A novel modified opposition‐based hunger games search algorithm to design fractional order proportional‐integral‐derivative controller for magnetic ball suspension system. Issue 1 (31st January 2022) - Izci, Davut; Ekinci, Serdar; Eker, Erdal; Kayri, Murat
Abstract: This study focuses on construction of novel enhanced metaheuristic algorithm using a modified opposition‐based learning technique and the hunger games search algorithm. The proposed modified opposition‐based hunger games search (mOBL‐HGS) algorithm is aimed to be used as an efficient tool to tune a fractional order proportional‐integral‐derivative (FOPID) controller in order to control a magnetic ball suspension system with greater flexibility. The challenging benchmark functions from CEC2017 test suite are used to confirm the greater performance of the proposed mOBL‐HGS algorithm. The proposed mOBL‐HGS algorithm is also utilized to reach the optimum values of a FOPID controller employed in a magnetic ball suspension system in order to demonstrate its capability in terms of a complex real‐world engineering problem. The latter case is confirmed through comparative evaluations of statistical analysis, convergence profile, transient response, frequency response, disturbance rejection, and robustness. The demonstrated results confirm the greater ability of the proposed approach to control a magnetic ball suspension system. Abstract : A novel mOBL‐HGS algorithm is developed. The greater performance of the mOBL‐HGS algorithm is shown on highly challenging CEC2017 test suite. The mOBL‐HGS algorithm is then proposed for optimal tuning of a FOPID controller employed in a magnetic ball suspension system and the efficiency of the proposed algorithm is confirmed via comparative assessments.