WO2021008163A1

WO2021008163A1 - Simulation model modeling method of aircraft engine distributed control system based on truetime

Info

Publication number: WO2021008163A1
Application number: PCT/CN2020/081010
Authority: WO
Inventors: 潘慕绚; 李义炜; 黄金泉
Original assignee: 南京航空航天大学
Priority date: 2019-07-17
Filing date: 2020-03-25
Publication date: 2021-01-21
Also published as: CN110471308A

Abstract

Provided is a simulation model modeling method of an aircraft engine distributed control system based on TrueTime, comprising the following steps: step (1): establishing an aircraft engine simulation model; step (2): establishing a simulation model of an aircraft engine smart sensor; step (3): establishing a simulation model of a smart actuator; step (4): establishing a distributed controller simulation model; step (5) establishing a simulation model of the distributed engine control system on the basis of a TrueTime simulation model of the engine, smart sensor, smart actuator, and controller. Under the premise of the aircraft engine distributed control architecture, by means of establishing an engine model based on Simulink, and smart sensor, controller, and smart actuator models based on TrueTime 2.0, using a time-triggered bus protocol, a distributed engine control system is constructed, and will actively encourage research on distributed control systems of advanced aircraft engines such as smart engines and multi-motor engines of the future.

Description

Simulation model modeling method of aero-engine distributed control system based on TrueTime

Technical field

The invention belongs to the technical field of aeroengine control, and in particular relates to a simulation model modeling method of aeroengine distributed control system based on TrueTime2.0.

Background technique

With the continuous development of aero-engines in aerodynamics, thermodynamics and machinery, its performance and efficiency have reached an unprecedented level, and the corresponding aero-engine control is also constantly developing. In order to reduce the total mass of the engine, improve engine performance, and reduce costs, modern engines use distributed control systems to replace traditional centralized control systems. Compared with the traditional centralized control system, the aero-engine distributed control system can significantly reduce the weight of the control system and improve the reliability and maintainability of the system. However, when researching distributed control systems, the existing modeling methods based on centralized control are no longer applicable, especially the network delay caused by distributed control systems, which plays an important role in the effect of the control system. In order to better study the aero-engine distributed control system, it is necessary to study its modeling method. The TrueTime toolbox is a toolbox developed by Lund University based on Simulink. It is used to simulate distributed real-time control systems and network control systems. With this toolbox, the dynamic process, control task execution and network interaction of distributed real-time control systems can be constructed. In this simulation environment, various scheduling strategies and network protocol multi-control system performance simulation can be studied, which makes the research of network control system easier.

Summary of the invention

In view of the above technical problems, the present invention proposes a simulation model modeling method of aero engine distributed control system based on TrueTime 2.0. Considering aeroengine distributed control system, using TrueTime2.0 to establish a model of multi-smart sensors and multi-smart actuators, and connect to the controller through a communication protocol, and the controller sets up multiple receiving modules to receive the corresponding smart sensor data. The smart sensor and smart actuator are connected with the aero engine model. The smart sensor detects the state of the engine and sends the data to the controller. The controller calculates the corresponding control value after receiving the smart sensor data, and then sends the data to the smart The actuator, the intelligent actuator returns the obtained data to the engine model.

A simulation model modeling method of aeroengine distributed control system based on TrueTime2.0, including the following steps:

Step 1) Establish an aero engine simulation model;

Step 2) Establish a simulation model of aero-engine intelligent sensor;

Step 3) Establish a simulation model of an aero engine controller;

Step 4) Establish a simulation model of the aero-engine intelligent actuator;

Step 5) Build a simulation model of aero-engine distributed control system based on TrueTime2.0;

Further, the specific steps in step 1) are as follows:

Step 1.1), using the Matlab Function module through the Simulink toolbox in Matlab;

Step 1.2), call the existing dynamic link library through the Function module to establish an aero engine simulation model;

Further, the specific steps in step 2) are as follows:

Step 2.1), use the Kernel module in TrueTime2.0 to build a smart sensor data receiving module for each smart sensor;

Step 2.2), use the Kernel module in TrueTime2.0 to establish a smart sensor data register module for each smart sensor;

Step 2.3), in the "Block parameters: Turetime Kernel" dialog box where the smart sensor receives the Kernel module, set the smart sensor to receive the Kernel module parameters. Including setting in the "Name of init function (MEX or MATLAB)" column to receive the initialization file of the Kernel module and name it as "Sensor_init.m"; setting [10] in the "Number of analog inputs and outputs" column to indicate The number of analog input signals of the smart sensor is 1, and the number of analog output signals is 0; set the network number of the smart sensor in the "(Network and)Node number(s)" column;

Step 2.4), initialize the smart sensor to receive the Kernel module. In the initialization file Sensor_init.m of the smart sensor receiving the Kernel module, set the scheduling mode of the smart sensor receiving the Kernel module to "deadline-monotonic scheduling", define the start time of the smart sensor as ts1, and the period when the smart sensor sends data to the network as Ts1 , Define the file name of the smart sensor signal processing "Sensor_code.m". According to these parameters, use the "ttCreatPeriodicTask()" function to create a periodic task for the smart sensor;

Step 2.5), create the "Sensor_code.m" file. In this file, write the smart sensor A/D interface data reading code, and write the code to send the data to the corresponding smart sensor data registration module.

Step 2.6), in the "Block parameters: Turetime Kernel" dialog box of the smart sensor registration Kernel module, set the smart sensor registration Kernel module parameters. Including setting the initialization file of the smart sensor registration Kernel module in the "Name of init function (MEX or MATLAB)" column and naming it "Buff_init.m"; setting [01] in the "Number of analog inputs and outputs" column to indicate The number of smart sensor analog input signals is 0, and the number of analog output signals is 1. Set the network number of the smart sensor registration module in the "(Network and)Node number(s)" column;

Step 2.7), initialize the smart sensor to register the Kernel module. In the initialization file "Buff_init.m" of the smart sensor registration Kernel module, set the smart sensor registration Kernel module scheduling method to "deadline-monotonic scheduling", define the smart sensor data registration file name "Buff_code.m", and use the ttCreateTask() function Create non-periodic tasks so that the smart sensor registration module is responsible for receiving the data sent by the smart sensor without periodic work.

Step 2.8), create the "Buff_code.m" file. In this file, use the "ttGetMsg" function to write the code to read data from the network; after judging that the data is not empty, output it from the D/A interface of the smart sensor registered Kernel module.

Further, the specific steps in step 3) are as follows:

Step 3.1), use the Kernel module in TrueTime2.0 to establish the controller Kernel module;

Step 3.2), in the "Block parameters: Turetime Kernel" dialog box of the controller Kernel module, set the controller Kernel module parameters. Including setting the initialization file of the controller Kernel module in the "Name of init function (MEX or MATLAB)" column and naming it "Controller_init.m"; setting [ncin ncout] in the "Number of analog inputs and outputs" column to indicate The number of analog input signals of the controller is ncin, and the number of analog output signals is ncout; set the network number of the controller in the "(Network and)Node number(s)" column;

Step 3.3), initialize the controller to receive the Kernel module. In the initialization file Controller_init.m that the controller receives the Kernel module, set the scheduling mode for the controller to receive the Kernel module to "deadline-monotonic scheduling", define the controller's start working time as ts2, and the controller to send data to the network cycle as Ts2 , Define the controller code file name "Controller_code.m". According to these parameters, use the "ttCreatPeriodicTask()" function to create the periodic task of the controller. In particular, a data structure "data" needs to be set in the function to save the parameters required by the controller code, which represents the local memory of the task , The data required in the controller code uses the data structure name prefix.

Step 3.4), create the "Controller_code.m" file. In this file, write the controller A/D interface data reading code, and use the parameters and PID control method set in step 3.3) to calculate the control value, and send it to the intelligent actuator.

Further, the specific steps in step 4) are as follows:

Step 4.1), use the Kernel module in TrueTime2.0 to establish an intelligent actuator network node model for each intelligent actuator;

Step 4.2) In the "Block parameters: Turetime Kernel" dialog box of the Kernel module of the smart actuator, set the parameters of the Kernel module of the smart actuator. Including setting the initialization file of the Kernel module of the intelligent actuator in the "Name of init function (MEX or MATLAB)" column and naming it as "Actuator_init.m; setting [01] in the "Number of analog inputs and outputs" column, indicating smart The number of actuator analog input signals is 0, and the number of analog output signals is 1. Set the network number of the intelligent actuator module in the "(Network and)Node number(s)" column;

Step 4.3), initialize the Kernel module of the intelligent actuator. In the initialization file "Actuator_init.m" of the Kernel module of the intelligent actuator, set the scheduling mode of the intelligent actuator Kernel module to "deadline-monotonic scheduling", define the code file name of the intelligent actuator "Actuator_code.m", and use the ttCreateTask() function Create non-periodic tasks so that the intelligent actuator module is responsible for receiving the data sent by the controller without periodic work.

Step 4.4), create "Actuator_code.m" file. In this file, use the "ttGetMsg" function to write the code to read data from the network; after judging that the data is not empty, output it from the D/A interface of the Kernel module of the intelligent actuator.

Further, the specific steps in step 5) are as follows:

Step 5.1), use the Network module in the TrueTime2.0 toolbox to establish a network characteristic model of the engine distributed control system;

Step 5.2), connect the output terminal of the EngineFcn module of the engine simulation model with the smart sensor receiving Kernel module, and connect the output of the smart sensor registering the Kernel module to the multiplexing module. Refer to the instruction input module (Simulink step module, etc.) and The multiplexing module (mux) is connected, and the output of the Kernel module of the intelligent actuator is connected to the input of the Simulink module of the engine model;

Step 5.3), according to the total number n of network nodes in the distributed control system of the engine, in "Block Parameters: TrueTime Network", set the "Number of nodes" column to n, indicating the number of network nodes in the distributed control network of the engine Is n;

Step 5.4), in "Block Parameters: TrueTime Network", set the "Static schedule" column to: [Smart Sensor Receives Kernel Number Controller Kernel Number], which indicates the network scheduling strategy of the distributed engine control system;

Step 5.5) In "Block Parameters: TrueTime Network", set the parameters in the FrameSize and DateRate columns to indicate the frame size and transmission speed of network data transmission respectively.

Beneficial effects: A TrueTime2.0-based aeroengine distributed control modeling method designed by the present invention can well simulate intelligent sensors, controllers and intelligent actuators under the distributed control of aeroengines under the communication protocol TTP/C It also realizes the acquisition of engine signals and the use of PID control algorithms to effectively control the engine.

Description of the drawings

Figure 1 is a schematic diagram of the TrueTime2.0 toolbox;

Figure 2 is a schematic diagram of the Kernel setting interface;

Figure 3 is a schematic diagram of the Network setting interface;

Figure 4 is a schematic diagram of the model structure of the distributed control system of the present invention.

Detailed ways

The present invention is a simulation model modeling method of aeroengine distributed control system based on TrueTime2.0, which includes the following steps:

Step 1) Establish an aero engine simulation model:

Step 2) Establish a simulation model of aero-engine intelligent sensor:

Step 3) Establish a simulation model of aero engine controller:

Step 4) Establish a simulation model of aero-engine intelligent actuator:

Step 5) Build a simulation model of aero-engine distributed control system based on TrueTime2.0:

Example

The present invention will be further described below with reference to the drawings and embodiments.

Aeroengine distributed control system is an important development direction of aeroengine control. It can effectively reduce the weight of the control system and improve system reliability and maintainability. The characteristic of the distributed control system is that in the distributed control system, the intelligent sensor converts the analog signal into a digital signal, and provides output such as speed and pressure ratio to the controller. The intelligent actuator accepts the signal sent by the controller and makes a response. To complete the corresponding control tasks, each smart sensor and smart actuator are connected to the controller through a data bus.

The TrueTime 2.0 toolbox is a toolbox developed by Lund University based on Simulink. It is used to simulate distributed real-time control systems and network control systems. This toolbox can be used to construct the dynamic process, control task execution and control tasks of the distributed real-time control system. Co-simulation environment for network interaction. The TrueTime 2.0 toolbox is shown in Figure 1. In this example, two modules, Kernel and Network, are mainly used. The Kernel module is used to simulate smart sensors, smart actuators and controllers, and Network is used to set network parameters. The Kernel setting is shown in Figure 2. The first line is the name of the initialization file called by the module; the third line is the number of analog input and output signals, represented by vectors; the fifth line is the network to which the module belongs and the number in the network , Expressed by a vector, if there is only one network, just fill in the number in the network. Figure 3 shows the setting of Network. The first line is the network type, and communication protocols such as CAN, TDMA and FlexRay can be selected; the second line is the number of the network; the third line is the number of nodes in the network, which can be determined according to the number of Kernel modules used. OK; for TDMA (TTP/C), Network adds a static schedule in the last line.

As mentioned in step 1, use Simulink's Matlab Function module to call the existing dynamic link library in the Function module, and use the engine high-pressure rotor speed n _H and pressure ratio EPR as the engine output, and the fuel W _f and the nozzle area A ₈ as The input volume of the engine is used to establish a simulation model of an aero engine.

As described in step 2, set the node numbers of the smart

sensor receiving modules

1 and 2 in the "(Network and)Node number(s)" column of "Block parameters: TureTime Kernel" shown in Figure 2 to

number

1, 2 respectively , Set the analog input and output quantity to [1 0] in the "Number of analog inputs and outputs" column. Write the smart sensor initialization file and code. Take smart sensor receiving module 1 as an example, use Matlab m language, set the initialization file name to ‘Sensor1_init’, and change the smart sensor 1 settings to make the initialization file name consistent. The initialization file code is shown in Appendix 1. In the initialization file, first use the ‘ttInitKernel(‘prioDM’)’ statement to complete the Kernel scheduling mode design, and this setting must be completed in the rest of the Kernel initialization. The smart sensor periodically detects the engine signal and needs to create a periodic task, so use ttCreatePeriodicTask in the smart sensor initialization file to create a periodic task. Set the task start time to 0s and cycle to 0.02s according to the requirements, which means that the task starts at 0s , Every 0.02s is a cycle, and the smart sensor code'Sensor1_code' is called in the sentence at the same time. The smart sensor file code is shown in appendix 2. When writing the smart sensor code, the code file name must be consistent with the code name set above. Use the statement'x=ttAnalogIn(1)' in the smart sensor code to read the smart sensor A/D interface In the data, x is the variable set by reading the data. Then use the'ttSendMsg(3,x,80)' statement to send the data to the register module 1, where 3 represents the data sending destination, that is, the node number of the register module 1, x is the variable in the above, and 80 represents every time the data is sent The size of the data sent is 80 bits. The initialization file and code of smart sensor 2 are similar to those of smart sensor 1, and the file name, code name, and destination of data transmission need to be modified, so I won't elaborate on it here.

The node numbers of

register modules

1 and 2 are set to 3 and 4 respectively, and the analog input and output quantities are [0 1]. The initialization file and code of the register module take register module 1 as an example. The initialization file is shown in appendix 3, using Matlab language , The initialization file name is set to'Buff1_init', and the initialization file name is changed in the setting of register module 1. The registration module is responsible for receiving the data sent by the smart sensor. It is a non-periodic task. Therefore, use ttCreateTask and ttAttachNetworkHandler to create aperiodic tasks. The names of the two created tasks should be the same. The task is started when the smart sensor message reaches the receiving module through the network. Set the relative deadline of the task to 0.02s during the task, and set the code'Buff1_code' used by register module 1 in ttCreateTask. When writing the code used by register module 1, the code name should be consistent with the above settings. The register module code is shown in appendix 4. In the code of register 1, use the statement'y=ttGetMsg' to read the data sent by the smart sensor receiving module through the network, where y is the variable set by the read data, and then use'ttAnalogOut (1,y)' statement sends the obtained data from the D/A interface, where y is the variable mentioned above, the channel number of the D/A interface, because the D/A interface does not transmit more than one in the register module Data, the channel number is set to 1. The initialization file and code of the registering module 2 are similar to that of the receiving module 1. The initialization file name and code name need to be modified, so I won't elaborate on this here.

As described in step 3, set the controller to “(Network and)Node number(s)” in the “Block parameters:TureTime Kernel” shown in Figure 2 and set the node number to column number 5, and set it in “Number of analog inputs and Set the analog input and output in the "outputs" column to [5 0]. When programming the controller module, similar to the smart sensor, use TTCreatePeriodicTask to create periodic tasks, start the task at 0s and take 0.02s as the cycle according to actual needs, and the initialization file is shown in Appendix 5. In particular, the PID control algorithm is used in the controller code, so a data structure needs to be added when creating a periodic task. In this example, the data structure is named'data', so the proportional and integral required by the algorithm in the controller code And the derivative parameters need to add the prefix of'data' such as the proportional parameter'data.K1'. In the initialization file, it is also necessary to complete the initialization of the algorithm-related quantities, and the related quantities should also be prefixed, so that the prefixed data can be passed to the code and stored. Set the controller code file name'PIDControl' when creating the controller task. When writing the controller code, the file name is consistent with this. The controller code is shown in appendix 6. In the code, use ttAnalogIn() to read the smart sensor A/D interface For data, the numbers 1 to 5 in parentheses indicate the order in which the A/D interface accesses data from top to bottom, the numbers 1 and 5 are used to read the number of smart sensors, the

numbers

2 and 4 are used to read the command signal, and the 3-bit clock signal. Provide time for the controller code, and provide time for the controller code. The controller adopts PID algorithm. After reading the smart sensor data and instruction information, it calculates the corresponding W _f and A ₈ , and then uses ttSendMsg to send the calculated data to the corresponding intelligent actuator.

As described in step 4, set the node number in the "(Network and)Node number(s)" column of the "(Network and)Node number(s)" in the "Block parameters: TureTime Kernel" shown in Figure 2 for the intelligent actuator to

number

6 and 7, respectively. In the "Number In the "analog inputs and outputs" column, set the analog input and output to [0 1]. The intelligent actuator is responsible for reading the data sent by the controller from the network. Its function is similar to that of the smart sensor registration module. Therefore, the initialization file and code of the intelligent actuator are also similar to the receiving module. You can modify the task name, code name and file name to execute intelligently. The organization initialization files and codes take the fuel oil actuator as an example, as shown in Appendix 7 and Appendix 8. So far, the intelligent sensors, controllers and intelligent actuator models in the distributed control system have been established and set up.

As described in step 5, use TrueTime's Network module to connect the engine model output terminal to the smart sensor receiving module, the input terminal to the smart actuator, and the controller to the smart sensor register module. In this example, 7 are used in total A Kernel, the communication network is TDMA, the frame size is set to 80bits, the data transmission speed is 80000bits/s, the static schedule is [1 5; 2 5], and the above settings are changed in the Network module. So far, the intelligent sensors, controllers and intelligent actuator models in the distributed control system have been established and set up. The final distributed control model of aeroengine based on True Time is shown in Figure 4.

appendix

Appendix 1 Sensor initialization code

function sensor1_init

ttInitKernel('prioDM');

starttime=0.0;

period=0.020;

ttCreatePeriodicTask('sensor_task1',starttime,period,'sensor_code1');

Appendix 2 Sensor Code

Appendix 3 Register initialization code

function Buff1_init

ttInitKernel('prioDM')

deadline=0.02;

ttCreateTask(Buff1_task',deadline,'Buff1_code');

ttAttachNetworkHandler('Buff1_task')

Appendix 4 Register Code

Appendix 5 Controller initialization code

function controller_init

ttInitKernel('prioDM')

data.Ts=0.02;

data.K11=0.8;

data.K22=1.8;

data.Ti1=0.08;

data.Ti2=0.25;

data.en1=0;

data.epi1=0;

data.un1=0;

data.upi1=0;

data.un=0;

data.upi=0;

data.duk1=0;

data.duk2=0;

data.en2=0;

data.epi2=0;

starttime=0.0;

period=0.02;

ttCreatePeriodicTask('controller_task',starttime,period,'controller_code',data);

Appendix 6 Controller Code

Appendix 7 Implementation agency initialization code

functionactuator1_init

ttInitKernel('prioDM');

deadline=10.0;

ttCreateTask('actuator1_task',deadline,'actuator1_code');

ttAttachNetworkHandler('actuator1_task')

Appendix 8 Code of Executing Agency

The above are only specific embodiments of the present invention, but the scope of protection of the present invention is not limited to this. It should be pointed out that those skilled in the art can easily think of modifications and improvements within the technical scope disclosed by the present invention. All should be covered within the protection scope of the present invention.

Claims

A TrueTime-based aeroengine distributed control system simulation model modeling method is characterized in that it includes the following steps:

Step 1) Establish an aero engine simulation model;

Step 2) Establish a simulation model of aero-engine intelligent sensor;

Step 3) Establish a simulation model of an aero engine controller;

Step 4) Establish a simulation model of the aero-engine intelligent actuator;

Step 5) Build a simulation model of aero-engine distributed control system based on TrueTime2.0.
The TrueTime-based aero-engine distributed control system simulation model modeling method according to claim 1, characterized in that: the specific steps in step 1) are as follows:

Step 1.1), build the EngineFcn module through the Function module in the Simulink toolbox in Matlab;

Step 1.2), call the dynamic link library of the aero-engine component-level model in the EngineFcn module to establish the aero-engine simulation model.
The TrueTime-based aeroengine distributed control system simulation model modeling method according to claim 1, wherein the specific steps in step 2) are as follows:

Step 2.1), use the Kernel module in TrueTime2.0 to establish a smart sensor data receiving Kernel module for each smart sensor;

Step 2.2), use the Kernel module in TrueTime2.0 to establish a smart sensor data register module for each smart sensor;

Step 2.3), in the "Block parameters: Turetime Kernel" dialog box of the smart sensor receiving the Kernel module, set the smart sensor to receive the Kernel module parameters, including: set the smart sensor to receive in the "Name of init function (MEX or MATLAB)" column The initialization file of the Kernel module is named "Sensor_init.m". Set [10] in the "Number of analog inputs and outputs" column to indicate that the number of analog input signals of the smart sensor is 1, and the number of analog output signals is 0; Set the network number of this smart sensor in the "(Network and)Node number(s)" column;

Step 2.4), initialize the smart sensor to receive the Kernel module: in the initialization file Sensor_init.m of the smart sensor to receive the Kernel module, set the scheduling mode of the smart sensor to receive the Kernel module to "deadline-monotonic scheduling", and define the smart sensor to start working time as ts1 , The period for the smart sensor to send data to the network is Ts1, and define the file name of the smart sensor signal processing "Sensor_code.m"; according to these parameters, use the "ttCreatPeriodicTask()" function to create a periodic task for the smart sensor;

Step 2.5), create a "Sensor_code.m" file, in this file, write the smart sensor A/D interface data reading code, and write the code to send the data to the corresponding smart sensor data registration module;

Step 2.6), in the "Block parameters: Turetime Kernel" dialog box of the smart sensor registration Kernel module, set the smart sensor registration Kernel module parameters, including: set the smart sensor registration in the "Name of init function (MEX or MATLAB)" column The initialization file of the Kernel module is named "Buff_init.m". Set [01] in the "Number of analog inputs and outputs" column to indicate that the number of analog input signals of the smart sensor is 0 and the number of analog output signals is 1. Set the network number of the smart sensor registration module in the "(Network and)Node number(s)" column;

Step 2.7), initialize the smart sensor registration Kernel module: in the initialization file "Buff_init.m" of the smart sensor registration Kernel module, set the smart sensor registration Kernel module scheduling method to "deadline-monotonic scheduling", and define the smart sensor data registration file name "Buff_code.m", use the ttCreateTask() function to create aperiodic tasks, so that the smart sensor registration module is responsible for receiving the data sent by the smart sensor;

Step 2.8), create a "Buff_code.m" file, in this file, use the "ttGetMsg" function to write the code to read data from the network; after judging that the data is not empty, register it from the smart sensor to the D/A of the Kernel module Output in the interface.
The TrueTime-based aeroengine distributed control system simulation model modeling method according to claim 1, wherein the specific steps in step 3) are as follows:

Step 3.1), use the Kernel module in TrueTime2.0 to establish the controller Kernel module;

Step 3.2), in the "Block parameters: Turetime Kernel" dialog box of the controller Kernel module, set the controller Kernel module parameters, including: set the controller Kernel module parameters in the "Name of init function (MEX or MATLAB)" column Initialize the file and name it "Controller_init.m", and set [ncin ncout] in the "Number of analog inputs and outputs" column to indicate that the number of analog input signals of the controller is ncin and the number of analog output signals is ncout. (Network and)Node number(s)" column to set the network number of the controller;

Step 3.3). Initialize the controller to receive the Kernel module: In the initialization file Controller_init.m that the controller receives the Kernel module, set the scheduling mode for the controller to receive the Kernel module to "deadline-monotonic scheduling", and define the starting time of the controller to be ts2 , The period for the controller to send data to the network is Ts2, and the controller code file name "Controller_code.m" is defined; according to these parameters, the "ttCreatPeriodicTask()" function is used to create the controller periodic task;

Step 3.4), create a "Controller_code.m" file, in this file, write the controller A/D interface data reading code, and use the parameters and PID control method set in step 3.3) to calculate the control value, and send it To smart actuators.
The TrueTime-based aeroengine distributed control system simulation model modeling method according to claim 1, characterized in that: in the step 3.3), the "ttCreatPeriodicTask()" function is used to create the periodic task of the controller, and in the function Set a data structure "data" to save the parameters required by the controller code. This data structure represents the local memory of the task, and the data required in the controller code uses the data structure name prefix.
The TrueTime-based aeroengine distributed control system simulation model modeling method according to claim 1, wherein the specific steps in step 4) are as follows:

Step 4.1), use the Kernel module in TrueTime2.0 to establish an intelligent actuator network node model for each intelligent actuator;

Step 4.2) In the "Block parameters:Turetime Kernel" dialog box of the intelligent actuator Kernel module, set the intelligent actuator Kernel module parameters, including: set the intelligent actuator Kernel in the "Name of init function (MEX or MATLAB)" column The initialization file of the module is named "Actuator_init.m". Set [01] in the "Number of analog inputs and outputs" column to indicate that the number of analog input signals of the intelligent actuator is 0 and the number of analog output signals is 1. Set the network number of the intelligent actuator module in the "(Network and)Node number(s)" column;

Step 4.3), initialize the Kernel module of the smart actuator: In the initialization file "Actuator_init.m" of the Kernel module of the smart actuator, set the scheduling mode of the smart actuator Kernel module to “deadline-monotonic scheduling”, and define the code file name of the smart actuator "Actuator_code.m", use the ttCreateTask() function to create aperiodic tasks, so that the intelligent actuator module is responsible for receiving the data sent by the controller;

Step 4.4), create the "Actuator_code.m" file, in the file, use the "ttGetMsg" function to write the code to read data from the network; after judging that the data is not empty, send it from the D/A of the Kernel module of the intelligent actuator Output in the interface.
The TrueTime-based aeroengine distributed control system simulation model modeling method according to claim 1, wherein the specific steps in step 5) are as follows:

Step 5.1), use the Network module in the TrueTime2.0 toolbox to establish a network characteristic model of the engine distributed control system;

Step 5.2), connect the output end of the EngineFcn module of the engine simulation model with the smart sensor receiving Kernel module, connect the output of the smart sensor register Kernel module to the multiplexing module, and connect the reference command input module to the multiplexing module , The output of the Kernel module of the intelligent actuator is connected with the input of the Simulink module of the engine model;

Step 5.3), according to the total number n of network nodes in the distributed control system of the engine, in "Block Parameters: TrueTime Network", set the "Number of nodes" column to n, indicating the number of network nodes in the distributed control network of the engine Is n;

Step 5.4), in "Block Parameters: TrueTime Network", set the "Static schedule" column to: [Smart Sensor Receives Kernel Number Controller Kernel Number], which indicates the network scheduling strategy of the distributed engine control system;

Step 5.5) In "Block Parameters: TrueTime Network", set the parameters in the FrameSize and DateRate columns to indicate the frame size and transmission speed of network data transmission respectively.