Optimization of PWL analog testing excitation by means of genetic algorithm

The method presented in this paper uses evolutionary computations to analog circuit testing stimulus shape optimization. The proposed testing excitation is a PWL waveform that generates responses of the tested circuit with appropriate relationship between current values of its specifications and the value of the observed parameter. The energy of error signal between nominal and actually obtained responses is designated for the analyzed parameter. The fitness function applied to the evolutionary system allows to optimize the separation level of the identified circuit states and to improve linearity for relationship between the energy level and the circuit state.