Multi-mode simulation method for flight environment simulation control system

Abstract

The invention provides a flight environment simulation control system multi-mode simulation method, and belongs to the technical field of aero-engines, and the method comprises the steps: selecting a full-digital simulation experiment or a semi-physical simulation experiment, a running object model and a control model, and the control model comprises a feedforward controller, an active disturbance rejection controller and an extended state observer; the feedforward controller calculates a feedforward control quantity according to an engine speed change rate output by the object model, the extended state observer estimates the total disturbance of the system to obtain an estimated value, the estimated value is fed back to the active anti-disturbance controller, and an initial control quantity is obtained through calculation; superposing the initial control quantity with the feedforward control quantity and the estimated value to obtain a final control quantity, and inputting the final control quantity into a hydraulic regulating valve flow model in an object model; the control parameters of the control model are set through a full-digital simulation experiment, and the set control parameters are optimized through a semi-physical simulation experiment, so that the simulation confidence and efficiency are improved, and the cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aero-engines, and particularly relates to a multi-mode simulation method for a flight environment simulation control system. BACKGROUND

[0002] With the rapid development of simulation technology and artificial intelligence technology, the flight environment simulation system in the field of aero-engine flight environment simulation is facing severe challenges such as rapid development of intelligent control technology and improvement of simulation test capability, and it is urgently needed to develop high-confidence simulation devices to test and research equipment models and simulation methods. At the same time, directly carrying out technical verification or testing on the flight environment simulation system and device through physical test means has problems such as high physical test cost (tens of thousands of yuan / hour) and high debugging risk, and especially there is a great technical risk and safety hazard in directly debugging and verifying the newly developed control technology on the real equipment of the test bed.

[0003] Due to the great technical advantages of simulation verification technology and virtual test in reducing technical risk, shortening development cycle and reducing cost, they have gradually become a new way of test control technology and equipment modeling simulation. For a long time, the field of flight environment simulation test mainly relies on digital modeling offline simulation means to carry out partial simulation research on equipment models or typical working conditions. For example, the aero-engine test bed modeling method, electronic device and storage medium (publication number: CN115616933A) proposes a modeling method for a virtual space digital twin model, and does not involve hardware-in-the-loop simulation and equipment adaptability verification problems. The aero-engine high-altitude test bed virtual test system, method, electronic device and medium (publication number: CN115329605A) proposes a joint simulation device composed of a simulation module and a main control module, and each simulation unit is provided with a simulation model. The time management unit of the main control module obtains ideal machine time for time synchronization through a time server, and does not involve semi-physical simulation and intelligent control problems. For the problem of high-precision control of flight environment pressure, the composite control technology in the technical research of the inlet and exhaust pressure regulating system (Measurement and Control Technology, 2009, No. 11) proposes a composite control method of feedforward and fuzzy control, which improves the inlet pressure precision, and does not involve the control method linked with engine speed; the high-altitude test bed inlet system anti-disturbance control method based on non-smooth feedback function (publication number: CN115562002B) realizes the control of the inlet pressure in the transition state test of the aero-engine through the joint action of the non-smooth feedback sliding mode controller algorithm and the nonlinear enhancement filtering algorithm in the inlet control system, and does not involve the method of feedforward and intelligent anti-disturbance control. SUMMARY

[0004] In view of this, an embodiment of the present application provides a multi-mode simulation method for a flight environment simulation control system, which at least partially solves the problem of low-cost, risk-free scientific research verification platform integration in the existing technology, and improves simulation confidence and efficiency.

[0005] The present application provides a multi-mode simulation method for a flight environment simulation control system, wherein the flight environment simulation control system includes a real-time simulation device, a PLC device, a hydraulic pump station, a throttle lever simulation device, and a regulating valve. The method includes: Start the hydraulic pump station, regulating valve, PLC device and real-time simulation device, select full digital simulation experiment or semi-physical simulation experiment, and run the object model and control model. The object model includes the hydraulic regulating valve flow model, air pipe network pressure and temperature model and engine flow model connected in sequence. The control model includes the feedforward controller, active disturbance rejection controller and extended state observer. When semi-physical simulation experiment is selected, the operating equipment includes PLC device, hydraulic pump station, hydraulic regulating valve and real-time simulation device, and PLC master control mode or real-time simulation device master control mode is selected. In PLC master control mode, the control model runs in the PLC device and the object model runs in the real-time simulation device. In real-time simulation device master control mode, both the control model and the object model run in the real-time simulation device. When a full digital simulation experiment is selected, the operating equipment includes a PLC device and a real-time simulation device, and both the control model and the object model are run in the real-time simulation device; Set the initial conditions for simulation, call the control model and object model simultaneously, and calculate the simulation parameters in real time; The feedforward controller calculates the feedforward control variable in real time based on the engine speed change rate output by the engine flow model. The extended state observer estimates the total system disturbance and feeds it back to the active disturbance rejection controller. The active disturbance rejection controller calculates the initial control variable in real time. The initial control variable is superimposed on the feedforward control variable and the estimated value to obtain the final control variable. The final control variable is input into the hydraulic control valve flow model to achieve dynamic control of the system pressure. The control parameters of the control model are adjusted through full digital simulation experiments. When the full digital simulation experiment passes, a semi-physical simulation experiment is carried out to optimize the control parameters adjusted by the full digital simulation experiment to meet the adaptability requirements of the control algorithm in the control model to the physical equipment.

[0006] According to a specific implementation method of an embodiment of the present application, when a semi-physical simulation experiment is selected, the PLC device and the real-time simulation device communicate in real time through an Ethernet switch; when a full digital simulation experiment is selected, the object model and the control model interact with each other in real time through a reflective memory switch.

[0007] According to a specific implementation manner of the embodiment of the present application, the simulation initial condition comprises an intake pressure, an intake temperature, a flight height, a Mach number, an engine rotating speed, a pre-valve pressure of the first hydraulic regulating valve, a pre-valve temperature of the first hydraulic regulating valve, a pre-valve pressure of the second hydraulic regulating valve, and a pre-valve temperature of the second hydraulic regulating valve.

[0008] According to a specific implementation manner of the embodiment of the present application, the hydraulic regulating valve flow model comprises a first hydraulic regulating valve flow model and a second hydraulic regulating valve flow model. The real-time calculation of the simulation parameter comprises: inputting the pre-valve pressure of the first hydraulic regulating valve, the pre-valve temperature of the first hydraulic regulating valve, a first valve flow cross-sectional area, a first flow coefficient, and a first valve opening degree into the first hydraulic regulating valve flow model to obtain a through flow of the first hydraulic regulating valve; inputting the pre-valve pressure of the second hydraulic regulating valve, the pre-valve temperature of the second hydraulic regulating valve, a second valve flow cross-sectional area, a second flow coefficient, and a second valve opening degree into the second hydraulic regulating valve flow model to obtain a through flow of the second hydraulic regulating valve; pushing a throttle lever simulation device to change the engine rotating speed, inputting the engine rotating speed, a throttle lever angle, the flight height, and the Mach number into the engine flow model to obtain an engine mass flow; inputting the obtained through flow of the first hydraulic regulating valve, the through flow of the second hydraulic regulating valve, and the engine mass flow into the air pipe network pressure and temperature model to real-time calculate the intake temperature and the intake pressure.

[0009] According to a specific implementation manner of the embodiment of the present application, the expression of the first hydraulic regulating valve flow model is: , , wherein, is a differential of the through flow m1 of the first hydraulic regulating valve, P1 is the pre-valve pressure of the first hydraulic regulating valve, T1 is the pre-valve temperature of the first hydraulic regulating valve, S1 is a first valve flow cross-sectional area, is a first flow coefficient, k1 is a first valve opening degree, R is a specific gas constant, and r1 is a radius of the first hydraulic regulating valve; the expression of the second hydraulic regulating valve flow model is: , , wherein, is the differential of the flow rate m2 through the second hydraulic regulating valve, P2 is the valve inlet pressure of the second hydraulic regulating valve, T2 is the valve inlet temperature of the second hydraulic regulating valve, S2 is the flow cross-sectional area of ​​the second valve, is the second flow coefficient, k2 is the second valve opening, and r2 is the radius of the second hydraulic regulating valve; The expression of the engine flow model is: , in, is the engine mass flow rate m engine The differential of , n is the engine speed, H is the flight altitude, Ma is the Mach number, m0 is the reference flow rate, a, b, c are the first coefficient, second coefficient and third coefficient determined by the test data calibration method respectively; The expression of the air pipe network pressure and temperature model is: , , Among them, T c is the intake pipe network cavity temperature, P c is the intake pipe network cavity pressure, V c is the volume of the intake pipe network cavity, T engine is the engine exhaust temperature, C p is the constant pressure specific heat capacity of the gas, C1 is the first average airflow velocity, C2 is the second average airflow velocity, C engine is the third average air velocity.

[0010] According to a specific implementation of the embodiment of the present application, the calculation formula of the feedforward control amount is: , Among them, u f is the feedforward control quantity, K f1 is the first feedforward gain, K f2 is the second feedforward gain, K f3 is the third feedforward gain, sign is the sign function, is the exponential decay term, α is the quadratic gain coefficient, β is the hysteresis compensation coefficient, is the high frequency attenuation gain, is the speed reduction coefficient, is the engine speed change rate, n is the engine speed, N1 is the boundary between the low speed zone and the medium speed zone, and N2 is the boundary between the high speed zone and the medium speed zone.

[0011] According to a specific implementation of the embodiment of the present application, the expression of the extended state observer is: , wherein z1 is a real-time estimation value of the actual output intake pressure of the system by the extended state observer, is a differential of z1, z2 is an estimation value of the change rate of the system output pressure, is a differential of z2, z3 is an estimation value of the total disturbance of the system, is a differential of z3, β1, β2, β3 are respectively a first gain coefficient, a second gain coefficient and a third gain coefficient of the extended state observer, is a saturation interval coefficient, b0 is a normalized coefficient of the control gain, u is a final control amount, is a switching threshold of the linear and nonlinear working intervals, e is a tracking error, sat is a saturation function, is an estimation value of the unknown dynamics and external disturbance.

[0012] According to a specific implementation manner of the embodiment of the present application, the active anti-disturbance controller calculates an initial control amount in real time, superimposes a feedforward control amount and an estimation value on the initial control amount, and obtains a final control amount, which includes: The tracking differentiator converts the step signal pressure set value into a smooth signal with smooth transition to avoid overshoot caused by the step signal; The active anti-disturbance controller calculates an initial control amount in real time based on the smooth transition pressure set value, the real-time estimation value of the actual output intake pressure of the system by the extended state observer, and the estimation value of the change rate of the system output pressure; The final control amount is obtained based on the initial control amount, the feedforward control amount and the estimation value of the total disturbance of the system.

[0013] According to a specific implementation manner of the embodiment of the present application, the expression of the tracking differentiator is: , wherein R1 is a speed factor, v1 is a smooth tracking signal of the pressure set value, is a first differential value of v1, v2 is a second differential value of v1, is a differential of v2, r(t) is the pressure set value.

[0014] According to a specific implementation manner of the embodiment of the present application, the calculation formula of the initial control amount is: , wherein e is a tracking error, is a differential of the tracking error e, k2 is a control gain, r f is a coefficient for determining the strength of nonlinearity, h f is a step length, fhan is a fastest control synthesis function, u0 is the initial control amount; The calculation formula of the final control amount is: .

[0015] Beneficial effects: In the embodiments of this application, a multi-mode simulation method for a flight environment simulation control system is designed to address technical issues such as accurate full-digital / semi-physical simulation of the aircraft engine flight environment, rapid pressure response and high-precision control in transient state tests, and multi-mode simulation design and system integration. The control system is composed of a real-time simulation device, a PLC device, a throttle lever simulation device, a host computer, a regulating valve, and a hydraulic pump station. It can realize two types of simulation experiments: full-digital simulation and semi-physical simulation. The aircraft engine flight environment simulation can be performed in either PLC device master control mode or real-time simulation device master control mode. High-precision pressure control is achieved through the engine speed feedforward and active anti-disturbance composite control algorithm in the control model. By constructing a flight environment simulation control system, the PLC control system, equipment, and model are integrated for operation. The full-digital and semi-physical technology is used to simulate the aircraft engine flight environment and test and verify the control method, reducing costs and improving simulation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 Schematic diagram of the structure of a flight environment simulation control system according to an embodiment of the present invention; Figure 2 A schematic diagram of a full digital and semi-physical simulation experiment according to an embodiment of the present invention; Figure 3 A schematic diagram of calculation logic of an object model and a control model according to an embodiment of the present invention; Figure 4 Graphs of simulation results according to an embodiment of the present invention, wherein (a) is a diagram showing the effect of pressure control, and (b) is a diagram showing the effect of control amount compensation and valve adjustment; Figure 5 1 is another simulation result diagram according to an embodiment of the present invention, wherein (a) is a simulation result diagram of air environment pressure, (b) is a simulation result diagram of Mach number, (c) is a simulation result diagram of flight altitude, and (d) is a simulation result diagram of engine flow. Figure 6 1 is a comparison chart of simulation results between the method of the present invention and the conventional PID control method, wherein (a) is a comparison chart of pressure results, and (b) is a comparison chart of pressure deviation results. DETAILED DESCRIPTION

[0018] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0019] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, in the absence of conflict, the features in the following embodiments and embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative work are within the scope of protection of this application.

[0020] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on this application, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement an apparatus and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this apparatus and / or practice this method.

[0021] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application. The illustrations only show components related to the present application and are not drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component can be changed at will, and the component layout type may also be more complicated.

[0022] Additionally, in the following description, specific details are provided to provide a thorough understanding of the examples. However, one skilled in the art will appreciate that the aspects described can be practiced without these specific details.

[0023] The present invention provides a multi-mode simulation method for a flight environment simulation control system. Figures 1 to 6 Provide a detailed description.

[0024] In one embodiment, referring to Figures 1 to 3, provides a multi-mode simulation method for a flight environment simulation control system, the flight environment simulation control system including a real-time simulation device, a PLC device, a hydraulic pump station, a throttle lever simulation device and a regulating valve, the method comprising: Step 1: Start the hydraulic pump station, regulating valve, PLC device, and real-time simulation device, select a full digital simulation experiment or a semi-physical simulation experiment, and run the object model and control model. The object model includes the hydraulic regulating valve flow model, air pipe network pressure and temperature model, and engine flow model connected in sequence. The control model includes a feedforward controller, an active disturbance rejection controller, and an extended state observer. When semi-physical simulation experiment is selected, the operating equipment includes PLC device, hydraulic pump station, hydraulic regulating valve and real-time simulation device, and PLC master control mode or real-time simulation device master control mode is selected. In PLC master control mode, the control model runs in the PLC device and the object model runs in the real-time simulation device. In real-time simulation device master control mode, both the control model and the object model run in the real-time simulation device. When a full digital simulation experiment is selected, the operating equipment includes a PLC device and a real-time simulation device, and both the control model and the object model are run in the real-time simulation device; Step 2: Set the initial conditions for the simulation, call the control model and the object model at the same time, and calculate the simulation parameters in real time; Step 3: The feedforward controller calculates the feedforward control variable in real time based on the engine speed change rate output by the engine flow model; the extended state observer estimates the total disturbance of the system to obtain an estimated value, and feeds it back to the active disturbance rejection controller; Step 4: The active disturbance rejection controller calculates the initial control variable in real time. The initial control variable is superimposed on the feedforward control variable and the estimated value to obtain the final control variable. The final control variable is input into the hydraulic control valve flow model to realize dynamic control of the system pressure. Step 5: Adjust the control parameters of the control model through a full digital simulation experiment. When the full digital simulation experiment passes, conduct a semi-physical simulation experiment to optimize the control parameters adjusted by the full digital simulation experiment to meet the adaptability requirements of the control algorithm in the control model to the physical equipment.

[0025] During implementation, if the PLC master control mode is selected, the control model, which includes a composite control algorithm for engine speed feedforward and active disturbance rejection, runs within the PLC device, while the object model runs within the real-time simulation device. Taking intake pressure simulation as an example, the control principle is as follows: After the control command is calculated using the PLC device's built-in composite control algorithm for engine speed feedforward and active disturbance rejection, a control signal is generated, which is transmitted through the PLC output module to the servo valve to drive the hydraulic control valve. The valve position feedback signal enters the PLC device through the PLC input module and is transmitted to the real-time simulation device via the network. The real-time simulation device calculates the flow rate of the hydraulic control valve in real time based on the valve position signal, while simultaneously running the intake pipe network cavity model and engine flow model, calculating the intake pressure signal, engine flow rate, and other signals in real time, and transmitting them to the PLC device's CPU via the network. The CPU then runs the composite control algorithm for engine speed feedforward and active disturbance rejection to achieve closed-loop control of the intake pressure.

[0026] When the real-time simulation device is in master control mode, both the control model and the object model run within the real-time simulation device. Taking intake pressure simulation as an example, the control principle is as follows: After the control command is calculated using the real-time simulation device's built-in engine speed feedforward and active disturbance rejection composite control algorithm, a control signal is generated and transmitted through the real-time simulation device's output card to the servo valve to drive the hydraulic control valve. The valve position signal enters the real-time simulation device via the input card. The real-time simulation device calculates the flow rate of the hydraulic control valve in real time based on the valve position feedback signal. Simultaneously, the intake pipe network cavity model and engine flow model are run to calculate real-time intake pressure, engine flow, and other signals. Pressure closed-loop control is then performed using the engine speed feedforward and active disturbance rejection composite control algorithm.

[0027] Furthermore, when a semi-physical simulation experiment is selected, the PLC device and the real-time simulation device communicate in real time through the Ethernet switch, and the PLC device, real-time simulation device, control valve and equipment model operate in conjunction to realize the semi-physical simulation of hardware in the loop; when a full digital simulation experiment is selected, the object model and the control model exchange information in real time through the reflective memory switch, and digital simulation of the flight environment conditions of the aircraft engine can be carried out.

[0028] In one embodiment, the simulation initial conditions include intake pressure, intake temperature, flight altitude, Mach number, engine speed, inlet pressure of the first hydraulic regulating valve, inlet temperature of the first hydraulic regulating valve, inlet pressure of the second hydraulic regulating valve, and inlet temperature of the second hydraulic regulating valve.

[0029] Furthermore, the hydraulic regulating valve flow model includes a first hydraulic regulating valve flow model and a second hydraulic regulating valve flow model; The real-time calculation simulation parameters include: Inputting the inlet pressure of the first hydraulic regulating valve, the inlet temperature of the first hydraulic regulating valve, the flow cross-sectional area of ​​the first valve, the first flow coefficient, and the first valve opening into the first hydraulic regulating valve flow model to obtain the flow rate through the first hydraulic regulating valve; Inputting the inlet pressure of the second hydraulic regulating valve, the inlet temperature of the second hydraulic regulating valve, the flow cross-sectional area of ​​the second valve, the second flow coefficient, and the second valve opening into the second hydraulic regulating valve flow model to obtain the flow rate passing through the second hydraulic regulating valve; Push the throttle lever simulation device to change the engine speed. Input the engine speed, throttle lever angle, flight altitude, and Mach number into the engine flow model to obtain the engine mass flow. The obtained flow rate through the first hydraulic regulating valve, the flow rate through the second hydraulic regulating valve, and the engine mass flow are input into the air pipe network pressure and temperature model to calculate the intake temperature and intake pressure in real time.

[0030] Furthermore, the expression of the flow model of the first hydraulic regulating valve is: , , in, is the differential of the flow rate m1 through the first hydraulic regulating valve, P1 is the valve inlet pressure of the first hydraulic regulating valve, T1 is the valve inlet temperature of the first hydraulic regulating valve, S1 is the flow cross-sectional area of ​​the first valve, is the first flow coefficient, k1 is the first valve opening, R is the specific gas constant, and r1 is the radius of the first hydraulic regulating valve; The expression of the flow model of the second hydraulic regulating valve is: , , in, is the differential of the flow rate m2 through the second hydraulic regulating valve, P2 is the valve inlet pressure of the second hydraulic regulating valve, T2 is the valve inlet temperature of the second hydraulic regulating valve, S2 is the flow cross-sectional area of ​​the second valve, is the second flow coefficient, k2 is the second valve opening, and r2 is the radius of the second hydraulic regulating valve; The expression of the engine flow model is: , in, is the engine mass flow rate m engine The differential of , n is the engine speed, H is the flight altitude, Ma is the Mach number, m0 is the reference flow rate, a, b, c are the first coefficient, second coefficient and third coefficient determined by the test data calibration method respectively; The expression of the air pipe network pressure and temperature model is: , , Among them, T c is the intake pipe network cavity temperature, P c is the intake pipe network cavity pressure, V c is the volume of the intake pipe network cavity, T engine is the engine exhaust temperature, C p is the constant pressure specific heat capacity of the gas, C1 is the first average airflow velocity, C2 is the second average airflow velocity, C engine is the third average air velocity.

[0031] In one embodiment, a feedforward controller is provided with a feedforward mapping function based on the dynamic characteristics of the engine. The feedforward mapping function is used to calculate the feedforward control amount in real time according to the engine speed change rate. The feedforward control amount is the feedforward compensation amount of the valve opening. The calculation formula of the feedforward control amount is: , Among them, u f is the feedforward control quantity, K f1 is the first feedforward gain, K f2 is the second feedforward gain, K f3 is the third feedforward gain, sign is the sign function, is the exponential decay term, α is the quadratic gain coefficient, β is the hysteresis compensation coefficient, is the high frequency attenuation gain, is the speed reduction coefficient, is the engine speed change rate, n is the engine speed, N1 is the boundary between the low speed zone and the medium speed zone, and N2 is the boundary between the high speed zone and the medium speed zone.

[0032] In one embodiment, the expression of the extended state observer is: , Among them, z1 is the real-time estimate of the actual output intake pressure of the system by the expanded state observer, is the differential of z1, z2 is an estimate of the rate of change of the system output pressure, is the differential of z2, z3 is the estimate of the total disturbance of the system, is the differential of z3, β1, β2, and β3 are the first, second, and third gain coefficients of the extended state observer, respectively. is the saturation interval coefficient, b0 is the normalization coefficient of the control gain, u is the final control amount, is the switching threshold between linear and nonlinear working ranges, e is the tracking error, sat is the saturation function, It is an estimate of unknown dynamics and external disturbances.

[0033] During specific implementation, the expanded state observer outputs the expanded state observer's real-time estimate z1 of the system's actual output intake pressure, the estimate z2 of the system's output pressure change rate, and the estimate z3 of the system's total disturbance. The expanded state observer's real-time estimate z1 of the system's actual output intake pressure is used to calculate with the pressure set value to obtain the tracking error, the estimate z2 of the system's output pressure change rate is used to input into the active anti-disturbance controller, and the estimate z3 of the system's total disturbance is used to calculate the final control quantity together with the initial control quantity and the feedforward control quantity.

[0034] In one embodiment, the active disturbance rejection controller calculates in real time an initial control variable, and the initial control variable is superimposed on a feedforward control variable and an estimated value to obtain a final control variable, including: The pressure setting value of the step signal is converted into a smooth signal with smooth transition through a tracking differentiator to avoid overshoot caused by the step signal; The active disturbance rejection controller calculates the initial control variable in real time based on the smoothly transitioned pressure setpoint, the real-time estimate of the system's actual output intake pressure by the expanded state observer, and the estimated value of the system's output pressure change rate. The final control variable is obtained based on the initial control variable, the feedforward control variable and the estimated value of the total disturbance of the system.

[0035] Furthermore, the tracking differentiator expression is: , Where R1 is the velocity factor, v1 is the smooth tracking signal of the pressure setting value, is the first differential value of v1, v2 is the second differential value of v1, is the differential of v2, and r(t) is the pressure setting value.

[0036] Furthermore, the calculation formula of the initial control amount is: , Where, e is the tracking error, is the differential of the tracking error e, k2 is the control gain, r f is the coefficient that determines the nonlinear strength, h f is the step length, fhan is the fastest control comprehensive function, u0 is the initial control amount; The calculation formula of the final control amount is: .

[0037] In specific implementation, the final control quantity is used to control the servo valve to drive the valve action, increase or decrease the valve flow, to quickly offset the impact of disturbances and improve the rapid response of pressure control.

[0038] In one embodiment, the control parameters of the control model are tuned through a full digital simulation experiment. When the full digital simulation experiment passes, a semi-physical simulation experiment is conducted to optimize the control parameters tuned by the full digital simulation experiment to meet the adaptability requirements of the control algorithm in the control model to the physical device, including: Step 5.1: Verify the engine speed feedforward and active anti-disturbance control algorithm through full digital simulation experiments, and adjust different feedforward control parameters (α, β, ), active anti-disturbance control parameters (k2, b0), when the percentage of deviation between the controlled pressure and the pressure setting value is no more than ±0.5%, the simulation experiment can be considered successful; Step 5.2: Based on the full digital simulation experiment, a semi-physical simulation experiment is conducted to adjust the feedforward control parameters (α, β, ), active anti-disturbance control parameters (k2, b0), etc. are semi-physical experimentally verified. When the regulating valve position frequently swings, or the deviation between the controlled pressure and the pressure setting value increases or fails to converge, the control parameters need to be optimized and readjusted. When the percentage of the deviation between the controlled pressure and the pressure setting value is observed to be no more than ±0.5%, the semi-physical simulation experiment can be considered successful and the control algorithm is feasible for deployment.

[0039] Furthermore, the multi-mode simulation method of the flight environment simulation control system further includes: Change the new test conditions and repeat steps 1 to 4 above to achieve real-time simulation of various working conditions of the aircraft engine working environment, verify the adaptability of the control algorithm to various working conditions, and ensure the accuracy and efficiency of the simulation test.

[0040] This application uses a real-time simulation device, a PLC device, a host computer, a throttle lever simulation device, a hydraulic pump station, a regulating valve and a switch to build a flight environment simulation control system. The real-time simulation device is used to run the test equipment model and the control model; the PLC device is used to control the algorithm operation, collect data and monitor the equipment operation; the host computer is used for simulation task design, real-time monitoring and command input and data viewing, etc.; the hydraulic pump station is used to provide power for the regulating valve operation; the regulating valve is used to simulate the test equipment operation and verify the algorithm adaptability; the throttle lever simulation device is used to generate throttle lever signals and simulate the engine acceleration and deceleration working process. Through the integrated linkage simulation of the PLC control system and the regulating valve equipment, a high-confidence simulation of the operation process of large-scale test equipment can be achieved. It can perform full-digital and semi-physical mode switching simulations, and can realize the simulation of the aviation engine flight environment under various working conditions through the two main control models of PLC and real-time simulation platform. A composite controller is constructed based on engine speed feedforward + active interference rejection. The engine speed change rate is obtained in real time through the feedforward controller to generate rapid valve compensation quality instructions. The system disturbance is observed in real time through the expanded state observer and the controlled pressure disturbance is quickly suppressed, thereby jointly achieving rapid pressure response and high-precision control, solving the problem of low-cost and risk-free scientific research verification platform integration and improving simulation confidence and efficiency.

[0041] In one embodiment, the control system pressure control effect, control amount compensation and valve adjustment effect are as follows: Figure 4 As shown in the figure, the valve adjustment achieves rapid compensation and faster response. The flight altitude, Mach number, ambient pressure and engine flow changes show the results as follows Figure 5 As shown, the pressure control effect of the simulation method of the present invention and the conventional PID control method is compared. Figure 6 The controlled pressure using the simulation method of the present invention can quickly follow the changes in the pressure setting value, with a maximum deviation of 0.64 kPa and a convergence time of 2 seconds. The maximum deviation of the controlled pressure using the conventional PID control algorithm is 5.39 kPa, and the convergence time lags behind the pressure setting value change time, with an adjustment time of 17 seconds. It can be seen that the simulation method proposed in the present invention has good transition state control accuracy and robustness.

[0042] The present invention uses a real-time simulation device, a PLC device, a throttle lever simulation device, a host computer and a regulating valve to form a multi-mode simulation control system that can truly simulate the operation of the test equipment. By integrating engine speed feedforward and active anti-disturbance control, a method is formed to achieve rapid pressure response and high-precision intelligent control, achieving rapid pressure response and high-precision control, solving the problem of low-cost and risk-free scientific research verification platform integration, and improving simulation confidence and efficiency.

[0043] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A multi-mode simulation method for a flight environment simulation control system, characterized in that: The flight environment simulation control system includes a real-time simulation device, a PLC device, a hydraulic pump station, a throttle lever simulation device and a regulating valve. The method includes: Start the hydraulic pump station, regulating valve, PLC device and real-time simulation device, select full digital simulation experiment or semi-physical simulation experiment, and run the object model and control model. The object model includes the hydraulic regulating valve flow model, air pipe network pressure and temperature model and engine flow model connected in sequence. The control model includes the feedforward controller, active disturbance rejection controller and extended state observer. When semi-physical simulation experiment is selected, the operating equipment includes PLC device, hydraulic pump station, hydraulic regulating valve and real-time simulation device, and PLC master control mode or real-time simulation device master control mode is selected. In PLC master control mode, the control model runs in the PLC device and the object model runs in the real-time simulation device. In real-time simulation device master control mode, both the control model and the object model run in the real-time simulation device. When a full digital simulation experiment is selected, the operating equipment includes a PLC device and a real-time simulation device, and both the control model and the object model are run in the real-time simulation device; Set the initial conditions for simulation, call the control model and object model simultaneously, and calculate the simulation parameters in real time; The feedforward controller calculates the feedforward control variable in real time based on the engine speed change rate output by the engine flow model. The extended state observer estimates the total system disturbance and feeds it back to the active disturbance rejection controller. The active disturbance rejection controller calculates the initial control variable in real time. The initial control variable is superimposed on the feedforward control variable and the estimated value to obtain the final control variable. The final control variable is input into the hydraulic control valve flow model to achieve dynamic control of the system pressure. The control parameters of the control model are adjusted through full digital simulation experiments. When the full digital simulation experiment passes, a semi-physical simulation experiment is carried out to optimize the control parameters adjusted by the full digital simulation experiment to meet the adaptability requirements of the control algorithm in the control model to the physical equipment.

2. The multi-mode simulation method for a flight environment simulation control system according to claim 1, characterized in that: When a semi-physical simulation experiment is selected, the PLC device and the real-time simulation device communicate in real time through an Ethernet switch. When a fully digital simulation experiment is selected, the object model and the control model exchange information in real time through a reflective memory switch.

3. The multi-mode simulation method for a flight environment simulation control system according to claim 1, characterized in that: The simulation initial conditions include intake pressure, intake temperature, flight altitude, Mach number, engine speed, valve inlet pressure of the first hydraulic regulating valve, valve inlet temperature of the first hydraulic regulating valve, valve inlet pressure of the second hydraulic regulating valve, and valve inlet temperature of the second hydraulic regulating valve.

4. The multi-mode simulation method for a flight environment simulation control system according to claim 3, characterized in that: The hydraulic regulating valve flow model includes a first hydraulic regulating valve flow model and a second hydraulic regulating valve flow model; The real-time calculation simulation parameters include: Inputting the inlet pressure of the first hydraulic regulating valve, the inlet temperature of the first hydraulic regulating valve, the flow cross-sectional area of ​​the first valve, the first flow coefficient, and the first valve opening into the first hydraulic regulating valve flow model to obtain the flow rate through the first hydraulic regulating valve; Inputting the inlet pressure of the second hydraulic regulating valve, the inlet temperature of the second hydraulic regulating valve, the flow cross-sectional area of ​​the second valve, the second flow coefficient, and the second valve opening into the second hydraulic regulating valve flow model to obtain the flow rate passing through the second hydraulic regulating valve; Push the throttle lever simulation device to change the engine speed. Input the engine speed, throttle lever angle, flight altitude, and Mach number into the engine flow model to obtain the engine mass flow. The obtained flow rate through the first hydraulic regulating valve, the flow rate through the second hydraulic regulating valve, and the engine mass flow are input into the air pipe network pressure and temperature model to calculate the intake temperature and intake pressure in real time.

5. The multi-mode simulation method for a flight environment simulation control system according to claim 4, characterized in that: The expression of the flow model of the first hydraulic regulating valve is: ， ， in, is the differential of the flow rate m1 through the first hydraulic regulating valve, P1 is the valve inlet pressure of the first hydraulic regulating valve, T1 is the valve inlet temperature of the first hydraulic regulating valve, S1 is the flow cross-sectional area of ​​the first valve, is the first flow coefficient, k1 is the first valve opening, R is the specific gas constant, and r1 is the radius of the first hydraulic regulating valve; The expression of the flow model of the second hydraulic regulating valve is: ， ， in, is the differential of the flow rate m2 through the second hydraulic regulating valve, P2 is the valve inlet pressure of the second hydraulic regulating valve, T2 is the valve inlet temperature of the second hydraulic regulating valve, S2 is the flow cross-sectional area of ​​the second valve, is the second flow coefficient, k2 is the second valve opening, and r2 is the radius of the second hydraulic regulating valve; The expression of the engine flow model is: ， in, is the engine mass flow rate m engine The differential of , n is the engine speed, H is the flight altitude, Ma is the Mach number, m0 is the reference flow rate, a, b, c are the first coefficient, second coefficient and third coefficient determined by the test data calibration method respectively; The expression of the air network pressure and temperature model is: ， ， Among them, T c is the intake pipe network cavity temperature, P c is the intake pipe network cavity pressure, V c is the volume of the intake pipe network cavity, T engine is the engine exhaust temperature, C p is the constant pressure specific heat capacity of the gas, C1 is the first average airflow velocity, C2 is the second average airflow velocity, C engine is the third average air velocity.

6. The multi-mode simulation method for a flight environment simulation control system according to claim 1, characterized in that: The calculation formula of the feedforward control quantity is: ， Among them, u f is the feedforward control quantity, K f1 is the first feedforward gain, K f2 is the second feedforward gain, K f3 is the third feedforward gain, sign is the sign function, is the exponential decay term, α is the quadratic gain coefficient, β is the hysteresis compensation coefficient, is the high frequency attenuation gain, is the speed reduction coefficient, is the engine speed change rate, n is the engine speed, N1 is the boundary between the low speed zone and the medium speed zone, and N2 is the boundary between the high speed zone and the medium speed zone.

7. The multi-mode simulation method for a flight environment simulation control system according to claim 6, characterized in that: The expression of the extended state observer is: ， Among them, z1 is the real-time estimate of the actual output intake pressure of the system by the expanded state observer, is the differential of z1, z2 is an estimate of the rate of change of the system output pressure, is the differential of z2, z3 is the estimate of the total disturbance of the system, is the differential of z3, β1, β2, and β3 are the first, second, and third gain coefficients of the extended state observer, respectively. is the saturation interval coefficient, b0 is the normalization coefficient of the control gain, u is the final control amount, is the switching threshold between linear and nonlinear working ranges, e is the tracking error, sat is the saturation function, is an estimate of unknown dynamics and external disturbances.

8. The multi-mode simulation method for a flight environment simulation control system according to claim 7, characterized in that: The active disturbance rejection controller calculates in real time to obtain an initial control variable, and the initial control variable is superimposed on the feedforward control variable and the estimated value to obtain a final control variable, including: The pressure setting value of the step signal is converted into a smooth signal with smooth transition through a tracking differentiator to avoid overshoot caused by the step signal; The active disturbance rejection controller calculates the initial control variable in real time based on the smoothly transitioned pressure setpoint, the real-time estimate of the system's actual output intake pressure by the expanded state observer, and the estimated value of the system's output pressure change rate. The final control variable is obtained based on the initial control variable, the feedforward control variable and the estimated value of the total disturbance of the system.

9. The multi-mode simulation method for a flight environment simulation control system according to claim 8, characterized in that: The tracking differentiator expression is: ， Where R1 is the velocity factor, v1 is the smooth tracking signal of the pressure setting value, is the first differential value of v1, v2 is the second differential value of v1, is the differential of v2, and r(t) is the pressure setting value.

10. The multi-mode simulation method for a flight environment simulation control system according to claim 9, characterized in that: The calculation formula of the initial control amount is: ， Where, e is the tracking error, is the differential of the tracking error e, k2 is the control gain, r f is the coefficient that determines the nonlinear strength, h f is the step length, fhan is the fastest control comprehensive function, u0 is the initial control amount; The calculation formula of the final control amount is: 。

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