A New Active Fault Tolerant Control System: Predictive Online Fault Estimation

Abstract

This study presents a new approach for active fault-tolerant controller (FTC) design for constrained nonlinear multi-variable systems. The proposed approach utilize the nonlinear model predictive controller (NMPC) and fault estimation method which is on basis of extended kalman filters (EKFs). The deficiency of actuators and sensors and also the plant states measurement errors are estimated by the suggested approach. A supervisor unit using the fault information and fault modeling per sampling time, corrects the predictor model of the controller and compensates actuator and sensor faults in control system. Furthermore, by the presented feedback compensation, the robustness of the designed method against plant faults and uncertainties is ensured. The important advantages of the proposed method are:(1) The suggested FTC scheme based on NMPC leads to calculate more accurate control action than MPC in nonlinear processes, (2) it is comprehensive in fault accommodation point of view because it is able to compensate all types of faults in control systems simultaneously, (3) it has low computational cost because of using NMPC by analytical solution, (4) it can handle control and states constraints to prevent of actuator saturations and unsafe situations, (5) the simplicity and effectiveness of the designed FTC scheme for real applications is more significant. Simulation results on continuous stirred tank reactor process verifies the superiority and capability of the designed approach.

Investigating the predictive contribution of attitude towards life and belief system on self-resilience and psychological toughness of cancer patients about the mediating role of emotion regulation

“…Application to medical and social sciences on the other hand needs more datapoints to fit a correct model. Methods, such as, LSTM, CNN and further deep learning methods in former studies, e.g., [56][57][58][59][60][61][62][63][64][65][66] need extensive datasets. Thus, expanding the datasets for future studies is fundamental.…”

Investigating the predictive contribution of attitude towards life and belief system on self-resilience and psychological toughness of cancer patients about the mediating role of emotion regulation

“…Application to medical and social sciences on the other hand needs more datapoints to fit a correct model. Methods, such as, LSTM, CNN and further deep learning methods in former studies, e.g., [56][57][58][59][60][61][62][63][64][65][66] need extensive datasets. Thus, expanding the datasets for future studies is fundamental.…”

https://www.academia.edu/93557562/Predicting_Power_and_Hydrogen_Generation_of_a_Renewable_Energy_Converter_Utilizing_Data_Driven_methods_A_Sustainable_Smart_Grid_Case_Study

“…The integration of the sustainable resources in smart grid is of particular importance [46]. This is mostly due to an effort to mitigate energy saving, clean energy, and climate change, as well as pressure by the governments to promote sustainable development and zero carbon emission [47][48][49][50]. The integration of renewable energy resources in the smart grid supports sus-tainable development [51].…”