CN112486141B - Unmanned aerial vehicle flight control program modeling and verifying method based on time automaton - Google Patents

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

A Modeling and Verification Method of UAV Flight Control Program Based on Time Automata

technical field

The invention relates to a method for modeling and verifying a UAV flight control program based on a time automaton, and belongs to the technical field of UAV automatic control.

Background technique

In recent years, UAVs have been widely used in environmental monitoring, meteorological detection, infrastructure operation and maintenance and other application scenarios. With the increasingly complex application environment and increasingly diverse tasks of UAVs, the remote control of UAVs and the formation coordination of multiple UAVs based on wireless communication have become an important development trend. However, factors such as the uncertainty of aerodynamic parameters and the failure of the actuator will seriously reduce the control accuracy of the UAV. Due to the openness of wireless communication, there are also influencing factors such as electromagnetic environment interference.

In order to improve the robustness of the UAV to unknown disturbances and actuator failures, the state error limit and the tracking error convergence performance, the UAV control algorithm needs to be optimized. For example, Beijing University of Aeronautics and Astronautics proposed a fault-tolerant guidance control method for UAV fixed-time path tracking, which uses backstepping method and fixed-time convergence line-of-sight guidance algorithm to ensure that UAV path tracking error converges within a fixed time. The fixed-time observer performs estimation compensation for the uncertainty, eliminating the influence of factors such as actuator failure and external environmental disturbance on the tracking performance (Journal of Beihang University, 2020.7), and so on.

However, it is difficult to accurately measure the unknown interference value, especially when the communication delay is large, the normal information exchange and the correct execution of the control algorithm may not be guaranteed. Therefore, it is very important to study the UAV control under the condition of communication delay. realistic meaning. For example, Northwestern Polytechnical University proposed a multi-UAV sliding mode consistent formation control method with time delay and interference constraints. Based on the consideration of time delay, an appropriate consensus algorithm was designed, and the sliding mode control (SMC) method was used to solve the formation system. Trajectory tracking and control problems in the system, and ensure the robustness of the system to external disturbances (Journal of Northwestern Polytechnical University, 2020.4).

In a word, the design and testing of the UAV flight control program is a complex technical problem, because it involves both automatic control algorithms and performance related to communication. To ensure the correctness of remote control commands, it is necessary to ensure the timeliness of information interaction. The communication process is completed within the specified time. The test of the control program is generally based on the typical black box test, and there is a problem that the test case cannot completely cover it. The industry adopts formal verification to avoid the above-mentioned test coverage problems. The basic idea is to check whether the system model satisfies the given properties by traversing the state space of the system model. For example, Yunnan University proposed a formal verification method for the stability of a robot fractional-order PID controller. The formal model is used to verify the stability of the fractional-order PID control system by using the formal model and theorems. However, this patent does not consider the wireless communication in the control process, so it cannot be fully applied to the scenario where the drone has electromagnetic interference on the wireless channel, and the factors such as the uncertainty of aerodynamic parameters and the intermittent failure of the actuator are insufficiently considered.

SUMMARY OF THE INVENTION

Aiming at the nonlinear characteristics and interference of unmanned aerial vehicles, problems such as random interference and communication delay need to be considered. , to establish a formal model of the UAV flight control program to verify the correctness of the control algorithm; at the same time, random factors are introduced, and through multiple simulations, the timeliness is counted, and improved in the presence of communication delays, external interference, etc. Robustness of drone flight control.

The present invention specifically adopts the following technical solutions to solve the above-mentioned technical problems:

A method for modeling and verifying a UAV flight control program based on a time automaton, comprising the following steps:

Step 1. Divide the command interaction process of the UAV flight control program into the main control process, message transmission, and wireless channel, and define the state and transition characteristics in the time automaton model based on the time automata formal modeling method;

Step 2. Based on the defined state and transition characteristics, establish a time automaton model of the UAV flight control program, and use a formal verification tool to perform a state space search to verify that the timing sequence of the UAV flight control program is correct;

Step 3. In view of the interference of the working environment of the UAV, define the interference factors in the state and transition characteristics, and regenerate the correlation matrix of the time automaton model to verify the boundedness of the time automaton model, that is, the flight of the UAV. The timeliness performance of the control program execution is confirmed within a limited time;

Step 4. Analyze the communication time consumption based on probability statistics, and verify that the operation process of the UAV flight control program can be completed within a predetermined time.

Further, as a preferred technical solution of the present invention, the step 1 defines the state and transition characteristics, specifically:

M=(L, Π, S, T, C, G, E)

Among them, L represents the three model levels of the main control process, message transmission and wireless channel of the UAV flight control program, Π represents the set of time constraints and message types of the main control process; S represents the state set in the time automaton model ; T represents the transition set, including the transition between model levels L, as well as the transition of message transmission and state transition; C represents the correspondence between S and Π; G represents the condition function including state transition; E represents the state caused by message transmission and timeout processing Converted expression function.

Further, as a preferred technical solution of the present invention, the step 2 establishes a time automaton model of the UAV flight control program, including:

Determine the state set S and transition set T of the UAV containing elements:

S = {s ₀ ... s _j | j∈0, 1, 2...}

T={t ₀ ...t _i |i∈0, 1, 2...}

Among them, s _j represents various states of the drone; t _i represents the transition between the states of the drone;

The UAV flight control program is modeled as a time automaton model, which is represented by an association matrix R:

Among them, r _ij represents the relationship between the transition t _i of the UAV and the state s _j .

Further, as a preferred technical solution of the present invention, the step 3 defines interference factors in the state and transition characteristics, including:

The state SOT is added to the message transmission model and the wireless channel model to define the timeout of the control event due to external interference; the expression function E is added to represent the interference factor.

Further, as a preferred technical solution of the present invention, the step 4 analyzes the communication time consumption based on probability statistics, including: introducing random factors into the transition model, the packet loss rate is simulated by the execution conditions of the transition, and the delay is passed through. Execution time simulation of state transition function G.

The present invention adopts the above-mentioned technical scheme, and can produce the following technical effects:

The method of the invention establishes a time automaton model based on a formal method, verifies the operability of the UAV flight control program through state space search, and analyzes the boundedness of the time automaton model, so as to alleviate the state space explosion problem; External interference in wireless remote control introduces random factors such as external electromagnetic environment interference, aerodynamic parameter uncertainty, and actuator failure. Robustness in complex environments. The invention has a wide range of applications, and can be applied to multi-functional UAV flight control, UAV formation, UAV-based meteorological detection, equipment inspection, and the like.

Description of drawings

FIG. 1 is a schematic flowchart of a method for modeling and verifying a UAV flight control program based on a time automaton according to the present invention.

FIG. 2 is a schematic diagram of a time automaton model of a UAV flight control program provided by the present invention.

Detailed ways

The technical solutions provided by the present invention will be described in detail below with reference to specific embodiments. It should be understood that the following specific embodiments are only used to illustrate the present invention and not to limit the scope of the present invention.

Embodiment 1, taking a certain existing drone flight control system as an example, the system can be applied to widely used drones such as quadrotor drones. Lidar, etc., can judge its own flight attitude, realize functions such as obstacle avoidance, and can accept external instructions to complete specific tasks. The present invention provides a method for modeling and verifying a UAV flight control program based on a time automaton. The modeling and verification process for the flight control program is shown in Figure 1, and specifically includes the following steps:

Step 1. The command interaction process of the UAV flight control program is divided into the main control process, message transmission, and wireless channel. The present invention is based on the time automata formal modeling method to define the relevant states and transition characteristics in the time automata model. ,Specifically:

M=(L, Π, S, T, C, G, E)

Among them, L represents the three model levels of the main control process, message transmission and wireless channel of the UAV flight control program, Π represents the set of time constraints and message types of the main control process; S represents the state set in the time automaton model ; T represents the transition set, including the transition between model levels L, as well as the transition of message transmission and state transition; C represents the correspondence between S and Π; G represents the condition function including state transition; E represents the state caused by message transmission and timeout processing Converted expression function.

Step 2. Based on the defined state and transition characteristics, establish a time automaton model of the UAV flight control program, use a formal verification tool to search the state space, and verify whether the timing of the UAV flight control program is correct;

According to the definition in step 1, the UAV flight control program is modeled as a time automaton model. Some models related to wireless communication are shown in Figure 2. The current state, controlled state, out-of-control, communication process and other states of the UAV are defined as the state set S:

S = {s ₀ ... s _j | j∈0, 1, 2...}

Similarly, as shown in Figure 2, the transitions of the UAV's establishment of communication links, task cycle execution, interruption control, and data transmission are defined as transition set T:

T={t ₀ ...t _i |i∈0, 1, 2...}

Among them, s ₀ ... s _j represents various states of the UAV; t ₀ ... t _i represents the transition between the states of the UAV;

The above-mentioned states s ₀ ... s _j are marked with UAVC, UAVP, ERR, COMM, etc. in FIG. 2 ; the above-mentioned transitions t ₀ ... t _i are marked with COMMConf, TaskProc, InterruptCon, SendData, etc. in FIG. 2 .

The UAV flight control program is modeled as a time automaton model containing j+1 states and i+1 transitions, which can be represented by an association matrix R:

Among them, r _ij represents the relationship between transition t _i and state s _j ;

Based on the correlation matrix R, the boundedness of the time automaton model is verified. On this basis, a formal verification tool is used to search the state space. The general SPIN tool can be used to describe the above model in PROMELA language to verify whether the timing of the control process is correct. .

Step 3. In view of the interference of the working environment of the drone, define the interference factor in the state and transition characteristics described in step 1, and add the state SOT to the message transmission model and wireless channel model to define the timeout of the control event due to external interference. , in the expression function E, the representation of electromagnetic, airflow and other interference factors is added, and the interference factors are set empirical values. And regenerate the correlation matrix of the temporal automaton model, and verify the boundedness of the temporal automaton model in the same way as in step 2, that is, the timeliness performance of the UAV flight control program execution is confirmed within a limited time.

Step 4. Analyze the communication time consumption based on probability statistics, and verify that the operation process of the UAV flight control program can be completed within a predetermined time.

The communication time consumption is analyzed based on probability statistics, that is, random factors such as electromagnetic interference and airflow are introduced into the transition model, such as the InterruptCon transition in Figure 2, and the random function rand is introduced into the execution conditions to simulate the delay, so that each simulation There are random differences in the delay, that is, the packet loss rate is simulated by the execution condition of the transition, the delay is simulated by the execution time of the state transition function G, and the delay is simulated by the execution time. On this basis, the verification process in step 3 is performed multiple times, that is, the state space search is repeated, so as to simulate the execution time of the UAV flight control program. Complete execution.

To sum up, the method of the present invention introduces random factors such as external electromagnetic environment interference, aerodynamic parameter uncertainty, actuator failure and other random factors for the external interference in the wireless remote control, and through multiple simulations, the timeliness of the UAV flight control program is improved. Perform statistical analysis to improve the robustness of UAVs in complex environments. The invention has a wide range of applications, and can be applied to multi-functional UAV flight control, UAV formation, UAV-based meteorological detection, equipment inspection, and the like.

The technical means disclosed in the solution of the present invention are not limited to the technical means disclosed in the above embodiments, but also include technical solutions composed of any combination of the above technical features. It should be pointed out that for those skilled in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications are also regarded as the protection 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 automata model of the unmanned aerial vehicle flight control program based on the defined state and transition characteristics, 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 main 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 message types of the main 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 represents a state transition function; e represents the expression function for message transmission, timeout handling causing state transitions.

3. The unmanned aerial vehicle flight control program modeling and verification method based on the time automaton as claimed in claim 1, wherein the step 2 of establishing a time automaton model of the unmanned aerial vehicle flight control program comprises:

determining that the state set S and the transition set T of the unmanned aerial vehicle contain elements:

S={s ₀ …s _s |j∈0,1,2…}

T={t ₀ …t _i |i∈0,1,2…}

wherein s is _j Representing various states of the drone; t is t _i Representing 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:

wherein r is _ij Representing transitions t of drones _i And state s _j The 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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