Purpose Patients with hypotension in emergency clinical situations require the administration of vasopressor drugs for a fast and correct return of the mean arterial pressure, done by either manual or automated administration which can be done by either manual or automated administration. The proportional-integral-derivative (PID) algorithm has been used for several years as one of the most understandable and easily implemented automatic control techniques. However, in situations where there is variability in the parameters of the process you want to control, as in the case of the mean arterial pressure (MAP) response in patients undergoing vasopressor infusion, the automatic control system can become challenging. This paper describes the development of a controller, considering the real-time identification of several types of patients. Methods The MAP response for phenylephrine (PHP) drug infusion and the controller were modeled by the MATLAB/Simulink computational tool and embedded each one on simple hardware platforms based on the low-cost microcontroller. The controller was designed considering a time for patient identification, allowing its adjustment according to the patient. To validate the feasibility of the controller, tests were conducted verifying the performance both in a computer simulation environment and in hardware-in-the-loop (HIL) simulation. In these tests, three tuning methods were used for control, based on the consolidated methods developed by Ziegler-Nichols and Skogestad. Results The results obtained show that the patient identification occurs in 200 s. The MAP control was obtained with a steady-state error of less than 0.31 mmHg, settling time with a maximum of 240.5 s, and peak overshoot of desired MAP value on the order of 5.5 mmHg in its worst case, considering all tuning methods. Conclusion The developed control system can identify the patient’s response type. The results obtained indicated that the controller demonstrated to be suitable for low peak overshoot and steady-state error values, allowing a smoother MAP control.