CN115981166B - Method, system, computer equipment and storage medium for controlling safe operation of motorcade - Google Patents
Method, system, computer equipment and storage medium for controlling safe operation of motorcade Download PDFInfo
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Abstract
The invention belongs to the technical field of safety operation control of motorcades, and particularly discloses a method, a system, computer equipment and a storage medium for safety operation control of motorcades. The control problem of the motorcade system studied by the invention can be regarded as the control problem of a multi-agent system, and the safety operation control method of the motorcade designed by the invention not only solves the cooperative control problem of the vehicle speed in the motorcade, but also considers the displacement path tracking and the like of the vehicles in the motorcade system, thereby having higher safety compared with the traditional motorcade system with the cooperative control of the speed. Meanwhile, in consideration of the problem of communication resource allocation, the fleet system studied by the invention adopts a distributed control method, namely, only data such as speed, distance and the like which need to be kept are transmitted to the head car, and information is transmitted between each car, so that the safe operation of the fleet system can be ensured.
Description
Technical Field
The invention belongs to the technical field of safety operation control of motorcades, and particularly relates to a method, a system, computer equipment and a storage medium for safety operation control of motorcades.
Background
In recent years, with the development of science and technology, the cooperative control of a fleet is also widely focused, and more problems of internal safety control of the fleet are also emerging. Therefore, the intelligent control is utilized to improve the safety and traffic efficiency of the fleet system, and has important significance for solving the problems. The team cooperative control is an intelligent multi-agent control method, is used for controlling the formation of vehicles on a single lane, and is beneficial to solving the overall control problem of the team. The main task of fleet control is how it can ensure that the speed of the following vehicle tracks the speed of the leading vehicle while maintaining a predetermined safe distance between the vehicles.
In addition, the traditional decentralized control has the advantages of strong pertinence, high information transmission efficiency and strong system adaptability, and has the defects of incomplete information, difficult overall coordination, high utilization rate of communication resources and global information required by vehicles at all times, thereby causing the waste of the communication resources. Many of the fleet systems under study are now based on mathematical models. However, due to the large-scale and complex development of vehicle systems, mathematical models thereof are often difficult to accurately build. Therefore, in the context of the big data age, data-driven control has attracted much attention. Model-free adaptive control (MFAC) is a data driven control method. The nonlinear system is expressed as a linear data model related to input and output data, and a control algorithm without system structure information is designed by using the linear data model. MFAC methods have been widely used in vehicle systems. Meanwhile, MFAC methods have been widely introduced into multi-agent systems to solve the problem of cooperative control.
Disclosure of Invention
The invention aims to provide a vehicle team safe operation control method which is not only beneficial to solving the cooperative control problem of the vehicle speed in a vehicle team system, but also considers factors such as the displacement path tracking of the vehicle, the failure of the vehicle in the vehicle team and the like so as to avoid collision in the vehicle team, so that the vehicle team system operation is safer; meanwhile, the invention also considers the problem of communication resource allocation, and adopts a distributed control method to ensure the safe operation of the motorcade system.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a vehicle team safe operation control method comprises the following steps:
step 1, establishing a dynamic model of a motorcade system;
step 2, converting a dynamic model of the motorcade system into a linearization model by using a dynamic linearization method;
step 3, giving control targets of the speed and the position of the motorcade system;
step 4, designing a distributed controller aiming at a motorcade control system;
and step 5, designing a performance function related to the control input and the pseudo partial derivative based on the linearization model and the distributed controller to obtain a control update law and a parameter estimation law of the fleet system, so as to realize safe operation control of the fleet.
In addition, on the basis of the fleet safety operation control method, the invention also provides a fleet safety operation control system which is suitable for the fleet safety operation control method, and the fleet safety operation control system adopts the following technical scheme:
a fleet safety operation control system, comprising:
the motorcade system model building module is used for building a dynamics model of the motorcade system;
the linearization module is used for converting a dynamic model of the motorcade system into a linearization model by using a dynamic linearization method;
the control target construction module is used for giving control targets of the speed and the position of the motorcade system;
the distributed controller design module is used for designing a distributed controller aiming at a fleet control system;
and the fleet safety operation control module is used for designing a performance function related to the control input and the pseudo partial derivative according to the linearization model and the distributed controller to obtain a control update law and a parameter estimation law of a fleet system and realize the fleet safety operation control.
In addition, on the basis of the fleet safety operation control method, the invention also provides computer equipment which comprises a memory and one or more processors.
The memory stores executable code, and the processor is used for realizing the steps of the fleet safety operation control method when executing the executable code.
Furthermore, on the basis of the fleet safety operation control method, the invention also provides a computer readable storage medium on which a program is stored.
The program, when executed by the processor, is adapted to carry out the steps of the above-mentioned fleet safety operation control method.
The invention has the following advantages:
as described above, the present invention describes a fleet safe operation control method, system, computer device, and storage medium. The control problem of the vehicle team system studied by the invention is regarded as the control problem of a multi-agent system, and the designed control method not only solves the problem of cooperative control of the speed of vehicles in the vehicle team, but also considers displacement path tracking and the like of the vehicles in the vehicle team system, compared with the traditional speed control problem, the distance kept between each two vehicles can be flexibly adjusted, so that the operation of the vehicle team system is safer. The linear data model designed by the invention can control the speed and the distance of the whole motorcade only by utilizing the brake and accelerator pedal control of the vehicle, and compared with the traditional dynamic model mode for establishing a state information matrix, the linear data model has the advantage of more solving the problem of processing a complex model of the vehicle. Meanwhile, the distributed control method is adopted in consideration of the problem of communication resource allocation, and only the data such as the speed, the distance and the like which need to be kept are transmitted to the head car, and the information is transmitted between each car, so that the safe operation of a motorcade system can be ensured. The control method of the motorcade designed by the invention can control the following motorcade through network communication only by controlling the brake and accelerator pedal of an operator on the head car.
Drawings
FIG. 1 is a flow chart of a method for controlling the safe operation of a fleet in an embodiment of the present invention.
Fig. 2 is a block diagram of a fleet system constructed in an embodiment of the present invention.
Fig. 3 is a communication diagram of a fleet system in an embodiment of the present invention.
Detailed Description
Example 1
The embodiment 1 describes a method for controlling safe operation of a fleet, so as to solve the problem of cooperative control of the vehicle speed in the fleet system and ensure that the fleet system operates more safely. In order to realize the above-mentioned motorcade safe operation control method, firstly, a motorcade system block diagram as shown in fig. 2 is built. In fig. 2, the actuators of the motorcade refer to the brake and the accelerator pedal of the automobile, the sensor is a speed position locator, the signal of each automobile in the motorcade is uploaded to a communication network and interacted with the speed position information of the neighbor automobile, and then the interacted neighbor automobile information is transmitted to the actuator end of the automobile, and the position and the speed of the automobile are controlled through the accelerator brake pedal, so that the control problem of the motorcade system is achieved.
Fig. 3 shows the safety distance of the motorcade in operation and the information interaction mode, and as can be seen from fig. 3, the follower 1 transmits information to the follower 2, the follower 2 transmits information to the follower 3, the follower 3 transmits information to the follower 4, and finally, the motorcade system can realize safe operation by only utilizing the information of the neighbor vehicles.
As shown in fig. 1, the fleet safety operation control method according to embodiment 1 includes the following steps:
step 1, establishing a dynamic model of a motorcade system, which is expressed as:
wherein,,irepresenting the first in a fleet systemiThe vehicle is a vehicle that is to be operated,i=1,2,…,n，nindicating the number of vehicles in the fleet system.
kIt is the moment in time when the vehicle is running,Tis the sampling time.
s i (k) Ands i (k+1) Respectively represent the first in the motorcade systemiVehicle atkTime of dayk+Displacement at time 1;v i (k) Andv i (k+1) Respectively represent the first in the motorcade systemiVehicle atkTime of dayk+Speed at time 1.
u i (k) Is an input to the system and is,u i (k) The expression of (2) is as follows:
u i (k)=a i (k)/[m i (k)r i (k)] (2)
a i (k) Is the firstiThe braking torque on the wheels of the vehicle,m i (k) Andr i (k) Respectively represent the firstiThe mass of the vehicle and the tire radius.
f i (v i (k) Is a nonlinear function, the expression of which is as follows:
f i (v i (k))=C a v i 2 (k)+gfcos(θ)+gsin(θ) (3)
C a andfrespectively represent the aerodynamic drag coefficient and the rolling drag coefficient,gandθthe gravitational constant and the slope angle are shown, respectively.
And 2, converting a dynamic model of the motorcade system into a linearization model by using a dynamic linearization method.
Δv i (k+1)=Δv i (k)+TΔu i (k)－Ψ i (k)Δv i (k) (4)
Wherein delta isv i (k)=v i (k)－v i (k-1) indicating that the vehicle is inkTime of day and time of dayk-a speed difference at time 1; deltav i (k+1) Indicating that the vehicle is ink+Time 1kA speed difference at the moment; deltau i (k) Indicating that the vehicle is inkTime of day and time of dayk-power input difference at time 1.
Ψ i (k) Is a pseudo partial derivative, and:
wherein,,v i (k-1) represents the firstiThe vehicle is at the firstk-speed at time 1.
Definition of the definitiony i (k)=[s i (k) v i (k) ] T And the linearization model is written in the following compact form:
y i (k+1)=A y i (k)+BΔu i (k)+C i (k)Δy i (k) (5)
wherein delta isy i (k)=y i (k)－y i (k-1) represents the firstiVehicle atkTime of day and time of dayk-displacement difference and velocity difference at time 1.
And step 3, on the basis of definite linearization model, giving control targets of the speed and the position of the motorcade system.
For a linearization model, a data-driven distributed control method is designed to realize a control task; the designed control method finally meets the following two conditions:
wherein,,Vrepresenting heel ofiVehicle adjacent neighbor set, the firstjThe vehicle is the firstiA neighbor vehicle of the vehicle;s j (k) Andv j (k) Respectively represent the firstjThe vehicle is at the firstkDisplacement and velocity of time of day.
ζ 1 Andζ 2 is a normal number of times, and the number of times is equal to the normal number,d ij is the firstiVehicle and the firstjMinimum safe distance between vehicles.
And 4, designing a distributed controller aiming at the fleet control system.
With a distributed controller, the desired speed and ideal following distance are transmitted by the lead vehicle to the vehicles behind the fleet and all vehicles can obtain information from the vehicles in front of and behind the neighbors; thus, the output of the distributed controller is described as:
wherein,,ξ i (k+1)、ξ i (k) Respectively represent the firstiDistributed controller of vehiclek+1 andkdisplacement and velocity of moment;Nrepresentation and the firstiThe number of vehicles adjacent to the vehicle,
representation and the firstiAll vehicles adjacent to the vehicle.
D ij =[d ij 0] T Indicating the safe distance of the vehicle and the speed at which the cooperative operation is maintained.
y j (k)=[s j (k) v j (k) ] T Whereins j (k) Andv j (k) Respectively represent the firstjThe vehicle is at the firstkDisplacement and velocity of moment; deltay j (k)=y j (k)－y j (k-1) represents the firstjVehicle atkTime of day and time of dayk-displacement difference and velocity difference at time 1;
Ψ j (k) Is a pseudo partial derivative, and:
it is possible that the air-conditioner is in a way that,v j *(k)∈(v j (k－1) ,v j (k) A) is provided; wherein,,v j (k－1)、v j (k) Represent the firstjThe vehicle is at the firstk－1、kVehicle speed at time.
In the above formula use
The establishment of this condition is based on a feedback controlleru i (k)=u i (k－1)+P i ξ i (k) And symmetry of undirected graph, i.ea ij =a ji 。
Wherein,,P i representation relates to distributed outputξ i (k) Feedback regulation factor of (i) about vehicleiVehicle following its neighborsjA feedback adjustment factor for distance, speed output of (c).
To facilitate distributed controller design, the output of the distributed controller is multiplied by two sidesI 2 =[1 1]The method comprises the following steps of:
ξ i (k+1)=I T ξ i (k)+a ii TΔu i (k)+δ ij (k) (8)
wherein,,
。
I T =[1,1+T]is a row vector designed to facilitate operation.
And step 5, designing a performance function related to the control input and the pseudo partial derivative based on the linearization model and the distributed controller to obtain a control update law and a parameter estimation law of the fleet system, so as to realize safe operation control of the fleet.
The control input is obtained by solving the following optimization problem:
wherein,,λ i is a penalty factor; solving the optimization problem and obtaining the control inputu i (k) The control update law of (2) is as follows:
wherein,,ρ i is a step factor; the following optimization problem is designed to estimate ψ i (k)：
Wherein,,
、/>
respectively represent vehiclesiIn the first placekAndkthe pseudo partial derivative at time-1, i.e. the part comprising the nonlinearity of the fleet system when it is converted from a nonlinear model to a linear model.
Solving the optimization problem to obtain a parameter estimation law of the pseudo partial derivative:
the control method of the fleet system is transformed as follows by combining the control update law and the parameter estimation law designed above:
wherein,,
the pseudo partial derivative of vehicle i at 1 st second is shown.
Wherein,,σis a positive constant greater than 0 and arbitrarily small.
Wherein,,
representing a vehiclejIn the first placekIs a pseudo-partial derivative of the first and second signals.
And realizing the safe operation control of the motorcade based on the control updating law and the parameter estimation law of the motorcade system.
As can be seen from the control methods of the fleet system, equations (13) - (15), the present invention addresses the problem of data driven fully distributed control of a nonlinear fleet, utilizing only the position and speed data of neighboring vehicles.
In addition, the control method of the invention also uses the data of the vehicle, which is also known data and does not relate to the information of the global network topology, so that the invention uses a completely distributed controller.
In addition, since the nonlinear fleet system is converted into the linearization model by the dynamic linearization mode, the nonlinear part of the fleet system is formed byΨ i (k) To express, to better update the pseudo-partial derivativeΨ i (k) A reset condition is added, and once the input increment is too small or the pseudo partial derivative is too small, the pseudo partial derivative is reset to the initial stateΨ i (k) Is thatΨ i (1)。
In addition, in order to verify the effectiveness of the fleet safety operation control method, the method also utilizes the compression mapping principle and the linear matrix inequality technology to demonstrate the feasibility of the fleet safety operation control method.
In order to ensure that the control objective in step 3 can be achieved, the following conditions are given for a given normal numberμ i 、ρ i 、λ i And a sampling time T, the fleet control target in step 3 may be achieved if the following conditions are met:
wherein the method comprises the steps of，PIs a positive definite matrix, and
wherein->
。
In order to prove the feasibility of the fleet safe operation control method, the compression mapping principle and the linear matrix inequality technology are needed. First, the estimated value of the pseudo partial derivative in the present invention is proved to be bounded, namely:
wherein,,
representing the parameter estimator atkEstimation error of time.
Second, distributed output values for fleet systemsξ i (k) Lyapunov equations are designed to solve the problem of cooperative control of fleet systems. The rewrite control law is as follows:
。
wherein the method comprises the steps of
，/>
And->
。
Inputting the control inputu i (k) Carry-in distributed outputξ i (k) In a compact form with respect to distributed output:
wherein,,
，/>
，/>
and->
。
Simplifying distributed outputξ i (k) The following form:
。
wherein,,
and: />
。
Design of Lyapunov functionV(k)=ξ i T (k)Pξ i (k) And is opposite tokTime +1kThe time is differentiated, and the formula is as follows:
according to known conditions
The method can obtain:
considering that the lyapunov difference function is bounded, and furthermore, the estimated value and the estimated error of the nonlinear pseudo-partial derivative according to the fleet system are bounded, the following inequality can be known:
wherein,,V(0)=ξ i T (0)Pξ i (0) Is the initial value of the output value of the distributed controller. As can be readily seen from the above formula,ξ i (k) Is bounded, meaning the feasibility of the fleet safe operation control method designed by the invention.
Compared with the traditional decentralized control scheme, the fleet safety operation control method in the embodiment 1 adopts a distributed control scheme for a fleet system, so that communication resources are saved more, and the flexibility, adaptability and reliability of the fleet are improved; meanwhile, the control method for the safe operation of the motorcade is not only the cooperative control problem on the speed of the vehicles in the motorcade system, but also the control of the safe distance between the motorcades, and the two factors are considered at the same time, so that the control method is more challenging.
The distributed controller used in the invention has outstanding control problems for a plurality of vehicles, can ensure the cooperative control of the speed of the motorcade and the control of the safety distance, and can obtain the expected speed and the safety distance of the operation of the motorcade by carrying out information interaction between each vehicle and the neighbors thereof, so that each vehicle is not required to directly carry out information interaction, and the consumption of communication resources is greatly reduced.
Example 2
Embodiment 2 describes a fleet safety operation control system based on the same inventive concept as the fleet safety operation control method described in embodiment 1 above. Specifically, the fleet safety operation control system includes:
a fleet safety operation control system, comprising:
the motorcade system model building module is used for building a dynamics model of the motorcade system;
the linearization module is used for converting a dynamic model of the motorcade system into a linearization model by using a dynamic linearization method;
the control target construction module is used for giving control targets of the speed and the position of the motorcade system;
the distributed controller design module is used for designing a distributed controller aiming at a fleet control system;
and the fleet safety operation control module is used for designing a performance function related to the control input and the pseudo partial derivative according to the linearization model and the distributed controller to obtain a control update law and a parameter estimation law of a fleet system and realize the fleet safety operation control.
It should be noted that, in the fleet safety operation control system, the implementation process of the functions and roles of each functional module is specifically detailed in the implementation process of the corresponding steps in the method in the above embodiment 1, and will not be described herein again.
Example 3
Embodiment 3 describes a computer device for implementing the steps of the fleet safety operation control method described in embodiment 1 above.
The computer device includes a memory and one or more processors. Executable code is stored in the memory for implementing the steps of the fleet safe operation control method described above when the executable code is executed by the processor.
In this embodiment, the computer device is any device or apparatus having data processing capability, which is not described herein.
Example 4
Embodiment 4 describes a computer-readable storage medium for implementing the steps of the fleet safety operation control method described in embodiment 1 above. The computer-readable storage medium in this embodiment 4 has stored thereon a program for implementing the steps of the above-described fleet safe operation control method when executed by a processor.
The computer readable storage medium may be an internal storage unit of any device or apparatus having data processing capability, such as a hard disk or a memory, or may be an external storage device of any device having data processing capability, such as a plug-in hard disk, a Smart Media Card (SMC), an SD Card, a Flash memory Card (Flash Card), or the like, which are provided on the device.
The foregoing description is, of course, merely illustrative of preferred embodiments of the present invention, and it should be understood that the present invention is not limited to the above-described embodiments, but is intended to cover all modifications, equivalents and alternatives falling within the spirit and scope of the present invention as defined by the appended claims.
Claims (4)
1. The method for controlling the safe operation of the motorcade is characterized by comprising the following steps:
step 1, establishing a dynamic model of a motorcade system;
step 2, converting a dynamic model of the motorcade system into a linearization model by using a dynamic linearization method;
step 3, giving control targets of the speed and the position of the motorcade system;
step 4, designing a distributed controller aiming at a motorcade control system;
step 5, designing a performance function about control input and pseudo partial derivative based on the linearization model and the distributed controller to obtain a control update law and a parameter estimation law of a fleet system, so as to realize safe operation control of the fleet;
in the step 1, the motorcade system dynamics model is expressed as:
where i represents the i-th vehicle in the fleet system, i=1, 2, …, n, n represents the number of vehicles in the fleet system;
k is the running time of the vehicle, and T is the sampling time;
s i (k) Sum s i (k+1) represents the displacement of the ith vehicle in the fleet system at the time k and the time k+1, respectively; v i (k) And v i (k+1) represents the speeds of the ith vehicle in the fleet system at the time k and the time k+1, respectively;
u i (k) Is a system input, u i (k) The expression of (2) is as follows:
u i (k)＝ a i (k)/[ m i (k) r i (k)] (2)
a i (k) Is the braking torque on the wheels of the ith vehicle, m i (k) And r i (k) Respectively representing the mass and the tire radius of the ith vehicle;
f i (v i (k) Is a nonlinear function, the expression of which is as follows:
f i (v i (k))＝ C a v i 2 (k)+gfcos(θ)+gsin(θ) (3)
C a and f represents aerodynamic drag coefficient and rolling drag coefficient, respectively, g and θ represent gravitational constant and slope angle, respectively;
in the step 2, a dynamic linearization method is utilized to convert a dynamic model of the fleet system into a linearization model:
Δv i (k+1)＝Δv i (k)+ TΔu i (k)－Ψ i (k)Δv i (k) (4)
wherein Deltav i (k)＝v i (k)－v i (k-1) represents a speed difference between the vehicle at the time k and the time k-1; deltav i (k+1) represents a speed difference between the vehicle at time k+1 and time k; deltau i (k) Representing a power input difference between the vehicle at time k and time k-1;
Ψ i (k) Is a pseudo partial derivative, and:
Wherein v is i (k-1) represents the speed of the ith vehicle at the time of k-1;
definition y i (k)＝[s i (k)v i (k)] T And the linearization model is written in the following compact form:
y i (k+1)＝A y i (k)+ BΔu i (k)+ C i (k)Δy i (k) (5)
wherein Δy i (k)＝y i (k)－y i (k-1) represents a displacement difference and a speed difference of the ith vehicle at the time k and the time k-1;
In the step 3, for the linearization model, a data-driven distributed control method is designed to realize a control task; the designed control method finally meets the following two conditions:
wherein the method comprises the steps ofV represents a neighbor set adjacent to the ith vehicle, which is a neighbor vehicle of the ith vehicle; s is(s) j (k) And v j (k) Respectively representing the displacement and the speed of the jth vehicle at the kth moment; zeta type 1 And zeta 2 Is a normal number d ij Is the minimum safe distance between the ith vehicle and the jth vehicle;
in the step 4, the output of the distributed controller is described as:
wherein, xi i (k+1)、ξ i (k) Respectively representing the displacement and the speed of the distributed controller of the ith vehicle at the k+1 time and the k time; n represents the number of vehicles adjacent to the i-th vehicle,
representing all vehicles adjacent to the ith vehicle;
D ij ＝[d ij 0] T representing the safe distance of the vehicle and the speed at which the cooperative operation is maintained;
y j (k)＝[s j (k)v j (k)] T ，s j (k) And v j (k) Respectively representing the displacement and the speed of the jth vehicle at the kth moment; wherein Δy j (k)＝y j (k)－y j (k-1) represents a displacement difference and a velocity difference of the jth vehicle at the time k and the time k-1;
Ψ j (k) Is a pseudo partial derivative, and:
bounded, v j *(k)∈(v j (k－1),v j (k) A) is provided; wherein v is j (k－1)、v j (k) Indicating that the jth vehicle is at the kth-1, k momentIs a vehicle speed of (2);
used in the formula
The establishment of this condition is based on the feedback controller u i (k)＝u i (k－1)+P i ξ i (k) And symmetry of undirected graph, i.e. a ij ＝a ji ；
Wherein P is i Representation pertains to distributed output ζ i (k) I.e. the feedback adjustment factor of the distance, speed output of the vehicle i from its neighbour vehicle j;
to facilitate distributed controller design, the output of the distributed controller is multiplied by I 2 ＝[1 1]The method comprises the following steps of:
ξ i (k+1)＝ I T ξ i (k)+ a ii TΔu i (k)+δ ij (k) (8)
wherein,,
I T ＝[1,1+T]the row vector is designed for facilitating operation;
The step 5 specifically comprises the following steps:
the control input is obtained by solving the following optimization problem:
wherein lambda is i Is a penalty factor; solving the optimization problem to obtain a control input u i (k) Is more controlled by (a)The new law is as follows:
wherein ρ is i Is a step factor; the following optimization problem is designed to estimate ψ i (k)：
Wherein,,
the pseudo partial derivatives of the vehicle i at the k-th moment and the k-1 th moment are respectively represented, namely, the pseudo partial derivatives comprise nonlinear parts when a vehicle fleet system is converted from a nonlinear model to a linear model;
μ i is a constant and mu i >0；Δv i (k-1) represents the speed difference Deltau between the k-1 time and the k-2 time of the vehicle i i (k-1) represents an input power difference of the vehicle i at the k-1 th time and the k-2 th time;
solving the optimization problem to obtain a parameter estimation law of the pseudo partial derivative:
the control method of the fleet system is transformed as follows by combining the control update law and the parameter estimation law designed above:
wherein,,
representing the pseudo-partial derivative of vehicle i at 1 st second;
wherein σ is a positive constant greater than 0 and arbitrarily small;
wherein,,
an estimated value representing the pseudo partial derivative of vehicle j at k;
and realizing the safe operation control of the motorcade based on the control updating law and the parameter estimation law of the motorcade system.
2. A fleet safe operation control system for implementing the fleet safe operation control method as set forth in claim 1, characterized in that the fleet safe operation control system comprises:
the motorcade system model building module is used for building a dynamics model of the motorcade system;
the linearization module is used for converting a dynamic model of the motorcade system into a linearization model by using a dynamic linearization method;
the control target construction module is used for giving control targets of the speed and the position of the motorcade system;
the distributed controller design module is used for designing a distributed controller aiming at a fleet control system;
and the fleet safety operation control module is used for obtaining a control update law and a parameter estimation law of a fleet system according to the linearization model and the distributed controller design performance functions related to the control input and the pseudo partial derivative and controlling the fleet safety operation.
3. A computer device comprising a memory and one or more processors, the memory having executable code stored therein, wherein the processor, when executing the executable code,
the method for controlling the safe operation of a motorcade according to claim 1.
4. A computer-readable storage medium having a program stored thereon, which when executed by a processor, implements the steps of the fleet safety operation control method as set forth in claim 1.
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