CN-122018543-A - Flight control method special for hydrogen energy unmanned aerial vehicle

CN122018543ACN 122018543 ACN122018543 ACN 122018543ACN-122018543-A

Abstract

The invention relates to the technical field of path control, and discloses a flight control method special for a hydrogen energy unmanned aerial vehicle, which comprises the following steps: and carrying out dimensionless time alignment on the multi-source sensing state, and extracting the exposure memory quantity of the reverse gravity drainage reflecting the history accumulation of the poor posture. And predicting the energy supply weakness degree of a future path section by utilizing the reverse gravity drainage exposure memory feed-forward, distributing the power specific gravity of the battery and the super capacitor in advance according to the energy supply weakness degree, and regulating and controlling the hydrogen discharge frequency. In addition, the memory and energy gap are incorporated into the path optimizing cost to reshape the safe flight path and travel speed. The invention eliminates time dislocation between transient obstacle avoidance and bottom energy response, and remarkably improves the robustness of long-endurance operation of the equipment under complex working conditions.

Inventors

LU BIN
HU YUFEN

Assignees

江苏飞睿得科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260416

Claims (8)

1. The utility model provides a dedicated flight control method of hydrogen energy unmanned aerial vehicle, is applied to the hydrogen energy unmanned aerial vehicle that contains proton exchange membrane fuel cell, super capacitor, oxygen suppliment subassembly, hydrogen supply subassembly, hydrogen discharging subassembly, sensor unit and many rotor subassemblies, its characterized in that includes: acquiring and synchronizing the sensing state quantity of the sensor unit, carrying out dimensionless processing according to the feasible value range of the rolling window to obtain a dimensionless state vector, and feedforward calculating a path power demand index; Extracting an inverse gravity drainage exposure memory reflecting the accumulation of unfavorable drainage based on the body system posture of the hydrogen energy unmanned aerial vehicle and the favorable drainage direction of the proton exchange membrane fuel cell; Predicting the power vulnerability of a future path section by utilizing the exposure memory capacity of the reverse gravity drainage and the oxygen supply sufficiency in the perception state quantity, and further outputting a future energy supply gap index; generating super capacitor target output and fuel cell target output according to the future energy supply gap index and the reverse gravity drainage exposure memory, and generating a hydrogen supply adjusting instruction and a continuous hydrogen discharge duty cycle in a synchronous and self-adaptive manner; Taking the exposure memory capacity of the inverse gravity drainage and the future energy supply gap index into path evaluation cost, and optimizing in a candidate path set to generate a reconstructed local path and along-path speed distribution; updating a gravity center position vector according to mass migration caused by fluid material consumption, and generating a feedforward compensation moment based on the gravity center position vector to correct a rotor wing target instruction; And evaluating the comprehensive risk of the system, generating an emergency take-over coefficient, and smoothly fusing the reconstructed local path and the emergency landing path by using the emergency take-over coefficient to generate a final command path.
2. The method for controlling the flight of the unmanned aerial vehicle with hydrogen energy according to claim 1, wherein the steps of obtaining and synchronizing the sensing state quantity of the sensor unit, performing dimensionless processing according to the feasible value range of the rolling window to obtain a dimensionless state vector, and performing feedforward calculation on the path power demand index comprise the following steps: Dividing the current perceived distance by the product of the current flying speed and the control period plus the sum of numerical stability items, and rounding up to determine the number of preview discrete steps to generate the rolling window; aligning the asynchronously acquired sensing state quantity to the current control moment by using a time interpolation method in combination with the numerical value stability term; carrying out normalization processing on the aligned perception state quantity according to the feasible value domain of the rolling window to form a dimensionless state vector, wherein the dimensionless state vector comprises a normalization speed, a normalization tangential acceleration, a normalization vertical acceleration, a normalization track tracking error, a normalization path curvature, a normalization rolling angle, a normalization pitch angle, a normalization hydrogen pressure, a normalization pressure risk, a normalization galvanic pile average temperature, a normalization temperature dispersion, a normalization temperature risk, a normalization galvanic pile current, a normalization oxygen supply sufficiency, a normalization super capacitor available charge state, a normalization local hydrogen concentration risk, a normalization barrier distance and a normalization gravity center position vector; And adding the product of the normalized speed and the normalized tangential acceleration, the product of the square of the normalized speed and the normalized path curvature, the normalized vertical acceleration and the normalized track tracking error to obtain a demand molecule, adding one sum of the demand molecules as a demand denominator, and dividing the demand molecule by the demand denominator to obtain the path power demand index.
3. The method for controlling the flight dedicated to the hydrogen unmanned aerial vehicle according to claim 2, wherein the step of extracting the reverse gravity drainage exposure memory reflecting the accumulation of the unfavorable drainage based on the body system posture of the hydrogen unmanned aerial vehicle and the favorable drainage direction of the proton exchange membrane fuel cell, comprises: subtracting the continuous product of the gravity direction unit vector, the direction cosine matrix from the machine system to the pile runner coordinate system and the unit vector of the favorable drainage direction, and dividing the obtained difference value by two to obtain normalized inverse gravity drainage exposure; the negative control period is used as an independent variable of a natural exponential function to obtain an exponent value, and a memory attenuation coefficient is obtained; dividing the normalization time of last hydrogen discharge by the sum of the normalization recovery time and the numerical stability term to obtain a normalization hydrogen discharge process; Multiplying the memory capacity of the reverse gravity drainage exposure of the previous period by the memory attenuation coefficient to obtain a first product term, multiplying a difference value subtracted by the memory attenuation coefficient, the normalized reverse gravity drainage exposure, the normalized stack current, the normalized hydrogen drainage process and a difference value subtracted by the normalized oxygen supply sufficiency to obtain a second product term, and adding the first product term and the second product term to obtain the memory capacity of the reverse gravity drainage exposure of the current period.
4. The method for controlling the flight dedicated to a hydrogen unmanned aerial vehicle according to claim 3, wherein predicting the power vulnerability of the future path segment by using the oxygen supply sufficiency in the reverse gravity drainage exposure memory and the perceived state quantity, and further outputting a future energy supply gap index, comprises: Carrying out sensitivity weight correction on the temperature of each sensing point by using the local flow velocity estimation value, and obtaining the normalized temperature dispersion by taking the difference between the corrected maximum value and the corrected minimum value; Continuously multiplying a difference value of subtracting the exposure memory of the inverse gravity drainage, a difference value of subtracting the normalized temperature dispersion, the normalized hydrogen pressure and the normalized oxygen supply sufficiency, and dividing the product result by a square, and subtracting the division result to obtain normalized path section power vulnerability as the power vulnerability; multiplying the difference value of subtracting the power vulnerability of the normalized path segment by the current normalized fuel cell output to obtain the available power of the fuel cell in the prediction time domain; And dividing the predicted load demand by the accumulated sum of the available power of the fuel cell, the supportable power of the super capacitor and the numerical stability term to obtain the future energy supply gap index.
5. The method for controlling the flight of the unmanned aerial vehicle for hydrogen energy according to claim 4, wherein the generating of the super capacitor target output and the fuel cell target output according to the future energy supply gap index and the reverse gravity drainage exposure memory, and the synchronous self-adaptive generating of the hydrogen supply adjusting instruction and the continuous hydrogen discharge duty cycle process comprise: multiplying the future energy supply gap index with the usable state of charge of the normalized super capacitor to obtain a first product, dividing the first product by the sum of the first product, a difference value subtracting the power vulnerability of the normalized path segment and the numerical stability term to obtain a super capacitor support proportion; Multiplying the super capacitor support proportion by the path power demand index at the current control moment to obtain normalized super capacitor target output serving as the super capacitor target output; multiplying a difference value obtained by subtracting the support proportion of the super capacitor by the path power requirement index at the current control moment to obtain a normalized fuel cell target output serving as the fuel cell target output; Multiplying the normalized fuel cell target output by the sum of one and the reverse gravity drainage exposure memory, and dividing the sum of one, the normalized pressure risk and the normalized temperature risk to obtain a normalized hydrogen supply adjustment instruction as the hydrogen supply adjustment instruction; Multiplying the reverse gravity drainage exposure memory quantity by the normalized pile current to obtain a third product, dividing the third product by the sum of the third product, a difference value obtained by subtracting the usable state of charge of the normalized super capacitor and the numerical stability term, and obtaining a normalized hydrogen discharge duty cycle process as the continuous hydrogen discharge duty cycle process.
6. The method of claim 5, wherein incorporating the reverse gravity drainage exposure memory and the future energy gap index into a path evaluation cost, optimizing in a candidate path set to generate a reconstructed local path and a path velocity profile, comprising: Obtaining a single-point normalized local hydrogen concentration risk, a single-point normalized temperature risk and a single-point normalized pressure risk corresponding to a single point on the candidate path, continuously multiplying a difference value subtracting the single-point normalized local hydrogen concentration risk, a difference value subtracting the single-point normalized temperature risk and a difference value subtracting the single-point normalized pressure risk, and obtaining a single-point system safety risk by subtracting the product result; Continuously multiplying a difference value for subtracting the single-point normalized obstacle approximation degree, a difference value for subtracting the corresponding inverse gravity drainage exposure memory amount, a difference value for subtracting the corresponding future energy supply gap index and a difference value for subtracting the single-point system safety risk by each candidate path, and obtaining a single-point cost of the candidate path by subtracting the square result after opening the square; selecting a candidate path with the minimum single-point cost integral of the candidate path along the normalized arc length infinitesimal from the candidate path set as the reconstruction local path; Obtaining an along-path reference speed, along-path inverse gravity drainage exposure memory quantity, along-path obstacle approximation degree and along-path future energy supply gap index distributed on the reconstruction local path, multiplying the along-path reference speed by a difference value for subtracting the along-path inverse gravity drainage exposure memory quantity and a difference value for subtracting the along-path obstacle approximation degree, and dividing by a sum value of the along-path future energy supply gap index to obtain the along-path speed distribution updated on the reconstruction local path.
7. The method of claim 6, wherein updating the gravity center position vector based on mass transfer due to fluid material consumption, generating a feedforward compensation torque based on the gravity center position vector to correct the rotor target command, comprises: The method comprises the steps of obtaining a normalized hydrogen storage mass based on initial state relative normalization, obtaining a resident liquid water equivalent mass, a normalized super-capacitor mass, a normalized load mass and a normalized machine body reference mass through recursion according to a water production intensity and the continuous hydrogen discharge duty cycle, multiplying and summing the obtained normalized hydrogen storage mass, the resident liquid water equivalent mass, the normalized super-capacitor mass, the normalized load mass, the normalized machine body reference mass and the numerical value stability item with corresponding normalized local gravity center position vectors to obtain a mass moment sum, adding the normalized hydrogen storage mass, the resident liquid water equivalent mass, the normalized super-capacitor mass, the normalized load mass, the normalized machine body reference mass and the numerical value stability item to obtain a total system mass, dividing the mass moment sum by the total system mass, and obtaining an updated gravity center position vector; Performing cross multiplication on the gravity center position vector and a resultant force vector required by normalized track tracking to obtain the feedforward compensation moment; and updating a normalized control distribution matrix according to the current reachable thrust of each rotor, adding the feedforward compensation moment and the normalized track tracking feedback moment, combining with the normalized target thrust, and multiplying the pseudo inverse matrix of the normalized control distribution matrix to obtain a normalized rotor target instruction as the rotor target instruction.
8. The method for controlling the flight dedicated to a hydrogen unmanned aerial vehicle according to claim 7, wherein evaluating the system overall risk and generating an emergency take-over coefficient, and smoothly fusing the reconstructed local path and the emergency landing path using the emergency take-over coefficient to generate a final command path, comprises: Multiplying a difference value of subtracting the corresponding normalized flatness risk, a difference value of subtracting the corresponding normalized headroom risk and a difference value of subtracting the corresponding normalized wind direction risk aiming at the candidate landing zone, and subtracting the product to obtain landing impracticability; Continuously multiplying a difference value for subtracting the normalized local hydrogen concentration risk, a difference value for subtracting the normalized temperature risk, a difference value for subtracting the normalized pressure risk, a difference value for subtracting the future energy supply gap index, a difference value for subtracting the current normalized obstacle approximation degree and a difference value for subtracting the landing impossibility, performing a cubic root operation on the continuous multiplication result, and obtaining the system comprehensive risk by subtracting the operation result; dividing the comprehensive risk of the system by the accumulated sum of the comprehensive risk, normalized residual executable energy and the numerical stability term to obtain the emergency take-over coefficient; selecting the optimal emergency landing path under an evaluation system containing the terrain cost; And multiplying a difference value obtained by subtracting the emergency takeover coefficient by the reconstruction local path and adding the product of the emergency takeover coefficient and the emergency landing path to obtain the final command path which is continuously fused.

Description

Flight control method special for hydrogen energy unmanned aerial vehicle Technical Field The invention relates to the technical field of path control, in particular to a flight control method special for a hydrogen energy unmanned aerial vehicle. Background The hydrogen energy unmanned aerial vehicle carrying the proton exchange membrane fuel cell and the super capacitor has remarkable advantages in the field of long-duration monitoring. However, existing flight control and energy management are typically independent of each other. The flight control mainly generates a thrust command according to the real-time space pose deviation, and the battery management passively follows the instantaneous power load to supply power. In the tasks of continuous posture change such as large-angle climbing, continuous spiral, obstacle detouring and the like, the directional flow channel in the battery can be in the direction which is unfavorable for the drainage of accumulated water for a long time. Meanwhile, because of inherent response retardation of the system exhaust and oxygen supply compressors, gas-liquid drainage blockage caused by the space attitude can be accumulated in the pile. Even if the unmanned plane recovers the flat flying posture, the internal oxygen starvation, local liquid water blocking and other bad state retention cannot be eliminated immediately. Existing conventional algorithms do not focus on adverse drainage effects accumulated by the pose history. When the system encounters sudden high loads or strong gusts at a stage where such implicit ponding does not completely subside, a sudden drop phenomenon occurs in which the actual available energy cannot match the external space flight control requirements. The serious disjoint of the space maneuvering and the internal energy response can lead to course runaway, so that the safety risk avoiding capability in the obstacle approaching operation period is weakened, and the control difficulty to be overcome is urgent. Disclosure of Invention The invention provides a flight control method special for a hydrogen energy unmanned aerial vehicle, which solves the technical problems in the background technology. The invention provides a flight control method special for a hydrogen energy unmanned aerial vehicle, which is applied to the hydrogen energy unmanned aerial vehicle comprising a proton exchange membrane fuel cell, a super capacitor, an oxygen supply assembly, a hydrogen discharge assembly, a sensor unit and a multi-rotor assembly, and comprises the following steps: acquiring and synchronizing the sensing state quantity of the sensor unit, carrying out dimensionless processing according to the feasible value range of the rolling window to obtain a dimensionless state vector, and feedforward calculating a path power demand index; Extracting an inverse gravity drainage exposure memory reflecting the accumulation of unfavorable drainage based on the body system posture of the hydrogen energy unmanned aerial vehicle and the favorable drainage direction of the proton exchange membrane fuel cell; Predicting the power vulnerability of a future path section by utilizing the exposure memory capacity of the reverse gravity drainage and the oxygen supply sufficiency in the perception state quantity, and further outputting a future energy supply gap index; generating super capacitor target output and fuel cell target output according to the future energy supply gap index and the reverse gravity drainage exposure memory, and generating a hydrogen supply adjusting instruction and a continuous hydrogen discharge duty cycle in a synchronous and self-adaptive manner; Taking the exposure memory capacity of the inverse gravity drainage and the future energy supply gap index into path evaluation cost, and optimizing in a candidate path set to generate a reconstructed local path and along-path speed distribution; updating a gravity center position vector according to mass migration caused by fluid material consumption, and generating a feedforward compensation moment based on the gravity center position vector to correct a rotor wing target instruction; And evaluating the comprehensive risk of the system, generating an emergency take-over coefficient, and smoothly fusing the reconstructed local path and the emergency landing path by using the emergency take-over coefficient to generate a final command path. The invention has the beneficial effects that the adverse drainage effect of the galvanic pile caused by space maneuver is extracted into the memory capacity exposed by the reverse gravity drainage, and the memory capacity is implemented in the whole process of power collaborative scheduling and route optimizing. By accurately predicting the shrinkage trend of the memory quantity on the subsequent available energy, the system can not only lead the machine body to bypass the navigation section which aggravates severe liquid discharge, but also call the super capacitor