Fault-tolerant Linear Parameter Varying Model Predictive Control Scheme for Industrial Processes (FT-LPVMPC)
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 CPU@2.7 GHz (2 Cores) with 6 GB of RAM.
- Matlab software R2016b or greater
Bernardi, Emanuel, and Eduardo J. Adam. "Fault-tolerant predictive control based on linear parameter varying scheme for industrial processes." Journal of the Taiwan Institute of Chemical Engineers 129 (2021): 1-14.
Send comments and questions to: