Nowadays, one of the most common problems in control system theory that should be tackled is how to improve the precision of a plant in steady state, under a change in the target value of the plant. Well known fact is that the models we use for designing controllers are not ideal. Thus, when the controller is applied to the real plant there is difference in between the expected and obtained results. Likewise, the controllers should be designed to be at the same time robust to uncertainties and also fast enough to drive the system to the desired value. The purpose of this paper is to describe and finally implement the approach in which the idea is to improve the precision of the system in steady state by adding an additive term to the control value calculated by the predesigned PID controller. The PID controller is designed in advance, and has poorly tuned integral term. Afterwards, when the desired target value is changed the PID controller is not aware of that change, so its performance starts to drop and as a result the steady state error starts to increase. Therefore, to preserve the exactness of the plant’s output an additive term to the control signal is calculated out of a polynomial second order model derived from the error values obtained in the previous measurements of the plant. The results from MATLAB simulations have shown that the PID controller could not keep up good performance when the target value of the system is changed. Hence, by adding an additive term to the control signal we gave to PID the needed ‘awareness’ and as a result of that we could improve the steady state error by small margin.