Design of a TS Based Fuzzy Nonlinear Unknown Input Observer with Fault Diagnosis Applications

TLDR: The article presents an NUIO based fault detection scheme for problem 1, gives sufficient conditions for problem 2, determines the maximum number of faults that can be isolated for problem 3, and proposes a fault diagnosis scheme using a bank of NUios to solve problem 4.

Abstract: An approach for nonlinear unknown input observer (NUIO) design for nonlinear systems representable by a Takagi-Sugeno (TS) fuzzy system. The proposed NUIO design for TS fuzzy systems is carried out for two cases: 1) the premise variables do not depend on the unmeasured state variables; and 2) the premise variables depend on the unmeasured state variables. Sufficient conditions for the existence of NUIOs are derived, and an LMI based observer design strategy is proposed. Once the NUIOs are designed, fault detection and isolation problems for nonlinear systems described by TS fuzzy systems using the new NUIO is presented. To solve the actuator fault isolation problem, a system structure with two groups of inputs where one group is treated as unknown inputs is developed. A bank of NUIOs is then designed in order to investigate the following fault diagnosis problems: 1) How can the NUIOs be used for detecting faults? 2) Under what conditions is it possible to isolate single and/or multiple faults? 3) What is the maximum number of faults that can be isolated simultaneously? 4) How can multiple fault isolation be achieved? The article presents an NUIO based fault detection scheme for problem 1, gives sufficient conditions for problem 2, determines the maximum number of faults that can be isolated for problem 3, and proposes a fault diagnosis scheme using a bank of NUIOs to solve problem 4.