Multivariable System Identification And Robust Control Of Multi-rotor UAV

In recent years,multi-rotor UAVs have been applied in various fields,such as film and televi-sion images,agricultural plant protection,power inspection,disaster relief,and logistics delivery.Multi-rotor drones are underactuated natural unstable systems.How to obtain high-quality control performance is a difficult problem for drone applications.Model-based advanced controls such as robust control have been widely used in the industry.Based on the model,the control quality can be improved,the adjustment of the controller design can be reduced,and the development cycle can be shortened.Asymptotic identification(asymptotic system identification)is a set of advanced mul-tivariate identification methods.From the theoretical level,the method and guidance of excitation signal design,parameter estimation,order selection and model verification are given.Based on the dynamic model of the multi-rotor UAV and the structure of the PID controller,the multi-variable identification of the multi-rotor UAV attitude loop model and H? control are completed.The main research results are:1)Using the multivariate asymptotic identification framework,an identification method for multi-rotor UAV attitude control model is designed.Since drones are naturally unstable systems,system identification tests must be performed under closed-loop conditions.The excitation signal is introduced in the hovering state,the power distribution value of each operating axis is used as the identification input,the attitude angular velocity is used as the identification output,the higher-order model is identified,and the low-order control model is obtained by reducing the frequency domain.2)The design of the excitation signal is crucial to the effectiveness of closed-loop identifica-tion.In this paper,a multi-rotor UAV PID controller structure is designed and a multi-rotor UAV closed-loop identification excitation signal method is designed.At the input of the attitude loop,ie,the attitude angular velocity reference value,a Generalized Binary Noise(GBN)signal is superim-posed,and multiple attempts are made to determine the amplitude and frequency of the excitation signal so that the excitation signal maximally stimulates the response of the system.It is the re-sponse of the low frequency band,and at the same time guarantees the closed loop stability during the test.At the same time,the GBN signal is superimposed on the input of the system power system to further improve the experimental results.3)Using robust control as a theoretical framework,a multivariable H? robust controller for multi-rotor UAVs is designed:In accordance with the control target of the system constant value tracking,the expected closed-loop response matrix is introduced and output.The weighted filter constructs the generalized object of the system,and solves the robust control problem of the object based on the linear matrix inequality(LMI)method,and obtains the controller with the minimum norm of the closed loop system H?.Compared with PID controller flight test,the superiority of this method is verified and it can meet the complex control requirements of multi-rotor UAV.