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System Identification And Fault Detection Of Complex Systems, Dapeng Luo

Electronic Theses and Dissertations

The proposed research is devoted to devising system identification and fault detection approaches and algorithms for a system characterized by nonlinear dynamics. Mathematical models of dynamical systems and fault models are built based on observed data from systems. In particular, we will focus on statistical subspace instrumental variable methods which allow the consideration of an appealing mathematical model in many control applications consisting of a nonlinear feedback system with nonlinearities at both inputs and outputs. Different solutions within the proposed framework are presented to solve the system identification and fault detection problems. Specifically, Augmented Subspace Instrumental Variable Identification (ASIVID) approaches …