Authors:
Ju Hyun Kim
;
Dae Seup Kim
and
Man Gyun Na
Affiliation:
Chosun University, Korea, Republic of
Keyword(s):
Fault Detection and Diagnostics, Fault-Tolerant Control, Fuzzy Model, Model Predictive Control, Space Reactor Power Control, Sequential Probability Ratio Test.
Related
Ontology
Subjects/Areas/Topics:
Computer and Microprocessor-Based Control
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
The control system is a key element of space reactor design to meet the space mission requirements of safety, reliability, survivability, economics, and autonomous action. The objectives of the proposed model predictive control are to minimize both the difference between the predicted TE power and the desired power, and the variation of control drum angle that adjusts the control reactivity. A genetic algorithm is used to optimize the model predictive controller. The model predictive controller is integrated with a fault detection and diagnostics algorithm so that the controller can work properly even under input and output measurement faults. Simulation results of the proposed controller show that the TE generator power level controlled by the proposed controller could track the target power level effectively even under measurement faults, satisfying all control constraints.