Using Neural Network to Estimate the Success Percent of Spacecraft Active Fault-Tolerant Controller

Determining the controller success percent is one of the important issues in spacecraft active fault-tolerant control. The importance of this subject is mainly related to the random and unpredictable nature of faults. On the other hand, since there exists a wide range of faults, various simulations will require enormous time. To resolve this issue, the neural network is used. First, the neural network is trained and its efficiency is verified. Then, considering the high speed of the trained network, a thorough investigation is performed based on a wide range of faults. The obtained results are dynamically sensible and show that as the fault increases, the probability of controller success will decrease.