An introduction to genetic algorithms
An introduction to genetic algorithms
A First Course in Fuzzy and Neural Control
A First Course in Fuzzy and Neural Control
MED '09 Proceedings of the 2009 17th Mediterranean Conference on Control and Automation
Fault tolerant control of multivariable processes using auto-tuning PID controller
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In this article different schemes for Fault Tolerant Control (FTC) based on Adaptive Control, Artificial Intelligence (AI) and Robust Control are proposed. These schemes includes a Model Reference Adaptive Controller with a Neural Network and a PID controller optimized by a Genetic Algorithm (MRAC-PID-NN), a Model Reference Adaptive Controller with a Sliding Mode Control (MRAC-SMC) and a classical Model Reference Adaptive Controller (MRAC). In order to compare the performance of these schemes, an Industrial Heat Exchanger was used as test bed in which two different types of faults (abrupt and gradual) with different magnitudes (10% and 20%) were simulated. The simulation results showed that the use of AI methods improves the FTC schemes, developing a robust control system against sensor faults and a wider threshold to accommodate actuator faults in comparison with the two other schemes.