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Wavelet-based techniques for fault detection usually employ one of two basic approaches, namely (a) decomposition of a measured signal containing fault-related information or (b) decomposition of a residue calculated as the difference between sensor readings and the output of a model. An alternative approach, which was recently proposed in, consists of employing the wavelet transform to identify a...
In this paper, a new energy based fault detection method for dissipative systems is proposed. Based on the dissipative properties, a so-called system energy balance will be first constructed. Then the fault detection for full states measurable case is carried out by checking the validity of this energy balance. For states unmeasurable case, the fault detection system design is achieved by an optimal...
This paper presents a systematic design framework for selecting the best sensor set to control an EMS system subject to satisfying a set of complex requirements such as optimum performance, robustness and sensor fault tolerance. The design framework combines the ℋ∞ robust control design, fault tolerance concept and heuristic approaches. The efficacy of the scheme is illustrated via application to...
This work compares the use of direct torque and flux control (DTFC) and model predictive control (MPC) for induction motor (IM) control. These two strategies are fundamentally different in operation since (i) DTFC decides the current control action based on a switching table constructed using a simplified model of the IM, whereas (ii) MPC decides the current control action by on-line minimization...
In this paper, an observer-based fault detection approach for a class of nonlinear systems is presented, which can be modeled by Takagi-Sugeno (TS) fuzzy models. We propose a sliding mode fuzzy observer that deals with bounded uncertainties in the plant and allows fault estimation based on an equivalent output error injection approach. Furthermore an adaption scheme based on pattern recognition algorithms...
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