Vehicle queue control method and system with time-varying gain expansion state observer

Abstract

The invention belongs to the technical field of distributed vehicle queue control, and provides a vehicle queue control method and system with a time-varying gain expansion state observer, and the method comprises the steps: building a vehicle dynamics model; external disturbance is estimated in real time based on the time-varying gain expansion state observer, and the initial differential peak phenomenon is effectively inhibited; stability analysis of an observer system is discussed according to conditions, and it is verified that the time-varying gain expansion state observer has a stricter and simpler stability proving process; designing an extended state observer for compensating external interference and unknown nonlinear terms of the model, and constructing a virtual controller and an actual controller by using a backstepping method based on the extended state observer and a fixed time stability theory; by designing a rapid fixed time backstepping control method, the system state converges to an expected signal within fixed time, and meanwhile, the system obtains good tracking performance.

Description

Technical Field

[0001] The present invention belongs to the technical field of distributed vehicle queue control, and in particular relates to a fast fixed-time queue tracking control method and system for interconnected vehicles based on a time-varying gain extended state observer. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Vehicle platoon control originated from the automated highway system in the field of intelligent transportation. Throughout the development of urban transportation, it plays a key role in ensuring travel safety, reducing pollution emissions and saving energy consumption. Therefore, it has become a key technology in the development of transportation, which was originally aimed at a single vehicle system and gradually developed and transitioned to a vehicle platoon system.

[0004] In the past few decades, the control community has maintained a high enthusiasm for studying the convergence rate of various systems. Among them, finite-time stability and fixed-time stability have attracted widespread attention due to their unique fast convergence characteristics. However, due to the existence of unmodeled dynamics, unknown parameters and external disturbances, it is difficult to obtain finite-time stability or fixed-time stability in practice. In view of this situation, the concept of practical finite-time / fixed-time stability is proposed. In this context, it is worth noting that fast fixed-time queue following control improves the convergence speed and performance. Therefore, the current research is to accelerate the convergence speed in practical engineering by constructing a fast fixed-time strategy.

[0005] For vehicle platoon systems, disturbance suppression / attenuation is an inevitable problem due to the impact of the environment on the vehicle and the disturbance caused by non-ideal characteristics in the vehicle system. The total disturbance estimate obtained from the extended state observer can compensate for the controller design to reduce the impact of the total disturbance on the feedback loop, significantly improve the suppression of disturbances, and enable the system to achieve the desired control performance under uncertain disturbances. From the perspective of its observation gain, the extended state observer can be divided into a linear extended state observer and a nonlinear extended state observer. The nonlinear extended state observer has high estimation accuracy and fast response speed, but its application in the engineering field is hindered by the large number of parameters required to be set and the complex stability analysis. The linear extended state observer is easy to set parameters and has advantages in stability analysis, but in the initial stage, the estimated initial values ​​of its state variables have a large deviation from the corresponding actual values, and the so-called "initial differential peak" phenomenon will occur. Therefore, how to design a time-varying gain extended state observer that has high observation accuracy, fast response speed, and can effectively suppress the "initial differential peak" phenomenon is a meaningful problem. Summary of the invention

[0006] The present invention aims to overcome the deficiencies of the prior art and provide a vehicle platoon control method and system with a time-varying gain extended state observer, which has ideal system transient performance, wide adaptability, high observation accuracy, strong robustness, fast convergence speed when the system state is close to the equilibrium point, and can realize external disturbance estimation.

[0007] To solve the above technical problems, the present invention is achieved as follows:

[0008] A first aspect of the present invention provides a vehicle platoon control method with a time-varying gain extended state observer, comprising the following steps:

[0009] (1) Establish a vehicle dynamics model under external disturbances and unknown nonlinear terms;

[0010] (2) Design a time-varying gain extended state observer to compensate for external disturbances and unknown nonlinear terms, and use the backstepping method to construct a virtual controller and an actual controller by combining the tracking differentiator output signal;

[0011] (3) Distributed fast fixed-time anti-interference queue tracking control is implemented in the backstepping method through the time-varying gain extended state observer and Lyapunov stability analysis.

[0012] Furthermore, before establishing the vehicle dynamics model, the present invention also includes obtaining status information and parameter information of each vehicle, and through information transmission between the leader vehicle and multiple follower vehicles, each follower vehicle obtains the status information and parameter information of other vehicles in real time.

[0013] Furthermore, the state information of the present invention includes position information, speed information and acceleration information of the vehicle.

[0014] Furthermore, the time-varying gain in the time-varying gain extended state observer of the present invention is as follows:

[0015]

[0016] Among them, η0 is a constant, η(t) is a time-varying gain, and ρ is a constant that controls the growth rate of η(t). Since the initial value of the state estimated in the initial stage has a large deviation from the actual value, the "initial difference peak" phenomenon has an adverse effect on the transient performance of the system. In the designed time-varying gain extended state observer, the initial value of η(t) is small, and its convergence speed can be adjusted according to different ρ values. Using different ρ values ​​can control its rate, and η(t) increases rapidly from a smaller initial value to a larger constant value η0. It avoids the occurrence of peak phenomenon, thereby improving the performance of the system.

[0017] Furthermore, the state space expression in the vehicle dynamics model of the present invention is:

[0018]

[0019] Where t represents time, x i,p ,x i,v ,x i,a represents the measurable system state, i.e., the position, velocity, and acceleration of the i-th vehicle, They are x i,p ,x i,v ,x i,a The derivative of w i represents the time-varying input disturbance of the i-th vehicle, u i (t) is the control input of the i-th vehicle. τ i >0 represents the engine time constant of the i-th vehicle.

[0020] Furthermore, the specific method of the time-varying gain extended state observer of the present invention to compensate for external interference and unknown nonlinear terms is as follows:

[0021]

[0022] Among them, e i,r is the observer error, is the state of the extended state observer, and Respectively The derivative of , p is the scaling gain, τ i represents the engine time constant of the vehicle, u i is the control input of the th vehicle, λ1,λ2 are positive constants, is a continuous function, defined as follows:

[0023]

[0024] in,

[0025] Furthermore, the present invention utilizes a tracking differentiator to estimate the derivative of the virtual controller.

[0026] A second aspect of the present invention provides a vehicle platoon control system with a time-varying gain extended state observer, comprising:

[0027] The model building module is configured to: build a vehicle dynamics model;

[0028] The signal compensation module is configured to: design a time-varying gain extended state observer for compensating external disturbances and unknown nonlinear terms, and construct a virtual controller and an actual controller using a backstepping method in combination with the tracking differentiator output signal;

[0029] The control module is configured as follows: The time-varying gain designed according to the time-varying gain extended state observer adopts the piecewise function form, which can accurately control the gain to adapt to different conditions to improve the accuracy and flexibility of the observer and realize distributed fast fixed-time anti-interference queue tracking control.

[0030] A third aspect of the present invention provides a medium having a program stored thereon, wherein when the program is executed by a processor, the steps in the above-mentioned vehicle queue control method with a time-varying gain extended state observer are implemented.

[0031] A fourth aspect of the present invention provides an electronic device, comprising a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned vehicle queue control method with a time-varying gain extended state observer when executing the program.

[0032] Aiming at the uncertain vehicle queue system with interference, the present invention designs a distributed fast fixed-time anti-interference queue tracking control strategy based on the time-varying gain extended state observer and the fixed-time stability theory. Firstly, a time-varying gain extended state observer is designed to realize the estimation of external disturbance. This method not only has a strict observation error convergence stability analysis process, but also weakens the "initial differential peak" phenomenon in the traditional linear extended state observation method. Secondly, a fast fixed-time backstepping controller with better performance than the fixed-time control strategy is constructed to achieve fast convergence within a fixed time. Finally, a fast fixed-time control method is derived in the backstepping framework using the time-varying gain extended state observer estimation and the fixed-time stability theory.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] (1) In order to achieve the stability of the vehicle system within a fixed time, the present invention constructs a fast fixed-time backstepping controller, which has better performance than the fixed-time control strategy. When the system state is close to the equilibrium point, the present invention uses linear terms instead of nonlinear terms to obtain a faster convergence speed.

[0035] (2) The present invention proposes a time-varying gain extended state observer to improve the observation accuracy and system robustness. Compared with the traditional linear extended state observer, the proposed time-varying gain extended state observer can suppress the initial peak phenomenon, thereby improving the transient performance of the system.

[0036] (3) The time-varying gain proposed in the present invention adopts a piecewise function form, which can accurately control the gain to adapt to different conditions to improve the accuracy and flexibility of the observer. In addition, compared with the nonlinear extended state observer, the proof process of the observer system is simpler and more rigorous.

[0037] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0039] Figure 1 It is a composition framework diagram of the vehicle platoon system of the present invention;

[0040] Figure 2 1 is a flow chart of a vehicle follower tracking control method based on a constant spacing strategy of the present invention;

[0041] Figure 3 is a schematic diagram of an actual vehicle queue provided by the first embodiment of the present invention;

[0042] Figure 4 It is a schematic diagram of the time-varying gain change curve of the present invention;

[0043] Figure 5 is a schematic diagram of a distributed platoon control technology for a vehicle follower based on a fast fixed time control strategy of the present invention;

[0044] Figure 6 is a reference speed curve diagram of the leading vehicle of the present invention;

[0045] Figure 7 is a real-time position curve diagram of a vehicle queue including one leader and three followers according to the present invention;

[0046] Figure 8 is a real-time speed curve diagram of a vehicle queue including one leader and three followers according to the present invention;

[0047] Fig. 9 is a graph of real-time spacing tracking error and speed error of a vehicle queue including one leader and three followers according to the present invention;

[0048] Fig.10 It is an error comparison diagram between the time-varying gain extended state observer designed by the present invention and the traditional linear extended state observer. DETAILED DESCRIPTION

[0049] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0050] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those of ordinary skill in the art to which the present invention belongs. In the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0051] Embodiment 1

[0052] like Figure 2 As shown, the first embodiment of the present invention provides a vehicle queue control method with a time-varying gain extended state observer, comprising the following steps:

[0053] (1) Establish a vehicle dynamics model under external disturbances and unknown nonlinear terms;

[0054] (2) Design a time-varying gain extended state observer to compensate for external disturbances and unknown nonlinear terms, and use the backstepping method to construct a virtual controller and an actual controller by combining the tracking differentiator output signal;

[0055] (3) Distributed fast fixed-time anti-interference queue tracking control is implemented in the backstepping method through the time-varying gain extended state observer and Lyapunov stability analysis.

[0056] Before establishing the vehicle dynamics model, it is necessary to obtain the status information and parameter information of each vehicle. Through the information transmission between the leader vehicle and multiple follower vehicles, each follower vehicle can obtain the status information and parameter information of other vehicles in real time. Among them, the status information includes the vehicle's position information, speed information and acceleration information.

[0057] Based on the state information and parameter information of each vehicle, a vehicle dynamics model based on Newton's second law is established under the condition of considering external interference and unknown nonlinear terms.

[0058] The vehicle platoon system targeted by this embodiment is composed as follows: Figure 1 As shown, the dynamic model of the i-th vehicle is transformed into a state space expression:

[0059]

[0060] Where t represents time, x i,p ,x i,v ,x i,a represents the measurable system state, i.e., the position, velocity, and acceleration of the i-th vehicle, They are x i,p ,x i,v ,x i,a The derivative of w i represents the time-varying input disturbance of the i-th vehicle, ui (t) is the control input of the i-th vehicle. τ i >0 represents the engine time constant of the i-th vehicle.

[0061] Secondly, a simplified linearized leader system model is designed:

[0062]

[0063] Among them, x 0,p ,x 0,v represents the measurable system state, i.e., the position and velocity of the leader, They are x 0,p ,x 0,v The derivative of .

[0064] In vehicle platoon control, the disturbance of the system is usually caused by unknown factors such as turbulence, wind, drag and internal influence. In order to complete the tracking control stably and continuously, the time-varying gain extended state observer is used to deal with external disturbances as follows:

[0065]

[0066] Among them, e i,r is the observer error, is the state of the extended state observer, Hehe Respectively The derivative of , p is the scaling gain, τ i represents the engine time constant of the vehicle, u i is the control input of the th vehicle, λ1,λ2 are positive constants, is a continuous function, and η(t) is a time-varying gain, defined as follows:

[0067]

[0068] in, is a constant satisfying η0 is a constant and ρ is a constant that controls the growth rate of η(t).

[0069] For the vehicle platoon control system, the spacing error based on the constant spacing strategy can be expressed as:

[0070] e i,p (t) = x i-1,p (t)-x i,p (t)-l i-1 (t)-d i (t)

[0071] Among them, z i,pis the tracking error after the conversion of the i-th vehicle, and constructs a new error conversion:

[0072] z i,p =e i,p

[0073] z i,v =x i,v -α i,p

[0074] z i,a =x i,a -α i,v

[0075] To estimate the virtual controller α i,p ,α i,v The derivative of , design the following tracking differentiator:

[0076] Since s-type functions are monotonic, bounded, and symmetric, they are suitable as tracking functions for tracking differentiators. Under the premise of ensuring the properties of symmetric functions, an improved s-type function is designed using amplitude factors and exponential factors, as follows:

[0077] Sig(∈;d,f,g)=sign(∈)·∣d[(1+e -f ) -1 -0.5]| g

[0078] Among them, d is an amplitude factor for adjusting the output amplitude, f and g are exponential factors satisfying g = h / k, and h and k are positive odd numbers. |·| ensures that Sig(∈) is meaningful in the real number domain, and the symbol sign(∈) is a sign function, which ensures that Sig(∈) is an odd function relative to the equilibrium point. Based on the improvement of the s-type function, a tracking differentiator is designed:

[0079]

[0080] Among them, φ i,p,1 ,φ i,p,2 is the state of the tracking differentiator, They are φ i,p,1 ,φ i,p,2 The derivative of is the design constant, ε i (t) is the input of the tracking differentiator technique. As the parameter g increases, the concave-convex nature of the Sig function near the equilibrium point is effectively changed, and it gradually approaches 0 through the transition from convex function to concave function. + This means that the equation based on the tracking differentiator has both high-speed tracking capability and high convergence stability.

[0081] Consider further the error signal of the tracking differentiator:

[0082]

[0083] in, is the error signal The upper or lower bound of φ. i,p,1 ,φ i,p,2 is the state of the tracking differentiator, They are φ i,p,1 ,φ i,p,2 The derivative of They are α i,p ,α i,v In addition, by scaling the inequality, we get:

[0084]

[0085] where ξ i,p ,ξ i,v is the inequality scaling factor.

[0086] Under the framework of backstepping, the virtual controller α is designed i,p ,α i,v as follows:

[0087]

[0088] Among them, γ1>0, β1>0, γ2>0, β2>0 are appropriate design parameters, and a, b, r, s are positive odd numbers satisfying a>b and r <s,

[0089] According to the system state space equation, virtual controller and tracking error signal, the tracking error signal z i,p ,z i,v ,z i,a The derivative is:

[0090]

[0091] In order to analyze whether the designed virtual controller and actual controller can make the entire vehicle platoon achieve internal stability and string stability, we select the following Lyapunov candidate function V:

[0092]

[0093] Then, the actual controller u i =u i (t) can be obtained:

[0094]

[0095] in, γ3>0 and β3>0 are designed parameters.

[0096] Derivative the selected Lyapunov function V, combined with the derivative of the tracking error The calculation can be obtained:

[0097]

[0098] Among them, it can be calculated:

[0099]

[0100] Substituting further into the formula, we can calculate:

[0101]

[0102] In order to ensure the generality of the proof, we define γ1=γ2=γ3=γ and β1=β2=β3=β.

[0103] The fixed-time stability of the observer estimation error and the tracking error is guaranteed to be zero for any t ≥ T0. Eight different cases are analyzed to demonstrate the stability of the fast fixed-time:

[0104] (1) When ∣z i,p ∣≥1,∣z i,v ∣≥1,∣z i,a When ∣≥1, there is

[0105]

[0106] (2) When ∣z i,p ∣<1,∣z i,v ∣<1,∣z i,a ∣<1, yes

[0107]

[0108] (3) When ∣z i,p ∣≥1,∣z i,v ∣≥1,∣z i,a ∣<1, yes

[0109]

[0110] (4) When ∣z i,p ∣≥1,∣z i,v ∣<1,∣z i,a ∣<1, yes

[0111]

[0112] (5) When ∣z i,p ∣<1,∣z i,v∣≥1,∣z i,a ∣≥1, yes

[0113]

[0114] (6) When ∣z i,p ∣<1,∣z i,v ∣<1,∣z i,a ∣≥1, yes

[0115]

[0116] (7) When ∣z i,p ∣<1,∣z i,v ∣≥1,∣z i,a ∣<1, yes

[0117]

[0118] (8) When ∣z i,p ∣≥1,∣z i,v ∣<1,∣z i,a ∣≥1, yes

[0119]

[0120] For the entire vehicle platoon, the derivative of V can be further written as:

[0121]

[0122] in,

[0123] Therefore, it can be seen that all signals of the vehicle platoon system are stable at fixed time. i,p ,z i,v ,z i,a Converges to the origin in a fixed time, regardless of the initial conditions. The goal of internal stability is achieved within a fixed time interval. Based on the above stability analysis, the stability proof of the string has been completed. So far, the stability of the system has been proved.

[0124] In order to prove the feasibility, effectiveness and correctness of this example, the present invention performs the following simulation examples:

[0125] In this simulation experiment, a practical controller based on a fixed-time strategy is designed for a vehicle platoon system with external disturbances, which can synchronize the position of the followers in the vehicle platoon with the time-varying position of the leader under external disturbances and unknown nonlinear terms. In addition, the tracking accuracy and transient performance of the system are improved on the basis of achieving synchronization. The time-varying reference speed of the leader is used to approximate driving under highway conditions.

[0126] First, the system model parameters are given: vehicle mass is m1 = 1000kg, m2 = 1600kg; engine time constant τ1 = τ2 = τ3 = 0.5s; vehicle length l0 = 2m, l1 = 2.5m, l2 = 4m; vehicle expected safety distance d i =8m. Secondly, the time-varying reference speed of the leader:

[0127]

[0128] The external disturbance term is: w i =2sin(0.2πt); the initial value of the system state is: x 0,p =32.5,x 1,p (0) = 22.5, x 2,p (0) = 12, x 3,p (0)=0,x 0,v (0) = x 1,v (0) = x 2,v (0) = x 3,v (0) = 15, x 0,a (0) = x 1,a (0) = x 2,a (0) = x 3,a (0) = 0; the parameters of the virtual controller and the actual controller are: a = 25, b = 18, r = 18, s = 25, γ1 = 55, γ2 = 20, γ3 = 120, β1 = 260, β2 = 280, β3 = 550; the parameters of the s-type function are: d = 5, f = 5, h = 5, k = 3; the parameters of the tracking differentiator are: The correlation coefficients of the extended state observer are: ρ=7,η0=20,p=1, The inequality scaling constant is: 1,p =ξ 2,p =ξ 3,p =ξ 1,v =ξ 2,v =ξ 3,v =0.05.

[0129] Combined with the attached drawings, the effectiveness of this example simulation is further illustrated:

[0130] The simulation results are as follows Figure 5-Figure 8 , the simulation results are shown in the figure. Figure 5 The position changes of the vehicle queue are depicted. No matter the leader is accelerating, decelerating or being disturbed, the vehicle positions have no overlap, no collision, and remain stable at the desired position. Figure 6 This shows that the following vehicles 1-3 have a better tracking effect on the leading vehicle; Figure 7It is shown that the spacing error of the vehicle platoon meets the string stability requirement in the vehicle platoon tracking control and is controlled within a bounded region within a fixed time; Figure 7 The figure below shows that the relative speed is actually stable within a fixed time, indicating that the speed of the follower vehicles 1-3 can track the speed of the leader vehicle; Figure 8 The error comparison diagram between the time-varying gain extended state observer and the traditional linear extended state observer is presented. It can be seen that after the system starts running, the time-varying gain extended state observer experiences a significant error in a short period of time, and then the time-varying gain extended state observer's estimate of the disturbance gradually approaches the actual disturbance. Therefore, the time-varying gain extended state observer can make the system have good transient performance; so far, the simulation proves the effectiveness of the proposed control scheme.

[0131] In this example, a distributed fast fixed-time queue tracking control method based on a time-varying gain extended state observer and a tracking differentiator is proposed for a vehicle queue system with time-varying unknown external disturbances. A fast fixed-time controller is designed to improve the convergence accuracy and convergence speed. The time-varying gain extended state observer estimates the external disturbance in real time and effectively suppresses the phenomenon of "initial differential peak". The stability analysis of the observer system is discussed in different cases, and it is verified that the time-varying gain extended state observer has a more rigorous and simple stability proof process. By designing a fast fixed-time backstepping control method, the system state converges to the desired signal within a fixed time. Then, the stability analysis is systematically proved using the Lyapunov stability theorem. Finally, the feasibility of the proposed vehicle queue control method is verified by a simulation example.

[0132] Embodiment 2

[0133] Embodiment 2 of the present invention provides a vehicle platoon control system with an extended state observer, including:

[0134] The model building module is configured to: build a vehicle dynamics model;

[0135] The signal compensation module is configured to: design a time-varying gain extended state observer for compensating for external disturbances and unknown nonlinear terms of the model, and construct a virtual controller and an actual controller using a backstepping method based on the time-varying gain extended state observer and fixed-time stability theory;

[0136] The control module is configured to: design a time-varying gain according to the extended state observer, and the gain implements the steps in the vehicle queue control method with the time-varying gain extended state observer described in the first aspect of the present invention.

[0137] The more detailed steps are the same as those in the first embodiment and will not be repeated here.

[0138] Embodiment 3

[0139] Embodiment 3 of the present invention provides a medium on which a program is stored. When the program is executed by a processor, the steps of the vehicle queue control method with a time-varying gain extended state observer as described in Embodiment 1 of the present invention are implemented.

[0140] The more detailed steps are the same as those in the first embodiment and will not be repeated here.

[0141] Embodiment 4

[0142] Embodiment 4 of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps in the vehicle queue control method with a time-varying gain extended state observer as described in Embodiment 1 of the present invention are implemented.

[0143] The more detailed steps are the same as those in the first embodiment and will not be repeated here.

[0144] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A vehicle platoon control method with a time-varying gain extended state observer, characterized in that: The following steps are involved: (1) Establish a vehicle dynamics model under external disturbances and unknown nonlinear terms; (2) Design a time-varying gain extended state observer to compensate for external disturbances and unknown nonlinear terms, and use the backstepping method to construct a virtual controller and an actual controller by combining the tracking differentiator output signal; (3) Distributed fast fixed-time anti-interference queue tracking control is implemented in the backstepping method through the time-varying gain extended state observer and Lyapunov stability analysis.

2. The vehicle platoon control method with a time-varying gain extended state observer according to claim 1, characterized in that: Before establishing the vehicle dynamics model, it also includes obtaining the status information and parameter information of each vehicle. Through information transmission between the leader vehicle and multiple follower vehicles, each follower vehicle can obtain the status information and parameter information of other vehicles in real time.

3. The vehicle platoon control method with a time-varying gain extended state observer according to claim 2, characterized in that: The state information includes position information, speed information and acceleration information of the vehicle.

4. The vehicle platoon control method with a time-varying gain extended state observer according to claim 2, characterized in that: The time-varying gain in the extended state observer is as follows: Where η0 is a constant, η(t) is a time-varying gain, and ρ is a constant that controls the growth rate of η(t).

5. The vehicle platoon control method with a time-varying gain extended state observer according to claim 2, characterized in that: The state space expression in the vehicle dynamics model is: Where t represents time, x i,p ,x i,v ,x i,a represents the measurable system state, i.e., the position, velocity, and acceleration of the i-th vehicle, They are x i,p ,x i,v ,x i,a The derivative of w i represents the time-varying input disturbance of the i-th vehicle, u i (t) is the control input of the i-th vehicle; τ i >0 represents the engine time constant of the i-th vehicle.

6. The vehicle platoon control method with a time-varying gain extended state observer according to claim 2, characterized in that: The specific method of the time-varying gain extended state observer to compensate external disturbances and unknown nonlinear terms is as follows: Among them, e i,r is the observer error, is the state of the extended state observer, and Respectively The derivative of , p is the scaling gain, τ i represents the engine time constant of the vehicle, u i is the control input of the th vehicle, λ1,λ2 are positive constants, is a continuous function, defined as follows: in, 7. The vehicle platoon control method with a time-varying gain extended state observer according to claim 2, characterized in that: The derivative of the virtual controller is estimated using a tracking differentiator.

8. A vehicle platoon control system with a time-varying gain extended state observer, characterized in that: include: The model building module is configured to: build a vehicle dynamics model; The signal compensation module is configured to: design a time-varying gain extended state observer for compensating external disturbances and unknown nonlinear terms, and construct a virtual controller and an actual controller using a backstepping method in combination with the tracking differentiator output signal; The control module is configured to design a time-varying gain according to a time-varying gain extended state observer to realize distributed fast fixed-time anti-interference queue tracking control.

9. A medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps of the vehicle platoon control method with a time-varying gain extended state observer are implemented.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the vehicle queue control method with a time-varying gain extended state observer as described in any one of claims 1 to 7 are implemented.

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