Multi-objective optimization algorithms in analog active filter design

In this paper, component values of analog active filter are optimized based on multi-objective optimization. For this purpose, the multi-objective inclined planes system optimization (MOIPO) algorithm is evaluated and applied as a powerful method in this field. The estimated variables values are selected based on the manufacturer's values of E12 series. By considering a fourth-order Butterworth filter, the global optimization capability of MOIPO is investigated. The performance of the proposed method is compared with the well-known algorithms, non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective particle swarm optimization (MOPSO). The simulation results prove that MOIPO is superior for the minimization quality factors deviation and cut-off frequency deviation compared to other methods.