This code presents a model-based strategy for fault tolerance in non-linear chemical processes. The structure of the proposed Active Fault-Tolerant Control System (AFTCS) is,

There, the Fault Detection and Diagnosis (FDD) stage uses banks of generalized observers to detect, isolate and estimate multiples faults. Specifically, a group of LPV Reduced-order Unknown Input Observers (LPV-RUIO) and LPV Output Observers with Unknown Input (LPV-UIOO) is used. Subsequently, this information is delivered to a reconfiguration mechanism that compensates the controller's input data, in order to achieve an acceptable post-fault system performance. The selected controller uses an Moving Horizon Estimation (MHE) technique to update the Model-based Predictive Control (MPC) internal model at each iteration time, enhancing the controller fault-tolerance capabilities.

Stability conditions of FDD module and Fault-Tolerant Control (FTC) unit are now guaranteed in terms of Linear Matrix Inequalities (LMI) problems.

Simulation results, based on a typical chemical industrial process, is given to illustrate the implementation and performance of such approach.

• At least an i5-3337U [email protected] GHz (2 Cores) with 6 GB of RAM.
• Matlab software R2016b or greater

• Yalmip
• Gurobi
• SeDuMi
• LMI Lab

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Emanuel Bernardi