Stratospheric aerostat pressure difference control method

Abstract

The invention discloses a stratospheric aerostat pressure difference control method, which belongs to the field of flight control, is used for aerostat pressure difference control, and comprises the following steps: starting an aerostat pressure difference control program, detecting the internal temperature condition of an aerostat caused by external environment change, judging whether the aerostat is in a normal environment or not, if so, changing the volume of an internal phase change air bag, and if not, judging that the aerostat is in the normal environment. If yes, the internal pressure of the aerostat changes, then whether the pressure difference is within the safety range or not is judged, if not, the volumes of the internal and external phase change air bags cooperatively change, the internal pressure change and the height change of the aerostat enable the external atmospheric pressure of the aerostat to change, and then whether the pressure difference is within the safety range or not is judged; and judging whether the pressure difference is within a safe range, if not, returning to detect the internal temperature condition of the aerostat caused by the change of the external environment, and if so, ending the pressure difference control method. Under the normal day and night alternation condition, the volume of the internal phase change air bag is adjusted, the internal pressure of the aerostat is adjusted, and the internal and external pressure difference of the stratospheric aerostat is always kept within a safe range.

Description

Technical Field

[0001] This invention discloses a differential pressure control method for stratospheric airships, belonging to the field of flight control. Background Technology

[0002] The current problem of differential pressure control in stratospheric airships is one of the obstacles to their long-term stationary operation. When the differential pressure inside and outside the airship is too large, it will shorten the service life of the skin material or even directly cause the skin to rupture. When the differential pressure inside and outside the airship is too small, the airship will not be able to maintain its normal aerodynamic shape. Stratospheric airships are in a complex thermodynamic environment, and during stationary operation, the airship will experience "overheating" and "overcooling" phenomena, resulting in the pressure inside the airship being much greater than or much less than the pressure outside the airship, which will have an adverse effect on the long-term stationary operation of the airship.

[0003] Current research focuses on improving the skin material to enhance its pressure resistance. In the control field, the pressure inside the main airbag is generally adjusted by changing the volume of the airbag inside the airship. However, this method changes the total mass of the airship, which in turn causes changes in the airship's altitude. The resulting changes in the external atmospheric pressure of the airship follow the same trend as the changes in the internal pressure of the airship, meaning that the pressure inside and outside the skin increases or decreases simultaneously. This makes the method less than ideal for regulating the pressure difference of the airship, and it cannot adjust the pressure difference in time when encountering cold clouds or other conditions that cause temperature changes or exceed the normal range. Summary of the Invention

[0004] The purpose of this invention is to provide a method for differential pressure control of stratospheric airships, so as to solve the problem of poor differential pressure control capability of airships in the prior art.

[0005] A method for differential pressure control of a stratospheric airship includes initiating a differential pressure control program for the airship, detecting the internal temperature of the airship caused by changes in the external environment, determining whether the airship is in a normal environment, and if so, changing the volume of the internal phase change gasbags, causing a change in the internal pressure of the airship, and then determining whether the differential pressure is within a safe range; if not, the volumes of the internal and external phase change gasbags change together, causing a change in the internal pressure of the airship, and the change in altitude causes a change in the external atmospheric pressure of the airship, and then determining whether the differential pressure is within a safe range. When determining whether the differential pressure is within a safe range, if not, return to check the internal temperature of the airship caused by changes in the external environment; if so, end the differential pressure control method.

[0006] The airship internal pressure control model is as follows: In the formula, P main V is the internal pressure of the main airbag, and V is the total volume of the main airbag and the internal phase change airbag, in meters. main It is the mass of the main airbag buoyant gas, R mainT is the ideal gas constant of the floating gas. main It is the internal temperature of the main airbag, m in It is the mass of the gaseous phase change working fluid inside the internal phase change airbag, R in T is the ideal gas constant of the gaseous phase change working fluid. in It is the internal temperature of the internal phase change airbag, and the superscript dot indicates the rate of change of the corresponding quantity.

[0007] An adaptive radial basis function neural network controller combined with a low-pass filter is designed for the airship internal pressure control model to obtain P. main It is then used as a negative feedback input low-pass filter: In the formula, f is an intermediate variable and U is the control input; The control law for the control input is: e1 = P d -P main ; In the formula, U * It is the control law that controls the input, P d It is the target pressure, k p k d e1 is a constant, and e1 is the error. It is the second derivative of the target pressure.

[0008] f is obtained by approximation using a radial basis function neural network. The radial basis function is the Gaussian function, and the Gaussian function outputs H. j for: b j = [b1, ...b m ] T ; In the formula, c ij where i is the number of inputs to the radial basis function neural network, and c ij j represents the j-th node in the hidden layer of the radial basis function neural network, and c ij Let b be the coordinate vector of the center point of the Gaussian function of the j-th neuron in the hidden layer, m be the maximum number of nodes in the hidden layer of the radial basis function neural network, and b be the coordinate vector of the center point of the Gaussian function of the j-th neuron in the hidden layer. j The width of the Gaussian function of the j-th neuron in the hidden layer; Using E as the input to a radial basis function neural network, the output of the radial basis function neural network is: H = [H1, H2, ... H] m ] T ; In the formula, It is an estimate of f. It is an estimate of the ideal weight W, and H is the value of H. j The matrix formed; design Adaptive law γ>; B = [0 1] T ; In the formula, γ is a positive parameter, B is a coefficient matrix, and λ is a symmetric positive definite matrix that satisfies the following constraints: Λ T λ+λΛ=-Q; In the formula, Λ is the intermediate matrix and Q is a positive parameter.

[0009] After obtaining the estimated value of f, the control law for the control input is:

[0010] When determining whether the airship is in a normal environment, set the temperature range inside the airship's main airbag [T]. min ,T max and the range of temperature change rates [ΔT] min ,ΔT max When the temperature inside the main airbag of the airship is not below [T] min T max The rate of temperature change within the airship's main airbag is not within [ΔT]. min ,ΔT max When inside, the altitude control system is activated to change the altitude of the airship.

[0011] Changing the height of the airship involves establishing a dynamic model of the airship in the vertical direction. The airship is subjected to buoyancy, gravity, drag, and additional inertial forces in the vertical direction. The nonlinear dynamic equation of the airship in the vertical direction is as follows: In the formula, h is the aerostat's dwell height, and v h It is the vertical velocity of the airship, m all It is the total mass of the airship, F B F D F add These are the buoyancy, drag, and additional inertial force acting on the airship, ρ. air It is atmospheric density, m ex It is the mass of the gaseous phase change working fluid inside the external phase change gasbag, ρ x V0 is the density of the gaseous phase-change working fluid at the airship's dwell altitude, V0 is the sum of the volumes of all other parts of the airship excluding the external phase-change gasbag, and C is...D It is the vertical aerodynamic coefficient, A s is the effective area in the vertical direction, and g is the gravitational acceleration.

[0012] Changing the height of the airship includes increasing the height by m ex As the system control input and h as the system control output, a hybrid sensitivity controller H∞ is designed. The state space of the system after linearization is: x = [hv] h ] T ; y = h; C g =[1 0]; D g =0; In the formula, x is the system state variable, u is the controller output, equivalent to the system control input, y is the system control output, and A is the system control output. g B g C g D g The state-space coefficient matrix of the linearized system is... It is the second derivative of h.

[0013] Add a sensitivity function S and a complementary sensitivity function T to the H∞ hybrid sensitivity controller: S = (1 + GK) -1 ; T = GK(1 + GK) -1 ; In the formula, the sensitivity function S is equivalent to the transfer function from the interference signal d to h, the singular value of S is less than 1, the complementary sensitivity function T is equivalent to the transfer function from the system control input to h, K is the H∞ hybrid sensitivity controller, and G is the state space of the linearized system.

[0014] Changing the aerostat altitude involves finding a rational function controller M(S) that satisfies the performance metric H∞ to ensure the stability of the closed-loop system. In the formula, W1 is the weighting function of the error, W2 is the weighting function of u, and W3 is the weighting function of h; By optimizing the upper bound of the H∞ norm of M(S), the H∞ norm of M(S) satisfies: ||M(S)|| ∞ ≤μ; In the formula, μ is the robustness parameter; We obtain G and the weighted function matrix W.i The generalized controlled object matrix P is: C2 = [C g 0 0 0]; D 21 =0; D 22 =D g ; In the formula, A wi B wi C wi D wi Let A, B1, B2, C1, C2, and D be the coefficients of the i-th weighting function after it has been transformed into matrix form. 11 D 12 D 21 D 22 Elements of the generalized controlled object matrix; K is obtained as follows: Z = 1 - XYμ -2 ; In the formula, A f Z, L, and F are the parameters to be determined, and X and Y are two solutions to the Riccati equation, which is:

[0015] Compared with the prior art, the present invention has the following beneficial effects: Under normal day-night alternation, the pressure difference of the airship during normal day-night alternation can be adjusted without changing the airship's altitude, thus keeping the internal and external pressure difference of the stratospheric airship within a safe range; even in special circumstances such as the appearance of cold clouds, the altitude control system can be activated to adjust the volume of the external phase change gasbag. As the internal pressure of the airship changes, the external atmospheric pressure also changes accordingly, and the combined effect keeps the internal and external pressure of the airship within a safe range. Attached Figure Description

[0016] Figure 1 This is a technical flowchart of the present invention; Figure 2 This is a block diagram of the internal pressure control system of a stratospheric airship; Figure 3 This is a block diagram of the stratospheric airship altitude control system; Figure 4 It is the change in pressure difference of a stratospheric airship during a day and night under uncontrolled conditions; Figure 5This is the pressure difference change of the stratospheric airship from 5 to 7 during the normal day-night cycle and the adjustment of the internal phase change airbag; Figure 6 This is the pressure difference change of the stratospheric airship from 17 to 19 during the normal day-night cycle and internal phase change gasbag adjustment. Figure 7 This is a diagram illustrating the effect of external phase change airbags in regulating the altitude of a stratospheric airship. Figure 8 This is a comparison chart showing the effects of regulating the pressure difference solely by the internal phase change airbag when encountering a sudden drop in temperature, versus regulating the pressure difference by the internal phase change airbag assisted by altitude control. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention are described clearly and completely below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0018] A method for differential pressure control of a stratospheric airship includes initiating a differential pressure control program for the airship, detecting the internal temperature of the airship caused by changes in the external environment, determining whether the airship is in a normal environment, and if so, changing the volume of the internal phase change gasbags, causing a change in the internal pressure of the airship, and then determining whether the differential pressure is within a safe range; if not, the volumes of the internal and external phase change gasbags change together, causing a change in the internal pressure of the airship, and the change in altitude causes a change in the external atmospheric pressure of the airship, and then determining whether the differential pressure is within a safe range. When determining whether the differential pressure is within a safe range, if not, return to check the internal temperature of the airship caused by changes in the external environment; if so, end the differential pressure control method.

[0019] The airship internal pressure control model is as follows: In the formula, P main V is the internal pressure of the main airbag, and V is the total volume of the main airbag and the internal phase change airbag, in meters. main It is the mass of the main airbag buoyant gas, R main T is the ideal gas constant of the floating gas. main It is the internal temperature of the main airbag, m in It is the mass of the gaseous phase change working fluid inside the internal phase change airbag, R in T is the ideal gas constant of the gaseous phase change working fluid. in It is the internal temperature of the internal phase change airbag, and the superscript dot - indicates the rate of change of the corresponding quantity.

[0020] An adaptive radial basis function neural network controller combined with a low-pass filter is designed for the airship internal pressure control model to obtain P. main It is then used as a negative feedback input low-pass filter: In the formula, f is an intermediate variable and U is the control input; The control law for the control input is: e1 = P d -P main ; In the formula, U * It is the control law that controls the input, P d It is the target pressure, k p k d e1 is a constant, and e1 is the error. It is the second derivative of the target pressure.

[0021] f is obtained by approximation using a radial basis function neural network. The radial basis function is the Gaussian function, and the Gaussian function outputs H. j for: b j = [b1, ...b m ] T ; In the formula, c ij where i is the number of inputs to the radial basis function neural network, and c ij j represents the j-th node in the hidden layer of the radial basis function neural network, and c ij Let b be the coordinate vector of the center point of the Gaussian function of the j-th neuron in the hidden layer, m be the maximum number of nodes in the hidden layer of the radial basis function neural network, and b be the coordinate vector of the center point of the Gaussian function of the j-th neuron in the hidden layer. j The width of the Gaussian function of the j-th neuron in the hidden layer; Using E as the input to a radial basis function neural network, the output of the radial basis function neural network is: H = [H1, H2, ... H] m ] T ; In the formula, It is an estimate of f. It is an estimate of the ideal weight W, and H is the value of H. j The matrix formed; design Adaptive law γ > 0; B = [0 1]T ; In the formula, γ is a positive parameter, B is a coefficient matrix, and λ is a symmetric positive definite matrix that satisfies the following constraints: Λ T λ+λΛ=-Q; In the formula, Λ is the intermediate matrix and Q is a positive parameter.

[0022] After obtaining the estimated value of f, the control law for the control input is:

[0023] When determining whether the airship is in a normal environment, set the temperature range inside the airship's main airbag [T]. min T max and the range of temperature change rates [ΔT] min ΔT max When the temperature inside the main airbag of the airship is not below [T] min T max The rate of temperature change within the airship's main airbag is not within [ΔT]. min ΔT max When inside, the altitude control system is activated to change the altitude of the airship.

[0024] Changing the height of the airship involves establishing a dynamic model of the airship in the vertical direction. The airship is subjected to buoyancy, gravity, drag, and additional inertial forces in the vertical direction. The nonlinear dynamic equation of the airship in the vertical direction is as follows: In the formula, h is the aerostat's dwell height, and v h It is the vertical velocity of the airship, m all It is the total mass of the airship, F B F D F add These are the buoyancy, drag, and additional inertial force acting on the airship, ρ. air It is atmospheric density, m ex It is the mass of the gaseous phase change working fluid inside the external phase change gasbag, ρ x V0 is the density of the gaseous phase-change working fluid at the airship's dwell altitude, V0 is the sum of the volumes of all other parts of the airship excluding the external phase-change gasbag, and C is... D It is the vertical aerodynamic coefficient, A S is the effective area in the vertical direction, and g is the gravitational acceleration.

[0025] Changing the height of the airship includes increasing the height by m ex As the system control input and h as the system control output, a hybrid sensitivity controller H∞ is designed. The state space of the system after linearization is: x = [hv] h ] T ; y = h; C g =[1 0]; D g =0; In the formula, x is the system state variable, u is the controller output, equivalent to the system control input, y is the system control output, and A is the system control output. g B g C g D g The state-space coefficient matrix of the linearized system is... It is the second derivative of h.

[0026] Add a sensitivity function S and a complementary sensitivity function T to the H∞ hybrid sensitivity controller: S = (1 + GK) -1 ; T = GK(1 + GK) -1 ; In the formula, the sensitivity function S is equivalent to the transfer function from the interference signal f to h, the singular value of S is less than 1, the complementary sensitivity function T is equivalent to the transfer function from the system control input to h, K is the H∞ hybrid sensitivity controller, and G is the state space of the linearized system.

[0027] Changing the aerostat altitude involves finding a rational function controller M(S) that satisfies the performance metric H∞ to ensure the stability of the closed-loop system. In the formula, W1 is the weighting function of the error, W2 is the weighting function of u, and W3 is the weighting function of h; By optimizing the upper bound of the H∞ norm of M(S), the H∞ norm of M(S) satisfies: ||M(S)|| ∞ ≤μ; In the formula, μ is the robustness parameter; We obtain G and the weighted function matrix W. i The generalized controlled object matrix P is: C2 = [C g 0 0 0]; D 21 =0; D 22 =D g ; In the formula, A wi B wi C wi D wi Let A, B1, B2, C1, C2, and D be the coefficients of the i-th weighting function after it has been transformed into matrix form. 11 D 12 D 21 D 22 Elements of the generalized controlled object matrix; K is obtained as follows: Z = 1 - XYμ -2 ; In the formula, A f Z, L, and F are the parameters to be determined, and X and Y are two solutions to the Riccati equation, which is:

[0028] The technical process of this invention is as follows: Figure 1 As shown, the process includes initiating the airship differential pressure control program, detecting the internal temperature of the airship caused by changes in the external environment, determining whether the airship is in a normal environment, and if so, changing the volume of the internal phase change gasbags, causing a change in the internal pressure of the airship, and then determining whether the differential pressure is within a safe range; if not, the volumes of the internal and external phase change gasbags change together, causing a change in the internal pressure of the airship, and the change in altitude causes a change in the external atmospheric pressure of the airship, and then determining whether the differential pressure is within a safe range; if the differential pressure is within a safe range, the process returns to detecting the internal temperature of the airship caused by changes in the external environment, and if so, the differential pressure control method ends.

[0029] Figure 2 This is a block diagram of the internal pressure control system of the stratospheric airship provided in the embodiment, which represents the matrix E and P formed by the error and the rate of change of error. d and The input to the control system yields U, which is then input into the internal phase change airbag to obtain m. in , will m in Inputting a stratospheric airship yields P main , will P main The input is a low-pass filter, which receives negative feedback. E is then fed into an RBF neural network and an adaptive algorithm, and the adaptive algorithm outputs... To the RBF neural network, the RBF neural network output To the control system; P d It is used as a positive feedback input and processed together with negative feedback.

[0030] Figure 3 This is a block diagram of the height control system, with the target height h as the input. d After entering the first controller, an error e2 is generated, which is then input to the H∞ sensitivity controller to generate u. This u is input to the stratospheric airship dynamics model and, together with the interference signal d, is input to the second controller to obtain h. The output of the first controller is also sent to the weighting function W1 of the error e2 to form z1. The output of the H∞ sensitivity controller is also sent to the weighting function of the control signal u to form z2. The output of the second controller is also sent to the weighting function W3 of the output h to form z3. W3 is synchronously sent to the first controller. z1, z2, and z3 are the corresponding signals used for system evaluation.

[0031] This invention replaces the air bladder inside a traditional stratospheric airship with an internal phase-change air bladder. This ensures that the total mass of the system remains unchanged during the adjustment of the airship's internal pressure. A pressure control model for the stratospheric airship's internal bladder is established, and an adaptive RBF neural network controller incorporating a low-pass filter is designed. The RBF neural network approximates and replaces the unknown functions in the internal pressure control model, and further designs the control law and adaptive law. The airship's operating environment is relatively complex, resulting in significant high-frequency vibration noise in the differential pressure feedback signal measured by the sensors, which can affect the normal operation of the controller. Therefore, after completing the design of the RBF neural network controller, a low-pass filter needs to be added to the feedback loop to filter out high-frequency noise. Meanwhile, since the airship's skin material does not require overly precise pressure differential control, maintaining the pressure differential within a certain safe range is sufficient to ensure the airship's long-term stationary operation. Therefore, the cutoff frequency of the low-pass filter can be appropriately reduced, sacrificing some of the system's dynamic characteristics. This reduces the need for the phase change system to frequently change its operating state, decreasing the workload of the phase change system and the airship's energy consumption. This allows for pressure control within the airship to cope with pressure changes caused by normal day-night temperature variations. For situations where cold clouds or other factors cause rapid temperature changes within the airship, simply adjusting the internal phase change gasbag may not meet the pressure differential control requirements. Therefore, when encountering such situations during airship operation, the buoyancy of the airship is adjusted by controlling the volume of the external phase change gasbag, thereby controlling the airship's altitude and altering the external atmospheric pressure. For altitude control, a vertical airship dynamic model was established, and a hybrid sensitivity controller was designed. The control scheme proposed in this invention can meet the pressure differential control requirements within and outside the airship's gasbag in most cases, providing a guarantee for the long-term stationary operation of stratospheric airships.

[0032] To verify the effectiveness of this invention, corresponding simulation experiments were conducted in MATLAB, using thermodynamic data from the vernal equinox for thermodynamic modeling. The volume of the main gasbag of the stratospheric airship was selected as 4200 m³. 3 The volume of both the inner and outer phase change airbags is 800m³. 3 The stratospheric airship carries helium as the buoyant gas (50 kg) and ammonia as the phase-change working fluid (80 kg), for a total system mass of 370 kg. The final result shows the change in pressure difference between the inside and outside of the airship after it has remained at an altitude of 20 km for one day. Figure 4 As shown.

[0033] Depend on Figure 4 It can be seen that the periods of fastest pressure increase and fastest pressure decrease inside and outside the airship during the day are 5:00-7:00 and 17:00-19:00, respectively. Assuming the safe pressure differential range of the airship skin material is 400Pa to 700Pa, from... Figure 5 and Figure 6 It is easy to see that the internal pressure control system designed in this invention can maintain the pressure difference between the inside and outside of the airship within a safe range during these two time periods. Therefore, the internal pressure control system designed in this invention can ensure that the pressure difference between the inside and outside of the stratospheric airship remains within a safe range under normal day-night alternation.

[0034] External phase change airbags effectively control the altitude of stratospheric airships. Figure 7 As shown, the simulation experiment used a cold cloud causing a sudden drop in the internal temperature of the stratospheric airship, representing a special situation that the airship might encounter during operation. After encountering the cold cloud, the simulation employed a method where only the internal phase-change gasbags regulated the internal pressure, and the altitude control system assisted in regulating the external atmospheric pressure. Figure 8 As shown, when the temperature changes drastically, due to the limited efficiency of the phase change system, adjusting only the internal phase change airbag cannot guarantee that the pressure difference between the inside and outside of the airship is within a safe range. However, by adjusting the airship's altitude, the pressure difference requirement can be met.

[0035] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for differential pressure control of a stratospheric airship, characterized in that, This includes initiating the airship differential pressure control program, detecting the internal temperature of the airship caused by changes in the external environment, determining whether the airship is in a normal environment, and if so, changing the volume of the internal phase change airbags, causing changes in the internal pressure of the airship, and then determining whether the differential pressure is within a safe range; if not, the volumes of the internal and external phase change airbags change together, causing changes in the internal pressure of the airship, and the change in altitude causes changes in the external atmospheric pressure of the airship, and then determining whether the differential pressure is within a safe range. When determining whether the differential pressure is within a safe range, if not, return to check the internal temperature of the airship caused by changes in the external environment; if so, end the differential pressure control method.

2. The method for differential pressure control of a stratospheric airship according to claim 1, characterized in that, The airship internal pressure control model is as follows: In the formula, P main V is the internal pressure of the main airbag, and V is the total volume of the main airbag and the internal phase change airbag, in meters. main It is the mass of the main airbag buoyant gas, R main T is the ideal gas constant of the floating gas. main It is the internal temperature of the main airbag, m in It is the mass of the gaseous phase change working fluid inside the internal phase change airbag, R in T is the ideal gas constant of the gaseous phase change working fluid. in It is the internal temperature of the internal phase change airbag, and the superscript dot indicates the rate of change of the corresponding quantity.

3. The method for differential pressure control of a stratospheric airship according to claim 2, characterized in that, An adaptive radial basis function neural network controller combined with a low-pass filter is designed for the airship internal pressure control model to obtain P. main It is then used as a negative feedback input low-pass filter: In the formula, f is an intermediate variable and U is the control input; The control law for the control input is: e1=P d -P main ; In the formula, U * It is the control law that controls the input, P d It is the target pressure, k p k d e1 is a constant, and e1 is the error. It is the second derivative of the target pressure.

4. The method for differential pressure control of a stratospheric airship according to claim 3, characterized in that, f is obtained by approximation using a radial basis function neural network. The radial basis function is the Gaussian function, and the Gaussian function outputs H. j for: b j =[b1,...b m ] T ; In the formula, c ij where i is the number of inputs to the radial basis function neural network, and c ij j represents the j-th node in the hidden layer of the radial basis function neural network, and c ij Let b be the coordinate vector of the center point of the Gaussian function of the j-th neuron in the hidden layer, m be the maximum number of nodes in the hidden layer of the radial basis function neural network, and b be the coordinate vector of the center point of the Gaussian function of the j-th neuron in the hidden layer. j The width of the Gaussian function of the j-th neuron in the hidden layer; Using E as the input to a radial basis function neural network, the output of the radial basis function neural network is: H=[H1,H2,…Hm] T ; In the formula, It is an estimate of f. It is an estimate of the ideal weight W, and H is the value of H. j The matrix formed; design Adaptive law γ>0; B＝[01] T ； In the formula, γ is a positive parameter, B is a coefficient matrix, and λ is a symmetric positive definite matrix that satisfies the following constraints: L T λ+λΛ=-Q; In the formula, Λ is the intermediate matrix and Q is a positive parameter.

5. The method for differential pressure control of a stratospheric airship according to claim 4, characterized in that, After obtaining the estimated value of f, the control law for the control input is:

6. The method for differential pressure control of a stratospheric airship according to claim 5, characterized in that, When determining whether the airship is in a normal environment, set the temperature range inside the airship's main airbag [T]. min T max and the range of temperature change rates [ΔT] min ΔT max When the temperature inside the main airbag of the airship is not below [T] min T max The rate of temperature change within the airship's main airbag is not within [ΔT]. min ΔT max When inside, the altitude control system is activated to change the altitude of the airship.

7. The method for differential pressure control of a stratospheric airship according to claim 6, characterized in that, Changing the height of the airship involves establishing a dynamic model of the airship in the vertical direction. The airship is subjected to buoyancy, gravity, drag, and additional inertial forces in the vertical direction. The nonlinear dynamic equation of the airship in the vertical direction is as follows: In the formula, h is the aerostat's dwell height, and v h It is the vertical velocity of the airship, m all It is the total mass of the airship, F B F D F add These are the buoyancy, drag, and additional inertial force acting on the airship, ρ. air It is atmospheric density, m ex It is the mass of the gaseous phase change working fluid inside the external phase change gasbag, ρ x V0 is the density of the gaseous phase-change working fluid at the airship's dwell altitude, V0 is the sum of the volumes of all other parts of the airship excluding the external phase-change gasbag, and C is... D It is the vertical aerodynamic coefficient, A S is the effective area in the vertical direction, and g is the gravitational acceleration.

8. The method for differential pressure control of a stratospheric airship according to claim 7, characterized in that, Changing the height of the airship includes increasing the height by m ex As the system control input and h as the system control output, a hybrid sensitivity controller H∞ is designed. The state space of the system after linearization is: x=[h v h ] T ; y = h; C g ＝[1 0]； D g ＝0； In the formula, x is the system state variable, u is the controller output, equivalent to the system control input, y is the system control output, and A is the system control output. g B g C g D g The state-space coefficient matrix of the linearized system is... It is the second derivative of h.

9. A method for controlling differential pressure in a stratospheric airship according to claim 8, characterized in that, Add a sensitivity function S and a complementary sensitivity function T to the Hoo hybrid sensitivity controller: S=(1+GK) -1 ; T=GK(1+GK) -1 ; In the formula, the sensitivity function S is equivalent to the transfer function from the interference signal d to h, the singular value of S is less than 1, the complementary sensitivity function T is equivalent to the transfer function from the system control input to h, K is the H∞ hybrid sensitivity controller, and G is the state space of the linearized system.

10. A method for controlling differential pressure in a stratospheric airship according to claim 9, characterized in that, Changing the aerostat altitude involves finding a rational function controller M(S) that satisfies the performance metric H∞ to ensure the stability of the closed-loop system. In the formula, W1 is the weighting function of the error, W2 is the weighting function of u, and W3 is the weighting function of h; By optimizing the upper bound of the H∞ norm of M(S), the H∞ norm of M(S) satisfies: ||M(S)|| ∞ ≤μ; In the formula, μ is the robustness parameter; We obtain G and the weighted function matrix W. i The generalized controlled object matrix P is: C2=[C g 0 0 0]; D 21 ＝0； D 22 =D g ; In the formula, A wi B wi C wi D wi Let A, B1, B2, C1, C2, and D be the coefficients of the i-th weighting function after it has been transformed into matrix form. 11 D 12 D 21 D 22 Elements of the generalized controlled object matrix; K is obtained as follows: Z=1-XYμ -2 ; In the formula, A f Z, L, and F are the parameters to be determined, and X and Y are two solutions to the Riccati equation, which is:

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