AGV platoon sliding mode control method based on preset time disturbance observer

Abstract

This invention provides an AGV platooning sliding mode control method based on a preset-time disturbance observer, belonging to the technical field of automatic control. Based on the preset-time theorem and considering external disturbances, this invention designs a specified-time disturbance observer to observe external disturbances and combines it with sliding mode control to design a specified-time controller to achieve the control scheme within a specified time range. Compared to traditional control schemes, this improved method is easier to implement and has a faster convergence time. By introducing a fusion strategy of a specified-time disturbance observer and sliding mode control, the proposed method significantly improves the overall performance of the AGV platooning system.

Description

Technical Field

[0001] This invention relates to the field of automatic control technology, and more particularly to an AGV formation sliding mode control method based on a preset time disturbance observer. Background Technology

[0002] With the development of logistics automation, collaborative operation of multiple AGV clusters has become a trend. Among them, vehicle queuing control is one of the key technologies, which aims to enable multiple AGVs to maintain a safe distance and stable formation while completing complex operations such as merging and changing lanes.

[0003] Uncontrollable convergence time: Most multi-AGV platoons operate in a fleet configuration. However, past studies on fleets have defined them longitudinally, limiting performance control to vehicles traveling in the same lane. In practical applications, AGV fleets inevitably encounter complex scenarios such as multi-lane merging and lane changes. Compared to these complex scenarios, traditional vehicle platoon control is limited to single-lane longitudinal movement, failing to achieve complex lateral and longitudinal collaborative control for dynamic multi-lane merging (e.g., intersection merging) and emergency lane changes (e.g., obstacle avoidance), resulting in poor adaptability to real-world logistics scenarios. Furthermore, it suffers from severe limitations in control time. For example, finite-time control relies on the system's initial state, requiring recalculation of time parameters during fleet reorganization. While fixed-time control is independent of the initial state, it cannot preset precise convergence times according to operational requirements, significantly impacting the collaborative control and accuracy of AGV fleets.

[0004] Insufficient anti-interference capability: Furthermore, when facing external uncertainties, such as the unknown disturbances caused by ground friction, load changes, and wind resistance during actual operation, as well as internal uncertainties including model parameter errors and actuator nonlinearity, traditional disturbance observers (such as neural network approximation types) require long training times, which cannot meet the needs of high-speed AGV operation scenarios. Disturbance estimation errors consistently remain above 20%, leading to continuous deviations in control inputs. The lack of consideration for actuator constraints such as motor torque saturation easily causes system instability under actual working conditions. For AGV platoon collaborative control, there is horizontal and vertical coupling control, making it impossible to accurately estimate external disturbances in a short time, and there is also the problem of too many parameters. All of these factors have a significant impact on the stability of AGV platoon control, the control accuracy of collaborative control, and safety issues. Summary of the Invention

[0005] In view of the technical problems mentioned in the background art above, such as the existing AGV formation control having insufficient accuracy, poor stability, and slow convergence due to the lateral and longitudinal coupling control, the AGV formation sliding mode control method based on a preset time disturbance observer is provided.

[0006] The technical means employed in this invention are as follows:

[0007] An AGV formation sliding mode control method based on a preset time disturbance observer includes the following steps: S1. Construct an AGV formation dynamics model based on the Newton-Euler equations and the Lagrange equations; S2, Current vehicle and distance to the vehicle in front Deflection angle relative to velocity direction Define and establish the error function between the two. Construct collision constraints; S3. Introducing auxiliary variables and time-varying gain term ,exist This can lead to an exponential growth effect. S4. Design disturbance estimation based on automatic control principles; S5. Set the time-varying scalar function to implement preset time control; S6. Combine sliding mode control with the design of a corresponding preset time sliding mode controller to control the coordination between the corresponding formations, and design the sliding surface. Using a sliding mode reaching law with a specified time ; S7. Introduce a longitudinal-lateral collaborative control architecture controller to ensure that the AGV can track the control target within a preset time. S8. Design a corresponding vehicle angle controller to realize the lateral angle control of AGV vehicles platooning through obstacles. S9. Perform stability verification on the longitudinal-lateral collaborative control architecture controller that adopts vehicle platooning control, as well as the vehicle cornering controller, to ensure their stability and accuracy.

[0008] Furthermore, in S1, the AGV formation dynamics model is as follows: ; ; in, and These represent the longitudinal position, lateral position, and speed direction of the AGV, respectively. Angle along the positive axis, velocity, angular velocity, acceleration; and These represent the mass and moment of inertia of the AGV, respectively. Indicates the distance between two wheels; Indicates the radius of the wheel; and These represent the torque of the left and right wheels, respectively. Indicates external interference; and These represent control input and wheel angle input, respectively.

[0009] Furthermore, in step S2, to enable the AGV to be used in multiple scenarios, the distance to the current vehicle and the vehicle in front is monitored. Deflection angle relative to velocity direction Define and establish the error function between the two. And construct collision constraints: ; ; , The lateral and longitudinal coordinates of the vehicle; the vehicle spacing is defined as follows: to ensure that adjacent vehicles avoid collisions and maintain communication connectivity. The following conditions must be met: ; in, and These represent the minimum distance to ensure security and the maximum distance to maintain effective communication, respectively. The vehicle fleet error design is as follows: , ; in, For the desired distance, and Satisfying inequalities ,definition and ; ; in, Indicates the minimum spacing. Indicates the maximum spacing.

[0010] Furthermore, in S3, the auxiliary variable for: ; .

[0011] Further, in step S4, the interference estimation expression is: ; in, Indicates the first The disturbance estimate for each AGV; This represents the linear gain coefficient of the perturbation observer; This represents the time term coefficient of the disturbance observer; The time adjustment function for the preset time observer; It is an auxiliary variable.

[0012] Furthermore, in S5, the time-varying scalar function for: ; in, Indicates the specified time. is a constant and , exist It is monotonically decreasing within the interval, and ,also: .

[0013] Furthermore, in step S6, according to a preset time principle, the sliding surface of the vehicle spacing is... : ; Represented as vehicle spacing, to ensure the stability of the entire convoy and to improve the coupling sliding surface, the following is introduced: ; in, For design parameters, when the design parameter area At that time, sliding surface Convergence guarantee They have the same convergence. To ensure the sliding surface and coupling sliding surface The convergence of, for The derivative is: ; The sliding surface of a vehicle corner is defined as:

[0014] in Both represent positive numbers, and ; Lateral sliding surface The time derivative is: ; To ensure the convergence of the coupled sliding surface, the following time arrival law is considered: ; in, Positive parameter, and .

[0015] Furthermore, in S7, the target tracking for: ; in , For gain parameters, For the parameters of the coupling sliding surface, For AGV quality, Let be the radius of the wheel, where The expression is:

[0016] .

[0017] Furthermore, in S8, the vehicle steering controller is... : ; in, The moment of inertia of the AGV. The radius of the wheel, The distance between the two wheels. For design parameters; For transverse sliding surface Time derivative, The second derivative of the heading deflection angle.

[0018] Furthermore, in S9, the stability verification formula for the longitudinal-lateral cooperative control architecture controller employing vehicle platooning control and the vehicle steering controller is as follows: ; ; ; in, For the global Lyapunov function, To control the Lyapunov function laterally, Let Lyapunov function be the perturbation observer. , To design the gain parameters, This represents the linear gain coefficient of the perturbation observer; This represents the time term coefficient of the disturbance observer. and It represents the coefficients that satisfy the Lyapunov stability theory.

[0019] Compared with the prior art, the present invention has the following advantages: Improved anti-interference accuracy and response speed: The time-limited interference observer can accurately estimate external disturbances with zero overshoot within a preset time. Compared with the traditional neural network observation method, the convergence speed is improved by more than 60%, and it is independent of the initial state, effectively reducing the impact of interference on formation stability. Control precision and efficiency optimization: The sliding mode control scheme based on preset time enables the formation spacing error and heading angle error to converge to zero within the preset time seconds, improving tracking error accuracy and enhancing the efficiency and safety of task execution in logistics scenarios. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 The flowchart illustrates the steps of an AGV formation sliding mode control method based on a preset time disturbance observer provided by the present invention.

[0022] Figure 2 This is a graph showing the convergence curve of the preset time perturbation observer in an embodiment of the present invention within a preset time.

[0023] Figure 3 The present invention provides a diagram showing the lane fusion curve changes of four AGVs in different lanes, as designed in an embodiment of the invention.

[0024] Figure 4 The diagram shows the curve of the vehicle spacing error when four AGVs are used in the vehicle formation controller designed for this embodiment of the invention.

[0025] Figure 5 The present invention provides a curve showing the variation of the tire angle controller error of four AGVs in an embodiment of the present invention.

[0026] Figure 6 A curve diagram showing the change in the turning angle of four AGV vehicles is designed for an embodiment of the present invention.

[0027] Figure 7 Figure I shows the curve changes of four AGVs changing lanes when they detect an obstacle, as designed for an embodiment of the present invention.

[0028] Figure 8 Figure II shows the curve changes of four AGVs changing lanes when they detect an obstacle, as designed for an embodiment of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] like Figures 1-8 As shown, this invention provides an AGV formation sliding mode control method based on a preset time disturbance observer, comprising the following steps: S1. Construct an AGV formation dynamics model based on the Newton-Euler equations and the Lagrange equations; in S1, the AGV formation dynamics model is as follows: ; ; in, and These represent the longitudinal position, lateral position, and speed direction of the AGV, respectively. Angle along the positive axis, velocity, angular velocity, acceleration; and These represent the mass and moment of inertia of the AGV, respectively. Indicates the distance between two wheels; Indicates the radius of the wheel; and These represent the torque of the left and right wheels, respectively. Indicates external interference; and These represent control input and wheel angle input, respectively.

[0032] S2, Current vehicle and distance to the vehicle in front Deflection angle relative to velocity direction Define and establish the error function between the two. In step S2, to enable the AGV to be used in multiple scenarios, collision constraints are established for the current vehicle and the distance to the vehicle in front. Deflection angle relative to velocity direction Define and establish the error function between the two. And construct collision constraints: ; ; To ensure that adjacent vehicles avoid collisions and maintain communication connectivity, vehicle spacing The following conditions must be met: ; in, and These represent the minimum distance to ensure security and the maximum distance to maintain effective communication, respectively. The vehicle fleet error design is as follows: , ; in, For the desired distance, and Satisfying inequalities ,definition and ; ; in, Indicates the minimum spacing. Indicates the maximum spacing.

[0033] S3. Introducing auxiliary variables and time-varying gain term ,exist An exponential growth effect occurs; in S3, the auxiliary variable for: ; .

[0034] S4. Design disturbance estimation based on automatic control principles; in S4, the disturbance estimation expression is: ; in, Indicates the first The disturbance estimate for each AGV; This represents the linear gain coefficient of the perturbation observer; This represents the time term coefficient of the disturbance observer; The time adjustment function for the preset time observer; It is an auxiliary variable.

[0035] S5. Set a time-varying scalar function to implement preset time control; in S5, the time-varying scalar function is: ; in, Indicates the specified time. is a constant and , exist It is monotonically decreasing within the interval, and ,also: .

[0036] S6. Combine sliding mode control with the design of a corresponding preset time sliding mode controller to control the coordination between the corresponding formations, and design the sliding surface. Using a sliding mode reaching law with a specified time In step S6, according to a preset time principle, the sliding surface of the vehicle spacing is... : ; To ensure the stability of the entire fleet and improve the coupling sliding surface, the following is introduced: ; Among them, when the design parameter area At that time, sliding surface Convergence guarantee They have the same convergence. To ensure the sliding surface and coupling sliding surface The convergence of, for The derivative is: ; The sliding surface of a vehicle corner is defined as:

[0037] in Both represent positive numbers, and ; Lateral sliding surface The time derivative is: ; To ensure the convergence of the coupled sliding surface, the following time arrival law is considered: ; in, Positive parameter, and .

[0038] S7. Introduce a longitudinal-lateral collaborative control architecture controller to ensure that the AGV can track the control target within a preset time; in S7, the target tracking... for: .

[0039] in , For gain parameters, For the parameters of the coupling sliding surface, For AGV quality, Let be the radius of the wheel, where The expression is:

[0040]

[0041] S8. Design a corresponding vehicle angle controller to achieve lateral angle control in AGV vehicle platooning obstacle crossing scenarios; in S8, the vehicle angle controller is... : .

[0042] in The moment of inertia of the AGV. The radius of the wheel, The distance between the two wheels. These are design parameters. For transverse sliding surface Time derivative, The second derivative of the heading deflection angle.

[0043] S9. Perform stability verification on the longitudinal-lateral cooperative control architecture controller using vehicle platooning control and the vehicle cornering controller to ensure their stability and accuracy. The stability verification formula for the longitudinal-lateral cooperative control architecture controller using vehicle platooning control and the vehicle cornering controller in S9 is as follows: ; ; .

[0044] in, For the global Lyapunov function, To control the Lyapunov function laterally, Let Lyapunov function be the perturbation observer. , To design the gain parameters, This represents the linear gain coefficient of the perturbation observer; This represents the time term coefficient of the disturbance observer. and It represents the coefficients that satisfy the Lyapunov stability theory.

[0045] Example To verify the practical application effect of the AGV platooning sliding mode control method based on a preset time disturbance observer proposed in this embodiment, this experiment uses an automated vehicle platooning system consisting of five vehicles as the control object, and utilizes the method of this embodiment to perform coordinated control on the platooning motion process of the automated vehicle platooning system. A simulation model of a platoon of five AGVs was built in Simulink, including one lead vehicle and four following vehicles. In the simulation, the vehicles... The parameter configuration is as follows: , , , , , , , , , , , , , , , .

[0046] Multi-lane merging: The acceleration of the lead vehicle changes in segments according to a formula. ; Verify the convergence of formation spacing error.

[0047] Dynamic lane change: The lead vehicle's heading angle can be switched manually. ; Test formation path tracking capabilities.

[0048] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. In the above embodiments of the present invention, the descriptions of each embodiment have their own emphasis; parts not described in detail in a certain embodiment can be referred to in the relevant descriptions of other embodiments. It should be understood that the disclosed technical content in the several embodiments provided in this application can be implemented in other ways.

[0049] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An AGV formation sliding mode control method based on a preset time disturbance observer, characterized in that, Includes the following steps: S1. Construct an AGV formation dynamics model based on the Newton-Euler equations and the Lagrange equations; S2, Current vehicle and distance to the vehicle in front Deflection angle relative to velocity direction Define and establish the error function between the two. Construct collision constraints; S3. Introducing auxiliary variables and time-varying gain term ,exist It produces an exponential growth effect; S4. Design disturbance estimation based on automatic control principles; S5. Set the time-varying scalar function to implement preset time control; S6. Combine sliding mode control with the design of a corresponding preset time sliding mode controller to control the coordination between the corresponding formations, and design the sliding surface. Using a sliding mode reaching law with a specified time ; S7. Introduce a longitudinal-lateral collaborative control architecture controller to ensure that the AGV can track the control target within a preset time. S8. Design a corresponding vehicle angle controller to realize the lateral angle control of AGV vehicles platooning through obstacles. S9. Perform stability verification on the longitudinal-lateral collaborative control architecture controller that adopts vehicle platooning control, as well as the vehicle cornering controller, to ensure their stability and accuracy.

2. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In S1, the AGV formation dynamics model is as follows: ； ； in, and These represent the longitudinal position, lateral position, and speed direction of the AGV, respectively. Angle along the positive axis, velocity, angular velocity, acceleration; and These represent the mass and moment of inertia of the AGV, respectively. Indicates the distance between two wheels; Indicates the radius of the wheel; and These represent the torque of the left and right wheels, respectively. Indicates external interference; and These represent control input and wheel angle input, respectively.

3. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In step S2, to enable the AGV to be used in multiple scenarios, the current vehicle and the distance to the vehicle in front are monitored. Deflection angle relative to velocity direction Define and establish the error function between the two. And construct collision constraints: ； ; , The lateral and longitudinal coordinates of the vehicle; the vehicle spacing is defined as follows: to ensure that adjacent vehicles avoid collisions and maintain communication connectivity. The following conditions must be met: ； in, and These represent the minimum distance to ensure security and the maximum distance to maintain effective communication, respectively. The vehicle fleet error design is as follows: , ； in, For the desired distance, and Satisfying inequalities ,definition and ; ; in, Indicates the minimum spacing. Indicates the maximum spacing.

4. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In S3, the auxiliary variable for: ; .

5. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In step S4, the interference estimation expression is: ； in, Indicates the first The disturbance estimate for each AGV; This represents the linear gain coefficient of the perturbation observer; This represents the time term coefficient of the disturbance observer; The time adjustment function for the preset time observer; It is an auxiliary variable.

6. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In S5, the time-varying scalar function for: ； in, Indicates the specified time. is a constant and , exist It is monotonically decreasing within the interval, and ,also: 。 7. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In step S6, according to a preset time principle, the sliding surface of the vehicle spacing is... : ； Represented as vehicle spacing, to ensure the stability of the entire convoy and to improve the coupling sliding surface, the following is introduced: ； in, For design parameters, when the design parameter area At that time, sliding surface Convergence guarantee They have the same convergence. To ensure the sliding surface and coupling sliding surface The convergence of, for The derivative is: ； The sliding surface of a vehicle corner is defined as: in Both represent positive numbers, and ; Lateral sliding surface The time derivative is: ； To ensure the convergence of the coupled sliding surface, the following time arrival law is considered: ； in, Positive parameter, and .

8. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In S7, the target tracking for: ； in , For gain parameters, For the parameters of the coupling sliding surface, For AGV quality, Let be the radius of the wheel, where The expression is: 。 9. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In S8, the vehicle steering controller is : ； in, The moment of inertia of the AGV. The radius of the wheel, The distance between the two wheels. For design parameters; For transverse sliding surface Time derivative, The second derivative of the heading deflection angle.

10. The AGV formation sliding mode control method based on a preset time disturbance observer according to claim 1, characterized in that, In S9, the stability verification formula for the longitudinal-lateral cooperative control architecture controller using vehicle platooning control and the vehicle steering controller is as follows: ； ； ； in, For the global Lyapunov function, To control the Lyapunov function laterally, Let Lyapunov function be the perturbation observer. , To design the gain parameters, This represents the linear gain coefficient of the perturbation observer; This represents the time term coefficient of the disturbance observer. and It represents the coefficients that satisfy the Lyapunov stability theory.

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