Earticle

An efficient method is presented to design filters without the similarity transform of their coupling coefficient matrix as circuit parameters, which is very tedious due to pivoting and deciding rotation angles needed during the iterations. The transfer function of a filter is directly used for the design and its desired form is derived by the optimized rational-function fitting technique. A 3rd order coaxial lowpass filter is taken as an example to validate the proposed method.

An algorithm is proposed to find a stable rational function, which is frequently used in the linear system theory, by curve-fitting a given data. This problem is essentially a nonolinear optimization problem. In order to converge faster to the solution, the following method is used. First, the coefficients of the denominator polynomial are fixed and only the coefficients of the numerator polynomial are adjusted by its linear relationships. Then the coefficients of the numerator are fixed and the coefficients of the denominator polynomial are adjusted by nonlinear programming. This whole process is repeated until a convergent solution is found. The solution obtained by this method converges better than by other algorithms and its versatility is demonstrated by applying it to the design of a feedback control system and a low pass filter.