Design Of Fault-tolerant Controller For Underwater Robot With Thruster Failure

Unmanned underwater vehicles(UUV)are widely used in commercial,scientific and military missions for various purposes.What makes this technology challenging is increasing the duration of the task and the unknown environment.It is necessary to embed fault-tolerant control paradigm into UUV to improve the reliability of the load and enable it to perform and complete complex tasks.Specifically,fault tolerant control(FTC)includes fault detection,identification,and control reconfiguration for fault compensation.The literature review shows that there is no systematic method for fault-tolerant control of UUV in the early survey.This study presents a layered approach to fault detection,identification and compensation(HFDIC),which integrates these functions systematically into different levels.The method uses adaptive finite impulse response(FIR)modeling and analysis at its first level to detect failure.Specifically,it contains a FIR filter for online adaptive modeling and a minimum mean square(LMS)algorithm to minimize the output errors between the monitored system and the filter during the modeling process.By analyzing the generated adaptive filter coefficients,we extract the fault information.The Hfdic also includes the two-level design of level two and level three parallel Kalman filters for fault identification using multiple model adaptive estimation(Mmae).The algorithm activates the latter level only when a failure is detected,and can return to the monitoring loop in the event of an error failure.On the basis of mmae,we use multiple sliding mode controllers and reconfigure the control law with the probabilistic weighted average of all elements to compensate for the failure.We have validated various analog actuators and sensor faults in the UUV steering and diving subsystem,and simulated the Hfdic(HFDI)of the offshore data of autonomous underwater vehicle(AUV).For both cases,we modeled the actuator and sensor fault as additional parameter changes in the observation matrix and the output equation respectively.The simulation results show that HFDIC can detect faults in real time,accurately identify faults with low computational cost,and reconfigure compensating actuators and sensor faults through control.In particular,using FAU data validation HFDI can confirm the performance of fault detection and recognition methods and provide important information about the performance of the carrier.