AGV trajectory tracking control method based on adaptive integral sliding mode controller
By designing an adaptive integral sliding mode controller, combined with a disturbance observer and adaptive gain adjustment, the trajectory tracking problem of AGV under complex disturbances was solved, achieving high-precision, fast-response, and robust control effects.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SICHUAN UNIVERSITY OF SCIENCE AND ENGINEERING
- Filing Date
- 2026-06-09
- Publication Date
- 2026-07-10
AI Technical Summary
Traditional control methods struggle to achieve high precision, rapid response, and strong robustness when dealing with the combined disturbances caused by model uncertainties and external disturbances in AGVs, and are prone to chattering and system instability.
A control method based on an adaptive integral sliding mode controller is adopted. A dual-layer adaptive integral sliding mode controller with linear velocity and angular velocity is designed. In combination with a disturbance observer, real-time estimation and feedforward compensation are performed. The sliding surface is optimized by adaptive gain adjustment and gain switching to achieve accurate estimation and compensation of complex disturbances.
It improves the accuracy and speed of AGV trajectory tracking, reduces control input spikes and chatter, and ensures that the system has high precision, fast response and strong robustness under complex working conditions.
Smart Images
Figure CN122363243A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of automatic control technology, and in particular to an AGV trajectory tracking control method based on an adaptive integral sliding mode controller. Background Technology
[0002] In intelligent manufacturing systems, Automated Guided Vehicles (AGVs) are key equipment for achieving flexible material handling and seamless integration between processes. Their application scale and technological level directly affect the overall efficiency and intelligence level of the production system. As one of the core technologies of AGVs, trajectory tracking control has a significant impact on the vehicle's operational stability, ride smoothness, and operational safety.
[0003] In actual operation, AGVs encounter complex disturbances caused by model uncertainties and external disturbances. Traditional PID controllers lack the ability to suppress nonlinear disturbances. Traditional sliding mode control methods rely on upper limits of disturbances or high switching gains, which can easily lead to chattering, actuator wear, or even system instability. Disturbance observer-based control methods can estimate complex disturbances in real time. However, when the system encounters multi-source heterogeneous complex disturbances such as sudden load changes during transport, changes in friction coefficients on complex road surfaces, and dynamic perturbations of motor operating parameters, conventional disturbance observers often struggle to accurately estimate the complex disturbances within a strictly limited time, resulting in a still large tracking error for the AGV during dynamic processes. Finite-time integral sliding mode control methods based on fixed gain can improve the trajectory tracking accuracy of AGVs and accelerate system convergence efficiency, but this comes at the cost of sacrificing the smooth transition of system states. Using a large fixed gain can cause huge transient spikes in the control input at points of sudden changes in trajectory curvature.
[0004] The composite control strategy based on multi-algorithm fusion combines the advantages of different control theories and can more effectively cope with the impact of composite disturbances caused by model uncertainty and external disturbances, thereby achieving control requirements such as high precision, fast response and strong robustness. Summary of the Invention
[0005] To address the shortcomings of traditional control methods, this invention provides an AGV trajectory tracking control method based on an adaptive integral sliding mode controller. Compared with traditional control methods, the control method proposed in this invention can simultaneously achieve high precision, fast response, and strong robustness when dealing with the combined disturbances caused by model uncertainty and external disturbances. This enables the AGV's actual trajectory to quickly and stably track the preset reference trajectory.
[0006] This invention is achieved using the following technical solution: An AGV trajectory tracking control method based on an adaptive integral sliding mode controller is applied to a controller configured on an AGV. The controller is connected to a motor driver for driving the left and right wheels of the AGV via an onboard communication bus. The method includes the following steps: Step S1: Establish the kinematic and dynamic models of the AGV containing complex disturbances; Step S2: Treat model uncertainties and external environmental disturbances as a composite disturbance, and design a disturbance observer based on the mathematical model of the AGV; Step S3: Input the reference linear velocity information and reference angular velocity information, design a linear velocity dual-layer adaptive integral sliding mode controller and an angular velocity dual-layer adaptive integral sliding mode controller for control, obtain the actual linear velocity information, actual angular velocity information and actual position information of the AGV, and then obtain the actual trajectory RT1 of the AGV so that the actual trajectory of the AGV tracks the reference trajectory.
[0007] Specifically, the mathematical expression of the model in step S1 is expressed as follows: ; in, These represent the x-coordinate, y-coordinate, and heading angle of the AGV's center of mass in the vehicle coordinate system, respectively. yes The derivative; This is the coordinate transformation matrix; It is a generalized velocity vector; Indicates linear velocity information; Represents angular velocity information; express The derivative; The generalized mass-inertia matrix, Indicates the mass of the AGV. This represents the moment of inertia of the AGV. Here is the damping matrix. and These are the equivalent damping coefficients for the linear velocity system and the angular velocity system, respectively; This represents the control input matrix in the model. Indicates linear velocity controller, Indicates angular velocity controller; This represents the time-varying composite perturbation matrix in the model. For time-varying composite disturbances affecting linear velocity, For time-varying composite disturbances affecting angular velocity; Indicates the current moment. This indicates transpose.
[0008] Specifically, step S2 includes the following sub-steps: Step S21: Design time-varying composite perturbations affecting linear velocity and time-varying composite disturbances affecting angular velocity The mathematical expression is: ; in, This is a sudden step term; Step S22: Design a linear velocity perturbation observer and angular velocity perturbation observer To estimate time-varying composite disturbances of linear velocity in real time Combined perturbation with time-varying angular velocity The mathematical expression is: ; in, The convergence exponent, which is a finite-time convergence factor, determines the convergence rate of the observer; , , , , and The gain is positive definite and all values are greater than zero. and The auxiliary variables for the linear velocity system and the angular velocity system are respectively, and their expressions are: , ,in, and For the internal state variables and auxiliary variables of the perturbation observer, which combine the kinematic and dynamic models, their derivatives are... and satisfy: ; ; in, This indicates the actual linear speed information of the AGV. This indicates the actual angular velocity information of the AGV; linear velocity disturbance observation error. and angular velocity disturbance observation error The expressions are as follows: , .
[0009] Specifically, step S3 includes the following sub-steps: Step S31: Provide the reference linear velocity information of the AGV. and reference angular velocity information The calculation formula is: ; ; Step S32: Based on the reference linear velocity information and reference angular velocity information Calculate linear velocity tracking error and angular velocity tracking error The calculation formula is: ; in, and These represent the actual linear velocity and actual angular velocity information of the AGV, respectively. Step S33: Tracking error based on linear velocity and angular velocity tracking error Design of a linear velocity dual-layer adaptive integral sliding surface and angular velocity dual-layer adaptive integral sliding surface The expression is: ; in, and These represent the reference linear velocity information. and reference angular velocity information The time derivative; and These are linear velocity dual-layer adaptive integral sliding surfaces. and angular velocity dual-layer adaptive integral sliding surface Adaptive gain of the first sliding surface as a function of time; , For the power sign function, where and Linear velocity tracking error and angular velocity tracking error The sign function, and The parameters are convergent in finite time. and These are linear velocity dual-layer adaptive integral sliding surfaces. and angular velocity dual-layer adaptive integral sliding surface The adaptive compensation gain of the second-layer sliding surface; and It is a single-layer integral sliding surface; Indicates the integrand The integration operation is performed within the time interval [0, t], where Let t be the integration variable, and t be the current time. Step S34: Based on the linear velocity dual-layer adaptive integral sliding surface Angular velocity dual-layer adaptive integral sliding surface The linear velocity controller is designed based on the kinematic and dynamic models of the AGV in step S1. and angular velocity controller The expressions are as follows: ; in, and These represent the estimated values of the combined disturbances acting on the linear velocity and the angular velocity, respectively. and These represent the observation errors for the combined disturbances acting on the linear velocity and the angular velocity, respectively. and For adaptive gain switching; Step S35: Input reference linear velocity information and reference angular velocity information The reference trajectory RT of the AGV is obtained after the kinematic model of the AGV. and via the linear velocity controller and angular velocity controller The actual linear velocity information of the AGV is obtained after the control action. and actual angular velocity information Input the actual linear speed information of the AGV. and actual angular velocity information After obtaining the kinematic model, the actual trajectory RT1 under the AGV trajectory tracking control method based on the adaptive integral sliding mode controller is obtained.
[0010] Specifically, step S34 further includes: setting the adaptive gain of the first layer sliding surface of the linear velocity. Adaptive compensation gain of the second-layer sliding mode surface of linear velocity Linear velocity switching gain Adaptive gain of the first layer sliding surface for angular velocity Adaptive compensation gain of the second-layer sliding mode surface for angular velocity Switching gain between angular velocity and The expressions are as follows: ; ; ; ; ; ; ; ; in, The first-layer adaptive growth rate of the linear velocity sliding surface gain. The first layer adaptive attenuation rate is the linear velocity sliding surface gain. The second-layer adaptive growth rate is the linear velocity sliding surface gain. The second layer adaptive attenuation rate is the linear velocity sliding surface gain. The adaptive growth rate of the linear velocity switching gain. An adaptive attenuation rate for gain switching at linear velocity; The first-layer adaptive growth rate of the angular velocity sliding surface gain. The first layer adaptive attenuation rate is the angular velocity sliding surface gain. The second-layer adaptive growth rate of the angular velocity sliding surface gain. The second layer adaptive attenuation rate is the angular velocity sliding surface gain. The adaptive growth rate of the angular velocity switching gain. The adaptive attenuation rate for angular velocity switching gain; The error threshold for adjusting the adaptive gain of the first layer of the linear velocity sliding surface. The error threshold for adjusting the adaptive gain of the second layer of the linear velocity sliding surface; Error threshold for adjusting gain during linear velocity switching; The error threshold for the adaptive gain adjustment of the first layer of the angular velocity sliding surface; The error threshold for the adaptive gain adjustment of the second layer of the angular velocity sliding surface; Error threshold for angular velocity switching gain adjustment; adaptive switching gain From the reference gain and adaptive terms Composition; Adaptive switching gain From the reference gain and adaptive terms composition; , , , , They represent , , , , , The derivative of .
[0011] Specifically, it also includes a performance comparison step, which specifically includes: Step S4: Design a sliding mode controller based on traditional control methods In contrast, its expression is: ; in, The controller is for controlling linear velocity information. A controller for controlling angular velocity information; Step S5: Input reference linear velocity information and reference angular velocity information Based on the reference trajectory RT obtained in step S35 and the actual trajectory RT1 under the AGV trajectory tracking control method based on the adaptive integral sliding mode controller, the sliding mode controller in the traditional control method described in step S4 is derived. The actual trajectory RT2 under the action; Step S6: The actual trajectory RT1 under the AGV trajectory tracking control method based on the adaptive integral sliding mode controller, and the sliding mode controller in the traditional control method are compared. The tracking performance of the actual trajectory RT2 and the reference trajectory RT under the action was compared.
[0012] Specifically, step S6 further includes: comparing the trajectory tracking performance, velocity convergence performance, and control input jitter and spikes of different methods.
[0013] The beneficial effects of this invention are as follows: This invention proposes an AGV trajectory tracking control method based on an adaptive integral sliding mode controller. This method designs an AGV kinematic and dynamic model that includes a composite disturbance consisting of model uncertainty and external disturbance. Based on this, a nonlinear disturbance observer with finite-time convergence is designed to achieve accurate estimation and feedforward compensation of the composite disturbance. A two-layer adaptive integral sliding mode controller is designed, which uses an adaptive gain law to adjust the sliding surface gain and switching gain in real time. The feedforward compensation function of the disturbance observer is combined with the two-layer adaptive sliding mode controller, which significantly improves the dynamic response performance and effectively reduces the control input spikes at the moment of trajectory change and the high-frequency chattering in the steady state stage.
[0014] Compared to traditional control methods, this invention accelerates the convergence speed of the system state, improves trajectory tracking accuracy, reduces the amplitude of control spikes, and avoids the risk of actuator saturation. This invention effectively suppresses the impact of combined disturbances—model uncertainty and external disturbances—on the actual operation of the AGV, ensuring that the system simultaneously achieves control objectives such as high precision, rapid response, and strong robustness under complex operating conditions. Attached Figure Description
[0015] 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.
[0016] Figure 1 This is a flowchart illustrating the overall process of the AGV trajectory tracking control method based on an adaptive integral sliding mode controller in this embodiment of the invention. Figure 2 This is a schematic diagram of the simulation results of linear velocity tracking error in an embodiment of the present invention; Figure 3 This is a schematic diagram of the simulation results of angular velocity tracking error in an embodiment of the present invention; Figure 4 This is a schematic diagram of the simulation results of the X-direction position tracking error in an embodiment of the present invention; Figure 5 This is a schematic diagram of the simulation results of the Y-direction position tracking error in an embodiment of the present invention; Figure 6 This is a schematic diagram of the simulation results of the actual trajectory RT1 of the method of the present invention, the actual trajectory RT2 of the traditional method, and the reference trajectory RT in an embodiment of the present invention; Figure 7 This is a schematic diagram of the comparative simulation results of the linear velocity control input in an embodiment of the present invention; Figure 8 This is a schematic diagram showing the comparative simulation results of angular velocity control input in an embodiment of the present invention. Detailed Implementation
[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.
[0018] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.
[0019] The following is in conjunction with the appendix Figure 1 ~Attached Figure 8 The following describes some embodiments of the present invention in detail. Unless otherwise specified, the following embodiments and features can be combined with each other.
[0020] This invention proposes an AGV trajectory tracking control method based on an adaptive integral sliding mode controller. Compared with traditional methods, the proposed control method can simultaneously achieve high precision, fast response, and strong robustness when dealing with the combined disturbances caused by model uncertainty and external disturbances. This allows the AGV's actual trajectory to quickly and stably track a preset reference trajectory. In a preferred embodiment, the method includes the following steps: Step S1: Establish the kinematic and dynamic models of the AGV containing complex disturbances; Step S2: Treat model uncertainties and external environmental disturbances as a composite disturbance, and design a disturbance observer based on the mathematical model of the AGV; Step S3: Input the reference linear velocity information and reference angular velocity information, design a linear velocity dual-layer adaptive integral sliding mode controller and an angular velocity dual-layer adaptive integral sliding mode controller for control, obtain the actual linear velocity information, actual angular velocity information and actual position information of the AGV, and then obtain the actual trajectory RT1 of the AGV; It also includes a performance comparison step, specifically including: Step S4: Design a sliding mode controller based on traditional control methods In contrast, its expression is: ; in, The controller is for controlling linear velocity information. A controller for controlling angular velocity information; Step S5: Input reference linear velocity information and reference angular velocity information Based on the reference trajectory RT obtained in step S35 and the actual trajectory RT1 under the AGV trajectory tracking control method based on the adaptive integral sliding mode controller, the sliding mode controller in the traditional control method described in step S4 is derived. The actual trajectory RT2 under the action; Step S6: The actual trajectory RT1 under the AGV trajectory tracking control method based on the adaptive integral sliding mode controller, and the sliding mode controller in the traditional control method are compared. The tracking performance of the actual trajectory RT2 and the reference trajectory RT under the action was compared.
[0021] The steps are explained in detail below with reference to specific embodiments: The specific implementation steps of the AGV trajectory tracking control method based on adaptive integral sliding mode controller are as follows: (1) Establish the dynamics and kinematics model of the AGV containing complex disturbances. The specific expression is as follows: ; in, These are the x-coordinate, y-coordinate, and heading angle of the AGV's center of mass in the vehicle coordinate system. yes The derivative of This is the coordinate transformation matrix. For generalized velocity vectors, Indicates linear velocity information, Represents angular velocity information. express The derivative of The generalized mass-inertia matrix, Indicates the mass of the AGV. This represents the moment of inertia of the AGV. Here is the damping matrix. and These are the equivalent damping coefficients for the linear velocity system and the angular velocity system, respectively. This represents the control input matrix in the model. Indicates linear velocity controller, Indicates angular velocity controller, Let represent the time-varying composite perturbation matrix in the model, where For time-varying composite disturbances affecting linear velocity, This refers to the time-varying composite disturbance that affects angular velocity.
[0022] In this embodiment, the AGV model parameters are specifically selected as: mass parameters. rotational inertia parameters The equivalent damping coefficient of the linear velocity system Angular velocity system equivalent damping coefficient .
[0023] Time-varying composite perturbation affecting linear velocity in the model Time-varying composite disturbances affecting angular velocity Designed as follows: ; in, This is a step term representing a sudden change.
[0024] (2) Design a disturbance observer to accurately estimate the time-varying composite disturbance of linear velocity and the time-varying composite disturbance of angular velocity. Its expression is: ; ; in, The specific parameter values are: , , , , , and The gain is positive definite and all values are greater than zero. Specific parameter values are: ; and The auxiliary variables for the linear velocity system and the angular velocity system are respectively, and their expressions are: , ,in, For actual linear velocity information, This is the actual angular velocity information. and For the internal state variables and auxiliary variables of the perturbation observer, which combine the kinematic and dynamic models, their derivatives are... and satisfy: , Perturbation observation error and The expressions are as follows: , .
[0025] (3) Design the dual-layer adaptive finite-time integral sliding mode controller of the present invention, with reference linear velocity information input into the model. Reference angular velocity information for: ; ; Based on the input reference linear velocity information and reference angular velocity information Actual linear velocity information after the control effect of the method of the present invention Actual angular velocity information Calculate linear velocity tracking error and angular velocity error Its expression is: .
[0026] Based on linear velocity tracking error Angular velocity tracking error To design a linear velocity dual-layer adaptive integral sliding surface and angular velocity dual-layer adaptive integral sliding surface The expressions are as follows: ; in, and They represent and The time derivative; and They are respectively and The adaptive gain of the first sliding surface, which varies with time, has a derivative that specifically satisfies: , ; in, The first-layer adaptive growth rate of the linear velocity sliding surface gain. The first layer adaptive attenuation rate is the linear velocity sliding surface gain. The first-layer adaptive growth rate of the angular velocity sliding surface gain. The first-layer adaptive attenuation rate is the angular velocity sliding surface gain; in this embodiment, the specific value is... , , , . The error threshold for adjusting the adaptive gain of the first layer of the linear velocity sliding surface is specifically selected as [value missing]. , The error threshold for the adaptive gain adjustment of the first layer of the angular velocity sliding surface is specifically selected as [value missing]. All adaptive rates are positive real numbers, and the error threshold is set according to the system's steady-state accuracy requirements. , For the power sign function, where and They are respectively and The sign function, and These are finite-time convergence parameters, with specific values as follows: , ; , They are respectively and The adaptive compensation gain of the second sliding surface has a derivative that specifically satisfies: , ; in, The second-layer adaptive growth rate is the linear velocity sliding surface gain. The second layer adaptive attenuation rate is the linear velocity sliding surface gain. The second-layer adaptive growth rate of the angular velocity sliding surface gain. The second-layer adaptive attenuation rate is the angular velocity sliding surface gain; in this embodiment, the specific value is... , , , . The error threshold for adjusting the adaptive gain of the second layer of the linear velocity sliding surface is specifically selected as [value missing]. , The error threshold for adjusting the adaptive gain of the second layer of the angular velocity sliding surface is specifically selected as [value missing]. The adaptive rates are all positive real numbers, and the error threshold is set according to the steady-state accuracy requirements of the system. and It is the inner sliding surface.
[0027] according to , The linear velocity controller of this invention is designed based on the kinematic and dynamic models of the AGV. and angular velocity controller The expressions are as follows: ; in, and These represent the estimated values of the combined disturbances acting on the linear velocity and the angular velocity, respectively. and These represent the observation errors for the combined disturbances acting on the linear velocity and the angular velocity, respectively. The adaptive switching gain of the linear velocity controller is expressed as follows: ,in, The reference gain has the following specific value: , The derivative of the adaptive term satisfies: ; in, The adaptive growth rate of the linear velocity switching gain. The adaptive attenuation rate for linear velocity switching gain is specifically valued as follows: , , The error threshold for adjusting the linear velocity switching gain is specifically set to [value]. All adaptive rates are positive real numbers, and the error threshold is set according to the system's steady-state accuracy requirements. The adaptive switching gain of the angular velocity controller is expressed as follows: ,in, The reference gain has the following specific value: , For the adaptive term, its derivative satisfies: ; in, The adaptive growth rate of the angular velocity switching gain. The adaptive attenuation rate for angular velocity switching gain is specifically set to... , , The error threshold for adjusting the angular velocity switching gain is specifically set to [value]. The adaptive rates are all positive real numbers, and the error threshold is set according to the steady-state accuracy requirements of the system.
[0028] (4) Design comparison method: traditional sliding mode controller Its expression is as follows: ; in, The controller is for controlling linear velocity information. A controller for controlling angular velocity information.
[0029] like Figures 1 to 8 As shown, the AGV trajectory tracking control method based on an adaptive integral sliding mode controller according to the present invention includes the following steps: (1) The implementation process of the AGV trajectory tracking control method based on adaptive integral sliding mode controller is as follows: Figure 1 In this embodiment, an AGV control system is considered, wherein the dynamics and kinematics model of the vehicle during movement is as follows: ; The specific model parameters selected are: mass parameters. rotational inertia parameters The equivalent damping coefficient of the linear velocity system Angular velocity system equivalent damping coefficient .
[0030] (2) In this embodiment, the reference angular velocity information and reference angular velocity information of the AGV are input as follows: ; Based on the input linear velocity and angular velocity, the AGV starts from a stationary state, with the linear velocity increasing linearly to 0.7 m / s and the angular velocity changing abruptly 4 times. Within 60 seconds, the kinematic model generates the reference trajectory RT of the AGV.
[0031] The composite perturbation input to the model is designed as follows: ; ; in, This is a step term representing a sudden change.
[0032] (3) Design a disturbance observer to estimate the composite disturbance, the expression of which is: ; ; In this embodiment, the specific parameter values are: , , , , , , .
[0033] (4) Design the dual-layer adaptive finite-time integral sliding mode controller of the present invention to achieve adaptive parameter update: Based on the input reference linear velocity information and reference angular velocity information Actual linear velocity information after the control effect of the method of the present invention Actual angular velocity information Calculate linear velocity tracking error and angular velocity error Its expression is: ; Based on linear velocity tracking error Angular velocity tracking error To design a linear velocity dual-layer adaptive integral sliding surface and angular velocity dual-layer adaptive integral sliding surface The expressions are as follows: ; in, and They represent and The time derivative; and They are respectively and The adaptive gain of the first sliding surface, which varies with time, has a derivative that specifically satisfies: , ; in, , , , , , , , ; , They are respectively and The adaptive compensation gain of the second sliding surface has a derivative that specifically satisfies: , ; in, , , , , , , and It is the inner sliding surface.
[0034] according to , The linear velocity controller of this invention is designed based on the kinematic and dynamic models of the AGV. and angular velocity controller The expressions are as follows: ; in, The adaptive switching gain of the linear velocity controller is expressed as follows: ,in, The reference gain has the following specific value: , The derivative of the adaptive term satisfies: ; in, , , ; The adaptive switching gain of the angular velocity controller is expressed as follows: ,in, The reference gain has the following specific value: , For the adaptive term, its derivative satisfies: ; in, , , .
[0035] (5) Design comparison method: traditional sliding mode controller Its expression is as follows: ; in, The controller is for controlling linear velocity information. A controller for controlling angular velocity information.
[0036] (6) Analyze the performance of trajectory tracking control: Error convergence performance analysis: by Figure 2 It can be seen that the linear velocity tracking error of the method of the present invention (solid black line) converges to the ±0.01 m / s neighborhood in approximately 0.288 s, while the traditional method (gray dotted line) requires approximately 0.76 s. In comparison, the convergence time of the method of the present invention is shortened by approximately 62.1% compared to the traditional method; Figure 3As shown in the convergence results of the angular velocity tracking error, at 30s, when the angular velocity command abruptly changes from -0.1 rad / s to 0.25 rad / s, the method of this invention (solid black line) converges to the ±0.003 rad / s neighborhood in only about 0.067s, while the traditional method (dotted gray line) requires about 0.917s. The convergence time of the method of this invention is significantly reduced by 92.7% compared to the traditional method. This fast convergence performance advantage is mainly attributed to the proposed two-layer adaptive mechanism, which dynamically optimizes the parameters of the sliding mode controller based on the system state, thereby achieving a faster dynamic response speed. The above results demonstrate that the method of this invention has a significant fast convergence performance advantage in trajectory tracking control. This advantage is mainly attributed to the proposed two-layer adaptive mechanism, which dynamically optimizes the parameters of the sliding mode controller based on the system state, thereby achieving a faster dynamic response speed.
[0037] Analysis of position tracking error and trajectory tracking results: From Figure 4 (X-direction position error) It can be seen that the position error curve (solid black line) of the method of this invention fluctuates closely around the zero error line throughout the entire control process, with extremely small error amplitude and rapid convergence. This indicates that the adaptive integral sliding mode controller designed in this invention can effectively compensate for model uncertainties and external disturbances, achieving high-precision trajectory tracking. In contrast, the traditional method (gray dotted line) showed significant error fluctuations in the later stages of the simulation, indicating that the fixed gain of the traditional control method cannot adapt to changes in disturbances when facing time-varying composite disturbances, leading to a decrease in tracking performance. From Figure 5 (Y-direction position error) It can be seen that the error curve of the method of the present invention maintains extremely high stability throughout the entire time domain, with almost no obvious overshoot or oscillation, while the traditional method shows a significant error peak again in the same time period, further verifying its limitations under complex disturbance conditions. Figure 6 The diagram shows a comparison of the overall trajectory tracking performance of the method of this invention and the traditional method on a two-dimensional plane. From the overall trajectory direction, the actual trajectory RT1 (black solid line) generated by the method of this invention almost completely overlaps with the reference trajectory RT (gray dashed line). In areas with large changes in trajectory curvature (such as curves or circular segments), the trajectory RT2 (gray dotted line) of the traditional method shows obvious deviation, while the trajectory RT1 of the method of this invention can still closely follow the reference trajectory. This further confirms that the method of this invention can effectively overcome the influence of complex disturbances and achieve high-precision, smooth trajectory tracking when dealing with complex path tracking tasks, verifying the effectiveness and superiority of the proposed control strategy.
[0038] Analysis of the comparison results of control inputs: From Figure 7The linear velocity control input result graph shows that the overall trend of the control input of the method of this invention (solid black line) and the traditional method (gray dotted line) is basically the same, both exhibiting periodic fluctuations. However, the control signal of the traditional method has obvious high-frequency chattering (sawtooth fluctuations). In contrast, the control curve of the method of this invention is the smoothest, with no obvious high-frequency noise. This indicates that the present invention, through a two-layer adaptive mechanism, automatically reduces the switching gain in the steady-state stage, effectively suppressing chattering and improving control performance. Figure 8 As can be seen from the (angular velocity control input) data, at the 30s trajectory abrupt change, the control input of the traditional method (gray dotted line) exhibits a momentary increase, with a peak amplitude reaching 306.5 N·m. In contrast, the overshoot amplitude of the method of this invention (black solid line) is effectively suppressed to 17.9 N·m, a significant reduction of 94.2% compared to the traditional method. Figure 8 The magnified view also shows that the method of the present invention effectively suppresses the high-frequency chattering phenomenon of the traditional method. In this embodiment, statistical calculations show that the root mean square (RMS) index, which reflects the global control energy, has an average value of approximately 11.99 N·m over the entire simulation period, which is also lower than that of the traditional method, proving that its overall control output is more stable and its energy consumption is lower.
[0039] The AGV trajectory tracking control method based on an adaptive integral sliding mode controller proposed in this invention significantly suppresses control input spikes in complex scenarios while retaining the system's high-precision tracking and rapid error convergence. It has stronger adaptive capabilities and engineering practicality, and is suitable for the high-precision, fast-response, and robust control requirements of AGV trajectory tracking in complex scenarios.
[0040] For the foregoing embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to this application.
[0041] The above embodiments describe the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Modifications and variations made by those skilled in the art without departing from the spirit and scope of the invention should be within the protection scope of the appended claims.
Claims
1. An AGV trajectory tracking control method based on an adaptive integral sliding mode controller, applied to a controller configured on an AGV, wherein the controller is connected to a motor driver for driving the left and right wheels of the AGV via an onboard communication bus, characterized in that... Includes the following steps: Step S1: Establish the kinematic and dynamic models of the AGV containing complex disturbances; Step S2: Treat model uncertainties and external environmental disturbances as a composite disturbance, and design a disturbance observer based on the mathematical model of the AGV; Step S3: Input the reference linear velocity information and reference angular velocity information, design a linear velocity dual-layer adaptive integral sliding mode controller and an angular velocity dual-layer adaptive integral sliding mode controller for control, obtain the actual linear velocity information, actual angular velocity information and actual position information of the AGV, and then obtain the actual trajectory RT1 of the AGV so that the actual trajectory of the AGV tracks the reference trajectory.
2. The AGV trajectory tracking control method based on an adaptive integral sliding mode controller as described in claim 1, characterized in that, The mathematical expression for the model in step S1 is as follows: ； in, These represent the x-coordinate, y-coordinate, and heading angle of the AGV's centroid in the vehicle coordinate system, respectively. yes The derivative; This is the coordinate transformation matrix; It is a generalized velocity vector; Indicates linear velocity information; Represents angular velocity information; express The derivative; The generalized mass-inertia matrix, Indicates the mass of the AGV. This represents the moment of inertia of the AGV. Here is the damping matrix. and These are the equivalent damping coefficients for the linear velocity system and the angular velocity system, respectively; This represents the control input matrix in the model. Indicates linear velocity controller, Indicates angular velocity controller; This represents the time-varying composite perturbation matrix in the model. For time-varying composite disturbances affecting linear velocity, For time-varying composite disturbances affecting angular velocity; Indicates the current moment. This indicates transpose.
3. The AGV trajectory tracking control method based on an adaptive integral sliding mode controller as described in claim 2, characterized in that, Step S2 specifically includes the following sub-steps: Step S21: Design time-varying composite perturbations affecting linear velocity and time-varying composite disturbances affecting angular velocity The mathematical expression is: ； in, This is a sudden step term; Step S22: Design a linear velocity perturbation observer and angular velocity perturbation observer To estimate the time-varying composite disturbance of linear velocity in real time Combined perturbation with time-varying angular velocity The mathematical expression is: ； in, The convergence exponent, which is a finite-time convergence factor, determines the convergence rate of the observer; , , , , and The gain is positive definite and all values are greater than zero. and The auxiliary variables for the linear velocity system and the angular velocity system are respectively, and their expressions are: , ,in, and For the internal state variables and auxiliary variables of the perturbation observer, which combine the kinematic and dynamic models, their derivatives are... and satisfy: ； ； in, This indicates the actual linear speed information of the AGV. This indicates the actual angular velocity information of the AGV; linear velocity disturbance observation error. and angular velocity disturbance observation error The expressions are as follows: , .
4. The AGV trajectory tracking control method based on an adaptive integral sliding mode controller as described in claim 3, characterized in that, Step S3 specifically includes the following sub-steps: Step S31: Provide the reference linear velocity information of the AGV. and reference angular velocity information The calculation formula is: ； ； Step S32: Based on the reference linear velocity information and reference angular velocity information Calculate linear velocity tracking error and angular velocity tracking error The calculation formula is: ； in, and These represent the actual linear velocity and actual angular velocity information of the AGV, respectively. Step S33: Tracking error based on linear velocity and angular velocity tracking error Design of a linear velocity dual-layer adaptive integral sliding surface and angular velocity dual-layer adaptive integral sliding surface The expression is: ； in, and These represent the reference linear velocity information. and reference angular velocity information The time derivative; and These are linear velocity dual-layer adaptive integral sliding surfaces. and angular velocity dual-layer adaptive integral sliding surface Adaptive gain of the first sliding surface as a function of time; , For the power sign function, where and Linear velocity tracking error and angular velocity tracking error The sign function, and The parameters are convergent in finite time. and These are linear velocity dual-layer adaptive integral sliding surfaces. and angular velocity dual-layer adaptive integral sliding surface The adaptive compensation gain of the second-layer sliding surface; and It is a single-layer integral sliding surface; Indicates the integrand The integration operation is performed within the time interval [0, t], where Let t be the integral variable, and t be the current time. Step S34: Based on the linear velocity dual-layer adaptive integral sliding surface Angular velocity dual-layer adaptive integral sliding surface The linear velocity controller is designed based on the kinematic and dynamic models of the AGV in step S1. and angular velocity controller The expressions are as follows: ； in, and These represent the estimated values of the combined disturbances acting on the linear velocity and the angular velocity, respectively. and These represent the observation errors for the combined disturbances acting on the linear velocity and the angular velocity, respectively. and For adaptive gain switching; Step S35: Input reference linear velocity information and reference angular velocity information The reference trajectory RT of the AGV is obtained after the kinematic model of the AGV. and via the linear velocity controller and angular velocity controller The actual linear velocity information of the AGV is obtained after the control action. and actual angular velocity information Input the actual linear speed information of the AGV. and actual angular velocity information After obtaining the kinematic model, the actual trajectory RT1 under the AGV trajectory tracking control method based on the adaptive integral sliding mode controller is obtained.
5. The AGV trajectory tracking control method based on an adaptive integral sliding mode controller as described in claim 4, characterized in that, Step S34 further includes: setting the adaptive gain of the first layer sliding surface of the linear velocity. Adaptive compensation gain of the second-layer sliding surface of linear velocity Linear velocity switching gain Adaptive gain of the first layer sliding surface for angular velocity Adaptive compensation gain of the second-layer sliding mode surface for angular velocity Switching gain between angular velocity and The expressions are as follows: ； ； ； ； ； ； ； ； in, The first-layer adaptive growth rate of the linear velocity sliding surface gain. The first layer adaptive attenuation rate is the linear velocity sliding surface gain. The second-layer adaptive growth rate is the linear velocity sliding surface gain. The second layer adaptive attenuation rate is the linear velocity sliding surface gain. The adaptive growth rate of the linear velocity switching gain. An adaptive attenuation rate for gain switching at linear velocity; The first-layer adaptive growth rate of the angular velocity sliding surface gain. The first layer adaptive attenuation rate is the angular velocity sliding surface gain. The second-layer adaptive growth rate of the angular velocity sliding surface gain. The second layer adaptive attenuation rate is the angular velocity sliding surface gain. The adaptive growth rate of the angular velocity switching gain. The adaptive attenuation rate for angular velocity switching gain; The error threshold for adjusting the adaptive gain of the first layer of the linear velocity sliding surface. The error threshold for adjusting the adaptive gain of the second layer of the linear velocity sliding surface; Error threshold for adjusting gain during linear velocity switching; The error threshold for the adaptive gain adjustment of the first layer of the angular velocity sliding surface; The error threshold for the adaptive gain adjustment of the second layer of the angular velocity sliding surface; Error threshold for angular velocity switching gain adjustment; adaptive switching gain From the reference gain and adaptive terms Composition; Adaptive switching gain From the reference gain and adaptive terms composition; , , , , They represent , , , , , The derivative of .
6. The AGV trajectory tracking control method based on an adaptive integral sliding mode controller as described in claim 5, characterized in that, It also includes a performance comparison step, specifically including: Step S4: Design a sliding mode controller based on traditional control methods In contrast, its expression is: ； in, The controller is for controlling linear velocity information. A controller for controlling angular velocity information; Step S5: Input reference linear velocity information and reference angular velocity information Based on the reference trajectory RT obtained in step S35 and the actual trajectory RT1 under the AGV trajectory tracking control method based on the adaptive integral sliding mode controller, the sliding mode controller in the traditional control method described in step S4 is derived. The actual trajectory RT2 under the action; Step S6: The actual trajectory RT1 under the AGV trajectory tracking control method based on the adaptive integral sliding mode controller, and the sliding mode controller in the traditional control method are compared. The tracking performance of the actual trajectory RT2 and the reference trajectory RT under the action was compared.
7. The AGV trajectory tracking control method based on an adaptive integral sliding mode controller as described in claim 6, characterized in that, Step S6 further includes: comparing the trajectory tracking performance, velocity convergence performance, and control input jitter and spikes of different methods.