Unmanned aerial vehicle robust flight control method based on nested saturation technology

Abstract

The invention discloses an unmanned aerial vehicle robust flight control method based on a nested saturation technology, which comprises the following steps: firstly, establishing an inertial coordinate system and a vehicle body coordinate system, and establishing kinematics and dynamics equations of a four-rotor unmanned aerial vehicle based on an Euler-Lagrange equation; and then an unmanned aerial vehicle robust controller based on a nested saturation technology is designed, and the system stability is proved. And finally, introducing a wind disturbance model, and verifying the robust performance of the flight control system through numerical simulation.

Description

Technical Field

[0001] The invention relates to the field of automatic control and provides a method for robust flight control of an unmanned aerial vehicle based on a nested saturation technology. Background Art

[0002] Quadrotors have the advantages of fully autonomous flight control, fixed-point hovering, and vertical take-off and landing, and have been widely used in civil and military fields. In actual flight, the physical constraint of the maximum motor speed defines the upper limit of the system control input. Especially when small quadrotors are maneuvering, the flight attitude or external interference will cause actuator saturation problems to occur frequently. Actuator saturation reduces the performance of the flight control system and may cause system instability. Therefore, it is crucial to consider the design of the control system with actuator saturation. At present, the commonly used control methods include PID, backstepping sliding mode control, etc. However, these methods either do not consider the actuator saturation problem, or limit the attitude angle to a safe range by setting the upper limit of the control input signal, which will reduce the robust performance of the UAV system. The Nested Saturation Control (NSC) designs the maximum control amount of the four throttles based on the actuator saturation parameters, which improves the anti-interference ability of the system while ensuring that the system has good dynamic performance, and has important practical value. Summary of the invention

[0003] The purpose of the present invention is to solve the actuator saturation problem by using nested saturation functions, and to provide a robust flight control method for UAVs based on nested saturation technology. When the UAV is subject to wind disturbance or other internal and external disturbances of the system, the CFO in the RNSC estimates and compensates for the disturbance, thereby enhancing the robustness of the system, improving the dynamic performance of the system, and reducing the steady-state error of the system. In order to achieve the above objectives, the present invention adopts the following technical solutions: S1: Establish the kinematic and dynamic model of the quadrotor UAV based on the Euler-Lagrange equations. S2: Divide the control of the quadrotor UAV into three channels, namely , , , which is controlled by the SC-PD controller Convergence, then design RNSC for and Control is performed and stability is proved. S3: Simulation is performed in the MATLAB / Simulink environment, and a wind disturbance model is introduced to verify the feasibility of the proposed robust control method, and compared with the PD control method and the nested saturation control method. Due to the adoption of the above technical scheme, the beneficial effects of the present invention are as follows: the present invention determines the upper bound of the output signal of the robust nested saturation controller based on the physical constraints of the quadrotor UAV actuator, improves the system dynamic performance, enhances the system anti-interference ability, and ensures the global asymptotic stability of the flight control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0004] Figure 1 It is the UAV system model in the inertial coordinate system and the body coordinate system; Figure 2 Figure 3 is a structural block diagram of the flight control system; Figure 4 is a rectangular trajectory tracking of the UAV under the action of wind disturbance. DETAILED DESCRIPTION

[0005] All features disclosed in this specification, or all steps in the disclosed methods or processes, except for mutually exclusive features and / or steps, can be combined in any way. Any feature disclosed in this specification (including any additional claims, abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features. Figure 1 Inertial coordinate system shown and body coordinate system ,in, and It is the position and attitude angle of the drone in the inertial coordinate system. To the inertial coordinate system The transformation matrix is Considering wind disturbance, the nonlinear dynamic equation of the quadrotor drone is established according to the Euler-Lagrange method: ,in, L = K - P is the Lagrangian operator, K and P are the kinetic energy and potential energy of the system, are the generalized coordinates of the system, and They represent the generalized control force and generalized resistance of the system. The total energy of the system includes the translational kinetic energy , rotational kinetic energy and gravitational potential energy : ,in, m is the mass of the aircraft, J is the inertia matrix, since in the system total energy equation and There are no cross terms, so we have , .in is the Coriolis term, which is considered as the internal disturbance of the system and together with the external disturbance is the total disturbance of the system. J is a non-singular matrix, so it can be controlled by To achieve control of the system. , we can get: , , , , , ,in, is the total thrust. To facilitate controller design, the desired yaw angle is set to 0, and the yaw angle error and position are controlled by the self-coupling-PD (Self-Coupling Proportional Derivative, SC-PD) control law. z The error converges and the control law is: , ,in, is the expected height, is the desired yaw angle, is the speed factor, and is the tracking error, and is the gain estimate. Since and will quickly converge to zero, so the system model is further simplified to , , , .by As an example, a robust controller based on nested saturation is designed. According to the classic nested saturation control law: Rewrite the quadrotor drone system model into a state space equation: , whose reference model is , here is the control input of the system, i.e., the output of the classic nested saturation controller , is the control quantity corresponding to the reference model system, is the system state variable, is the reference system state variable, is the total disturbance inside and outside the system. , the control goal is to make the error between the system and the reference model Converges to zero, that is, the error dynamics: is stable if it exists So that the following If satisfied, then the expected error dynamic response can be obtained. , and can inversely solve RNSC: . yes Substitute the above controller into Available The above formula and The difference can be obtained When: When the error dynamic response is , by configuring the state feedback gain matrix Make the system asymptotically stable. This is the robust nested saturation controller proposed in this invention. The overall structure diagram of the system is as follows: Figure 2 In order to verify the effectiveness of the robust nested saturation control method for the quadrotor UAV in the present invention, a numerical simulation was carried out. The model parameters in the simulation are shown in Table 1. The wind disturbance model is shown in Figure 3, where Figures 3(a), 3(b), and 3(c) represent the linear velocity components of the wind disturbance along the body coordinate axes x, y, and z, respectively, and Figures 3(d), 3(e), and 3(f) represent the angular velocity components of the wind disturbance along the body coordinate axes x, y, and z, respectively. The rectangular trajectory is tracked, the initial state is (0m, 0m, 0m, 0˚, 0˚, 0˚), the simulation time is 120 seconds, and the simulation results are shown in Figure 4, where reference represents the expected response, PD represents the response of both the inner and outer loops under PD control, and SC-PD+NSC represents ( z, ψ ) is controlled by SC-PD, ( x, θ ) and( y, f ) is controlled by NSC, and SC-PD+RNSC expresses ( z, ψ ) is controlled by SC-PD, ( x, θ ) and( y, f ) is controlled by RNSC. In the case of wind disturbance, the UAV rises to 15m and then performs rectangular trajectory tracking. The system performance indicators of the UAV at 20s along the x-axis and 40s along the y-axis are given in Table 2. As shown in Table 2, compared with NSC and PD control, RNSC has smaller overshoot and steady-state error, and shorter adjustment time. In Figure 4, RNSC suppresses the influence of interference on the flight control system, and the maximum attitude angle is 20°, which is still within the range of safe flight. Figure 4 (e) and Figure 4 (f) show the pitch angle under the PD controller. i and roll angle fRapid changes in a short period of time will reduce system stability and even pose a potential danger to the safety of the drone. In Figure 4 (b) and Figure 4 (d), overshoots occurred on the x-axis and z-axis at 20s, 40s, 60s, and 80s, respectively. This is because the robust nested saturation control method proposed in the present invention is attitude decoupled, while the attitude of the quadcopter drone is not decoupled under the control of the classic PD method. The present invention is not limited to the aforementioned specific embodiments. The present invention extends to any new feature or any new combination disclosed in this specification, as well as any new method or process step or any new combination disclosed.

Claims

1. A robust flight control method for an unmanned aerial vehicle based on nested saturation technology, characterized in that: The specific steps of this method are as follows: S1: Establish inertial coordinate system and body coordinate system, and establish kinematic and dynamic equations of quadrotor UAV based on Euler-Lagrange equations. S2: Design a robust controller for UAV based on nested saturation technology, and prove the stability of the system. S3: Introduce wind disturbance model and verify the robust performance of flight control system through numerical simulation.

2. The method for robust flight control of an unmanned aerial vehicle based on nested saturation technology according to claim 1, characterized in that: The specific process of step one is as follows: Establish the inertial coordinate system as shown in Figure 1 and body coordinate system ,in, and It is the position and attitude angle of the drone in the inertial coordinate system. To the inertial coordinate system The transformation matrix is Considering wind disturbance, the nonlinear dynamic equation of the quadrotor drone is established according to the Euler-Lagrange method: ,in, L = K - P is the Lagrangian operator, K and P are the kinetic energy and potential energy of the system, are the generalized coordinates of the system, and They represent the generalized control force and generalized resistance of the system. The total energy of the system includes the translational kinetic energy , rotational kinetic energy and gravitational potential energy : ,in, m is the mass of the aircraft, J is the inertia matrix, since in the system total energy equation and There are no cross terms, so we have , 3. The method for robust flight control of an unmanned aerial vehicle based on nested saturation technology according to claim 1, characterized in that: The specific process of step 2 is as follows: is the Coriolis term, which is considered as the internal disturbance of the system and together with the external disturbance is the total disturbance of the system. J is a non-singular matrix, so it can be controlled by To achieve control of the system. , we can get: , , , , , ,in, is the total thrust. To facilitate controller design, the desired yaw angle is set to 0, and the yaw angle error and position are controlled by the self-coupling-PD (Self-Coupling Proportional Derivative, SC-PD) control law. z The error converges and the control law is: , ,in, is the expected height, is the desired yaw angle, is the speed factor, and is the tracking error, and is the gain estimate. Since and will quickly converge to zero, so the system model is further simplified to , , , .by As an example, a robust controller based on nested saturation is designed. According to the classic nested saturation control law: Rewrite the quadrotor drone system model into a state space equation: , whose reference model is , here is the control input of the system, i.e., the output of the classic nested saturation controller , is the control quantity corresponding to the reference model system, is the system state variable, is the reference system state variable, is the total disturbance inside and outside the system. The robust nested saturation control law (RNSC) is designed as: in is the observed value of the total disturbance by the compensation function observer (CFO). The overall structure diagram of the system is shown in Figure 2.

4. The method for robust flight control of an unmanned aerial vehicle based on nested saturation technology according to claim 1, characterized in that: The robust performance of the quadrotor drone system under wind disturbance is tested in the MATLAB / Simulink environment. The specific steps are as follows: S1: Set the parameters, initial state and expected state of the UAV system, establish a wind model and apply wind disturbance to the UAV during flight. S2: Take the deviation between the system output and the expected value as the controller input, where SC-PD is ( z, ψ ) To control, RNSC x, θ ) and( y, Φ) Control the drone to achieve the desired value. S3: Adjust the amplitude parameters of the nested saturation functions of each layer of RNSC , SC-PD controller parameters and CFO parameters, and compare and analyze the PD control method and the nested saturation control method.

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