Fault Diagnosis And Fault-Tolerant Control For An Unmanned Quadrotor Helicopter

With the rapid development of science and technology,the maturity and functionality of the unmanned quadrotor helicopter(UQH)are becoming more and more perfect.Owing to the simple mechanical structure,affordable cost,and superior performance,the UQH has been widely applied in civilian and military domains.Therefore,it is an urgent requirement to enhance the safety,reliability,and availability of the UQH.However,due to the poor working conditions,unstable electronic components and aging actuators,the UQH is prone to faults.In this case,fault detection and diagnosis(FDD)and fault-tolerant control(FTC)are important parts of the UQH system to ensure its safe flight.Therefore,in the dissertation,considering sensor faults and actuator faults,some FDD and FTC methods are proposed for the QUH.The main results achieved in this dissertation include:1.With the consideration of sensor faults,a nonlinear FDD scheme is proposed for the UQH.To mitigate the negative impact of model uncertainties,the kinematic model of an UQH rather than the dynamic model is employed to design the FDD scheme.A two-stage extended Kalman filter(TSEKF)is developed for detecting,isolating and identifying sensor faults.Considering that the TSEKF is insensitive to time-varying faults,two adaptive two-stage extended Kalman filters are further proposed by integrating TSEKF with different forgetting factor schemes.Several experiments are implemented on an UQH platform to test the proposed FDD scheme,where bias fault,drift fault,and oscillatory fault are considered.Experimental results demonstrate that the FDD methods are effective for diagnosing sensor faults in different fault scenarios.2.With the consideration of actuator faults,a robust FDD scheme is developed for the UQH in the presence of external disturbances.First,the dynamic model of a UQH taking into account actuator faults and external disturbances is constructed.Then,treating the actuator faults and external disturbances as augmented system states,an adaptive augmented state Kalman filter(AASKF)is developed.Next,in order to reduce the computational load of AASKF,an adaptive three-stage Kalman filter(AThSKF)is proposed by decoupling the AASKF into three subfilters.Finally,simulation results demonstrate the AThSKF-based FDD scheme can not only detect and isolate actuator faults but also estimate fault magnitudes even if the UQH suffers from external disturbances.3.With the consideration of sensor and actuator faults,a novel FDD scheme is derived for the UQH.The dynamic model of the UQH,including sensor and actuator faults,is introduced.According to the fault type,a model set that includes normal model,sensor fault model,actuator fault model is designed,which overcomes the shortcoming of the conventional Interacting multiple model(IMM)method that the model set library is too large.Considering the feature of models,the sub-filters in the improved IMM(IIMM)method are designed.By the switching logic algorithm,the matched fault model is chosen,and the fault information is provided.Simulation results prove that the IIMMbased FDD scheme is an effective tool to deal with sensor and actuator faults for UQH.4.With the consideration of trajectory tracking under sensor faults,a nonlinear active fault-tolerant tracking control(AFTTC)scheme is designed for the UQH.The proposed AFTTC scheme is divided into two loops,where the outer loop and inner loop controllers are designed for the position control and the attitude control,respectively.The sliding mode control(SMC)algorithm is introduced to make the UQH track the desired trajectory and yaw angle,and to stabilize the pitch and roll motions.For implementing the active fault-tolerant control,a fault detection and diagnosis(FDD)unit is constructed by utilizing a robust three-step unscented Kalman filter.Based on the precise fault information,the SMC-based control laws are updated online to mitigate the adverse effects of sensor faults.Simulation results show that the proposed AFTTC scheme works well in both normal and different faulty scenarios.5.With the consideration of trajectory tracking under actuator faults,a robust AFTTC scheme is presented for the UQH.The proposed AFTTC scheme is designed based on a well-known model reference adaptive control(MRAC)framework that guarantees the global asymptotic stability of the UQH system.To mitigate the negative impacts of model uncertainties and enhance system robustness,a radial basis function neural network is incorporated into the AFTTC scheme for adaptively identifying the model uncertainties online and modifying the reference model.Meanwhile,actuator dynamics are considered to avoid undesirable performance degradation.Furthermore,a FDD method is constructed to diagnose loss-of-effectiveness faults in actuators.Based on the fault information,a fault compensation term is added to the control law to compensate for the adverse effects of actuator faults.Simulation results show that the proposed AFTTC enables the UQH to satisfactorily track the desired trajectory in the absence/presence of actuator faults.The dissertation deeply explores the FDD and FTC strategies,which significantly improve the safety and reliability of the UQH.The research results not only are applicable to UQH system,but also have a good theoretical reference for study on FDD and FTC of other aircraft.