CN112486141A - Unmanned aerial vehicle flight control program modeling and verifying method based on time automaton - Google Patents

Unmanned aerial vehicle flight control program modeling and verifying method based on time automaton Download PDF

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CN112486141A
CN112486141A CN202011351643.2A CN202011351643A CN112486141A CN 112486141 A CN112486141 A CN 112486141A CN 202011351643 A CN202011351643 A CN 202011351643A CN 112486141 A CN112486141 A CN 112486141A
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unmanned aerial
aerial vehicle
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刘佳
钱昌宇
卞方舟
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Nanjing University of Information Science and Technology
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    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract

The invention discloses an unmanned aerial vehicle flight control program modeling and verifying method based on a time automaton, which comprises the following steps: dividing a command interaction process of an unmanned aerial vehicle flight control program into a master control process, message transmission and a wireless channel, and defining the state and the transition characteristic in a time automaton model; establishing a time automaton model of the unmanned aerial vehicle flight control program, searching a state space by using a formal verification tool, and verifying that the time sequence of the unmanned aerial vehicle flight control program in the operation process is correct; aiming at the interference of the working environment of the unmanned aerial vehicle, defining interference factors in the state and the transition characteristic, regenerating a correlation matrix of a time automaton model, and verifying the boundedness of the model, namely confirming the timeliness performance executed by the flight control program of the unmanned aerial vehicle in limited time; and analyzing the communication time consumption based on probability statistics, and verifying that the unmanned aerial vehicle flight control program operation process can be completed within a preset time. The invention can improve the robustness of the unmanned aerial vehicle in a complex environment.

Description

Unmanned aerial vehicle flight control program modeling and verifying method based on time automaton
Technical Field
The invention relates to an unmanned aerial vehicle flight control program modeling and verifying method based on a time automaton, and belongs to the technical field of unmanned aerial vehicle automatic control.
Background
In recent years, unmanned aerial vehicles are widely applied in application scenes such as environment monitoring, meteorological detection, infrastructure operation and maintenance and the like. Along with the increasing complexity of application environments and the increasing diversity of tasks of unmanned aerial vehicles, remote control of unmanned aerial vehicles and formation cooperation of multiple unmanned aerial vehicles based on wireless communication have become important development trends. However, the control accuracy of the unmanned aerial vehicle is seriously reduced by factors such as uncertainty of pneumatic parameters and faults of an actuating mechanism, and influence factors such as electromagnetic environment interference exist due to the openness of wireless communication.
In order to improve the robustness of the unmanned aerial vehicle to unknown interference and actuator faults, state error limitation and tracking error convergence performance, an unmanned aerial vehicle control algorithm needs to be optimized. For example, Beijing aerospace university proposes a fixed time path tracking fault-tolerant guidance control method for an unmanned aerial vehicle, which ensures that the path tracking error of the unmanned aerial vehicle converges within fixed time by using a backstepping method and a fixed time convergence sight guidance algorithm, estimates and compensates uncertainty by using a nonlinear fixed time observer, and eliminates the influence of factors such as actuator faults and external environment interference on tracking performance (Beijing aerospace university academic newspaper, 2020.7), and the like.
However, the unknown interference value is difficult to be accurately measured, and especially when the communication delay is large, normal information interaction and correct execution of a control algorithm may not be guaranteed, so that it is very important to research unmanned aerial vehicle control under the condition of communication delay. For example, northwest industrial university proposes a multiple unmanned aerial vehicle sliding mode consistency formation control method with time delay and interference constraints, designs a proper consistency algorithm on the basis of considering time delay, solves the problems of track tracking and control in a formation system by using a Sliding Mode Control (SMC) method, and ensures the robustness of the system to external disturbance (university of northwest industrial university, 2020.4).
In summary, the design and testing of the flight control program of the unmanned aerial vehicle are complex technical problems, because the design and testing relate to both the automatic control algorithm and the performance related to communication, and to ensure the correctness of the remote control command, the timeliness of information interaction needs to be ensured, and the communication process is completed within a specified time. The test of the control program is generally based on a typical black box test at present, and the problem that the test case cannot be completely covered exists. The industry uses formal verification to avoid the test coverage problem described above. The basic idea is to check whether the system model satisfies a given property by traversing the state space of the system model. For example, Yunnan university proposes a formal verification method for stability of a robot fractional order PID controller, the application number is 201610485045.1, a high-order logic formal model of the fractional order PID controller and a fractional order closed-loop control system is established for the robot fractional order PID controller, and the stability of the fractional order PID control system is verified by utilizing the formal model and theorem. However, the patent does not consider wireless communication in the control process, and is not completely applicable to a scene that the unmanned aerial vehicle has electromagnetic interference on a wireless channel, and the consideration on factors such as uncertainty of pneumatic parameters and intermittent faults of an actuating mechanism is insufficient.
Disclosure of Invention
Aiming at the problems of random interference, communication delay and the like of the nonlinear characteristic and the received interference of the unmanned aerial vehicle, the invention provides a method for modeling and verifying the flight control program of the unmanned aerial vehicle based on a time automaton, wherein a formalized model of the flight control program of the unmanned aerial vehicle is established based on the time automaton, and the correctness of a control algorithm is verified; meanwhile, randomness factors are introduced, time efficiency is counted through multiple times of simulation, and robustness of unmanned aerial vehicle flight control is improved under the conditions of communication time delay, external interference and the like.
The invention specifically adopts the following technical scheme to solve the technical problems:
an unmanned aerial vehicle flight control program modeling and verification method based on a time automaton comprises the following steps:
step 1, dividing a command interaction process of an unmanned aerial vehicle flight control program into a master control process, message transmission and a wireless channel, and defining states and transition characteristics in a time automaton model based on a time automaton formal modeling method;
step 2, establishing a time automaton model of the unmanned aerial vehicle flight control program based on the defined state and the transition characteristic, searching a state space by using a formal verification tool, and verifying that the time sequence of the unmanned aerial vehicle flight control program operation process is correct;
step 3, aiming at the interference of the working environment of the unmanned aerial vehicle, defining interference factors in the state and the transition characteristic, regenerating a correlation matrix of a time automaton model, and verifying the boundedness of the time automaton model, namely confirming the timeliness performance executed by the flight control program of the unmanned aerial vehicle in limited time;
and 4, analyzing the communication time consumption based on probability statistics, and verifying that the operation process of the unmanned aerial vehicle flight control program can be completed within a preset time.
Further, as a preferred technical solution of the present invention, the step 1 defines the state and the transition characteristic, specifically:
M＝(L，Π，S，T，C，G，E)
l represents three model levels of a master control process, message transmission and a wireless channel of an unmanned aerial vehicle flight control program, and pi is a set representing time constraint and a message type of the master control process; s represents a state set in the time automaton model; t represents a transition set, including the transitions between model levels L and the transitions of message transmission and state transition; c represents the corresponding relation between S and pi; g denotes a conditional function including state transitions; e represents the expression function for message transmission, timeout handling causing state transitions.
Further, as a preferred technical solution of the present invention, the step 2 of establishing a time automaton model of the unmanned aerial vehicle flight control program includes:
determining that the state set S and the transition set T of the unmanned aerial vehicle contain elements:
S＝{s0…sj|j∈0，1，2…}
T＝{t0…ti|i∈0，1，2…}
wherein s isjRepresenting various states of the drone; t is tiRepresenting transitions between states of the drone;
modeling an unmanned plane flight control program into a time automaton model, and expressing by using an incidence matrix R:
Figure BDA0002801063130000031
wherein r isijRepresenting transitions t of dronesiAnd statesjThe relationship between them.
Further, as a preferred technical solution of the present invention, the step 3 defines an interference factor in the state and transition characteristic, and includes:
adding state SOT in a message transmission model and a wireless channel model for defining the overtime of a control event due to external interference; the representation of the disturbance factor is added in the expression function E.
Further, as a preferred technical solution of the present invention, the step 4 of analyzing the communication time consumption based on probability statistics includes: random factors are introduced into the transition model, the packet loss rate is simulated through the execution conditions of the transition, and the delay is simulated through the execution time of the state conversion function G.
By adopting the technical scheme, the invention can produce the following technical effects:
the method is based on a formalization method, a time automatic machine model is established, the operability of the unmanned aerial vehicle flight control program is verified through state space search, the boundedness of the time automatic machine model is analyzed, and the problem of state space explosion is relieved; random factors such as external electromagnetic environment interference, uncertainty of pneumatic parameters, faults of an actuating mechanism and the like are introduced aiming at external interference in wireless remote control, and the timeliness of a flight control program of the unmanned aerial vehicle is subjected to statistical analysis through multiple times of simulation, so that the robustness of the unmanned aerial vehicle in a complex environment is improved. The invention has wide application range and can be applied to the flight control of multifunctional unmanned aerial vehicles, formation of unmanned aerial vehicles, meteorological detection based on the unmanned aerial vehicles, equipment inspection and the like.
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Fig. 1 is a schematic flow chart of the unmanned aerial vehicle flight control program modeling and verification method based on the time automaton.
Fig. 2 is a schematic diagram of a time automaton model of an unmanned aerial vehicle flight control program provided by the invention.
Detailed Description
The technical solutions provided by the present invention will be described in detail below with reference to specific examples, and it should be understood that the following specific embodiments are only illustrative of the present invention and are not intended to limit the scope of the present invention.
Embodiment 1 takes a certain current unmanned aerial vehicle flight control system as an example, and this system can be applicable to the unmanned aerial vehicle of wide application such as four rotor unmanned aerial vehicle, through carried inertial navigation system, camera, laser radar etc. when flying, judges the flight gesture of self, realizes keeping away functions such as barrier to can accept external instruction and accomplish specific task. The invention provides a modeling and verification method of an unmanned aerial vehicle flight control program based on a time automaton, wherein the modeling and verification process of the flight control program is shown in figure 1, and the method specifically comprises the following steps:
step 1, dividing the command interaction process of the unmanned plane flight control program into a master control process, message transmission and a wireless channel, defining relevant states and transition characteristics in a time automaton model based on a time automaton formalized modeling method, and specifically:
M＝(L，Π，S，T，C，G，E)
l represents three model levels of a master control process, message transmission and a wireless channel of an unmanned aerial vehicle flight control program, and pi is a set representing time constraint and a message type of the master control process; s represents a state set in the time automaton model; t represents a transition set, including the transitions between model levels L and the transitions of message transmission and state transition; c represents the corresponding relation between S and pi; g denotes a conditional function including state transitions; e represents the expression function for message transmission, timeout handling causing state transitions.
Step 2, establishing a time automaton model of the unmanned aerial vehicle flight control program based on the defined state and the transition characteristic, searching a state space by using a formal verification tool, and verifying whether the time sequence of the unmanned aerial vehicle flight control program operation process is correct or not;
and modeling the unmanned plane flight control program into a time automaton model according to the definition in the step 1. As shown in fig. 2, a part of models related to wireless communication define states of the unmanned aerial vehicle, such as a current state, a controlled state, an out-of-control state, and a communication process, as a state set S:
S＝{s0…sj|j∈0，1，2…}
similarly, as shown in fig. 2, transitions of the unmanned aerial vehicle, such as establishing a communication link, performing a task cycle, interrupting control, sending data, and the like, are defined as a transition set T:
T＝{t0…ti|i∈0，1，2…}
wherein s is0...sjRepresenting various states of the drone; t is t0...tiRepresenting transitions between states of the drone;
the above state s0...sjLabeled UAVC, UAVP, ERR, COMM, etc. in FIG. 2; transition t as described above0...tiFIG. 2 is marked with COMMConf, TaskProc, InterruptCon, SendData, etc.
Modeling the unmanned plane flight control program as a time automaton model containing j +1 states and i +1 transitions, which can be represented by a correlation matrix R:
Figure BDA0002801063130000051
wherein r isijRepresents a transition tiAnd state sjThe relationship between;
based on the correlation matrix R, the bounding property of the time automaton model is verified, on the basis, a formal verification tool is used for searching the state space, a general SPIN tool can be adopted, the model is described in a PROMELA language, and whether the time sequence of the control process is correct or not is verified.
And 3, aiming at the interference of the working environment of the unmanned aerial vehicle, defining interference factors in the state and transition characteristics in the step 1, adding a state SOT in a message transmission model and a wireless channel model for defining the overtime of a control event due to external interference, and adding the representation of the interference factors such as electromagnetism, airflow and the like in an expression function E, wherein the interference factors are set empirical values. And regenerating a correlation matrix of the time automaton model, and verifying the boundedness of the time automaton model in the same way as in the step 2, namely confirming the time efficiency of the unmanned aerial vehicle flight control program execution in a limited time.
And 4, analyzing the communication time consumption based on probability statistics, and verifying that the operation process of the unmanned aerial vehicle flight control program can be completed within a preset time.
Analyzing the communication time consumption based on probability statistics, namely introducing random factors such as electromagnetic interference, airflow and the like into a transition model, such as an interraptCon transition in FIG. 2, introducing a random function rand into an execution condition, simulating time delay, so that random difference exists in time delay of each simulation, namely packet loss rate is simulated through the execution condition of the transition, time delay is simulated through the execution time of a state conversion function G, and time delay is simulated through the execution time. On the basis, the verification process in the step 3 is executed for multiple times, namely, the state space search is repeatedly carried out, so that the execution time of the unmanned aerial vehicle flight control program is simulated, and the verification control process and the wireless remote control operation can be executed within the preset time according to the time sequence.
In conclusion, the method introduces random factors such as external electromagnetic environment interference, uncertainty of pneumatic parameters, faults of an execution mechanism and the like aiming at external interference in wireless remote control, and statistically analyzes the timeliness of the flight control program of the unmanned aerial vehicle through multiple times of simulation, so that the robustness of the unmanned aerial vehicle in a complex environment is improved. The invention has wide application range and can be applied to the flight control of multifunctional unmanned aerial vehicles, formation of unmanned aerial vehicles, meteorological detection based on the unmanned aerial vehicles, equipment inspection and the like.
The technical means disclosed in the invention scheme are not limited to the technical means disclosed in the above embodiments, but also include the technical scheme formed by any combination of the above technical features. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and such improvements and modifications are also considered to be within the scope of the present invention.

Claims (5)

1. An unmanned aerial vehicle flight control program modeling and verification method based on a time automaton is characterized by comprising the following steps:
step 1, dividing a command interaction process of an unmanned aerial vehicle flight control program into a master control process, message transmission and a wireless channel, and defining states and transition characteristics in a time automaton model based on a time automaton formal modeling method;
step 2, establishing a time automaton model of the unmanned aerial vehicle flight control program based on the defined state and the transition characteristic, searching a state space by using a formal verification tool, and verifying that the time sequence of the unmanned aerial vehicle flight control program operation process is correct;
step 3, aiming at the interference of the working environment of the unmanned aerial vehicle, defining interference factors in the state and the transition characteristic, regenerating a correlation matrix of a time automaton model, and verifying the boundedness of the time automaton model, namely confirming the timeliness performance executed by the flight control program of the unmanned aerial vehicle in limited time;
and 4, analyzing the communication time consumption based on probability statistics, and verifying that the operation process of the unmanned aerial vehicle flight control program can be completed within a preset time.
2. The unmanned aerial vehicle flight control program modeling and verification method based on the temporal automaton according to claim 1, wherein the step 1 defines state and transition characteristics, specifically:
M＝(L,Π,S,T,C,G,E)
l represents three model levels of a master control process, message transmission and a wireless channel of an unmanned aerial vehicle flight control program, and pi is a set representing time constraint and a message type of the master control process; s represents a state set in the time automaton model; t represents a transition set, including the transitions between model levels L and the transitions of message transmission and state transition; c represents the corresponding relation between S and pi; g denotes a conditional function including state transitions; e represents the expression function for message transmission, timeout handling causing state transitions.
3. The method for modeling and verifying the flight control program of the unmanned aerial vehicle based on the time automaton as claimed in claim 1, wherein the step 2 of establishing the time automaton model of the flight control program of the unmanned aerial vehicle comprises:
determining that the state set S and the transition set T of the unmanned aerial vehicle contain elements:
S＝{s0…sj|j∈0,1,2…}
T＝{t0…ti|i∈0,1,2…}
wherein s isjRepresenting various states of the drone; t is tiRepresenting transitions between states of the drone;
modeling an unmanned plane flight control program into a time automaton model, and expressing by using an incidence matrix R:
Figure FDA0002801063120000011
wherein r isijRepresenting transitions t of dronesiAnd state sjThe relationship between them.
4. The method for modeling and verifying the flight control program of the unmanned aerial vehicle based on the time automaton as claimed in claim 2, wherein the step 3 defines interference factors in the state and transition characteristics, including:
adding state SOT in a message transmission model and a wireless channel model for defining the overtime of a control event due to external interference;
the representation of the disturbance factor is added in the expression function E.
5. The method for modeling and verifying the flight control program of the unmanned aerial vehicle based on the time automaton as claimed in claim 2, wherein the step 4 is to analyze the communication time consumption based on probability statistics, and comprises:
random factors are introduced into the transition model, the packet loss rate is simulated through the execution conditions of the transition, and the delay is simulated through the execution time of the state conversion function G.
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