Parameter estimation of multivariable system using Fuzzy State Space Algorithm / Razidah Ismail … [et al.]

Fuzzy State Space Model (FSSM) was developed to cope with the demand and performance due to the increase in the system complexity. The main feature of the model is the development of the Fuzzy State Space Algorithm (FSSA) for determination of input parameters that can be applied to any multivariable dynamic system. In this project, the FSSA is applied to the superheater system in the combined cycle power plant. The initial phase involved the development of the FSSM of the superheater system. In order to enhance the implementation of the algorithm, it is necesssary to develop an efficient computation program together with the user's interface. In the next phase, the transformation of FSSM to fuzzy graph is studied. The theory from directed graphs is explored to define and interpret the interconnections structure underlying the dynamics of the interacting systems. It is hoped that new concepts of dynamic connective stability of complex systems will be mathematically formalised. The proposed new approach is expected to provide a faster and innovative tool for simulation and analysis of multi variable system.