A. Cardoso, P. Gil, J. Henriques, P. Carvalho, H. Duarte-Ramos, and A. Dourado (Portugal)
Fault-tolerant control systems, fault diagnosis, model based predictive control, online training, robustness.
A robust fault-tolerant control framework is proposed and applied to a Distributed Solar Collector field. The framework considers a model-based approach to estimate the system's state variables for supervision and fault diagnosis purposes and a model-based predictive control combined with a recurrent neural network. The supervisor system includes a fault detection filter to generate residual signals, which are used to isolate and identify the faults. The control system is based on a non linear adaptive constrained model-based predictive control scheme with steady-state offset compensation. To assess the controller's robustness and fault tolerance, some faults on the actuator, sensors and system parameters were considered.
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