A Novel Fractional Order Proportional Integral-Fractional Order Proportional Derivative Controller Design Based on Symbiotic Organisms Search Algorithm for Speed Control of a Direct Current Motor

In this study, the effectiveness of symbiotic organisms search (SOS) algorithm including Zwee Lee Gaing (ZLG) objective function in determining the fractional order (FO) proportional integral and FO proportional derivative (FOPI-FOPD) controller parameters is investigated. To this aim, an FOPI-FOPD controller is designed to control speed of a direct current motor. To calculate the controller parameters in an optimal manner, the SOS algorithm is used and the ZLG function is included within this algorithm as a cost function. The performance of the SOS algorithm is compared with a number of different algorithms to substantiate the method's superiority, including the atomic search optimization (ASO), opposition-based hybrid manta ray foraging optimization (OBL-MRFO), chaotic atom search optimization (ChASO), equilibrium optimizer (EO), arithmetic optimization algorithm (AOA), and gorilla troops optimizer (GTO) algorithms. For performance evaluation, settling time, maximum overshoot, and rise time of the motor speed are chosen as evaluation criteria. The results indicate that the minimum settling time (0.0118 s) and minimum rise time (0.0071 s) are obtained with the SOS-based FO controller compared to the other optimization methods. Thus, the SOS algorithm provides superior system performance, as evidenced by reduced overshoot, shorter settling time, and faster rise time. This highlights the effectiveness of the SOS-based controller in achieving optimal system response. In addition, to verify the robustness of the proposed method, the impact of disturbance effects such as changes in the motor dynamics and load variations are evaluated. The findings reveal that the proposed method surpasses previous techniques in terms of robustness, demonstrating its superior resilience to disturbances in the motor system.