ANFIS Controller for Water Level Control of a Boiler Drum

The water level in boiler drum is the critical control parameter to be addressed for providing the efficient and safe operation of steam generators in power plants. The regulation is achieved by using the Artificial Intelligence (AI) technique, namely, Adaptive Neuro-Fuzzy Inference System (ANFIS). It has the capability of self-learning as ANN with the linguistic expression function of fuzzy inference, whose membership functions and fuzzy rules are acquired from a large lot of existing data instead of experience. So, it is well renowned for its control performance in the power system area due to the nonlinear nature and robustness to system parameters uncertainties in multidisciplinary domains and power system too. Here, ANFIS controller takes the error and change of error in water level as inputs to control the actuator of inflow water such that the steam flow out of the steam generator meets the requirement of turbine unit set point which indirectly resembles the demanded load by the Generation System Operator (GSO). The performance of the proposed ANFIS controller is analyzed in terms of tracking the water level set point of boiler drum. For this purpose, a boiler model is developed using the MATLAB/SIMULINK working platform. Then, the proposed ANFIS controller is designed and tested on it for water level regulation. The simulation results are examined and compared with existing FIS technique.