorithms (GAs) is used to diagnose individual cell frequencies in a coupled cavity chain with no need of any probe insertion. The cell frequencies and couplings between the cells are determined in terms of the measured pass-band performance. It will simplify the tuning processes and make the tuning of the sealed cavity possible. The solution is cast as an optimization problem and GAs is used as a function optimizer to solve this problem. Moreover, in order to expedite the convergence, nonlinear least squares method is added as one kind of mutation into GAs, which makes GAs converge faster and improves the precision of the solution. The effectiveness of the new technique has been demonstrated through some numerical examples, and the results have also been compared with those of the conventional GAs