CN112799312A - Self-navigation unmanned aerial vehicle test method and system, communication equipment and storage medium - Google Patents
Self-navigation unmanned aerial vehicle test method and system, communication equipment and storage medium Download PDFInfo
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Abstract
本发明提供一种自导航无人飞行器测试方法及系统、通信设备和存储介质，该方法包括：基于仿真上位机构建多个模型并进行耦合；将耦合后的模型进行编译并下载至仿真目标机实时运行，以搭建实时仿真平台；将真实待测的自导航无人飞行器部件连接至实时仿真平台，以构成硬件在环仿真与测试平台；在硬件在环仿真与测试平台上进行各种控制策略和算法性能的测试和验证；在测试结束后，根据测试结果输出相关测试报告，并对控制策略以及相关算法的效果进行分析和评价。本发明的技术方案通过利用电子解算技术将电气系统模型和非电气系统模型进行耦合，从而打破原有FPGA编程复杂、调试困难的屏障。
The invention provides a self-navigation unmanned aerial vehicle testing method and system, communication equipment and storage medium. The method includes: constructing a plurality of models based on a simulation host computer and coupling them; compiling and downloading the coupled models to a simulation target computer Run in real time to build a real-time simulation platform; connect the real self-navigation UAV components to be tested to the real-time simulation platform to form a hardware-in-the-loop simulation and test platform; perform various control strategies on the hardware-in-the-loop simulation and test platform and algorithm performance test and verification; after the test, output the relevant test report according to the test results, and analyze and evaluate the effect of the control strategy and related algorithms. The technical scheme of the present invention uses the electronic solution technology to couple the electrical system model and the non-electrical system model, thereby breaking the original FPGA's complicated programming and difficult debugging barriers.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicles, in particular to a self-navigation unmanned aerial vehicle testing method and system, communication equipment and a storage medium.
Background
With the continuous progress of science and technology, military affairs and industries of all countries in the world are developing towards diversification and high technology. However, the development of high-tech devices usually costs a lot of manpower and material resources, which results in resource consumption that is hard to bear. In the field of high-tech equipment mainly for self-navigation unmanned aerial vehicles, the traditional test method usually evaluates the performance of the system through on-site actual test signals, but is gradually abandoned by various countries due to the defects of high cost, high restriction and the like. Therefore, the search for a safe, economical and effective test mode has become a key and difficult point of research in various countries in the world. Therefore, the existing mode that ground testing is required in the original self-navigation unmanned aerial vehicle identification test is broken through, and the semi-physical simulation test system is constructed by combining the field physical environment and the virtual simulation environment, so that the aim of semi-physical simulation test of the self-navigation unmanned aerial vehicle is fulfilled, and the method is a necessary way for realizing efficient, low-cost and low-risk development and verification of the self-navigation unmanned aerial vehicle and other tip equipment.
Semi-physical simulation refers to that partial physical objects of the self-navigation unmanned aerial vehicle are put into a simulation system consisting of simulation equipment for dynamic test, so that the simulation result is more real and effective. Compared with the traditional outfield test method, the semi-physical simulation has the advantages of short period, repeatability, good confidentiality and the like, and simultaneously has the advantage of high authenticity compared with digital simulation.
Currently, in the prior art, testing and verification research for a self-navigation unmanned aerial vehicle system mainly focuses on a simulation test of a full-digital self-navigation unmanned aerial vehicle system built through mathematical modeling software, for example, a Matlab/Simulink simulation tool is used to simulate the whole self-navigation unmanned aerial vehicle system.
However, the method has the problems that the self-navigation unmanned aerial vehicle system is modeled by digital simulation tools such as Simulink and the like, the dynamic characteristics and the physical reaction of external equipment cannot be accurately simulated, and the method mostly adopts an equivalent linear system approximate model or simulation input data given based on an algorithm, so that the system can only carry out simulation verification in an ideal environment and has low accuracy. And a physical simulation test method is directly adopted, complex FPGA programming is needed, and a large number of system debugging tasks cause that debugging is difficult.
Disclosure of Invention
In view of this, the invention aims to provide a self-navigation unmanned aerial vehicle testing method and system, a communication device and a storage medium, wherein an electrical system model and a non-electrical system model are coupled, so that a barrier that an original FPGA is complex in programming and difficult to debug is broken.
The invention provides a self-navigation unmanned aerial vehicle testing method, which comprises the following steps:
establishing a plurality of models based on a simulation upper mechanism and coupling;
compiling the coupled model and downloading the model to a simulation target machine for real-time operation so as to build a real-time simulation platform;
connecting a real self-navigation unmanned aerial vehicle component to be tested to the real-time simulation platform to form a hardware-in-loop simulation and test platform;
testing and verifying the performance of various control strategies and algorithms on the hardware-in-loop simulation and test platform;
and after the test is finished, outputting a related test report according to the test result, and analyzing and evaluating the control strategy and the effect of the related algorithm.
Preferably, the plurality of models include an electrical system model, and the step of building the electrical system model based on a simulation host computer includes:
and establishing the electric system model including the direct current transformer, the motor driver, the bleeder circuit, the protection circuit and the electric system fault based on the simulation upper mechanism.
Preferably, the plurality of models include a non-electrical system model, the non-electrical system model includes a target motion control model, a seeker motion control model, a motion control model of a self-navigation unmanned aerial vehicle body, and a model for signal transmission and processing, and the step of establishing the non-electrical system model based on a simulation host computer includes:
simulating the motion state of a target, and constructing the target motion control model on the simulation upper computer;
simulating the motion process of a seeker steering engine, and constructing a seeker motion control model on the simulation upper computer;
simulating the process from the generation of a control signal to the change of the flight state of the self-navigation unmanned aerial vehicle body, and constructing a motion control model of the self-navigation unmanned aerial vehicle body on the simulation upper computer;
and simulating the interference in the real environment, and constructing a model for signal transmission and processing on the simulation upper computer.
Preferably, the plurality of models includes an electrical system model and a non-electrical system model, and the step of coupling specifically includes:
coupling the electrical system model and the non-electrical system model is accomplished by using or controlling power, measurement signals, and door opening and closing signals in an electrical system of the self-navigating unmanned aerial vehicle.
In another aspect, the present invention further provides a self-navigation unmanned aerial vehicle test system, wherein the system includes:
the modeling module is used for building a plurality of models based on a simulation upper mechanism and coupling the models;
the download module is used for compiling the coupled model and downloading the model to a simulation target machine for real-time operation so as to build a real-time simulation platform;
the connecting module is used for connecting the real self-navigation unmanned aerial vehicle component to be tested to the real-time simulation platform so as to form a hardware-in-loop simulation and test platform;
the verification module is used for testing and verifying the performance of various control strategies and algorithms on the hardware-in-loop simulation and test platform;
and the output module is used for outputting a related test report according to the test result after the test is finished, and analyzing and evaluating the control strategy and the effect of the related algorithm.
Preferably, the plurality of models includes an electrical system model, the modeling module is further configured to:
and establishing the electric system model including the direct current transformer, the motor driver, the bleeder circuit, the protection circuit and the electric system fault based on the simulation upper mechanism.
Preferably, the plurality of models includes a non-electrical system model including a target motion control model, a seeker motion control model, a motion control model of a self-piloting unmanned aerial vehicle body, and a model of signal transmission and processing, the modeling module further being configured to:
simulating the motion state of a target, and constructing the target motion control model on the simulation upper computer;
simulating the motion process of a seeker steering engine, and constructing a seeker motion control model on the simulation upper computer;
simulating the process from the generation of a control signal to the change of the flight state of the self-navigation unmanned aerial vehicle body, and constructing a motion control model of the self-navigation unmanned aerial vehicle body on the simulation upper computer;
and simulating the interference in the real environment, and constructing a model for signal transmission and processing on the simulation upper computer.
Preferably, the plurality of models includes an electrical system model and a non-electrical system model, the modeling module is further configured to:
coupling the electrical system model and the non-electrical system model is accomplished by using or controlling power, measurement signals, and door opening and closing signals in an electrical system of the self-navigating unmanned aerial vehicle.
In yet another aspect, the present invention further provides a communication device, wherein the communication device includes a memory and a processor, the memory stores computer processing instructions, and the processor executes the self-navigation unmanned aerial vehicle test method by calling the computer processing instructions.
In yet another aspect, the present invention further provides a computer readable storage medium, wherein the computer readable storage medium has stored thereon a computer program, which when executed by a processor, implements the steps of the self-piloting unmanned aerial vehicle testing method described previously.
The technical scheme provided by the invention has the following advantages: by coupling a plurality of models, the barrier that the original FPGA is complex in programming and difficult to debug is broken.
Drawings
FIG. 1 is a schematic flow chart illustrating a self-navigation UAV testing method according to an embodiment of the present invention;
FIG. 2 is a coupling diagram illustrating coupling and associating an electrical system model with a non-electrical system model of a self-navigating UAV according to an embodiment of the present invention;
FIG. 3 is an enlarged schematic diagram of a non-electrical system model of FIG. 2 according to an embodiment of the present invention;
FIG. 4 is an enlarged schematic diagram of the electrical system model of FIG. 2 in accordance with one embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a real-time simulation test platform of a self-navigation UAV test system according to an embodiment of the present invention;
FIG. 6 is an enlarged schematic structural diagram of a simulation model of the real-time simulation target aircraft-UAV system shown in FIG. 5 according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a self-navigation unmanned aerial vehicle test system 1 according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The following will describe a self-navigation unmanned aerial vehicle testing method and system provided by the invention in detail.
Fig. 1 is a schematic flow chart of a self-navigation unmanned aerial vehicle testing method according to an embodiment of the present invention.
In step S1, a plurality of models are created and coupled based on the simulation host.
In this embodiment, the plurality of models may be divided into two groups, one group being an electrical system model and the other group being a non-electrical system model. The method comprises the following steps of establishing an electrical system model based on a simulation upper mechanism, wherein the multiple models comprise the electrical system model, and the step of establishing the electrical system model based on the simulation upper mechanism comprises the following steps:
and establishing the electric system model including the direct current transformer, the motor driver, the bleeder circuit, the protection circuit and the electric system fault based on the simulation upper mechanism.
In the embodiment, an electrical system model in the self-navigation unmanned aerial vehicle test system is established on a simulation upper computer based on Matlab/Simulink, wherein the electrical system model mainly comprises a DC-DC direct current transformer, a motor driver, a corresponding bleeder circuit, a protection circuit and the like. In addition, the electric system model also comprises an electric system fault model which is used for realizing fault modes such as short circuit, grounding, open circuit and the like caused by aging or failure of devices such as resistors, inductors, chips and the like.
In this embodiment, the plurality of models include a non-electrical system model, the non-electrical system model includes a target motion control model, a seeker motion control model, a motion control model of the self-navigation unmanned aerial vehicle body, and a model for signal transmission and processing, and the step of constructing the non-electrical system model based on the simulation upper computer includes:
simulating the motion state of a target, and constructing a target motion control model on a simulation upper computer;
simulating the motion process of a seeker steering engine, and constructing a seeker motion control model on a simulation upper computer;
simulating the process from the generation of the control signal to the change of the flight state of the self-navigation unmanned aerial vehicle body, and constructing a motion control model of the self-navigation unmanned aerial vehicle body on a simulation upper computer;
and simulating interference in a real environment, and constructing a signal transmission and processing model on the simulation upper computer.
In the embodiment, the non-electrical system model can comprehensively simulate the whole motion control process of the target, the seeker and the self-navigation unmanned aerial vehicle body, can truly reflect the guidance state of the self-navigation unmanned aerial vehicle, and is convenient for carrying out comprehensive test on the overall performance of the self-navigation unmanned aerial vehicle. In addition, due to the adoption of a modular design idea, the non-electrical system model also has the capability of independently testing each subsystem, which is very important for the analysis and the optimized operation of the self-navigation unmanned aerial vehicle system.
In the embodiment, the target motion control model simulates the motion state of a target and provides target information for tests such as seeker control, unmanned aerial vehicle guidance and tracking. The target motion control model is realized by adopting a double-shaft turntable model, wherein the yaw angle and the pitch angle are used for simulating the position change of a target in the horizontal and height directions.
In the embodiment, the seeker motion control model simulates the motion process of the seeker steering engine, and the seeker provides accurate positioning information for tasks such as target tracking, fixed-point take-off and landing of the self-navigation unmanned aerial vehicle. The seeker movement control model mainly comprises: a kinematics model, a tracking controller model and a target calibration model. The kinematics model adopts a double-shaft turntable controlled by double motors to simulate the motion process of a seeker steering engine. The tracking controller model adopts four-ring control strategies of a current ring, a speed ring, a stabilizing ring and a position ring, and ensures the accurate control of the seeker. The target calibration model is used for identifying the position of the target and forming a guide instruction to be sent to the motion control model of the self-navigation unmanned aerial vehicle body. In addition, according to different calculation algorithms, target information can be determined by using information modes such as vision, radar and the like, so that the method is widely applied to testing of various guide heads.
In this embodiment, the motion control model of the self-piloting unmanned aerial vehicle body is used for simulating the process from the generation of the control signal to the change of the flight state of the self-piloting unmanned aerial vehicle body, and is mainly divided into three parts: the system comprises a flight controller module, a kinematics and dynamics module and a sensor module. The flight controller module simulates a flight control computer of the unmanned aerial vehicle, receives a target signal sent by a seeker, combines the self attitude and position information and strategies such as path optimization, and adopts a control algorithm to complete the calculation of a control law and the output of a control signal. The kinematics and dynamics module simulates the attitude kinematics characteristics of the actuator and the unmanned aerial vehicle, receives the output signal of the flight controller module, and realizes the attitude adjustment of the unmanned aerial vehicle through the control of a plurality of motors and the actuator. The sensor module mainly simulates sensor functions of a gyroscope, an accelerometer and the like, and feeds signals such as self-navigation unmanned aerial vehicle body attitude and the like back to the flight controller module to realize unmanned aerial vehicle control.
In the embodiment, the signal transmission and processing model simulates interference in a real environment, and the signal transmission and processing model is adopted to receive the position signal of the target and transmit the position signal to the guide head module through different modes. The model of this signal transmission and processing can utilize different information processing strategies, realizes the transmission of multiple signal mode including signals such as vision, radar to satisfy self-navigation unmanned vehicles's test demand, wherein, radar target echo signal's production flow includes: the down-conversion of input signals, superposition delay, Doppler frequency and the like, up-conversion, power control and output. In addition, an interference injection module is adopted in a signal transmission and processing model, so that disturbing signals such as false target signals and noise signals can be added into basic signals to simulate interference in a real environment, and the signal transmission and processing model has high reality and wide applicability.
In this embodiment, the coupling in step S1 includes:
coupling the electrical system model and the non-electrical system model is accomplished by using or controlling power, measurement signals, and door opening and closing signals in the electrical system of the self-navigating unmanned aerial vehicle.
In the present embodiment, an electronic solution technology is mainly used to couple and associate an electrical system model of a self-navigation unmanned aerial vehicle with a non-electrical system model (including a target motion control model, a seeker motion control model, a motion control model of a self-navigation unmanned aerial vehicle body, and a model for signal transmission and processing). In the embodiment, an electronic calculation technology is designed, so that the non-electrical system model is coupled with the electrical system model of the self-navigation unmanned aerial vehicle by using or controlling a power supply, a measurement signal and a door opening and closing signal in the electrical system of the self-navigation unmanned aerial vehicle. In addition, the electronic calculation technology designed in the embodiment can automatically translate the electrical system designed based on Simulink into hardware language on the premise of not needing FPGA code compiling experience, and automatically download the electrical system model to FPGA for operation in real-time simulation. The electronic calculation technology can make full use of the characteristics of the FPGA, so that the system has a high calculation rate, the transient characteristics of the electrical system can be accurately simulated, the coupling relation is shown in figure 2, the enlarged structure diagram of the non-electrical system model is shown in figure 3, and the enlarged structure diagram of the electrical system model is shown in figure 4.
In step S2, the coupled model is compiled and downloaded to a simulation target machine for real-time operation, so as to build a real-time simulation platform.
In the embodiment, the self-navigation unmanned aerial vehicle test model is arranged and configured according to the requirements of real-time simulation, and comprises self-navigation unmanned aerial vehicle components needing to be tested, a signal interface and a communication module for data interaction with simulation management software, after the whole simulation model is determined to be capable of running off line, a simulation machine is selected as a target machine, the model is compiled, downloaded and run through simulation software, and a real-time simulation platform of the self-navigation unmanned aerial vehicle semi-physical test system is built.
In step S3, the real self-navigation unmanned aerial vehicle component to be tested is connected to the real-time simulation platform to form a hardware-in-loop simulation and test platform.
In this embodiment, a real self-guided unmanned aerial vehicle component to be tested is connected to a real-time simulation platform of a self-guided unmanned aerial vehicle semi-physical test system to form a self-guided unmanned aerial vehicle semi-physical test system rapid control prototype and a hardware-in-loop simulation and test platform, and the real-time simulation platform of the self-guided unmanned aerial vehicle semi-physical test system configures corresponding hardware and communication interface modules according to an actual communication interface mode of the real component to be tested.
Different from a traditional semi-physical test mode, the method supports in-loop test of various self-navigation unmanned aerial vehicle key components, and can realize in-loop test of the following key components by utilizing access signals of hardware and a communication interface of a real component to be tested to replace signals of a corresponding simulation model: (1) testing a flight control computer and a control algorithm of the unmanned aerial vehicle; (2) testing sensors such as a gyroscope and an acceleration; (3) testing a seeker and a control algorithm; (4) testing circuits such as driving and voltage transformation; (5) and (5) testing the reliability in the failure mode. In addition, the test system designed in the embodiment also supports joint test simulation of various self-navigation unmanned aerial vehicle key components, and can comprehensively test the overall performance of the system.
In step S4, various control strategies and algorithm performance tests and verifications are performed on the hardware-in-loop simulation and test platform.
In this embodiment, the simulation management software running in the simulation upper computer can implement the following functions: setting simulation parameters such as system parameters, control parameters and reference signals of the simulation model; setting simulation working conditions, including conventional design working conditions and fault working conditions (such as circuit faults, signal transmission faults and the like); the acquisition and display of simulation data comprises the following steps: seeker data, self-navigation unmanned aerial vehicle body attitude data and the like, and a data post-processing function after the test is finished.
In step S5, after the test is finished, a relevant test report is output according to the test result, and the control strategy and the effect of the relevant algorithm are analyzed and evaluated.
In the embodiment, after the working condition set by the simulation, according to the data result recorded and stored in the simulation upper computer in the test process, the corresponding data report and the test report are output, the control strategy and the algorithm effect are analyzed and evaluated, the analysis result is fed back to the designer, and the optimization work of the algorithm is completed based on the result.
According to the test method and steps described above, the structure of a real-time simulation test platform suitable for the self-navigation unmanned aerial vehicle test system in the embodiment is shown in fig. 5, and the schematic structural diagram of an enlarged version of the real-time simulation target machine-unmanned aerial vehicle system simulation model is shown in fig. 6. The real-time simulation test platform mainly comprises the following three parts:
1) a component to be tested: the real measured object is connected with the real-time simulation platform through a hardware IO or an interface mode of a communication interface to realize data interaction, so as to replace signals of a corresponding simulation model, for example, a component to be measured comprises a flight controller, a seeker and a fault mode test of the unmanned aerial vehicle, and also comprises a gyroscope, an acceleration sensor, an inverter, a voltage transformation circuit and the like, which are not listed herein;
2) the simulation management system comprises: the method comprises the following steps of connecting and communicating with a real-time simulation platform through an Ethernet, and building models such as an aircraft electrical system model, a target motion control model, a seeker motion control model and a motion control model of a self-navigation unmanned aerial vehicle body based on Matlab/Simulink software; the functions of model configuration, automatic compiling, downloading, running and the like of the model are realized through a simulation software environment according to real-time simulation requirements; the simulation management software realizes the setting of relevant parameters of the test system and the input of test conditions, records data in the simulation test process in real time, and can automatically generate a test report and a report from the simulation test result;
3) a real-time simulation platform: the real-time simulation target machine can run an electrical system model of the self-navigation unmanned aerial vehicle in real time, and comprises a DC-DC direct-current transformer, a motor driver, a corresponding bleeder circuit, a protection circuit and fault models such as short circuit, grounding, open circuit and the like; and a motion and control model comprising: the motion control model comprises a target motion control model, a seeker motion control model and a motion control model of a self-navigation unmanned aerial vehicle body. The hardware data interface unit comprises an analog input and output interface, a digital input and output interface, and various data interfaces such as RS422, 1553B, optical fibers and CAN, and is mainly responsible for realizing real-time signal interaction between the part to be tested and the simulator.
In the embodiment, the requirements of research and development of the self-navigation unmanned aerial vehicle are comprehensively considered, the designed semi-physical test system of the self-navigation unmanned aerial vehicle integrates modeling and control technologies of various components such as a target, a seeker and an unmanned aerial vehicle, real-time test of various key components such as a flight control computer, a gyroscope and an acceleration sensor, the seeker, a driving circuit and a transformation circuit and joint test among the components can be realized by combining real-time simulation of a target machine, real-time calculation and real components to be tested, real and reliable control objects and operation environments are provided for research and development and test of the self-navigation unmanned aerial vehicle, and comprehensive software, hardware and communication in-loop test is performed on aspects such as optimized operation, cooperative control and fault protection of the components of the self-navigation unmanned aerial vehicle.
Fig. 7 is a schematic structural diagram of a self-navigation test system 1 for an unmanned aerial vehicle according to an embodiment of the present invention.
In the present embodiment, the self-navigation unmanned aerial vehicle test system 1 includes a modeling module 2, a download module 3, a connection module 4, a verification module 5, and an output module 6.
And the modeling module 2 is used for building a plurality of models based on the simulation upper mechanism and coupling the models.
In this embodiment, the plurality of models may be divided into two groups, one group being an electrical system model and the other group being a non-electrical system model. Wherein the plurality of models includes an electrical system model, the modeling module 2 is further configured to:
and establishing the electric system model including the direct current transformer, the motor driver, the bleeder circuit, the protection circuit and the electric system fault based on the simulation upper mechanism.
In the embodiment, an electrical system model in the self-navigation unmanned aerial vehicle test system is established on a simulation upper computer based on Matlab/Simulink, wherein the electrical system model mainly comprises a DC-DC direct current transformer, a motor driver, a corresponding bleeder circuit, a protection circuit and the like. In addition, the electric system model also comprises an electric system fault model which is used for realizing fault modes such as short circuit, grounding, open circuit and the like caused by aging or failure of devices such as resistors, inductors, chips and the like.
In this embodiment, the plurality of models include a non-electrical system model, the non-electrical system model includes a target motion control model, a seeker motion control model, a motion control model of the self-navigation unmanned aerial vehicle body, and a model for signal transmission and processing, and the modeling module 2 is further configured to:
simulating the motion state of a target, and constructing a target motion control model on a simulation upper computer;
simulating the motion process of a seeker steering engine, and constructing a seeker motion control model on a simulation upper computer;
simulating the process from the generation of the control signal to the change of the flight state of the self-navigation unmanned aerial vehicle body, and constructing a motion control model of the self-navigation unmanned aerial vehicle body on a simulation upper computer;
and simulating interference in a real environment, and constructing a signal transmission and processing model on the simulation upper computer.
In the embodiment, the non-electrical system model can comprehensively simulate the whole motion control process of the target, the seeker and the self-navigation unmanned aerial vehicle body, can truly reflect the guidance state of the self-navigation unmanned aerial vehicle, and is convenient for carrying out comprehensive test on the overall performance of the self-navigation unmanned aerial vehicle. In addition, due to the adoption of a modular design idea, the non-electrical system model also has the capability of independently testing each subsystem, which is very important for the analysis and the optimized operation of the self-navigation unmanned aerial vehicle system.
In the embodiment, the target motion control model simulates the motion state of a target and provides target information for tests such as seeker control, unmanned aerial vehicle guidance and tracking. The target motion control model is realized by adopting a double-shaft turntable model, wherein the yaw angle and the pitch angle are used for simulating the position change of a target in the horizontal and height directions.
In the embodiment, the seeker motion control model simulates the motion process of the seeker steering engine, and the seeker provides accurate positioning information for tasks such as target tracking, fixed-point take-off and landing of the self-navigation unmanned aerial vehicle. The seeker movement control model mainly comprises: a kinematics model, a tracking controller model and a target calibration model. The kinematics model adopts a double-shaft turntable controlled by double motors to simulate the motion process of a seeker steering engine. The tracking controller model adopts four-ring control strategies of a current ring, a speed ring, a stabilizing ring and a position ring, and ensures the accurate control of the seeker. The target calibration model is used for identifying the position of the target and forming a guide instruction to be sent to the motion control model of the self-navigation unmanned aerial vehicle body. In addition, according to different calculation algorithms, target information can be determined by using information modes such as vision, radar and the like, so that the method is widely applied to testing of various guide heads.
In this embodiment, the motion control model of the self-piloting unmanned aerial vehicle body is used for simulating the process from the generation of the control signal to the change of the flight state of the self-piloting unmanned aerial vehicle body, and is mainly divided into three parts: the system comprises a flight controller module, a kinematics and dynamics module and a sensor module. The flight controller module simulates a flight control computer of the unmanned aerial vehicle, receives a target signal sent by a seeker, combines the self attitude and position information and strategies such as path optimization, and adopts a control algorithm to complete the calculation of a control law and the output of a control signal. The kinematics and dynamics module simulates the attitude kinematics characteristics of the actuator and the unmanned aerial vehicle, receives the output signal of the flight controller module, and realizes the attitude adjustment of the unmanned aerial vehicle through the control of a plurality of motors and the actuator. The sensor module mainly simulates sensor functions of a gyroscope, an accelerometer and the like, and feeds signals such as self-navigation unmanned aerial vehicle body attitude and the like back to the flight controller module to realize unmanned aerial vehicle control.
In the embodiment, the signal transmission and processing model simulates interference in a real environment, and the signal transmission and processing model is adopted to receive the position signal of the target and transmit the position signal to the guide head module through different modes. The model of this signal transmission and processing can utilize different information processing strategies, realizes the transmission of multiple signal mode including signals such as vision, radar to satisfy self-navigation unmanned vehicles's test demand, wherein, radar target echo signal's production flow includes: the down-conversion of input signals, superposition delay, Doppler frequency and the like, up-conversion, power control and output. In addition, an interference injection module is adopted in a signal transmission and processing model, so that disturbing signals such as false target signals and noise signals can be added into basic signals to simulate interference in a real environment, and the signal transmission and processing model has high reality and wide applicability.
In this embodiment, the modeling module 2 is further configured to:
coupling the electrical system model and the non-electrical system model is accomplished by using or controlling power, measurement signals, and door opening and closing signals in the electrical system of the self-navigating unmanned aerial vehicle.
In the present embodiment, an electronic solution technology is mainly used to couple and associate an electrical system model of a self-navigation unmanned aerial vehicle with a non-electrical system model (including a target motion control model, a seeker motion control model, a motion control model of a self-navigation unmanned aerial vehicle body, and a model for signal transmission and processing). In the embodiment, an electronic calculation technology is designed, so that the non-electrical system model is coupled with the electrical system model of the self-navigation unmanned aerial vehicle by using or controlling a power supply, a measurement signal and a door opening and closing signal in the electrical system of the self-navigation unmanned aerial vehicle. In addition, the electronic calculation technology designed in the embodiment can automatically translate the electrical system designed based on Simulink into hardware language on the premise of not needing FPGA code compiling experience, and automatically download the electrical system model to FPGA for operation in real-time simulation. The electronic calculation technology can make full use of the characteristics of the FPGA, so that the system has a high calculation rate, the transient characteristics of an electrical system can be accurately simulated, and the coupling relation of the system is shown in FIG. 2.
And the downloading module 3 is used for compiling the coupled model and downloading the model to a simulation target machine for real-time operation so as to build a real-time simulation platform.
In the embodiment, the self-navigation unmanned aerial vehicle test model is arranged and configured according to the requirements of real-time simulation, and comprises self-navigation unmanned aerial vehicle components needing to be tested, a signal interface and a communication module for data interaction with simulation management software, after the whole simulation model is determined to be capable of running off line, a simulation machine is selected as a target machine, the model is compiled, downloaded and run through simulation software, and a real-time simulation platform of the self-navigation unmanned aerial vehicle semi-physical test system is built.
And the connecting module 4 is used for connecting the real self-navigation unmanned aerial vehicle component to be tested to the real-time simulation platform so as to form a hardware-in-loop simulation and test platform.
In this embodiment, a real self-guided unmanned aerial vehicle component to be tested is connected to a real-time simulation platform of a self-guided unmanned aerial vehicle semi-physical test system to form a self-guided unmanned aerial vehicle semi-physical test system rapid control prototype and a hardware-in-loop simulation and test platform, and the real-time simulation platform of the self-guided unmanned aerial vehicle semi-physical test system configures corresponding hardware and communication interface modules according to an actual communication interface mode of the real component to be tested.
And the verification module 5 is used for testing and verifying the performance of various control strategies and algorithms on the hardware-in-loop simulation and test platform.
In this embodiment, the simulation management software running in the simulation upper computer can implement the following functions: setting simulation parameters such as system parameters, control parameters and reference signals of the simulation model; setting simulation working conditions, including conventional design working conditions and fault working conditions (such as circuit faults, signal transmission faults and the like); the acquisition and display of simulation data comprises the following steps: seeker data, self-navigation unmanned aerial vehicle body attitude data and the like, and a data post-processing function after the test is finished.
And the output module 6 is used for outputting a related test report according to the test result after the test is finished, and analyzing and evaluating the control strategy and the effect of the related algorithm.
In the embodiment, after the working condition set by the simulation, according to the data result recorded and stored in the simulation upper computer in the test process, the corresponding data report and the test report are output, the control strategy and the algorithm effect are analyzed and evaluated, the analysis result is fed back to the designer, and the optimization work of the algorithm is completed based on the result.
In this embodiment, the detailed functions of each module in the apparatus item can be referred to the detailed description of the corresponding position in the foregoing method item, and will not be described repeatedly here.
In addition, the invention also provides communication equipment, wherein the communication equipment comprises a memory and a processor, the memory stores computer processing instructions, and the processor executes the self-navigation unmanned aerial vehicle testing method by calling the computer processing instructions.
In addition, the present invention also provides a computer readable storage medium, wherein the computer readable storage medium has a computer program stored thereon, and the computer program, when executed by a processor, implements the steps of the self-navigation unmanned aerial vehicle testing method described above.
The technical scheme provided by the invention has the following advantages:
1) the technical scheme of the invention provides a convenient graphical modeling environment, and can realize the modeling of a dynamic system of a differential algebraic equation or an ordinary differential equation and a discrete event model; developers can complete modeling and simulation of a system model with extremely high refinement degree without implementing a large amount of codes and algorithms, so that development time is saved;
2) according to the self-navigation unmanned aerial vehicle testing system of the real-time simulation platform, distributed parallel calculation is realized according to the characteristics of various models in different time scales, a slowly-varying model (such as a kinematics and dynamics module) is placed into a CPU to realize large-step simulation, a quickly-varying model (such as an electric system model of the self-navigation unmanned aerial vehicle) is placed into an FPGA to realize quick small-step simulation, and the transient characteristics of an electric system are accurately simulated;
3) the method comprises the steps that an electric system model and a non-electric system model (including a target motion control model, a seeker motion control model, a motion control model of a self-navigation unmanned aerial vehicle body and a signal transmission and processing model) of the self-navigation unmanned aerial vehicle are coupled and associated through an electronic calculation technology, the electronic calculation technology can automatically translate an electric system designed based on Simulink into a hardware language on the premise of not needing hardware programming experience such as Verilog, and the coupling of the electric system model and the non-electric system model is achieved through transmission of a power supply, a measurement signal and a gate opening and closing signal, so that the barrier that the original FPGA is complex in programming and difficult to debug is broken;
4) based on a modularized joint design method, the real-time simulation platform has various test modes, not only supports independent test of each subsystem, but also supports joint simulation test of multiple components, so that the platform can simultaneously have the independent test capability of each subsystem and the integral comprehensive performance test capability of the system, thereby solving the problems that the test object of the original test system is single and the integral performance of the system cannot be completely mastered, and in addition, the platform can repeatedly simulate the operation of the self-navigation unmanned aerial vehicle system under various working conditions, including the simulation of electrical faults (such as direct-current voltage short circuit and short circuit of other resistors and chips, grounding and open circuit fault modes) and communication faults (such as noise, packet loss and the like), and can realize the omnibearing test and verification of the control strategy and reliability of the self-navigation unmanned aerial vehicle;
5) in addition, the real-time simulation platform can realize parameterized configuration of a simulation model, can modify relevant parameters of a system, a controller and the like on line, change the running state in real time, does not need to be downloaded and compiled again, and can realize on-line real-time debugging of control parameters according to running waveforms and data before and after parameter modification.
It should be noted that, in the above embodiments, the included units are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be realized; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
In addition, it can be understood by those skilled in the art that all or part of the steps in the method for implementing the embodiments described above can be implemented by instructing the relevant hardware through a program, and the corresponding program can be stored in a computer readable storage medium, such as a ROM/RAM, a magnetic disk, or an optical disk.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
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