There is a continuous effort to develop efficient control mechanisms for power converters as it is a challenging task due to nonlinear nature of such systems. As part of the ongoing effort in the related field, a novel control method is presented in this paper. The proposed method with this study involves a fractional order proportional-integral-derivative (FOPID) controller and the development of a novel metaheuristic algorithm for tuning in order to achieve optimum performance of a buck converter system. In terms of the metaheuristic algorithm, an improved version of the hunger games search (IHGS) algorithm is developed by enhancing the intensification and the diversification abilities of the hunger games search (HGS) algorithm with the aid of Nelder-Mead simplex method and the random learning mechanism, respectively. Several classical unimodal, multimodal, and fixed dimensional benchmark functions along with CEC2019 test suite are used to confirm the improved structure of the developed IHGS algorithm. A novel objective function is also constructed in this study by modifying the structure of the performance index known as integral of squared error. The novel IHGS algorithm together with the novel objective function are proposed as an efficient tool to design a FOPID controller employed in a buck converter system. The proposed method's superiority for the operation of a buck converter system is confirmed comparatively with transient and frequency responses along with robustness analysis in terms of parametric uncertainties and measurement noise along with input and load voltage fluctuations using the best performing methods of artificial ecosystem optimization algorithm based PID, Lévy flight distribution algorithm based PIDA and Harris hawks optimization algorithm based FOPID controllers. The other capable approaches reported in the literature are also used to further confirm the excellent ability of the proposed method for controlling a buck converter system.