Appropriate controller parameter identification is essential for perfect control of the chosen industrial system. The designed controller must support better outcomes during the setpoint, multiple-setpoint, and disturbance rejection operations. This research aims to develop a PID tuning technique for a DC motor model using a hummingbird-optimizer (HO). This work finds the optimal values of \({K}_{p}\) , \({K}_{i}\) , and \({K}_{d}\) using the HO, and the performance is monitored using a novel objective value consisting of the \({M}_{p}\) , \(ISE\) , and \(IAE\) . The performance of the HO is then verified against a few chosen heuristic algorithms, and based on the achieved performance metrics; the merit of the HO on the selected problem is confirmed. The experimental outcome demonstrates that the proposed technique helped to provide a smooth reference and disturbance operation with ISE and IAE compared to other approaches of this study.