Flight control structure of electric tilting six-rotor unmanned aerial vehicle in helicopter mode

Abstract

The electric tilting rotorcraft has three flight modes including a helicopter mode, a tilting transition mode and a propeller aircraft mode, and flight of the three modes is achieved through a flight control system. The invention discloses a special flight control system structure of an electric tilting six-rotor unmanned aerial vehicle in a helicopter mode, and solves the problems of insufficient robustness, low attitude control precision, response lag and the like of traditional PID control (proportional-integral-derivative control) under ground effect interference. The structure adopts an instruction input-double loop control-control distribution-feedback correction closed loop architecture, an outer loop dynamically optimizes parameters through a fuzzy-PID controller, an inner loop ensures rate response through traditional PID control, and control distribution is realized based on an electric tilt rotor configuration. The flight control system structure is suitable for vertical take-off and landing, hovering, low-speed flight, attitude control and the like of the electric tilting six-rotor unmanned aerial vehicle in a helicopter mode.

Description

Technical Field

[0001] This invention relates to the field of aircraft flight control technology, specifically to a flight control system structure for an electric tilt-hexcopter UAV in helicopter mode, applicable to helicopter mode flight of an electric tilt-hexcopter UAV, including vertical take-off and landing, hovering, and low-speed flight. Background Technology

[0002] In helicopter mode, the flight control of an electric tiltrotor aircraft relies on rotor thrust to provide lift and control attitude, offering significant advantages such as vertical takeoff and landing (VTOL) without the need for a runway, and the ability to adapt to complex takeoff and landing environments. However, flight control in helicopter mode faces numerous technical challenges, such as the susceptibility of aerodynamic characteristics to ground effect, which can affect the accuracy of flight dynamics; and the difficulty of dynamically adapting to complex operating conditions due to fixed parameters in traditional PID controllers. Therefore, there is an urgent need to design a dedicated flight control system architecture to improve the control accuracy and flight stability of the electric tiltrotor aircraft's flight control system in helicopter mode. Summary of the Invention

[0003] Technical problems to be solved This invention discloses a flight control system structure for an electric tilt-rotor hexacoach UAV in helicopter mode, aiming to solve technical problems such as poor robustness of traditional PID controllers, insufficient thrust control accuracy, disordered rotor thrust distribution logic, and weak wind resistance.

[0004] Technical solution To achieve the above objectives, this invention constructs a closed-loop flight control system structure of "command input - fuzzy PID dual-loop control - control allocation - feedback correction", the specific framework of which is as follows: Figure 3 As shown, the included modules are as follows: 1. Command Input Module: Used to receive vertical takeoff and landing, hovering, roll, pitch, and yaw commands from the remote controller or autonomous flight control system. It can quickly generate high-precision control targets, specifically as follows: Desired Altitude Resolution reaches 0.001m, expected roll angle With a resolution of 0.1°, the desired pitch angle is... With a resolution of 0.1°, the desired yaw rate is... The resolution is This module updates at a frequency of up to 400Hz, with response latency controlled within... It can ensure zero command loss and zero mis-sending, effectively guaranteeing the reliability and timeliness of signal transmission.

[0005] 2. Dual-loop control module (internal and external): Based on the six-degree-of-freedom rigid body flight dynamics model of the UAV, a hierarchical control strategy is adopted to achieve precise control, such as... Figure 4 As shown, the external circuit is for height Roll angle Pitch angle Applying a fuzzy PID controller to control the error (like and error change rate Normalization to Domain of discourse, dynamically adjusts PID parameters; inner loop targets high rate of change. Roll rate Pitch rate yaw rate It adopts traditional PID control; the final output is a standardized control quantity, tension control quantity. Roll, pitch, and yaw control variables This enables precise adjustment of the drone's attitude and motion.

[0006] 3. Control Distribution Module: A unique design for the six-rotor configuration. This module constructs a thrust distribution matrix based on rotor geometry parameters and anti-torque coefficient through precise flight dynamics modeling. Using this matrix, control quantities can be linearly mapped to target commands for the six rotors, achieving precise thrust distribution control.

[0007] 4. Feedback Unit: Composed of an inertial measurement unit (IMU), it acquires angular velocity at a frequency of 400Hz (accuracy). ) and vertical acceleration (accuracy) Data; Kalman filtering algorithm is used to fuse data, and real-time altitude is estimated by fusing vertical acceleration quadratic integral and barometer altitude. (Filtering delay) ); and also supports passing through Reverse push actual total pulling force When there is a deviation from the target total tension, it will automatically correct. The control parameters enable real-time monitoring and precise feedback adjustment of flight status.

[0008] To achieve the above objectives, fuzzy PID control is used. Based on fuzzy PID control theory, the three proportional, integral, and derivative control parameters in PID control are considered. To determine the correlation, Mamdani's fuzzy inference method was adopted, and the control system input was selected as the error. e and the rate of change of error ec The control system output consists of proportional, integral, and derivative correction coefficients. The linguistic variables for both input and output in their respective domains are negative large (NB), negative medium (NM), negative small (NS), zero (ZO), positive small (PS), positive medium (PM), and positive large (PB); that is, the error is defined. e Error change rate ec With correction factor The fuzzy subsets are all .

[0009] The fuzzy control rule is applied to the Mamdani fuzzy inference function module to obtain a fuzzy controller for parameter optimization of the PID controller. Simultaneously, the output term under this fuzzy control rule is determined. With input items e and ec The nonlinear correspondence. The output terms of the fuzzy controller... The correction coefficients are input as corresponding elements to the PID controller to obtain a complete fuzzy PID controller, where the correction coefficients are... It optimizes the coefficients of the PID controller in real time through fuzzy logic operations and fuzzy rules to achieve the ideal control effect, enabling the control system to adapt to parameter changes and resist external disturbances.

[0010] Through the above design, the flight control system can achieve high-precision control, fast response and engineering practicality, and is suitable for vertical take-off and landing, hovering, low-speed flight and attitude control of electric tilt-rotor UAVs in helicopter mode.

[0011] Beneficial effects The beneficial effects of this invention are mainly reflected in the following aspects: 1. Improved system robustness and dynamic adaptability: The system adopts a dual-loop control architecture of "outer loop fuzzy PID + inner loop traditional PID". Compared with the traditional PID controller with fixed parameters, the fuzzy PID can dynamically adjust the proportional, integral, and derivative parameters in real time according to the error and the rate of change of the error. This design effectively solves the problem of poor robustness of traditional PID in the face of ground effect interference and complex operating conditions, and significantly enhances the anti-interference capability and flight stability of the UAV in helicopter mode.

[0012] 2. Significantly Improved Attitude Control Response Speed ​​and Accuracy. Simulation results show that the system significantly reduces the system settling time while ensuring system stability. For example, in roll channel control, the settling time using fuzzy PID control is shorter than that of traditional PID. This design balances flight stability and agility, resolving the contradiction in traditional control where "shortening the settling time leads to overshoot."

[0013] 3. Achieved precise rotor thrust distribution and execution: by constructing a specialized thrust distribution matrix. The system can linearly map total thrust, roll, pitch, and yaw commands to specific target commands for the six rotors and accurately convert them into motor signals. This allocation logic based on precise dynamic modeling solves the problem of thrust allocation logic disorder that may occur in a six-rotor configuration, ensuring the precise execution of vertical takeoff and landing, hovering, and attitude adjustments in each axis (such as differential thrust to achieve roll / pitch). Attached Figure Description

[0014] Figure 1 A top view and rotor steering diagram of an electric tilt-rotor hexacopter in helicopter mode. Figure 2 Block diagram of the flight control system of an electric tilt-rotor hexacopter UAV in helicopter mode. Figure 3 Block diagram of the inner and outer loop control structure of the flight control system of an electric tiltrotor hexacopter in helicopter mode. Figure 4 Simulated altitude curve of an electric tilt-rotor hexacopter UAV Figure 5 Simulated altitude change rate curve of an electric tilt-rotor hexacoach UAV Figure 6 Simulated roll angle curve of an electric tilt-rotor hexacoach UAV Figure 7 Simulated roll rate curves of an electric tilt-rotor hexacoach UAV Figure 8 Simulated pitch angle curves of an electric tilt-rotor hexacoach UAV Figure 9 Simulated pitch rate curves of an electric tilt-rotor hexacoach UAV Detailed Implementation Step 1: According to... Figure 2 and Figure 3 The diagram illustrates the flight control system structure of an electrically powered tilt-rotor hexacopter UAV in helicopter mode, establishing the corresponding control framework. The included modules are as follows: 1. Command Input Module: Used to receive vertical takeoff and landing, hovering, roll, pitch, and yaw commands from the remote controller or autonomous flight system. It can quickly generate high-precision control targets, specifically as follows: Desired Altitude Resolution reaches 0.001m, expected roll angle With a resolution of 0.1°, the desired pitch angle is... With a resolution of 0.1°, the desired yaw rate is... The resolution is This module updates at a frequency of up to 400Hz, with response latency controlled within... It can ensure zero command loss and zero mis-sending, effectively guaranteeing the reliability and timeliness of signal transmission.

[0015] 2. Dual-loop control module: Based on a six-degree-of-freedom rigid body dynamics model, a hierarchical control strategy is adopted to achieve precise control, such as... Figure 3 As shown, the external circuit is for height Roll angle Pitch angle Applying a fuzzy PID controller to control the error (like and error change rate Normalization to Domain of discourse, dynamically adjusts PID parameters; inner loop targets high rate of change. Roll rate Pitch rate yaw rate It adopts traditional PID control; the final output is a standardized control quantity, tension control quantity. Roll, pitch, and yaw control variables This enables precise adjustment of the aircraft's attitude and motion.

[0016] 3. Control Distribution Module: A unique design for the six-rotor configuration. This module constructs a thrust distribution matrix based on rotor geometry parameters and anti-torque coefficient through precise dynamic modeling. Using this matrix, control quantities can be linearly mapped to target commands for the six rotors, achieving precise thrust distribution control.

[0017] 4. Feedback Unit: Composed of an inertial measurement unit (IMU), it acquires angular velocity at a frequency of 400Hz (accuracy). ) and vertical acceleration (accuracy) Data; Kalman filtering algorithm is used to fuse data, and real-time altitude is estimated by fusing vertical acceleration quadratic integral and barometer altitude. (Filtering delay) ); and also supports passing through Reverse push actual total pulling force When there is a deviation from the target total tension, it will automatically correct. The control parameters enable real-time monitoring and precise feedback adjustment of flight status.

[0018] Step 2: Establish the control allocation matrix. The specific steps are as follows: From a flight control perspective, an electric tiltrotor UAV in helicopter flight mode can be approximated as a multi-rotor aircraft, since all its manipulations are achieved by changing the rotor speed. Therefore, the goal of this step is to calculate the required rotor speeds for the desired attitude. Control assignment was first proposed in flight control system design. Its basic idea is to distribute control commands to the actuators according to certain optimization objectives, while satisfying the constraints of the actuators. Essentially, solving the control assignment matrix is ​​also solving the constraint equations of the dynamic system on the controller.

[0019] The resultant force and resultant torque of the electric tiltrotor UAV are calculated using parameters such as rotor speed. The flight control system design reverses this process, using a control allocation matrix to convert the control outputs of the four channels of the helicopter flight mode (including roll, pitch, yaw, and throttle channels)—that is, the desired lift and torque obtained through the control law—into the rotational speeds of each rotor, thus ensuring the aircraft can achieve the expected flight attitude. Since multi-rotor aircraft have multiple power actuators, various power combinations can be generated based on different geometric distribution structures. Therefore, different control allocation matrices need to be solved for different structural layouts to determine the most reasonable control output combination. Based on the configuration of this electric tiltrotor UAV, the control allocation matrix is ​​calculated. M for (2) The calculation process from the control output of the four channels in helicopter mode to the control commands of each rotor is as follows: (3) In the formula, For the first Control commands for each rotor ; The four elements are the control outputs for the throttle, roll, pitch, and yaw channels.

[0020] In helicopter flight mode, altitude control has a dual-loop structure, with the inner loop being the climb rate control loop, which uses PID control; and the outer loop being the altitude control loop, which uses fuzzy PID control.

[0021] The flight control system of an electric tiltrotor UAV is simulated using vertical climb and hovering at a constant altitude without attitude change in helicopter flight mode as the verification targets. The initial altitude of the system is given. 1m, initial climb rate The initial attitude angle is 0 m / s. All Initial attitude angular rate Both are 0 rad / s. The expected input of the system. for To compare the control effects, fuzzy PID control and PID control were used in the height control loop respectively. After simulation and debugging, the controller parameters and simulation results of the height control system were obtained as follows: Figure 4 and Figure 5 As shown. According to... Figure 4 and Figure 5 The simulation results shown calculate the corresponding control system performance indicators. A PID controller is used in all inner loops. In the case of error band, the system settling time of the external loop using a PID controller For, overshoot steady-state error The system settling time using a fuzzy PID controller For, overshoot steady-state error The comparison between the simulation curves and system performance parameters shows that, under the condition of ensuring system convergence and error-free operation, the initial response of the system before 5 seconds is similar regardless of whether fuzzy PID control or traditional PID control is used. However, the dynamic performance after 5 seconds is significantly better with fuzzy PID control, and both the system settling time and convergence time are significantly improved. At the same time, since the altitude control loop uses a fuzzy PID controller, the simulated response of the climb rate of its inner loop is also significantly improved. This proves that for the altitude control of the controlled object in helicopter mode, fuzzy PID can achieve better control results.

[0022] Attitude control includes three-axis attitude control: roll, pitch, and yaw. Only the yaw rate is controlled in the yaw direction, using a traditional PID method, so it will not be elaborated further. When designing the attitude angle and attitude rate control loops, the pitch and roll channels employ a dual-loop control structure, with the outer loop being the attitude angle control loop and the inner loop being the attitude rate control loop. The yaw channel typically only needs to control the yaw rate, thus achieving the attitude control objective while simplifying the control system and meeting practical application requirements.

[0023] The flight control system of an electric tiltrotor UAV in helicopter flight mode (roll, pitch, and yaw) was simulated for verification purposes. The roll and pitch channels used PID controllers in their inner loops, and PID and fuzzy PID controllers in their outer loops, respectively. The yaw channel used a single-loop control system with PID control. When calculating the performance indicators of the control system based on the simulation results of the three attitude channels, [the simulation parameters were selected]. Error band. Given the initial height of the system. 1m, initial climb rate The initial attitude angle is 0 m / s. All Initial attitude angular rate All are 0 rad / s.

[0024] (1) Roll control simulation To verify the roll motion control loop, a flight altitude command signal was input at the start of the simulation to simulate the aircraft changing its flight attitude in the air. This was done to prevent the flight altitude from dropping to 0 due to changes in the roll angle, which could affect the accuracy of the roll angle verification simulation. Right roll was defined as positive and left roll as negative. Roll angle command signals of 0.1745, 0.1745, and 0 were input at 10s, 17s, and 24s respectively, simulating the UAV completing continuous roll motions with roll angles of 10°, -10°, and 0° in the air. The response of the roll channel was observed. The simulation results of the roll motion control system are as follows: Figure 6 and Figure 7 As shown.

[0025] (2) Pitch control simulation The verification of the pitch motion control loop is similar to that of roll. The aircraft's nose-down (pitch) is defined as negative, and nose-up (pitch) as positive. At the start of the simulation, a 5m altitude command signal is given, and pitch angle command signals of 0.0873, -0.0873, and 0 are given at 10s, 17s, and 24s respectively. The simulation is performed to simulate the aircraft completing continuous pitch movements of 5°, -5°, and 0° in the air, and the response of the pitch channel is observed. The simulation results of the pitch motion control system are as follows: Figure 8 and Figure 9 As shown (3) Analysis of attitude control simulation results For the rolling channel, simulation curves of 10s to 17s were selected to calculate the system performance index. The performance index using fuzzy PID control was: , , The performance index of PID control is , , .

[0026] For the pitch channel, simulation curves ranging from 10s to 17s were selected to calculate the system performance indicators. The performance indicators using fuzzy PID control were as follows: , , The performance index of PID control is , , .

[0027] from Figures 6-9A comparison of simulation curves and system performance indicators shows that although both PID control and fuzzy PID control can ensure that the system's overshoot and steady-state error are zero, the system using fuzzy PID control has a significantly shorter settling time, reducing the settling time compared to PID control. .

[0028] In the process of adjusting a traditional PID controller, there are problems such as overshoot when shortening the settling time, and steady-state error or longer settling time when eliminating the overshoot. These three performance indicators cannot be simultaneously achieved. In actual adjustment, for the sake of flight stability, priority is given to ensuring steady-state error and overshoot, sacrificing some settling time performance. Fuzzy PID control, however, can ensure that all three performance indicators are within a relatively ideal range. Furthermore, for attitude control, both accuracy (i.e., steady-state error and overshoot) and the time to reach the desired attitude (i.e., settling time) are required, which has stringent requirements. Therefore, it can be concluded that using fuzzy PID to design the controller for the roll and pitch channels of the helicopter mode can achieve better control results.

Claims

1. A flight control structure for an electrically tilting hexacopter unmanned aerial vehicle (UAV) in helicopter mode, characterized in that, It includes an instruction input module, an internal and external dual-loop control module, a control distribution module, and a feedback unit. Each module is connected in sequence to form a closed-loop control. The command input module receives commands for vertical takeoff and landing, hovering, roll, pitch, and yaw, and outputs the desired altitude. Expected roll angle Desired pitch angle Desired yaw rate ; The dual-loop control module adopts an architecture of "external loop attitude / position control + internal loop rate control": the external loop is for altitude control. Roll angle Pitch angle A fuzzy PID controller is used, with the inner loop targeting the height change rate. Roll rate Pitch rate yaw rate It uses a traditional PID controller to output standardized control quantities. , ; The control distribution module is designed based on the configuration of an electrically tilting six-rotor rotor, and constructs a thrust distribution matrix. M Total pulling command , roll command Pitch commands and yaw command The solution is converted into target control commands corresponding to the six rotors. ; Subsequently, based on the conversion relationship between motor control commands and PWM control signals, the PWM control signal values ​​corresponding to each motor are accurately calculated; The feedback unit consists of an inertial measurement unit that collects attitude rate and vertical acceleration data in real time, calculates altitude using the UAV flight dynamics model, and feeds it back to the dual-loop control module.

2. The electrically operated tilting hexacopter UAV according to claim 1, characterized in that, The configuration and rotor steering of the UAV are shown in Figure 1. The control logic for it is as follows: vertical motion is achieved by synchronous changes in the thrust of the six rotors; roll is achieved by differential thrust of rotors 1, 3, 5 and 2, 4, 6; pitch is achieved by differential thrust of rotors 5, 6 and 1-4; and yaw is achieved by the anti-torque difference (positively correlated with thrust) of rotors 1, 4, 5 and 2, 3, 6.

3. The flight control system structure of the electric tilt-rotor hexacopter UAV in helicopter mode according to claim 1, characterized in that, The input universe of discourse of the fuzzy-PID controller is The output universe of discourse is [-4, 4], and the input linguistic variable is the error. e (Command value - Feedback value) and error rate of change ec The output language variable is , , ;Fuzzy subsets are all ,error e use Gaussian membership function, rate of change of error ec Trigonometric membership functions are used.

4. The flight control system structure of the electric tilt-rotor hexacopter UAV in helicopter mode according to claim 1, characterized in that, The tension distribution matrix satisfy: \ MERGEFORMAT (1) In the formula, This is the control command for the rotor, and the control value range is [0,1].

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