This paper presents a concept of the cloud -based tool that extends the auto-tuning capabilities accessible in the PID function blocks available in Programmable Logic Controllers. Based on the data collected during the built-in auto-tuning experiment, a dynamical model of the process is obtained in the cloud environment and then by any more or less advanced method a new set of PID tunings is proposed based on different closed-loop performance criteria predefined by the user. This method can be an alternative for the for the autotuning methods accessible in the PID function blocks and in this paper, its usability in industrial control systems is validated using virtual commissioning technique based on Siemens equipment and programming environments.