Unknown input estimation for diesel engine based on Takagi-Sugeno Fuzzy Descriptor systems

In this paper a type of proportional integral fuzzy observers (PI-Fuzzy Observer) based on Takagi-Sugeno Fuzzy (TS-Fuzzy) Descriptor models is proposed with application in a real system. The state and unknown input estimation problems for a diesel engine air-path system is solved by using a PI-Fuzzy Observer. The proposed approach offers all the degrees of observer design and also, sufficient stability conditions and the observer gains that are obtained starting from the theory of linear matrix inequalities (LMIs). A TS-Fuzzy descriptor model of the process is developed in order to facilitate the design of the PI-Fuzzy Observer. The obtained results indicate that the observer is able to accurately reconstruct the states and the unknown inputs of the system.