Model-based Tracking for Agent-based Control Systems in the Case of Sensor Failures

The study on artificial intelligence (AI) methods for tuning of particle accelerators has been reported in many literatures. This paper presents tuning method for agent-based control systems of transport lines in the case of sensor/actuator failures. The method uses model-based tracking concept to relax the demand on sensor data. The condition for successful operation of the stated scheme is derived, and the concept is demonstrated through simulation by applying it to the model of microtron, transport line-1 and booster of indus accelerator. The results show that this approach is very effective in transport line control during sensor/actuator failures.