This paper deals with data-driven fault diagnosis of three phase induction motor. The tools from subspace identification based data driven scheme are utilized to design a framework of fault detection and isolation. The fault detection scheme is so designed that it caters for even small magnitude faults. In order to discriminate different faults, a fault isolation algorithm is proposed. Isolation thresholds are designed. The results show the effectiveness of the proposed schemes

Time-delays, model uncertainties, faults, and disturbances are frequently the main causes of performance degradation and instability in industrial process control. This article presents a fault-tolerant robust model predictive control design for processes that involve the above effects and process constraints. The uncertainties are modeled into a polytopic affine form based on variations in the system's parameters. A new model based on augmentation of the state variables and tracking error is used that provides increased degrees of freedom for the control design and guarantees tracking performance. A parameter-dependent Lyapunov Krasovskii functional is used to design a state-feedback control that reduces the conservatism of the conventional approach and ensures robust stability and tracking performance of the closed-loop system. At each sampling instant, a control action is computed by solving an online constrained optimization problem that minimizes the upper bound of the "worst-case" performance index. Finally, the proposed framework is employed for the fault-tolerant control of a continuous stirred tank reactor to demonstrate its effectiveness in mitigating actuator faults and tracking the desired set-point.

A nonlinear robust fault detection scheme for synchronous generators in power systems is presented. The higher-order model of a synchronous generator having nonlinearity in dynamics is considered. A nonlinear observer-based fault detection (FD) scheme is proposed so that the designed FD is robust against disturbances, uncertainties, and sensitive to faults. To this end, a mixed $\mathcal {L}_{-}/\mathcal {L}_\infty$ induced norm-based framework is proposed, and various faults that are encountered in synchronous generators are investigated. The success of the proposed scheme is demonstrated through an application to IEEE 9-bus and 3-machine systems.