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The definition of the generalized input fault vector is presented, and the geometric invariability of collinear vectors is also discussed.
By building mathematical model for HAGC (hydraulic automation gauge control) system of strip rolling mill, treating faults as unknown inputs induced by model uncertainty, and analyzing fault direction, an unknown input fault diagnosis observer group was designed.
Moreover, in order to overcome the interference of input fault, one can use a fault-tolerant control scheme for unknown sampled-data nonlinear singular system by modifying the conventional self-tuner control (STC).
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The presented method can effectively cope with partially abrupt and/or gradual system input faults.
The other is an active fault tolerance state-space self-tuner using the OKID method and modified autoregressive moving average with exogenous inputs (ARMAX) model-based system identification for unknown sampled-data nonlinear singular system with input faults.
where x l is the l th input, h l is the l th coefficients, l = 0,1,..., L - 1. Since FIR filters are composed of MAC units, the fault model can be classified into multiplier-input fault (MIF) model and adder-input fault (AIF) model.
input observer, fault reconstruction, consistency techniques, nonlinear systems.
The designed input and fault diagnosis techniques are illustrated by numerical simulation.
Numerical simulation results indicate the applicability of the proposed auxiliary input in fault detection.
Within this framework, previous work has demonstrated that a minimally harmful input guaranteeing fault diagnosis can be obtained by solving a Mixed Integer Quadratic Program (MIQP).
To this aim, a global active methodology is defined in order to synthesize an additive optimal control input from fault detection and isolation results.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com