A composite coaxial high-speed helicopter flight / turboshaft engine integrated control system

Abstract

The present invention discloses a hybrid coaxial high-speed helicopter flight / turboshaft engine integrated control system, comprising the following steps: based on control mechanism parameters output by the flight control system, a hybrid coaxial high-speed helicopter fuzzy torque prediction model outputs a flight torque lead prediction value for the hybrid coaxial high-speed helicopter system; the flight torque lead prediction value is superimposed with a variable transmission ratio proportional coefficient and then input into a turboshaft engine system identification model to obtain a fuel prediction value, which is further superimposed with the output of the engine control system to obtain the fuel input of the turboshaft engine system; the flight torque lead prediction value error is calculated, and if the error value is greater than a threshold, the fuzzy torque prediction model is updated using flight state parameters of the hybrid coaxial high-speed helicopter system; the relative error value of the current power turbine speed is calculated, and if the relative error value is greater than a threshold, the turboshaft engine system identification model is updated using a recursive least squares algorithm based on the real-time and historical torque inputs and power turbine speed of the turboshaft engine system. The present invention enhances the stability of the hybrid coaxial high-speed helicopter flight / turboshaft engine integrated control system, improves the response speed of the turboshaft engine, and reduces overshoot and droop of the power turbine speed, while taking into account the constant speed control target of the turboshaft engine.

Description

Technical Field

[0001] The present invention relates to a composite coaxial high-speed helicopter flight / turboshaft engine integrated control method, belonging to the technical field of system control and simulation in aerospace propulsion theory and engineering. Background Art

[0002] Compound coaxial high-speed helicopters are a typical configuration for the next generation of high-speed helicopters, boasting enhanced offensive capabilities, maneuverability, and combat capabilities compared to conventional single-rotor helicopters. The most recent compound coaxial high-speed helicopters to complete flight tests in the United States include the X-2 high-speed attack helicopter and the S-97 Raider high-speed helicopter, with the SB>1 DEFIANT military helicopter currently under development. Clearly, compound coaxial high-speed helicopters will become key combat aircraft of the future.

[0003] The compound coaxial high-speed helicopter itself is coupled to the turboshaft engine. Specifically, the power turbine output speed transmits the current main rotor speed and tail propeller speed to the coaxial high-speed helicopter system through the transmission system. The required torque generated by the coaxial high-speed helicopter system is then transmitted to the turboshaft engine through the transmission system. When the coaxial high-speed helicopter experiences a disturbance, the required torque changes, which in turn causes the speed generated by the turboshaft engine to change. This, in turn, causes the speed of the helicopter's main rotor and tail propeller to change through the transmission system, which in turn affects the helicopter. Similarly, when the engine experiences a disturbance, the disturbance is also transmitted to the helicopter and then back to the engine itself. To achieve a constant turboshaft engine speed during flight, the integrated flight / turboshaft engine control system of the compound coaxial high-speed helicopter is a key issue in the research of this model.

[0004] Currently, research on helicopter / engine integrated control systems focuses solely on conventional single-rotor helicopters or variable-rotor speed helicopters, and has not specifically targeted compound coaxial high-speed helicopters. Conventional helicopter / engine integrated control systems utilize a cascaded PID control structure based on collective pitch feedforward. However, for compound coaxial high-speed helicopters, the required torque of the tail propeller also causes the speed to change. Furthermore, since compound coaxial high-speed helicopters have multiple flight modes, including fixed-wing, transition, and helicopter modes, the torque generated in these different flight modes can also vary significantly. Therefore, a new helicopter / engine integrated control scheme, tailored to the flight characteristics of compound coaxial high-speed helicopters, is needed to ensure that the turboshaft engine maintains a constant speed during flight, meeting high-quality flight requirements. Summary of the Invention

[0005] The present invention provides a composite coaxial high-speed helicopter flight / turboshaft engine integrated control system, which enhances the stability of the coaxial high-speed helicopter / turboshaft engine system, improves the response speed of the turboshaft engine, reduces the overshoot and droop of the power turboshaft speed, and solves the problems described in the above background technology.

[0006] The technical solution adopted by the present invention is a composite coaxial high-speed helicopter flight / turboshaft engine integrated control system, which includes: a coupling system and a feedforward compensation control system;

[0007] The coupling system includes: a compound coaxial high-speed helicopter system, a turboshaft engine system, a variable transmission ratio transmission system, a flight control system, an engine control system, and an atmospheric parameter acquisition system; the feedforward compensation control system includes: a compound coaxial high-speed helicopter fuzzy torque prediction model, a turboshaft engine system identification model, a fuzzy torque prediction model update module, a system identification model update module, and a variable transmission ratio proportional coefficient calculation module;

[0008] The flight instructions of the aircraft and the feedback control results of the compound coaxial high-speed helicopter system are transmitted to the flight control system together. The flight control system outputs the control mechanism parameters to the compound coaxial high-speed helicopter system and the compound coaxial high-speed helicopter fuzzy torque prediction model according to the input data. The compound coaxial high-speed helicopter fuzzy torque prediction model calculates the torque prediction value that the power system needs to provide under the control mechanism parameters, and inputs the torque to the variable transmission ratio proportional coefficient calculation module and the fuzzy torque prediction model update module; the variable transmission ratio proportional coefficient calculation module calculates the transmission proportional coefficient and transmits it to the turboshaft engine system identification model; the fuzzy torque prediction model update module calculates the error according to the torque prediction value, the flight state parameters provided by the compound coaxial high-speed helicopter system, and the torque data output by the variable transmission ratio transmission system. If the error exceeds the set error threshold, the parameters of the compound coaxial high-speed helicopter fuzzy torque prediction model are updated; the compound coaxial high-speed helicopter fuzzy torque prediction model is used to update the parameters of the fuzzy torque prediction model. The high-speed helicopter system receives data from the atmospheric parameter acquisition system and calculates the torque required by the rotor according to the control mechanism parameters; the torque is transmitted to the fuzzy torque prediction model update module; the composite coaxial high-speed helicopter system and the turboshaft engine system are mechanically connected through a variable transmission ratio transmission system; the turboshaft engine system outputs real-time data and historical data of the power turbine speed and real-time data and historical data of the torque data to the system identification model update module, and the system identification model update module calculates the error between the current torque and speed and the torque and speed to be achieved, and compares the error with the set threshold. If it is greater than the threshold, this will send information to the turboshaft engine system identification model to update the parameters of the turboshaft engine system identification model; the turboshaft engine system receives atmospheric data and fuel data collected by the atmospheric parameter acquisition system; the fuel data is the weighted result of the fuel supply data output by the engine control system and the fuel prediction value output by the turboshaft engine system identification model.

[0009] Specifically, the fuzzy torque prediction model of the composite coaxial high-speed helicopter is:

[0010]

[0011] Among them, X is the flight state parameter vector, including three-axis speed, angular velocity, attitude angle and flight altitude; U is the control mechanism parameter, including main rotor collective pitch, differential collective pitch, longitudinal cyclic pitch, lateral cyclic pitch, elevator angle, rudder angle, tail propeller collective pitch; Y is the rotor required torque advance prediction value, including the main rotor and tail propeller required torque prediction values; F i is the membership function when the forward speed is equal to im / s; A i ,B i ,C i ,D i They are state matrix, control matrix, output matrix and transfer matrix respectively. Specifically, the membership function selects trigonometric function; Ai ,B i ,C i ,D i It is obtained by linearizing and calculating the compound coaxial high-speed helicopter system offline, with X as the state quantity, Y as the output quantity, and U as the input quantity.

[0012] Specifically, the turboshaft engine system identification model is:

[0013]

[0014] Among them, y(t), u1(t), u2(t) are the output item power turbine speed at time t, input item 1 torque input, input item 2 fuel input; n a ,n b1 ,n b2 is the order of the model; a1, b 10 , b 20 , Specifically, the order of the model is selected by the Bayesian Information Criterion (BIC), and the order n a ,n b1 ,n b2 They are 3, 4, and 2 respectively. The system identification model parameters are all obtained through offline calculation.

[0015] Specifically, the thresholds α and β are set to 10% and 1.5% respectively.

[0016] Specifically, the system identification model update module will use the recursive least squares method to update the parameters of the turboshaft engine system identification model once for a duration of T based on the real-time and historical torque inputs and power turbine speed of the turboshaft engine system; when the update is performed, the original parameters of the system identification model will continue to be used to calculate the fuel prediction value, and will be replaced with the updated parameters after the update is completed.

[0017] Specifically, the update time T is set to 10s.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] The present invention designs a composite coaxial high-speed helicopter flight / turboshaft engine integrated control system and method, taking into account the constant speed control target of the turboshaft engine. The method has a simple and effective structure, does not require manual parameter adjustment, enhances the stability of the coaxial high-speed helicopter / turboshaft engine system, improves the response speed of the turboshaft engine, and reduces the overshoot and droop of the power turboshaft speed.

[0020] The present invention further constructs a composite coaxial high-speed helicopter fuzzy torque prediction model based on fuzzy state space and a turboshaft engine system identification model based on the ARX model, effectively enabling advanced prediction of helicopter torque and fuel requirements. Furthermore, the present invention also incorporates a fuzzy torque prediction model update module and a system identification model update module, enabling automatic, real-time updates based on different flight scenarios and conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a specific structural block diagram of a composite coaxial high-speed helicopter flight / turboshaft engine integrated control system of the present invention.

[0022] Figure 2 This is a comparison chart of the forward flight speed change curves of a compound coaxial high-speed helicopter.

[0023] Figure 3 This is a comparison chart of the altitude change curves of compound coaxial high-speed helicopters.

[0024] Figure 4 It is a comparison chart of the relative speed change curves of the turboshaft engine power turbine.

[0025] Figure 5 This is a comparison chart of the instantaneous fuel quantity change curve of the turboshaft engine.

[0026] Figure 6 This is a comparison chart of the change curves of the main rotor collective pitch and tail propeller collective pitch of a compound coaxial high-speed helicopter.

[0027] Figure 7 This is a comparison chart of the torque lead prediction value and the actual value curve of the compound coaxial high-speed helicopter rotor.

[0028] Figure 8 It is a comparison chart of the parameter change curves of the turboshaft engine system identification model update. DETAILED DESCRIPTION

[0029] The technical solution of the present invention is described in detail below through a specific embodiment in conjunction with the accompanying drawings:

[0030] like Figure 1 As shown, the hybrid coaxial high-speed helicopter flight / turboshaft engine integrated control system in this embodiment consists of a coupling system and a feedforward compensation control system. The coupling system comprises the hybrid coaxial high-speed helicopter system, the turboshaft engine system, the variable transmission ratio transmission system, the flight control system, the engine control system, and atmospheric parameters; the feedforward compensation control system comprises the hybrid coaxial high-speed helicopter fuzzy torque prediction model, the turboshaft engine system identification model, the fuzzy torque prediction model update module, the system identification model update module, and the variable transmission ratio proportional coefficient.

[0031] Specifically, in a single-step simulation, the fuzzy torque prediction model of the compound coaxial high-speed helicopter outputs the required torque advance prediction value of the compound coaxial high-speed helicopter system according to the control mechanism parameters output by the flight control system; the required torque advance prediction value error is calculated, and if the error value is greater than the threshold α, the fuzzy torque prediction model is updated using the flight state parameters of the compound coaxial high-speed helicopter system; the required torque advance prediction value is superimposed with the variable transmission ratio proportional coefficient and input into the turboshaft engine system identification model to obtain the fuel prediction value, and further superimposed with the output of the engine control system to obtain the fuel input of the turboshaft engine system; the relative error value of the current power turbine speed is calculated, and if the relative error value is greater than the threshold β, the recursive least squares (RLS) algorithm is used to update the parameters of the turboshaft engine system identification model according to the real-time and historical torque inputs and power turbine speed of the turboshaft engine system.

[0032] The following is a further detailed description of each of the main parts:

[0033] 1) Fuzzy torque prediction model for composite coaxial high-speed helicopter and fuzzy torque prediction model update module

[0034] The fuzzy torque prediction model of the composite coaxial high-speed helicopter is generated based on the TS fuzzy linearization state space, as shown in the following formula:

[0035]

[0036] Where X is the flight state parameter vector, including three-axis velocity, angular velocity, attitude angle and flight altitude; U is the control mechanism parameter, including main rotor collective pitch, differential collective pitch, longitudinal cyclic pitch, lateral cyclic pitch, elevator deflection angle, rudder deflection angle, tail propeller collective pitch; Y = [Q MRp ;Q PRp ] is the advance prediction value of the rotor torque required, including the torque prediction value required by the main rotor and tail propeller; F i is the membership function when the forward velocity is equal to im / s; A i ,B i ,C i ,D i They are state matrix, control matrix, output matrix, and transfer matrix respectively. Specifically, X is provided by the initial state of the composite coaxial high-speed helicopter system or the fuzzy torque prediction model update module, and U is provided by the control mechanism parameters output by the flight control system; A i ,B i ,C i ,D iX is the state quantity, Y is the output quantity, and U is the input quantity. It is obtained by linearizing the composite coaxial high-speed helicopter system offline. The membership function selects trigonometric function. The membership function and membership space are as follows:

[0037]

[0038] Furthermore, the fuzzy torque prediction model of the composite coaxial high-speed helicopter is updated in real time through the fuzzy torque prediction model update module. The specific update logic is: calculate the required torque advance prediction value error. If the error value is greater than the threshold α, the current flight state parameters of the composite coaxial high-speed helicopter system (including three-axis speed, angular velocity, Euler angle and flight altitude) are input as X into the fuzzy torque prediction model. Specifically, the error is calculated as follows:

[0039]

[0040] Where d is the calculated error value; Q MRr ,Q MRp ,Q PRr ,Q PRp ,Q IN They are respectively the true value of main rotor torque, the predicted value of main rotor torque, the true value of tail thrust torque, the predicted value of tail thrust torque, and the true value of engine torque input; ratio MR ,ratio PR are the variable reduction ratio coefficients of the main rotor and the tail propeller respectively.

[0041] Specifically, the setting of the threshold α is extremely important. A too large value will reduce the model's prediction accuracy and lead to inaccurate torque lead predictions. A too small value will increase the model's computational complexity and burden the hardware system. After multiple simulation experiments, the threshold α was set to 10%.

[0042] Furthermore, the output of the fuzzy torque prediction model of the composite coaxial high-speed helicopter is Y=[Q MRp ,Q PRp ] T After changing the transmission ratio coefficient, the torque input advance prediction value is obtained and input into the turboshaft engine system identification model. Specifically, the torque input advance prediction value Q INp The calculation formula is as follows:

[0043] Q INp =[ratio MR ,ratio PR ][Q MRp ,Q PRp ] T

[0044] 2) Turboshaft engine system identification model and system identification model update module

[0045] The turboshaft engine system identification model adopts the DISO ARX system identification model, and its general form is as follows:

[0046]

[0047] Among them, y(t), u1(t), u2(t) are the output item power turbine speed at time t, input item 1 torque input, input item 2 fuel input; n a ,n b1 ,n b2 is the order of the model; a1, b 10 , b 20 , The model parameters are identified by the system. Specifically, the order of the model is selected by the Bayesian Information Criterion (BIC), which is calculated as follows:

[0048]

[0049] Where, y(t), are the actual output of the power turbine speed in the training data and the predicted output of the power turbine speed of the system identification model; N is the number of data points used in the training model.

[0050] Specifically, the model order with the smallest BIC value is selected, and the order n a ,n b1 ,n b2 They are 3, 4, and 2 respectively; the turboshaft engine system identification model parameters are obtained through offline calculation.

[0051] Furthermore, when the turboshaft engine system identification model is used for prediction, the calculation formula is as follows:

[0052]

[0053] Among them, y c is the constant speed value of the turboshaft engine; u1(t), u1(t-1), ..., u1(t-nb1) are the current simulation step, the previous simulation step, ..., the previous n simulation steps respectively. b1 The required torque advance prediction output by the fuzzy torque prediction model of the composite coaxial high-speed helicopter in the simulation step is the torque advance prediction input value obtained by superimposing the variable transmission ratio proportional coefficient; u2(t-1),…,u2(tn b2 ) are respectively the first simulation step, ..., the first n b2 The fuel prediction value output by the turboshaft engine system identification model during the simulation step.

[0054] Furthermore, the turboshaft engine system identification model is updated in real time via the system identification model update module. Specifically, the relative error value of the current power turbine speed is calculated. If the relative error value is greater than a threshold value β, an update of duration T is performed: the recursive least squares (RLS) algorithm is used to update the parameters of the turboshaft engine system identification model based on the real-time and historical torque inputs and power turbine speed of the turboshaft engine system. When the update is executed, the original parameters of the system identification model continue to be used to calculate the fuel prediction value, and after the update is completed, the updated parameters are replaced (the update does not change the model order).

[0055] Specifically, the setting of the threshold β is extremely important. A value that is too large will result in reduced prediction accuracy and inaccurate fuel predictions. A value that is too small will lead to frequent updates of the system identification model, increasing the model's computational complexity and burdening the hardware system. After multiple simulation experiments, the threshold β was set to 1.5%.

[0056] Specifically, the setting of time duration T will affect the model's prediction performance. If it is too long, the system will not update in a timely manner and will increase the burden on the hardware system. If it is too short, the model parameters will not converge and the update will not be effective. After multiple simulation experiments, time duration T was set to 10 seconds.

[0057] Specifically, the RLS algorithm update parameter formula is as follows:

[0058]

[0059] Among them, θ(t) is the row vector composed of the system identification model parameters; P(t-1) is the covariance matrix of the previous simulation step, with an initial value of δI, δ is a large positive number that affects the parameter convergence speed, specifically 1000; φ(t) is the regression vector containing the real input and output historical data of the turboshaft engine; λ is the forgetting factor, specifically 1, indicating that the sensitivity to new and old data is the same; y(t) is the actual output value of the power turbine speed in the current simulation step.

[0060] In order to verify the effect of the above technical solution, a simulation test of the effect of the composite coaxial high-speed helicopter flight / turboshaft engine integrated control system of the present invention was carried out under variable flight conditions. c Set to 1000m, the reference instruction NP of the relative speed of the power turbine is c Set to 100%, the helicopter forward flight speed command V xc like Figure 2 Specifically, when t=5s, V xc From 0m / s to 4m / s 2 The acceleration is uniformly accelerated to 120m / s at 35s; when t is between 35-40s, V xc Maintain 120m / s; then -4m / s2 The acceleration is decelerated to 120m / s at 70s and maintained until the end of the simulation. The specific simulation results are as follows Figures 2 to 8 As shown in Figure 2, the comparative simulation only includes the coupled system and does not use the feedforward compensation control system.

[0061] Depend on Figure 2 、 3 It can be seen that this solution can improve the flight stability of the composite coaxial high-speed helicopter, increase the response speed, and maintain a more stable altitude. Figure 4 、 5 As can be seen, this scheme significantly reduces turboshaft engine speed overshoot and droop, while also improving response speed to a certain extent. The instantaneous fuel output in this scheme is more advanced than that without the integrated control method. This is because the composite coaxial high-speed helicopter fuzzy torque prediction model in this scheme makes an advance prediction of the rotor torque required, and the turboshaft engine system identification model makes an advance prediction of the fuel input. As a result, the engine speed is more stable and the instantaneous fuel input is more advanced.

[0062] Figure 7 The actual value of the helicopter rotor torque required obtained by simulation using this technical solution and the required torque advance prediction value output by the composite coaxial high-speed helicopter fuzzy torque prediction model. Figure 7 It can be seen that the composite coaxial high-speed helicopter fuzzy torque prediction model and fuzzy torque prediction model update module provided in this solution can accurately predict the required rotor torque. Furthermore, the fuzzy torque prediction model update module determines whether an update is needed based on the error between the actual required torque value and the predicted value. If the error gradually increases to a threshold value α over time (e.g., at t≈17, 20, or 70 seconds), the update module automatically updates the fuzzy torque prediction model to restore its prediction accuracy.

[0063] Figure 8 This is a curve diagram of the model parameter changes during the first update of the system identification model update module when simulating using this technical solution. The diagram only contains the parameters of input item 1 torque input u1(t), that is, b 10 ,b 11 ,b 12 ,b 13 ,b 14 Changes over time. Specifically, when the relative error value of the power turbine speed is greater than the threshold β (e.g., t≈13.5, 40s), a parameter update of 10s will be performed. During this process, there are 16286 simulation steps or iterations. During the update process, the original system identification model parameters are continued to be used for fuel prediction, and the new parameters are replaced after the update is completed. Figure 4 、 7,8, we can see that this system has the property of self-updating and can adapt to different types of flight environments and flight states.

Claims

1. A composite coaxial high-speed helicopter flight / turboshaft engine integrated control system, the system comprising: Coupled systems and feedforward compensation control systems; The coupling system includes: a compound coaxial high-speed helicopter system, a turboshaft engine system, a variable transmission ratio transmission system, a flight control system, an engine control system, and an atmospheric parameter acquisition system; the feedforward compensation control system includes: a compound coaxial high-speed helicopter fuzzy torque prediction model, a turboshaft engine system identification model, a fuzzy torque prediction model update module, a system identification model update module, and a variable transmission ratio proportional coefficient calculation module; The flight instructions of the aircraft and the feedback control results of the compound coaxial high-speed helicopter system are transmitted to the flight control system together. The flight control system outputs the control mechanism parameters to the compound coaxial high-speed helicopter system and the compound coaxial high-speed helicopter fuzzy torque prediction model according to the input data. The compound coaxial high-speed helicopter fuzzy torque prediction model calculates the torque prediction value that the power system needs to provide under the control mechanism parameters, and inputs the torque to the variable transmission ratio proportional coefficient calculation module and the fuzzy torque prediction model update module; the variable transmission ratio proportional coefficient calculation module calculates the transmission proportional coefficient and transmits it to the turboshaft engine system identification model; the fuzzy torque prediction model update module calculates the error according to the torque prediction value, the flight state parameters provided by the compound coaxial high-speed helicopter system, and the torque data output by the variable transmission ratio transmission system. If the error exceeds the set error threshold α, the parameters of the compound coaxial high-speed helicopter fuzzy torque prediction model are updated; the compound coaxial high-speed helicopter fuzzy torque prediction model is used to update the parameters of the fuzzy torque prediction model. The high-speed helicopter system receives data from the atmospheric parameter acquisition system and calculates the torque required by the rotor based on the control mechanism parameters; the torque is transmitted to the fuzzy torque prediction model update module; the composite coaxial high-speed helicopter system and the turboshaft engine system are mechanically connected through a variable transmission ratio transmission system; the turboshaft engine system outputs real-time data and historical data of the power turbine speed and real-time data and historical data of the torque data to the system identification model update module, and the system identification model update module calculates the error between the current torque and speed and the torque and speed to be achieved, and compares the error with the set threshold value. If it is greater than the threshold value β, this will send information to the turboshaft engine system identification model to update the parameters of the turboshaft engine system identification model; the turboshaft engine system receives atmospheric data and fuel data collected by the atmospheric parameter acquisition system; the fuel data is the weighted result of the fuel supply data output by the engine control system and the fuel prediction value output by the turboshaft engine system identification model.

2. A composite coaxial high-speed helicopter flight / turboshaft engine integrated control system as claimed in claim 1, characterized in that: The fuzzy torque prediction model of the composite coaxial high-speed helicopter is: Among them, X is the flight state parameter vector, including three-axis speed, angular velocity, attitude angle and flight altitude; U is the control mechanism parameter, including main rotor collective pitch, differential collective pitch, longitudinal cyclic pitch, lateral cyclic pitch, elevator angle, rudder angle, tail propeller collective pitch; Y is the rotor required torque advance prediction value, including the main rotor and tail propeller required torque prediction values; F i is the membership function when the forward speed is equal to im / s; A i ,B i ,C i ,D i They are state matrix, control matrix, output matrix and transfer matrix respectively.

3. A composite coaxial high-speed helicopter flight / turboshaft engine integrated control system as claimed in claim 1, characterized in that: The turboshaft engine system identification model is: Among them, y(t), u1(t), u2(t) are the output item power turbine speed at time t, input item 1 torque input, input item 2 fuel input; n a ,n b1 ,n b2 is the order of the model; Identify model parameters for the system.

4. A composite coaxial high-speed helicopter flight / turboshaft engine integrated control system as claimed in claim 1, characterized in that: The thresholds α and β are set to 10% and 1.5% respectively.

5. The composite coaxial high-speed helicopter flight / turboshaft engine integrated control system according to claim 2, characterized in that: The membership function selects trigonometric function; A i ,B i ,C i ,D i It takes X as the state quantity, Y as the output quantity, and U as the input quantity, and is obtained by performing linear offline calculation on the compound coaxial high-speed helicopter system.

6. A composite coaxial high-speed helicopter flight / turboshaft engine integrated control system as claimed in claim 3, characterized in that: The order of the model is selected by the Bayesian information criterion, and the order n a ,n b1 ,n b2 They are 3, 4, and 2 respectively; the system identification model parameters are all obtained through offline calculation.

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