Controllers are mostly used to improve the control system performance. The works related to controllers attract researchers since the controller can be applied to solve many industrial problems involving speed and position. Fuzzy logic controller (FLC) gains popularity since it is widely used in industrial application. However, the FLC structure is still lacking in terms of the accuracy and time response. Although there are optimization technique used to obtain both accuracy and time response, it is still lacking. Therefore, this research presents works on the FLC system which is the fuzzy inference system that will be optimized by the modified adaptive bats sonar algorithm (MABSA) for the DC servo motor position control. The MABSA will be optimized with the range of the membership input in the FLC. The research aims are to achieve accuracy while minimizing the time response of the DC servo motor. This is done by designing the FLC using the Matlab toolbox. After the FLC is designed completely, the Simulink block diagram for the DC servo motor and FLC are built to see the performance of the controller. The range of the membership function for inputs and outputs will be optimized by the MABSA to get the best positional values. The performance of the developed FLC with the optimized MABSA is verified through the simulation and robustness tests with the system that did not use the FLC and also the system without MABSA. It was demonstrated from the study that the proposed FLC with optimization of MABSA algorithm was able to yield an improvement of 3.8% with respect to the rise time in comparison to other control schemes evaluated. When compared with PSO algorithm, proposed FLC optimized by MABSA showed improvement by 12.5% in rise time and 10% in settling time. PSO-FLC also give 0.6% steady state error compared to the MABSA-FLC. In conclusion, the results validate the better performance in terms of rise time and settling time of the developed FLC that has been optimized by the MABSA
