Hypersonic vehicle flight-propulsion integrated adaptive control method under coupling identification

Abstract

The application belongs to the technical field of hypersonic vehicle control, and particularly relates to a hypersonic vehicle flight-propulsion integrated adaptive control method under coupling identification. The method comprises the following steps: constructing a hypersonic vehicle flight-propulsion integrated dynamic model, constructing a flight-propulsion multi-input multi-output state space model and performing online coupling identification, constructing a flight-propulsion coupling degree according to the online coupling identification result of RGA, and designing an adaptive coordinated control method based on the flight-propulsion coupling degree. The application realizes the integration of flight-propulsion coupling degree identification and coordinated control strength adjustment by changing the flight-propulsion cross feedback control effect in real time through coordinated control coefficients, and has a wide application prospect.

Description

Technical Field

[0001] This invention belongs to the field of hypersonic vehicle control technology, specifically relating to an integrated adaptive control method for hypersonic vehicle flight and thrust under coupled identification. Background Technology

[0002] With the development of hypersonic flight technology, air-breathing hypersonic vehicles are gradually evolving towards larger flight envelopes, higher maneuverability, and longer sustained flight durations. Hypersonic vehicles typically employ a highly integrated overall configuration of airframe and propulsion system. The forebody of the hypersonic vehicle participates in the compression of the engine's incoming airflow, while the thrust and additional torque generated by the propulsion system directly affect the vehicle's motion, creating a clear two-way coupling between the flight and propulsion systems. Changes in the vehicle's angle of attack, speed, and altitude alter the engine inlet airflow and incoming airflow conditions, thus affecting the propulsion system's operating state. Conversely, changes in fuel supply and engine operating state alter the vehicle's attitude through thrust, eccentric torque, and additional aerodynamic forces from the aft body. Therefore, the flight control and propulsion control of hypersonic vehicles cannot be treated as two completely independent systems.

[0003] The existing technology has the following main shortcomings: The first issue is the quantitative description of the flight-propulsion coupling degree. Existing integrated flight-propulsion analysis typically uses dynamic coefficients, local partial derivatives, or state sensitivity to describe the interaction between flight and propulsion states. These parameters can explain the direction and magnitude of the influence of a change in one variable on another. However, hypersonic integrated flight-propulsion systems are essentially multi-input multi-output systems, where multiple control inputs, such as elevators and fuel regulation, simultaneously affect both flight and propulsion states. Analyzing only a single dynamic coefficient is insufficient to directly reflect the changes in the actual control capability of a particular input-output channel after other control loops are closed, and it is also difficult to make a unified comparison of the relative coupling strength between different channels.

[0004] Secondly, the flight-thrust coupling relationship exhibits a significant condition-dependent characteristic. When a hypersonic vehicle operates within its wide flight envelope, parameters such as Mach number, altitude, angle of attack, and fuel equivalence ratio all change, leading to corresponding alterations in aerodynamic forces, thrust, and dynamic coefficients. A weaker flight-thrust interaction under one flight condition may be significantly stronger under another. Therefore, using fixed coupling coefficients or analyzing the coupling relationship offline at only a few typical operating points is insufficient to continuously reflect the dynamic changes in the degree of flight-thrust coupling throughout the entire flight process.

[0005] Secondly, there is a lack of direct adaptive connection between the coupling analysis results and the controller. Some existing control methods can already consider the fly-thrust coupling terms in the state-space model and improve system control performance using methods such as full-state feedback, pole placement, and sliding mode control. However, the controller's coordination action is usually determined by pre-set feedback structures or control parameters. For operating conditions with relatively weak actual coupling, maintaining strong cross-feedback may increase additional control actions; while when the coupling significantly increases, the fixed coordination control strength may be insufficient. Therefore, it is necessary to further feed back the real-time fly-thrust coupling degree directly to the controller, so that the control action can be adjusted according to changes in the coupling state.

[0006] Existing related patent technologies also have certain limitations: Patent application CN201711157176.8 proposes a method for evaluating the coupling effect degree of air-breathing aircraft. This method considers the strong coupling effect between the center of mass motion, attitude motion, and air-breathing propulsion. By establishing a linearized coupling equation, it analyzes the coupling terms caused by air-breathing propulsion and constructs corresponding coupling effect description parameters to evaluate the coupling degree between different systems. This method can quantitatively evaluate the multi-system coupling of air-breathing aircraft, but its technical focus is mainly on evaluating the coupling terms and the degree of coupling effect. It does not further establish an online coupling identification mechanism based on the relative gain change of input-output, nor does it directly convert the obtained coupling degree into flight thrust coordination control gain for real-time adjustment.

[0007] Patent application CN201711119283.1 proposes a multi-system correlation modeling method for hypersonic vehicles oriented towards control. This method starts from the design requirements of the control system, establishing correlations between aerodynamic, propulsion, and structural subsystems and the core dynamic system. It evaluates the impact of different subsystems on the core control system using open-loop or closed-loop indices, thereby selecting the coupling subsystems that need to be retained. This method can provide a relatively complete analytical framework for multi-system coupling modeling of hypersonic vehicles, but it mainly addresses which subsystems need to be included in the control model and how to establish correlation models. Its focus remains on correlation modeling and system selection; it does not establish real-time relative gain matrices for the specific input-output channels between elevators, fuel regulation and angle of attack, and propulsion states, nor does it continuously adjust the coordination level of the flight thrust controller according to the coupling strength.

[0008] Patent application CN201910333259.0 proposes a coordinated control method for hypersonic vehicles based on dynamic coupling analysis. This method targets the longitudinal system of a hypersonic vehicle, obtaining the dynamic coupling relationship matrix between system state variables and control input variables through dynamic coupling analysis. Based on this matrix, a coordinated controller is designed, allowing the coupling analysis results to further participate in the controller design. While this technology embodies the "coupling analysis-coordinated control" approach, its research focuses primarily on the dynamic coupling between variables within the longitudinal system of a hypersonic vehicle. It does not yet address the bidirectional coupling between the flight system and propulsion system of air-breathing hypersonic vehicles, constructing an online RGA (Rapid Adaptive Control) structure with elevator and fuel regulation as inputs and flight and propulsion states as outputs. Furthermore, it does not construct a unified coupling parameter for continuously adjusting the cross-feedback strength between the flight and propulsion systems.

[0009] In summary, existing technologies have conducted relevant research on multi-system correlation modeling, coupling degree evaluation, dynamic coupling coordinated control, and flight-propulsion integrated feedback control of hypersonic vehicles. However, for the problem of the real-time change of the coupling relationship between the flight system and the propulsion system under the wide flight envelope with the operating conditions, there is still a lack of a method that can quantify the flight-propulsion interaction online from the perspective of multi-input multi-output control channels and directly use the obtained coupling information to adjust the coordinated control parameters. Summary of the Invention

[0010] The purpose of this invention is to provide an adaptive control method for hypersonic vehicles integrating flight and thrust under coupling identification. Based on an integrated flight and thrust dynamics model, this invention introduces a relative gain matrix to identify the relative interactions between the elevator, fuel regulation and angle of attack, and propulsion status online. On this basis, a comprehensive flight-thrust coupling degree is constructed, and the cross-coordination control action of flight and thrust is dynamically adjusted according to the comprehensive coupling degree, thus achieving a further extension from "coupling relationship analysis" to "online identification of coupling degree - adaptive adjustment of control strength".

[0011] This method first establishes an integrated flight-propulsion dynamic model that includes both flight and propulsion states. Based on this, it constructs a multi-input multi-output coupling relationship from elevator deflection and fuel equivalence ratio control commands to angle of attack and velocity. Subsequently, it obtains a multi-input multi-output state space model of flight and propulsion based on the current flight state, and uses a relative gain matrix to identify the main flight control channel, the main propulsion control channel, and the two cross channels online. Furthermore, it constructs the flight-propulsion coupling degree based on the relative gain matrix and converts the flight-propulsion coupling degree into coordinated control coefficients. Finally, it changes the flight-propulsion cross-feedback control action in real time based on the coordinated control coefficients, realizing the integration of flight-propulsion coupling degree identification and coordinated control strength adjustment.

[0012] To achieve the above objectives, the technical solution of the present invention is as follows: An integrated adaptive control method for hypersonic vehicles based on coupled identification, the specific steps of which are as follows: Step 1: Construct an integrated flight and propulsion dynamic model for hypersonic vehicles; A dynamic model capable of simultaneously describing the longitudinal motion state of the aircraft and the state changes of the propulsion system was established, and a small perturbation model was obtained by performing small perturbations, which provides a foundation for the subsequent construction of the flight-propulsion coupling channel and the identification of the degree of coupling.

[0013] Under hypersonic flight conditions, the influence of flight state on the propulsion system is mainly reflected in the effects of variables such as angle of attack and velocity on the engine airflow and air mass flow rate; the influence of the propulsion system on flight state is mainly reflected in thrust, eccentric thrust torque, and additional aerodynamic torque. In order to describe the above two-way relationship in a unified model, the fuel equivalence ratio is introduced as a propulsion system state variable into the longitudinal dynamic equation of the aircraft.

[0014] Fuel equivalence ratio is expressed as: (1) in, Fuel equivalence ratio, For flight speed, For the angle of attack, For fuel equivalence ratio command, This indicates the nonlinear relationship between fuel equivalence ratio and speed, angle of attack, and fuel equivalence ratio commands.

[0015] Ignoring the influence of lateral parameters, a force analysis is performed on the longitudinal channel of the hypersonic vehicle to establish an integrated flight-thrust dynamic model: (2) Among them, the superscript " " represents the first derivative, It is the pitch angular velocity. It is the pitch moment of inertia. It is the aerodynamic pitching moment; It is the trajectory inclination angle; For the mass of the aircraft, and These represent thrust and lift, respectively. Represents gravitational acceleration; The pitch angle, Flight altitude; It is the pitching moment generated by the propulsion system. By introducing the fuel equivalence ratio as a state variable, the traditional equations are expanded. This state variable connects the flight state with the propulsion system, and can quantify the flight-propulsion coupling relationship to a certain extent.

[0016] By linearizing the integrated flight-thrust dynamics model shown in equation (2) near the equilibrium flight state with small perturbations, we obtain the small perturbation model: (3) in, For flight speed disturbance, Let be the trajectory tilt angle disturbance. The pitch angular velocity disturbance is... This represents the fuel equivalence ratio disturbance. This represents the elevator deflection angle disturbance. For the angle of attack disturbance, This represents the fuel equivalence ratio command disturbance. Let be the partial derivative of thrust with respect to velocity. Let be the partial derivative of thrust with respect to angle of attack. This is the partial derivative of thrust with respect to fuel equivalence ratio; Let be the partial derivative of the axial force with respect to the velocity. Let be the partial derivative of the axial force with respect to the angle of attack. Let be the partial derivative of the axial force with respect to the fuel equivalence ratio. This is the partial derivative of the axial force with respect to the elevator deflection angle; Let be the partial derivative of the normal force with respect to the velocity. Let be the partial derivative of the normal force with respect to the angle of attack. Let be the partial derivative of the normal force with respect to the fuel equivalence ratio. This is the partial derivative of the normal force with respect to the rudder deflection angle; The disturbance force is caused by the change in the projection of gravity along the axial direction. The disturbance force caused by the change in the projection of gravity onto the normal direction; This is the partial derivative of the aerodynamic pitching moment with respect to velocity. Let be the partial derivative of the thrust pitching moment with respect to velocity. Let be the partial derivative of the aerodynamic pitching moment with respect to the angle of attack. Let be the partial derivative of the thrust pitching moment with respect to the angle of attack. This is the partial derivative of the aerodynamic pitching moment with respect to the pitching angular velocity. Let be the partial derivative of the aerodynamic pitching moment with respect to the elevator deflection angle. Let be the partial derivative of the thrust pitching moment with respect to the fuel equivalence ratio. This is the additional eccentric moment disturbance term caused by gravity due to the shift of the center of mass or the change of the point of application of force. Let be the partial derivative of the fuel equivalence ratio with respect to flight speed. Let be the partial derivative of fuel equivalence ratio with respect to angle of attack. This is the partial derivative of the fuel equivalence ratio with respect to the fuel equivalence ratio command. This is an additional perturbation term in the fuel equivalence ratio channel.

[0017] Step 2: Construct a multi-input multi-output state-space model of the flight propulsion system and perform online coupling identification; The integrated flight-propulsion coupled dynamics model in step 1 is transformed into a flight-propulsion multi-input multi-output state-space model suitable for relative gain matrix (RGA) analysis, and the relative interaction between the flight control channel and the propulsion control channel is obtained through the relative gain matrix.

[0018] Based on the small perturbation model in step 1, select: (4) in, State vectors are identified for fly-push coupling.

[0019] Because the calculation focuses on the degree of flight-thrust coupling, and in order to reduce the burden of online computation, RGA only selects the physical quantities that best reflect the flight-thrust coupling effect, and focuses on the relative effects of elevator and fuel command on angle of attack and speed.

[0020] Therefore, the control input is selected as follows: (5) in, The control input disturbance vector is identified for the fly-thrust coupling.

[0021] The RGA analysis output is selected as follows: (6) in, This is the output vector for RGA analysis.

[0022] This constitutes a two-input, two-output flight thrust coupling system that transmits commands from elevator deflection and fuel equivalence ratio to angle of attack and speed.

[0023] The small perturbation model in step 1 is uniformly written as: (7) in, Sampling time, and The first The state matrix and control matrix under the current flight conditions at each sampling time. In the first The disturbance vector formed by gravity projection and other external disturbances under the current flight conditions at each sampling time.

[0024] The output relationship is as follows: (8) Formulas (7) and (8) form the multi-input multi-output state-space model of the fly-thrust engine.

[0025] Among them, the output matrix of RGA analysis for: (9) In the Each sampling time, based on the current flight condition. , and Construct the transfer function matrix: (10) in, For the first The input-output transfer function matrix of the flyback at each sampling time; For complex variables, use the Laplace transform. For the state matrix Identity matrices of the same order.

[0026] The transfer function matrix expands to: (11) in, For the first The transfer function from elevator deflection angle disturbance to angle of attack disturbance at each sampling time. For the first The transfer function from the fuel equivalence ratio command perturbation to the angle of attack perturbation at each sampling time. For the first The transfer function from elevator angle disturbance to flight speed disturbance at each sampling time. For the first The transfer function of fuel equivalence ratio from command disturbance to flight speed disturbance at each sampling time.

[0027] and These correspond to the two main control channels: elevator-angle of attack and fuel command-speed. and It corresponds to two cross-action channels: the fuel command-angle of attack channel and the elevator-speed channel.

[0028] Further calculate the steady-state gain matrix corresponding to the current operating point, as shown in formula (12): (12) in, For the first The steady-state gain matrix at each sampling time. (Symbol) This indicates taking the limit of the transfer function at zero frequency.

[0029] The steady-state gain matrix is ​​shown in equation (13): (13) in, For the first Steady-state gain of elevator-angle of attack channel at each sampling time For the first Steady-state gain of the fuel command-angle of attack cross channel at each sampling time. For the first Steady-state gain of elevator-velocity cross channel at each sampling time For the first Steady-state gain of the fuel command-speed main channel at each sampling time.

[0030] The relative gain RGA matrix is ​​calculated based on the steady-state gain matrix as shown in formula (14): (14) in, For the first The relative gain matrix at each sampling time point, denoted by " " indicates Hadamard element-wise product, For the first The inverse of the steady-state gain matrix at each sampling time.

[0031] The RGA matrix is ​​represented as follows: (15) in, For the first The relative gain of the elevator-angle of attack main channel at each sampling time. For the first The relative gain of the fuel command-angle of attack cross channel at each sampling time. For the first The relative gain of the elevator-velocity cross channel at each sampling time. For the first The relative gain of the fuel command-speed main channel at each sampling time.

[0032] Step 3: Construct the fly-thrust coupling degree based on the RGA online coupling identification results; The RGA online coupling identification results obtained in step 2 are further converted into scalar indices that can characterize the strength of flight-thrust coupling under the current flight conditions, and control parameters for subsequent coordinated control and adjustment are constructed.

[0033] To ensure the validity of the relative gain matrix calculation, the determinant of the steady-state gain matrix is ​​first defined as shown in formula (16): (16) in, For the first Steady-state gain matrix at each sampling time The determinant is used to determine whether the steady-state gain matrix has a unique inverse matrix.

[0034] For a non-singular two-input two-output steady-state gain matrix, the RGA matrix can be directly expanded as follows: (17) From the matrix structure of a two-input two-output RGA, we can obtain: (18) as well as: (19) And satisfy formula (20): (20) Then, the validity of the input-output pairing is determined using the main channel RGA elements. When formula (21) is satisfied, it is considered that the control directions of the elevator-angle of attack and fuel command-speed main channels are consistent at the current operating point, and the coupling degree can be evaluated by using RGA elements.

[0035] (twenty one) Define the relative gain parameter of the main channel: (twenty two) in, For the first The main channel relative gain parameter at each sampling time, subscript Indicates the main control channel.

[0036] Define the cross-channel relative gain parameters: (twenty three) in, For the first Cross-channel relative gain parameters at each sampling time, subscript This represents a cross-coupled channel. From formula (20): (twenty four) When there is no coupling, the ideal relative gain matrix is: (25) in, This is the RGA matrix corresponding to the ideal weakly coupled state.

[0037] Therefore, the fly-thrust coupling degree is defined as shown in formula (26): (26) in, For the first The fly-push coupling degree at each sampling moment is used to represent the degree to which the relative gain of the current main control channel deviates from the ideal value of 1.

[0038] To reduce the rapid fluctuations caused by model parameter updates and numerical calculations, the fly-thrust coupling degree is smoothed using a first-order method: (27) in, For the first The smoothed fly-push coupling at each sampling time point The coupling smoothing coefficient satisfies formula (28): (28) Further set the weak coupling threshold and strong coupling threshold : (29) Construct coordinated control coefficients based on the smoothed fly-thrust coupling degree: (30) in, For the first The flight-thrust coordination control coefficients at each sampling time, with values ​​ranging from 0 to 1, are used to determine the degree of participation of cross-coordination control in the current control cycle.

[0039] Step 4: Design an adaptive coordinated control method based on the flight-thrust coupling degree; The flight-propulsion coupling degree and its corresponding coordination control coefficient obtained in step 3 are introduced into the flight-propulsion integrated feedback controller, so that the controller can adjust the degree of participation of cross-coordination feedback online according to the coupling strength between the flight system and the propulsion system under the current flight conditions.

[0040] A baseline state feedback controller is designed based on the multi-input multi-output state-space model of the fly-propeller. The baseline feedback gain matrix is ​​expressed as: (31) in, The base propulsion integrated state feedback gain matrix is ​​used as the reference. This is the basic feedback gain matrix, used to achieve the basic control tasks of the main flight channel and the main propulsion channel. This is the cross-coordination feedback gain matrix, used to compensate for the cross-coupling between the flight system and the propulsion system.

[0041] Adjust the actual feedback gain online based on the fly-thrust coordination control coefficient: (32) in, For the first The time-varying feedback gain matrix actually used at each sampling time.

[0042] Define state tracking error: (33) in, For the first The state tracking error vector at each sampling time. In the first Each sampling time point is a reference state perturbation vector defined relative to the equilibrium operating point. For the first The actual state perturbation vector is defined relative to the equilibrium operating point at each sampling time.

[0043] The feedback control increment is: (34) in, For the first The feedback control increment generated by the adaptive coordinated feedback controller at each sampling time, subscript This indicates that the feedback control increment is generated by the coordinating controller.

[0044] The feedback control increment specifically includes: (35) in, For the first Elevator deflection disturbance at each sampling time. For the first The fuel equivalence ratio to command disturbance at each sampling time. When the actual feedback gain approaches 0, it approaches the value of 0. The system primarily utilizes elevators to control flight attitude and fuel regulation to control speed; as the coupling between flight and thrust increases, The corresponding increase in cross-coordination feedback matrix The level of participation gradually increases, enabling elevator control to better consider changes in propulsion status, while fuel control can better consider changes in flight status.

[0045] The beneficial effects of this invention are: (1) Based on the integrated longitudinal dynamics model of flight propulsion, online coupling identification is performed, retaining necessary states such as speed, trajectory tilt angle, pitch rate, angle of attack and fuel equivalence ratio, without changing the original longitudinal flight dynamics model structure for RGA calculation.

[0046] (2) Using elevator deflection angle and fuel equivalence ratio commands as inputs and angle of attack and flight speed as outputs, a well-structured two-input two-output flight-thrust coupling system is formed, which can analyze the two main control channels and the two cross-action channels respectively.

[0047] (3) Using RGA to evaluate the changes in effective input-output gain after other control loops are closed can further reflect the mutual influence between flight control and propulsion control when multiple control loops are working simultaneously, compared to analyzing only a single dynamic coefficient.

[0048] (4) In view of the fact that the two-input two-output RGA has only one independent relative gain parameter, the present invention uses the degree of deviation of the main channel relative gain from the ideal value 1 to define the fly-push coupling degree, so as to avoid repeatedly fusing multiple related RGA parameters.

[0049] (5) Further utilize the flight-propulsion coupling degree to generate coordinated control coefficients, and change the cross-feedback effect online according to the coordinated control coefficients. Reduce unnecessary cross-control when the coupling effect is weak, and improve the coordination effect between the flight and propulsion systems when the coupling effect is enhanced. Attached Figure Description

[0050] Figure 1 This is the overall system architecture flowchart; Figure 2 This is a graph showing the relative gain changes between the main channel and the cross channel of the RGA. Figure 3 This is a curve showing the change in the flight-thrust coupling degree; Figure 4 It is a curve showing the changes in the coordination control coefficient; Figure 5 This is a graph showing the angle-of-attack tracking results; Figure 6 It is a graph showing the velocity response results; Figure 7 It is a graph showing the change in the fuel equivalence ratio command.

[0051] Figure 8 It is a graph showing the change in elevator deflection angle. Detailed Implementation

[0052] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings and technical solutions.

[0053] The present invention provides an integrated adaptive control method for hypersonic vehicles under coupled identification, the basic process of which is as follows: Figure 1 As shown. The specific steps of this embodiment are as follows: Step 1: Construct an integrated flight and propulsion dynamic model for hypersonic vehicles; Based on formula (2), small perturbations were performed, resulting in the following perturbation equations. The velocity perturbation equation is: (36) Therefore, the first row of the state matrix for: (37) first row of the control matrix for: (38) The trajectory tilt angle disturbance equation is: (39) Therefore, the second row of the state matrix for: (40) and the second row of the control matrix : (41) The pitch angular velocity disturbance equation is: (42) Therefore, the third row of the state matrix for: (43) and the third row of the control matrix : (44) Since the angle of attack is further selected in the state vector, according to the integrated flight and thrust dynamics model, i.e., formula (2), the following relationship can be obtained: (45) (46) Therefore: (47) Formula (47) under small perturbation conditions: (48) In the small perturbation equation: (49) Substituting into formula (48), we get: (50) Therefore, the fourth row of the state matrix for: (51) and the fourth row of the control matrix : (52) The small perturbation relationship of fuel equivalence ratio is expressed as: (53) Therefore, the fifth row of the state matrix for: (54) and the fifth row of the control matrix : (55) Combining the above, we obtain the first... State matrix of each working point: (56) The control matrix is: (57) Therefore, at each sampling moment, a local configuration can be reconstructed based on the current flight state. and .

[0054] Step 2: Construct a multi-input multi-output state-space model of the flight propulsion system and perform online coupling identification; The RGA analysis output is: (58) The corresponding output matrix is: (59) according to , and Define the input-output transfer function matrix of the flypick: (60) It is then divided into four input-output channels: elevator-angle of attack, fuel command-angle of attack, elevator-speed, and fuel command-speed.

[0055] In practical implementation, RGA requires the steady-state gain of the above four channels, therefore, according to: (61) Substituting into formula (60), we get: (62) When the state matrix of the current working point When not singular, we have: (63) Formula (63) is equivalent to the method of calculating steady-state gain defined by the zero-frequency limit of the transfer function. In specific online calculations, the steady-state gain can be obtained directly using formula (63), thereby avoiding the need to explicitly expand the complete transfer function expression at each sampling time.

[0056] According to formula (17), the relative gains of the main channel and the cross channel are respectively: (64) (65) In actual online calculations, it is also necessary to determine the numerical validity of the calculation results. First, determine... Is it in a reversible state? Secondly, determine... Is it close to singular? When the matrix condition satisfies the preset calculation requirements and satisfies formula (66), it is considered that the two main control channels, elevator-angle of attack and fuel command-speed, have consistent control directions at the current operating point, and the coupling degree can continue to be calculated using the current RGA results. The positive relative gain criterion of the two main channels is consistent with the validity judgment of the input-output pairing of the main channel RGA elements.

[0057] (66) when When approaching singularities, RGA elements exhibiting non-finite values, or significant numerical anomalies occur in the current result, the subsequent coordinated control parameters are not directly altered based on these anomalies; instead, the RGA value from the previous valid sampling time is maintained. This approach avoids non-physical abrupt changes in relative gain, coupling, and coordinated control coefficients caused by deterioration in local model numerical conditions.

[0058] Step 3: Construct the fly-thrust coupling degree based on the RGA online coupling identification results; Formula (27) performs first-order smoothing on the original fly-thrust coupling degree to suppress instantaneous changes. In this embodiment, the following value is taken: (67) Right now: (68) Further set the weak coupling threshold and strong coupling threshold as follows: (69) (70) The corresponding coordination control coefficients are calculated as follows: (71) Calculated from coupling degree And use it to change the fundamental relationship of cross-feedback participation.

[0059] Step 4: Design an adaptive coordinated control method based on the flight-thrust coupling degree; To achieve this effect in the specific control process, the complete reference fly-thrust state feedback gain matrix is ​​first set up: (72) in, The first line corresponds to elevator deflection control, and the second line corresponds to fuel equivalence ratio control commands. Indicates the first The control input pair for the first Feedback gain for each state error.

[0060] The complete baseline feedback is divided into main control feedback and flight thrust cross-feedback. The basic feedback matrix is ​​set as follows: (73) in, The basic feedback gain from trajectory tilt angle error to elevator. The basic feedback gain from pitch angular velocity error to elevator. The basic feedback gain from angle of attack error to elevator; The basic feedback gain for speed error to fuel equivalence ratio command. This is the basic feedback gain from the actual fuel equivalence ratio error to the fuel command.

[0061] The cross-coordination feedback matrix is ​​defined as follows: (74) Right now: (75) in, The cross-feedback gain for speed error in elevator control. The cross-feedback gain for fuel equivalence ratio error in elevator control; , and These are the cross-feedback gains that participate in the adjustment of fuel equivalence ratio control commands, namely, the trajectory tilt angle, pitch rate, and angle of attack error.

[0062] Therefore, in the The actual state feedback matrix used at each sampling time Can be written as: (76) in, For the first A matrix of time points.

[0063] The feedback control increment can then be obtained based on the state tracking error.

[0064] Step 5: Simulation verification; This embodiment performs numerical simulations under a given hypersonic flight condition. The initial flight altitude in this embodiment is set to... The initial Mach number is set to The initial flight speed is obtained based on the local speed of sound at the current altitude. The total simulation time is set to... The sampling period is set to That is, throughout the entire simulation process, state updates, local model calculations, and control command refreshes are performed according to a fixed sampling period.

[0065] After initializing the parameters as described above, read the current state variables at each sampling time and recalculate the local dynamic parameters. and The current RGA, flight-thrust coupling degree, and coordinated control coefficients are then obtained, and elevator deflection angle and fuel equivalence ratio control commands are calculated. These two control inputs are then applied to the original nonlinear flight-thrust integrated dynamics model to calculate the state at the next sampling moment, thus forming a continuous closed-loop simulation process.

[0066] Depend on Figure 2 As can be seen, the relative gain of the main channel remained positive throughout the simulation, generally within the range of approximately 1.3 to 1.45. This indicates that the two main control relationships, elevator-angle of attack and fuel command-speed, did not experience any reversal in control direction during the simulation, and the selected main input-output pairing remained effective. At the same time, the relative gain of the main channel deviated significantly from 1, and the relative gain of the cross channel deviated significantly from 0. This indicates that when another control loop is working simultaneously, the effective gain of the current channel will change significantly. This demonstrates that there is a non-negligible cross interaction between the flight system and the propulsion system.

[0067] Depend on Figure 3 As can be seen, the calculated flight-thrust coupling degree mainly falls within the range of approximately 0.35 to 0.45 after the initial brief adjustment, and exhibits phased changes with flight conditions. This indicates that the flight-thrust coupling degree defined in this embodiment can reflect the changes in the degree of input-output interaction under different flight conditions, rather than being a fixed constant. The overall trend of the original coupling degree and the smoothed coupling degree after processing is basically consistent, with only slight differences in the rapidly changing region. This shows that the first-order smoothing process does not change the overall variation law of the flight-thrust coupling degree, while reducing the rapid fluctuations caused by local model updates and numerical calculations.

[0068] Depend on Figure 4 It is evident that the coordinated control coefficient and the smoothed flight-thrust coupling degree exhibit a consistent trend. When the flight-thrust coupling degree increases, the coordinated control coefficient increases accordingly; conversely, when the flight-thrust coupling degree decreases, the coordinated control coefficient decreases accordingly. During most of the flight time in this example: (77) That is, the flight-thrust cross-feedback is partially involved in most of the flight process, rather than simply using two discrete control modes of on or off.

[0069] Figures 5 to 8 This primarily reflects the closed-loop control performance of the proposed integrated flight-thrust adaptive coordinated control method. Simulation results show that the actual angle of attack can track the nominal angle of attack well after an initial brief adjustment, indicating that the system has good longitudinal attitude tracking capability. The flight speed changes continuously and smoothly throughout the simulation, without significant oscillations or abrupt changes. The fuel equivalence ratio control command and elevator deflection can be dynamically adjusted around their respective nominal values, and are corrected accordingly with changes in flight state and coupling degree. Overall, under varying flight-thrust coupling conditions, the designed control method can maintain stable angle of attack and speed responses, while ensuring continuous changes in propulsion control and control surface control, demonstrating that the coordinated control method based on RGA coupling degree adjustment of cross-feedback strength has good closed-loop control performance.

Claims

1. A hypersonic vehicle flight-thrust integrated adaptive control method under coupled identification, characterized in that, The specific steps are as follows: Step 1: Construct an integrated flight and propulsion dynamic model for hypersonic vehicles; A dynamic model capable of simultaneously describing the longitudinal motion state of the aircraft and the state changes of the propulsion system was established, and a small perturbation model was obtained by performing small perturbations, which provides a basis for the subsequent construction of the flight-propulsion coupling channel and the identification of the degree of coupling. Step 2: Construct a multi-input multi-output state-space model of the flight propulsion system and perform online coupling identification; The integrated flight-propulsion coupled dynamics model in step 1 is transformed into a flight-propulsion multi-input multi-output state-space model suitable for relative gain matrix (RGA) analysis, and the relative interaction between the flight control channel and the propulsion control channel is obtained through the relative gain matrix. Step 3: Construct the fly-thrust coupling degree based on the RGA online coupling identification results; The RGA online coupling identification results obtained in step 2 are further converted into scalar indices that can characterize the strength of flight-thrust coupling under the current flight conditions, and control parameters for subsequent coordinated control and adjustment are constructed. Step 4: Design an adaptive coordinated control method based on the flight-thrust coupling degree; The flight-propulsion coupling degree and its corresponding coordination control coefficient obtained in step 3 are introduced into the flight-propulsion integrated feedback controller, so that the controller can adjust the degree of participation of cross-coordination feedback online according to the coupling strength between the flight system and the propulsion system under the current flight conditions.

2. The hypersonic vehicle flight-thrust integrated adaptive control method under coupled identification according to claim 1, characterized in that, Step 1 is as follows: In order to describe the above two-way relationship in a unified model, the fuel equivalence ratio is introduced as a propulsion system state variable into the longitudinal dynamics equation of the aircraft. Fuel equivalence ratio is expressed as: (1) in, Fuel equivalence ratio, For flight speed, For the angle of attack, For fuel equivalence ratio command, This indicates the nonlinear relationship between fuel equivalence ratio and speed, angle of attack, and fuel equivalence ratio commands; Ignoring the influence of lateral parameters, a force analysis is performed on the longitudinal channel of the hypersonic vehicle to establish an integrated flight-thrust dynamic model: (2) Among them, the superscript " " represents the first derivative, It is the pitch angular velocity. It is the pitch moment of inertia. It is the aerodynamic pitching moment; It is the trajectory inclination angle; For the mass of the aircraft, and These represent thrust and lift, respectively. Represents gravitational acceleration; The pitch angle, Flight altitude; It is the pitching moment generated by the propulsion system; by introducing the fuel equivalence ratio as a state variable, the traditional equations are expanded. This state variable connects the flight state with the propulsion system and can quantify the flight-propulsion coupling relationship to a certain extent. The flight-thrust integrated dynamics model shown in formula (2) is linearized with small perturbations near the equilibrium flight state to obtain the small perturbation model.

3. The hypersonic vehicle flight-thrust integrated adaptive control method under coupled identification according to claim 2, characterized in that, The small perturbation model is as follows: (3) in, For flight speed disturbance, Let be the trajectory tilt angle disturbance. The pitch angular velocity disturbance is... This represents the fuel equivalence ratio disturbance. This represents the elevator deflection angle disturbance. For the angle of attack disturbance, This represents the fuel equivalence ratio command disturbance. Let be the partial derivative of thrust with respect to velocity. Let be the partial derivative of thrust with respect to angle of attack. This is the partial derivative of thrust with respect to fuel equivalence ratio; Let be the partial derivative of the axial force with respect to the velocity. Let be the partial derivative of the axial force with respect to the angle of attack. Let be the partial derivative of the axial force with respect to the fuel equivalence ratio. This is the partial derivative of the axial force with respect to the elevator deflection angle; Let be the partial derivative of the normal force with respect to the velocity. Let be the partial derivative of the normal force with respect to the angle of attack. Let be the partial derivative of the normal force with respect to the fuel equivalence ratio. This is the partial derivative of the normal force with respect to the rudder deflection angle; The disturbance force is caused by the change in the projection of gravity along the axial direction. The disturbance force caused by the change in the projection of gravity onto the normal direction; This is the partial derivative of the aerodynamic pitching moment with respect to velocity. Let be the partial derivative of the thrust pitching moment with respect to velocity. Let be the partial derivative of the aerodynamic pitching moment with respect to the angle of attack. Let be the partial derivative of the thrust pitching moment with respect to the angle of attack. This is the partial derivative of the aerodynamic pitching moment with respect to the pitching angular velocity. Let be the partial derivative of the aerodynamic pitching moment with respect to the elevator deflection angle. Let be the partial derivative of the thrust pitching moment with respect to the fuel equivalence ratio. This is the additional eccentric moment disturbance term caused by gravity due to the shift of the center of mass or the change of the point of application of force. Let be the partial derivative of the fuel equivalence ratio with respect to flight speed. Let be the partial derivative of fuel equivalence ratio with respect to angle of attack. This is the partial derivative of the fuel equivalence ratio with respect to the fuel equivalence ratio command. This is an additional perturbation term in the fuel equivalence ratio channel.

4. The hypersonic vehicle flight-thrust integrated adaptive control method under coupled identification according to claim 1, characterized in that, Step 2 is as follows: Based on the small perturbation model in step 1, select: (4) in, Identify the state vector for the fly-push coupling; Therefore, the control input is selected as follows: (5) in, The control input disturbance vector for the fly-thrust coupling identification; The RGA analysis output is selected as follows: (6) in, The output vector is used for RGA analysis; This constitutes a two-input two-output flight thrust coupling system that transmits elevator deflection and fuel equivalence ratio commands to angle of attack and speed. The small perturbation model in step 1 is uniformly written as: (7) in, Sampling time, and The first The state matrix and control matrix under the current flight conditions at each sampling time. In the first The disturbance vector formed by gravity projection and other external disturbances under the current flight conditions at each sampling time; The output relationship is as follows: (8) Formulas (7) and (8) form the multi-input multi-output state-space model of the fly-thrust engine; Among them, the output matrix of RGA analysis for: (9) In the Each sampling time, based on the current flight condition. , and Construct the transfer function matrix: (10) in, For the first The input-output transfer function matrix of the flyback at each sampling time; For complex variables, use the Laplace transform. For the state matrix An identity matrix of the same order; The transfer function matrix expands to: (11) in, For the first The transfer function from elevator deflection angle disturbance to angle of attack disturbance at each sampling time. For the first The transfer function from the fuel equivalence ratio command perturbation to the angle of attack perturbation at each sampling time. For the first The transfer function from elevator deflection disturbance to flight speed disturbance at each sampling time. For the first The transfer function of fuel equivalence ratio from command disturbance to flight speed disturbance at each sampling time; and These correspond to the two main control channels: elevator-angle of attack and fuel command-speed. and It corresponds to two cross-acting channels: fuel command-angle of attack and elevator-speed channel; Further calculate the steady-state gain matrix corresponding to the current operating point, as shown in formula (12): (12) in, For the first The steady-state gain matrix at each sampling time; symbol This indicates taking the limit of the transfer function at zero frequency; The steady-state gain matrix is ​​shown in equation (13): (13) in, For the first Steady-state gain of elevator-angle of attack channel at each sampling time For the first Steady-state gain of the fuel command-angle of attack cross channel at each sampling time. For the first Steady-state gain of elevator-velocity cross channel at each sampling time For the first Steady-state gain of the fuel command-speed main channel at each sampling time; The relative gain RGA matrix is ​​calculated based on the steady-state gain matrix as shown in formula (14): (14) in, For the first The relative gain matrix at each sampling time point, denoted by " " indicates Hadamard element-wise product, For the first The inverse of the steady-state gain matrix at each sampling time; The RGA matrix is ​​represented as follows: (15) in, For the first The relative gain of the elevator-angle of attack main channel at each sampling time. For the first The relative gain of the fuel command-angle of attack cross channel at each sampling time. For the first The relative gain of the elevator-velocity cross channel at each sampling time. For the first The relative gain of the fuel command-speed main channel at each sampling time.

5. The hypersonic vehicle flight-thrust integrated adaptive control method under coupled identification according to claim 1, characterized in that, Step 3 is as follows: To ensure the validity of the relative gain matrix calculation, the determinant of the steady-state gain matrix is ​​first defined as shown in formula (16): (16) in, For the first Steady-state gain matrix at each sampling time The determinant is used to determine whether the steady-state gain matrix has a unique inverse matrix; For a non-singular two-input two-output steady-state gain matrix, the RGA matrix can be directly expanded as follows: (17) From the matrix structure of a two-input two-output RGA, we get: (18) as well as: (19) And satisfy formula (20): (20) Then, the RGA elements of the main channel are used to determine the effectiveness of the input-output pairing. When the formula (21) is satisfied, it is considered that the control directions of the elevator-angle of attack and fuel command-speed of the two main channels are consistent at the current working point, and the RGA elements can be used to evaluate the degree of coupling. (21) Define the relative gain parameter of the main channel: (22) in, For the first The main channel relative gain parameter at each sampling time, subscript Indicates the main control channel; Define the cross-channel relative gain parameters: (23) in, For the first Cross-channel relative gain parameters at each sampling time, subscript Represents the cross-coupled channel; obtained from formula (20): (24) When there is no coupling, the ideal relative gain matrix is: (25) in, The RGA matrix corresponding to the ideal weakly coupled state; Therefore, the fly-thrust coupling degree is defined as shown in formula (26): (26) in, For the first The fly-push coupling degree at each sampling moment is used to represent the degree to which the relative gain of the current main control channel deviates from the ideal value of 1; To reduce the rapid fluctuations caused by model parameter updates and numerical calculations, the fly-thrust coupling degree is smoothed using a first-order method: (27) in, For the first The smoothed fly-push coupling at each sampling time point The coupling smoothing coefficient satisfies formula (28): (28) Further set the weak coupling threshold and strong coupling threshold : (29) Construct coordinated control coefficients based on the smoothed fly-thrust coupling degree: (30) in, For the first The flight-thrust coordination control coefficients at each sampling time, with values ​​ranging from 0 to 1, are used to determine the degree of participation of cross-coordination control in the current control cycle.

6. The hypersonic vehicle flight-thrust integrated adaptive control method under coupled identification according to claim 1, characterized in that, Step 4 is as follows: A baseline state feedback controller is designed based on the multi-input multi-output state-space model of the fly-propeller. The baseline feedback gain matrix is ​​expressed as: (31) in, The base propulsion integrated state feedback gain matrix is ​​used as the reference. This is the basic feedback gain matrix, used to achieve the basic control tasks of the main flight channel and the main propulsion channel. This is the cross-coordination feedback gain matrix, used to compensate for the cross-coupling between the flight system and the propulsion system; Adjust the actual feedback gain online based on the fly-thrust coordination control coefficient: (32) in, For the first The time-varying feedback gain matrix actually used at each sampling time; Define state tracking error: (33) in, For the first The state tracking error vector at each sampling time. In the first Each sampling time point is a reference state perturbation vector defined relative to the equilibrium operating point. For the first The actual state perturbation vector defined at each sampling time relative to the equilibrium operating point; The feedback control increment is: (34) in, For the first The feedback control increment generated by the adaptive coordinated feedback controller at each sampling time, subscript This indicates that the feedback control increment is generated by the coordinating controller; The feedback control increment specifically includes: (35) in, For the first Elevator deflection disturbance at each sampling time. For the first The fuel equivalence ratio to command disturbance at each sampling time; when When the actual feedback gain approaches 0, it approaches the value of 0. The system uses elevators to control flight attitude and fuel regulation to control speed; as the coupling between flight and thrust increases, The corresponding increase in cross-coordination feedback matrix The level of participation gradually increases, enabling elevator control to better consider changes in propulsion status, while fuel control can better consider changes in flight status.

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