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the observing and analyzing the simulation and real-
time results, when a fault occurs the PFTC scheme
using neural network plus PI controller design had
achieved its desired set point and stability.
Meanwhile, the PFTC using PI feedback control
design achieves its desired set point but does not
improve its steady state error as compared to PFTC
scheme. Hence, it can be proved that proposed PFTC
scheme using neural network plus PI controller mode
design is one of the most efficient techniques to
ensure the system performance does not degrade and
set point is achieved in spite of fault and disturbances.
Framework of PFTCS is a realistic choice when
efficient fault diagnosis procedure is not available.
However how to take into account the prior
knowledge of the system faults, is a key work in the
passive fault tolerant control system design. In further
works PFTC scheme can be designed for multiple
faults like system and sensor faults occurring at the
same time. Also other than neural network another
soft computing techniques can be used (e.g. Adaptive
Neuro-Fuzzy Inference System (ANFIS)) for PFTC
scheme.
ACKNOWLEDGMENT
This work was carried out in Instrumentation and
Process Control (IPC) Laboratory at the Department
of Chemical Engineering, Dharmsinh Desai
University, Nadiad-387001, Gujarat, India. The
authors also would like to express very great
appreciation to Dr. M. S. Rao and Mr. Pratik Soni for
his valuable and constructive suggestions during the
planning and development of this research work.
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A Framework for Fault-tolerant Control for an Interacting and Non-interacting Level Control System using AI
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