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Anti-disturbance And Fault-tolerant Tracking Control For Quadrotor Unmanned Aerial Vehicle

Posted on:2024-01-01Degree:MasterType:Thesis
Country:ChinaCandidate:J R ZhangFull Text:PDF
GTID:2542307061970539Subject:Ordnance Science and Technology
Abstract/Summary:PDF Full Text Request
With the advantages of vertical takeoff and landing,hovering in the air and high mobility,quadrotor unmanned aerial vehicle(QUAV)has played an important role in military and civil fields,such as reconnaissance and strike,electronic countermeasure,environmental monitoring,aerial photography and mapping,and has gradually become the research focus in recent years.However,the QUAV is a typical multi-variable nonlinear system with strong coupling and underactuation.Due to the small size and light weight,the QUAV is extremely sensitive to unknown external disturbance.In addition,the QUAV is complex and time-varying in the practical flight environment,and it is easy to cause component fault,which will seriously threaten its flight safety and mission accomplishment.Therefore,this paper aims to solve the robust anti-disturbance and fault-tolerant control problems of the QUAV which suffers from external disturbance and actuator fault.The main contents are listed as follows:1.The nonlinear mathematical model of QUAV is established.Based on the two related coordinate systems and their transformation relations of the QUAV,the rigid body model,the control efficiency model and the power unit model of the QUAV are established.Moreover,the relevant parameters of QUAV are determined using parameter identification methods.Finally,simulation results reflect the availability of the established model.2.A robust tracking control strategy based on the interval observer is developed for the QUAV.Firstly,the nonlinear mathematical model of QUAV with unknown time-varying disturbance is established.Then,the nonlinear interval observer is devoted to estimate the unknown disturbance.Different from the traditional disturbance observer,the interval observer is able to cover the possible value of the disturbance at each time,especially before the error dynamic convergence.Finally,based on the backstepping control method and Lyapunov theory,an anti-disturbance trajectory tracking controller is designed.The simulation results show that the developed anti-disturbance tracking control strategy improves the anti-disturbance capability of the QUAV.Meanwhile,the tracking error of the closed-loop system is bounded.3.A robust fault-tolerant tracking control strategy based on compensation control is proposed for the QUAV.First,the mathematical model of QUAV with unknown disturbance and actuator failure is established.Second,the nominal controller is designed for the QUAV with only disturbance,and the interval observer is used to estimate the unknown disturbance.Meanwhile,the compensation term is constructed for the actuator fault to reduce its negative impact.Finally,under the framework of backstepping control technology,a robust compensation fault-tolerant controller for QUAV is proposed.Numerical simulation shows that the developed controller suppresses the influence of actuator failure on flight performance and achieve satisfactory tracking effect.4.Flight experiment of the QUAV.Firstly,the hardware components and software architecture of the experimental platform are described in detail.Then,using the idea of model-based design(MBD),the backstepping control method is applied on the flight controller of QUAV.By means of the Matlab and Simulink simulation platform,the simulation program is transformed into embedded code and a trajectory tracking simulation experiment executed in software-in-the-loop is developed,to verifying the feasibility of the MBD development mode.Finally,an anti-disturbance attitude tracking real experiment for QUAV is conducted,and the results show that the designed attitude controller can ensure the stable flight attitude of QUAV.
Keywords/Search Tags:quadrotor unmanned aerial vehicle, backstepping control, interval observer, compensation fault-tolerant control, trajectory tracking, model-based design
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