Most practical Boiler systems are characterized by high uncertainty which makes them difficultrnto maintain good stability margins and performance properties for closed loop system. In case ofrnconventional control, if plant parameter changes we cannot assure about the system performance.rnHence it is necessary to design robust control for uncertain plant. Among the various strategiesrnproposed to tackle this problem, Quantitative Feedback Theory (QFT) has proved its superiorityrnespecially in the face of significant parametric uncertainty. The feature of QFT is that it can takerncare of large parametric uncertainty along with phase (degree) and magnitude (dB) informationrnat each working frequency. To achieve good performance of industrial boiler system whichrnreduce fuel consumption rate and improves efficiency, dynamic variables such as fuel flow, airrnflow and pressure of boiler must be controlled. In the first step plant is identified by usingrnexperimental data by the mean of converting into a group of linear time invariant (LTI) uncertainrnplants. After representation of the uncertain dynamic system in general control configuration andrnmodeling the parametric uncertainties, nominal performance, robust stability and robustrnperformance against disturbances are analyzed by the concept of robust control.rnFinally, Linear time invariant (LTI) has been carried out and two controllers are compared. As inrnthe PID controller case, the initial PID design balances reference tracking and disturbancernrejection. In this case as well, the controller yields some overshoot in the reference-trackingrnresponse, and suppresses the input disturbance with a longer settling time. The output in responsernto a unit step disturbance should remain within the range [âˆ’1, 1] at all times, and it should returnrnto 0 as quickly as possible y(t) should at least be less than 0.1 after 3 sec).rnFrom simulation we observed settling time 20.9 seconds and overshoots 30.7%. But bothrnController and pre-filter controllers guarantee robust performance of the system against thernuncertainties and result in desired time responses of the output variables. By applying QFTrnrobust control, system tracks the desire reference inputs in a less time and with smoother timernresponses. It is observed from the simulation results that the overshoot is 0%, rising time isrn0.0199 seconds and the settling time is 0.0369 seconds and Peak time is 0.0939 seconds withrnQFT controller. It is further observed that the proposed controller has robust stable andrnPerformance.