Optimizing an LDO voltage regulator by evolutionary algorithms considering tolerances of the circuit elements

A low-dropout (LDO) voltage regulator is optimized by evolutionary algorithms. Basically, tolerance analysis is performed alike a worst-case analysis within SPICE to rank the circuit elements presenting higher sensitivities, and according to the target specifications associated to two objectives, namely: Power Supply Rejection (PSR) and output capacitor value. The results from the tolerance analysis are used to propose for the first time a chromosome of the LDO to perform multiobjective optimization by evolutionary algorithms. In addition, the computed tolerances are used to establish reduced search spaces for the circuit elements included into the chromosome, so that the optimization by applying the non-dominated sorting genetic algorithm (NSGA-II) being accelerated. As a result, the main contribution is the application of tolerance analysis to set the chromosome that includes few circuit elements to optimize an LDO voltage regulator, and to establish reduced search spaces to accelerate computing time.