Research On Key Technology Of Electromechanical Fault Tolerant Control For UAV Short-distance Landing

With the continuous increase in the demand for modern warfare,the technology of large and medium-sized military unmanned aerial vehicles(UAVs)is rapidly developing in the world.Short-range landing is an important technology for safe recovery under the special environment of large and medium-sized UAVs.It has been receiving more attention from relevant research scholars at home and abroad.Electromechanical control system,as the core system for the successful landing of large and medium-sized UAVs,is often affected by sensor failures,actuator failures,and saturation of control inputs.Such impact could create a huge threat to save landing of UAVs on island reefs and aircraft carriers.Therefore,the fault-tolerant control technology of electromechanical systems is an extremely important research topic in UAV systems.Based on the background of a large-sized UAV national project,the autonomous fault-tolerant control method for integrated electromechanical management system(IEMS)is studied in the thesis.The main research contents and contributions are as follows:1.Aiming at the problem of stable tracking under the constraint slip ratio of UAVs during landing taxiing phase,the minimum learning parameter dynamic surface control method which based on the barrier Lyapunov function is proposed.Firstly,the asymmetric barrier Lyapunov function is introduced in this method to solve the problem of output constraint of system.Then,the dynamic surface technique is used to design the controller according to the neural network estimation of the minimum learning parameter.Considering the external disturbance and output constraint,the high precision tracking control performance of slip ratio can be achieved in UAV landing taxiing phase by implementing this controller.At last,in comparison with the traditional adaptive control method,the proposed approach has lower degree of compute,which indirectly short the braking distance.2.Considering the four different types of fault common wheel speed sensor,a finite-time fault control mechanism based on observer technology is proposed.First of all,in order to solve the problem of inaccurate measurement of sensor state under fault,a nonlinear sliding mode observer is designed to diagnose and reconstruct the fault.Then,the non-singular terminal sliding mode fault-tolerant controller is designed by using the estimated information to ensure the tracking performance of the optimal slip ratio in a finite-time under multiple types of runways,and shortens the landing braking distance of the UAV during sensor failure.At last,simulation results demonstrate that the fault-tolerant control algorithm has fast response time and better fault-tolerant effect.3.Considering the failure of the UAV’s actuator,a fault-tolerant landing control method based on nonlinear observer is proposed.Firstly,a nonsingular terminal sliding mode observer is developed to estimate the sum of actuator fault and external disturbance.Secondly,this estimated information is employed to implicitly reconfigure the compensative control algorithm.Thirdly,an integrated fault-tolerant controller based on fractional sliding mode is designed to improve the robustness of system.Finally,the simulation results show that,compared with the integer-order control method for this system,the proposed approach can track the desire slip ratio with fast response in case of failure of the actuator.4.A novel neural network fault-tolerant control strategy based on robust switch term is proposed for fault-tolerant control problem with multiple constraints such as output constraint,control input saturation,system uncertainty and external disturbance,when UAV may be landing on short runway.Firstly,adaptive neural networks are used to estimate the sum of nonlinearities and uncertainties in the braking system.Secondly,the robust switching term is introduced to compensate the impact of the neural network exceeding the approaching value,and the transient performance of the system is improved.After that,based on the Lyapunov method,the stability of the fault-tolerant control system is analyzed.In the end,the result simulations confirm the effectiveness of the proposed fault-tolerant control method under multiple constraints.5.Aiming at the requirements of UAV high-precision heading control,an adaptive neural network fault-tolerant corrective control method based on barrier Lyapunov is proposed.Firstly,by designing the barrier Lyapunov function and control compensation system to solve the system input and output constraints problem,a complex adaptive neural network fault-tolerant control method is proposed in back-stepping framework.Next,in order to avoid the “complexity explosion” problem in controller design,a sliding mode differentiator is used to calculate the derivative of the virtual control signal.Then,the low-pass filter is introduced in the method to effectively solve the problems of the operational algebraic-loop.At last,the simulation results show that this method can still make the output tracking error not violate the constraint interval in the case of multi-actuator faults,and the UAV can still obtain better correction performance.