Practical modeling and controlling of power plants in practical situationswillproduce better and more accurate simulation results as compared to using empirical model of the plant since it is limited to only numerical simulation using the MATLAB software. Thus, for accuracy, simulation should be carried out with practical plant models that are subjected to unpredicted disturbances and not only restricted to known disturbances such as simulated faults.

In addition, new model could also be built for further understandings on the behaviours of the power generation plants. With this new model, one can have a better grasp and understanding on the performances of the plant when subjected to different disturbances, how different types of controllers can help to improve their performances and the robustness of these controllers when subjected to different operating conditions of the power plant.

With the increased in the importance of having robust controllers implemented in the plant model, intelligent and/or robust control systems can be implemented to cater for such needs.

The intelligent control systems should be able to achieve sustained desired behaviour under conditions of uncertainty such as unpredictable environmental changes. Thus, such control system can be implemented in the form of fuzzy logic control systems since the fuzzy set theory is used to model uncertainties associated with imprecision, vagueness and lack of information, which will usually be the case when the controllers are designed before knowing which system model it will be used on.