Trajectory tracking control method for car-like mobile robot in unreliable communication environment

Abstract

The invention discloses a trajectory tracking control method for a car-like mobile robot in an unreliable communication environment. The method comprises the following steps: 1, establishing a kinematic model and a dynamic model of the car-like mobile robot; 2, designing a robot digital twin platform based on the three-dimensional model of the vehicle-like mobile robot and an ROS transmission communication mechanism; 3, aiming at the problems of communication time delay and data packet loss caused in an unreliable communication environment, designing a switching elastic compensator and a proportional differential plus damping controller, and acting on the virtual end vehicle-like mobile robot; according to the speed information of the virtual end vehicle-like mobile robot, feedforward control quantity and a feasible track are provided for the physical end vehicle-like mobile robot; 4, designing a double-closed-loop control strategy of the physical end vehicle-like mobile robot; according to the invention, the influence of an unreliable communication environment is reduced, the robustness and tracking precision of the vehicle-like mobile robot are improved, and visual monitoring of the physical-end vehicle-like mobile robot can be realized through the virtual-end vehicle-like mobile robot.

Description

Technical Field

[0001] The present invention relates to the technical field of digital twin and mobile robot tracking control, and in particular to a synchronous trajectory tracking control method of a vehicle-like mobile robot based on digital twin technology in an unreliable communication environment. Background Art

[0002] With the rapid development of Industry 4.0 and intelligent manufacturing, mobile robots have received more and more attention in the fields of industrial production, warehousing and logistics due to their unique kinematic characteristics and broad application prospects. In practical applications, control systems generally rely on network communications for data transmission and command issuance. Unreliable communication environments inevitably cause the system to face problems such as network time-varying delays and random data packet loss, which seriously affect control performance and system stability. In recent years, digital twin technology, as a bridge connecting the physical world and the information world, has provided new ideas and methods for solving problems in network control systems by building virtual mappings of physical entities and realizing real-time interaction between physical entities and virtual entities. This technology can not only monitor and predict system status in real time, but also optimize control strategies through virtual-real fusion to improve the overall performance of the system.

[0003] In the field of industrial automation, digital twin technology has shown great application potential and opened up new ways to solve control problems in complex industrial systems. Related search literature is as follows:

[0004] Reference 1: Wang W, Liu M, Li J. Research and realization of virtual-real control of robot system for off-heap detector assisted installation based on digital twin[J], IEEE Journal of Radio Frequency Identification, 2022(6):810-814. Research and realization of virtual-real control of robot system for off-heap detector assisted installation based on digital twin, IEEE Journal of Radio Frequency Identification, 2022(6):810-814.

[0005] Reference 2: Sheng J, Zhang Q, Li H, Shen S, Ming R, Jiang J, Li Q, Su G, Sun B, Wang J, Yang J, Huang C. Digital twin driven intelligent manufacturing for FPCB etching production line, Computers Industrial Engineering, 2023(186): 109763). Digital twin driven intelligent manufacturing for FPCB etching production line, Computers Industrial Engineering, 2023(186): 109763).

[0006] Reference 3: Zhao L, Nie Z, Xia Y, Li H. Virtual-Physical Tracking Control for a Car-Like Mobile Robot Based on Digital Twin Technology. IEEE Transactions on Industrial Electronics, 2024(71): 16348-16356. Virtual-Physical Tracking Control for a Car-Like Mobile Robot Based on Digital Twin Technology, IEEE Transactions on Industrial Electronics, 2024(71): 16348-16356.

[0007] Through searching, it can be seen that although digital twin technology has achieved remarkable results in the industrial field, the research on its application in trajectory tracking control of mobile robots is still relatively scarce. Literature 3, which is the latest achievement involving system robots, digital twins and trajectory tracking, only realizes the virtual mapping of physical motion states, but does not realize the mutual mapping of virtual and physical, and does not consider the random delay and packet loss during network transmission. Therefore, it is very important to consider the information interaction between physical and virtual car-like mobile robots in an unreliable communication environment and ensure the synchronous tracking of trajectories. Summary of the invention

[0008] The purpose of the present invention is to provide a trajectory tracking control method for a vehicle-like mobile robot based on digital twins in an unreliable communication environment, so as to achieve real-time tracking and prediction of the behavior of the physical system and provide more accurate decision support; the specific scheme is as follows:

[0009] A trajectory tracking control method for a vehicle-like mobile robot in an unreliable communication environment comprises the following steps:

[0010] Step 1: Establish kinematic model and dynamic model of the car-like mobile robot;

[0011] Step 2: Design a robot digital twin platform based on the three-dimensional model of the car-like mobile robot and the ROS transmission and communication mechanism;

[0012] Step 3: To address the communication delay and data packet loss problems caused by unreliable communication environments, a switching elastic compensator and a proportional differential plus damping controller are designed to act on the virtual end-car mobile robot; based on the speed information of the virtual end-car mobile robot, a feedforward control quantity and a feasible trajectory are provided for the physical end-car mobile robot;

[0013] Step: 4: Design a dual closed-loop control strategy for the physical end car-like mobile robot.

[0014] Furthermore, in step 1, the steps of establishing the kinematic model and dynamic model of the vehicle-like mobile robot are as follows:

[0015] The kinematic model of the car-like mobile robot is expressed as:

[0016]

[0017] Where i∈{P,V}, P represents the physical end, V represents the virtual end,

[0018]

[0019] (x i (t),y i (t)) is the position of the car-like mobile robot, θ i (t) is the yaw angle of the car-like mobile robot;

[0020] The dynamic model of the car-like mobile robot is expressed as:

[0021]

[0022] Among them, v i (t) and ω i (t) are the linear velocity and yaw angular velocity of the vehicle-like mobile robot, M represents the weight of the vehicle, γ is the moment of inertia of the vehicle-like mobile robot, R represents the radius of the wheel, and are the motor torques of the rear and front wheels respectively, d f (d r ) is the longitudinal distance between the centre of gravity and the front (rear) wheel; and Where s = r, f is the lateral turning force and the longitudinal friction force respectively; and is given as:

[0023]

[0024] Where F is the coefficient of kinetic friction, G s represents the cornering stiffness; considering the motor circuit, and It is expressed as:

[0025]

[0026] in is the input voltage to the motor, Indicates the speed of the motor, Ω s , H s , C e and T n are resistance, motor ratio, back EMF constant and torque constant respectively; hence the power system can be rewritten as:

[0027]

[0028] in

[0029]

[0030] in and is the total disturbance;

[0031] Definitions i (t) = [v i (t),ω i (t)] T , The kinetic model is then rewritten as:

[0032]

[0033] Furthermore, in step 2, the framework for constructing the digital twin platform of the vehicle-like mobile robot includes: a physical vehicle-like mobile robot, an intelligent traffic sandbox, a virtual vehicle-like mobile robot, a virtual-reality interaction platform, and network communication;

[0034] The virtual-reality interaction platform is used for data processing, status monitoring and application services;

[0035] The network communication includes: ROS communication for sending commands from the virtual-reality interaction platform to the physical car-like mobile robot, visualization simulation software for realizing the visualization of the movement of the car-like mobile robot, ROS communication for sending commands from the virtual-reality interaction platform to the virtual car-like mobile robot, and ROS topics for transmitting the collected physical and virtual car-like mobile robot status data.

[0036] Furthermore, in step 3, the steps of designing the switching elastic compensator and the proportional differential plus damping controller are as follows:

[0037] Step 3.1: Design a switching elastic compensator based on a zero-order holder and a proportional-derivative compensator:

[0038]

[0039] Among them, for any i∈{P,V}, represents the state information of the car-like mobile robot after compensation, s i (t) is the speed information of the car-like mobile robot, τ i (t) represents random delay, is the compensation coefficient;

[0040] Step 3.2: Based on the received state information of the physical car mobile robot and its own state information, design a proportional differential plus damping controller:

[0041]

[0042] where k V ,λ V , ρ V is the controller gain;

[0043] Step 3.3: Considering the nonlinear characteristics of the car-like mobile robot, the influence of external disturbances and unreliable communication environment, a nonlinear extended observer is designed to estimate the robot state and disturbance:

[0044]

[0045] To improve the accuracy of trajectory tracking, and The states s are i (t) and the disturbance d i The estimated value of (t), β i and α i is an adjustable positive constant;

[0046] Defining the estimation error and The observation error system is expressed as:

[0047]

[0048] β i and α i Take appropriate parameters so that the estimated error and Converges to a sufficiently small value with a certain upper bound;

[0049] Thus, the control input of the dynamics model of the virtual end-like mobile robot can be obtained.

[0050] Furthermore, in step 4, the steps of designing the dual closed-loop control strategy of the physical end vehicle-like mobile robot are as follows:

[0051] Step 4.1: Based on the kinematic model of the vehicle-like mobile robot, design a backstepping controller to implement outer loop control to ensure that the vehicle-like mobile robot tracks the reference trajectory;

[0052] Among them, the backstepping controller The design is as follows:

[0053]

[0054] Among them, L 1 , L 2 , L 3 and L 4 is an adjustable positive definite parameter, the position error Defined as:

[0055] H P (t) = F e (q r (t)-q P (t))

[0056] Among them, q r (t) = [x r (t),y r (t),θ r (t)] T is the reference trajectory, q P (t) = [x P (t),y P (t),θ P (t)] T is the actual trajectory,

[0057]

[0058] Step 4.2: For the physical end, design a switching elastic compensator based on a zero-order holder and a proportional differential compensator:

[0059]

[0060] in, represents the state information of the virtual car-like mobile robot after compensation, τ V (t) represents the random network delay when transmitting from the virtual end to the physical end, is the compensation coefficient;

[0061] Step 4.3: Based on the dynamic model of the car-like mobile robot, design an inner-loop control strategy that relies on a weighted averager to achieve high-precision speed tracking; the weighted averager is:

[0062]

[0063] Among them, 0 <c 1 <1 and 0 <c 2 <1 satisfies c 1 +c 2 =1; in tracking control, when the position error between the physical car mobile robot and the reference trajectory exceeds 0.05m, the physical car mobile robot will prioritize tracking the reference trajectory, i.e., c 1 = 0 and c 2 =1; on the contrary, when the position error is less than 0.05 meters, the trajectory of the virtual car-like mobile robot is mapped to the physical car-like mobile robot, thereby setting and To correct trajectories and improve the tracking accuracy of physical and virtual car-like mobile robots;

[0064] Step 4.4: Design the proportional derivative plus damping controller of the inner loop controller:

[0065]

[0066] where k P ,λ P , ρ P is the controller gain;

[0067] Step 4.5: Design a nonlinear extended observer to estimate the state and disturbance of the physical end car-like mobile robot:

[0068]

[0069] in and The states s are P (t) and the disturbance d P The estimated value of (t), β P and α P is an adjustable positive constant;

[0070] Defining the estimation error and Then the observation error system can be expressed as:

[0071]

[0072] β P and α P Taking appropriate parameters can make the estimation error and Converges to a sufficiently small value with a certain upper bound;

[0073] Thus, the control input of the dynamics model of the physical end car-like mobile robot is obtained

[0074] By adopting the above technical solution, the present invention has the following technical effects:

[0075] (1) There will be a large number of on-site experiments during the debugging process of the car-like mobile robot. The digital twin system designed by the present invention can effectively improve the debugging process, reduce the hardware burden, and visualize the motion state of the virtual car-like mobile robot;

[0076] (2) Considering the unreliable communication environment with random delay and packet loss, the present invention designs a switching elastic compensation mechanism and a nonlinear extended observer, which has better robustness and trajectory tracking accuracy;

[0077] (3) In the process of designing the controller of the physical end vehicle-like mobile robot, the present invention designs a dual closed-loop control strategy with higher tracking accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 This is a schematic diagram of the structure of the vehicle-like mobile robot of the present invention;

[0079] Figure 2 It is a schematic diagram of the framework of the digital twin platform of the mobile robot of the present invention;

[0080] Figure 3 It is a schematic diagram of the trajectory tracking control method of a vehicle-like mobile robot in an unreliable communication environment of the present invention;

[0081] Figure 4 A schematic diagram of the position error of the vehicle-like mobile robot provided by the present invention;

[0082] Figure 5 Schematic diagram of the movement trajectories of the physical mobile robot and the virtual mobile robot in an embodiment of the present invention. DETAILED DESCRIPTION

[0083] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0084] This embodiment provides a trajectory tracking control method for a vehicle-like mobile robot in an unreliable communication environment. Figure 1 This is a schematic diagram of the structure of the vehicle-like mobile robot in this embodiment, which specifically includes the following steps:

[0085] Step 1: Establish the kinematic model and dynamic model of the car-like mobile robot;

[0086] like Figure 1 As shown, {X, O, Y} is the global coordinate, G brepresents the center of gravity of the physical car-like mobile robot, O P represents the center point of the rear wheel axle, (x P (t),y P (t)) is the position of the physical end-like mobile robot, θ P (t) represents the yaw angle of the physical end car-like mobile robot, is the deflection angle of the front wheel, and the longitudinal distance d between the center of gravity and the front wheel f = 0.2m, longitudinal distance d between the center of gravity and the rear wheel r =0.16m.

[0087] The kinematic model of the car-like mobile robot can be expressed as:

[0088]

[0089] Where i∈{P,V}, P represents the physical end, V represents the virtual end,

[0090]

[0091] (x i (t),y i (t)) is the position of the car-like mobile robot, θ i (t) is the yaw angle of the car-like mobile robot;

[0092] The dynamic model of the car-like mobile robot is as follows:

[0093]

[0094] where v i (t) and ω i (t) are the linear velocity and yaw angular velocity of the vehicle-like mobile robot, the weight of the vehicle M = 3.6 kg, and the moment of inertia of the vehicle-like mobile robot γ = 0.25 kg / m 2 , the radius of the wheel R = 0.06m, and are the motor torques of the rear and front wheels respectively, d f (d r ) is the longitudinal distance between the center of gravity and the front (rear) wheel, and Where s=r, f is the lateral turning force and longitudinal friction force respectively. and Given as

[0095]

[0096] Where F is the coefficient of kinetic friction, G s represents the cornering stiffness; considering the motor circuit, and It is expressed as:

[0097]

[0098] in, is the input voltage to the motor, Indicates the speed of the motor, Ω s , H s , C e and T n They are resistance, motor transmission ratio, back electromotive force constant and torque constant respectively; further, the power system is rewritten as:

[0099]

[0100] in

[0101]

[0102]

[0103] in and is the total disturbance;

[0104] Definitions i (t) = [v i (t),ω i (t)] T , The kinetic model is then rewritten as:

[0105]

[0106] Step 2: Design a robot digital twin platform based on the three-dimensional model of the car-like mobile robot and the ROS transmission and communication mechanism. The platform framework includes: a physical car-like mobile robot, an intelligent traffic sandbox, a virtual car-like mobile robot, a virtual-reality interaction platform, and network communication, such as Figure 2 As shown;

[0107] The virtual-reality interaction platform is used for data processing, status monitoring and application services;

[0108] Network communications include: ROS communication for sending commands from the virtual-reality interaction platform to the physical car-like mobile robot, visualization simulation software for visualizing the motion of the car-like mobile robot, ROS communication for sending commands from the virtual-reality interaction platform to the virtual car-like mobile robot, and ROS topics for transmitting collected status data of the physical and virtual car-like mobile robots.

[0109] Step 3: To address the communication delay and data packet loss issues caused by unreliable communication environments, design a switching elastic compensator and a proportional differential plus damping controller:

[0110] like Figure 3 As shown, the lower area represents the trajectory tracking process of the virtual end-type car mobile robot; first, in view of the random delay and packet loss in the communication network, a switching elastic compensator based on a zero-order holder and a proportional differential compensator is designed:

[0111]

[0112] in, represents the state information of the physical end car-like mobile robot after compensation, τ P (t) represents the random network delay when transmitting from the physical end to the virtual end, and the compensation coefficient

[0113] Then, based on the state information of the physical end car-like mobile robot received and combined with its own current state information, a proportional differential plus damping controller is designed:

[0114]

[0115] Among them, the controller gain

[0116] Next, considering the nonlinear characteristics of the car-like mobile robot, the influence of external disturbances and unreliable communication environment, a nonlinear extended observer is designed to estimate the state and disturbance of the car-like mobile robot:

[0117]

[0118] To improve the accuracy of trajectory tracking, and The states s are V (t) and the disturbance d V The estimated value of (t), positive constant β V =30 and α V =1000;

[0119] Defining the estimation error and Then the observation error system can be expressed as:

[0120]

[0121] Finally, the control input of the dynamics model of the virtual end car-like mobile robot is obtained

[0122] Step 4: Design a dual closed-loop control strategy for the physical end vehicle-like mobile robot:

[0123] like Figure 3 As shown in the figure, the upper area represents the trajectory tracking process of the physical end vehicle-like mobile robot; based on the kinematic model of the vehicle-like mobile robot, a backstepping controller is designed to implement outer loop control to ensure that the vehicle-like mobile robot tracks the reference trajectory. The design is as follows:

[0124]

[0125] The positive definite parameter L 1 =0.02, L 2 =1.54,L 3 =0.24 and L 4 =0.33, such as Figure 4 The schematic diagram of the position error of the car-like mobile robot is shown in Figure 2. The definition is as follows:

[0126] H P (t) = F e (q r (t)-q P (t))

[0127] Among them, the reference trajectory q r (t) = [x r (t),y r (t),θ r (t)] T ,

[0128]

[0129] Then, for the physical end, a switching elastic compensator based on a zero-order holder and a proportional differential compensator is designed:

[0130]

[0131] in represents the state information of the virtual car-like mobile robot after compensation, τ V (t) represents the random network delay when transmitting from the virtual end to the physical end, and the compensation coefficient

[0132] In addition, the inner loop control based on the car-like mobile robot is designed to track the robot's speed; since the controller has a signal from the backstepping controller and speed information from the virtual side So we need to design a weighted averager first:

[0133]

[0134] where c 1 +c 1 =1;

[0135] Next, design the proportional derivative plus damping controller of the inner loop controller:

[0136]

[0137] Among them, the controller gain

[0138] Secondly, a nonlinear extended observer is designed to estimate the state and disturbance of the physical end car-like mobile robot:

[0139]

[0140] in and The states s are P (t) and the disturbance d P The estimated value of (t), positive constant β P =30 and α P =1000;

[0141] Defining the estimation error and Then the observation error system can be expressed as:

[0142]

[0143] Finally, we get the control input of the physical end car-like mobile robot

[0144] The reference trajectory of the car-like mobile robot is set to be a circle with a diameter of 3 meters. Figure 5 This is a schematic diagram of the movement trajectory of the physical mobile robot and the virtual mobile robot. It can be seen that their trajectories can track the reference trajectory well in an unreliable network environment.

Claims

1. A trajectory tracking control method for a vehicle-like mobile robot in an unreliable communication environment, characterized in that: It includes the following steps: Step 1: Establish the kinematic model and dynamic model of the vehicle-like mobile robot; Step 2: Design the digital twin platform of the robot based on the 3D model of the vehicle-like mobile robot and the ROS transmission communication mechanism; Step 3: Aiming at the problems of communication delay and data packet loss caused by the unreliable communication environment, design a switching elastic compensator and a proportional derivative plus damping controller, which act on the virtual vehicle-like mobile robot; according to the speed information of the virtual vehicle-like mobile robot, provide the feedforward control quantity and the feasible trajectory for the physical vehicle-like mobile robot; Step 4: Design the double closed-loop control strategy for the physical vehicle-like mobile robot.

2. According to the method for trajectory tracking control of a vehicle-like mobile robot in an unreliable communication environment as described in claim 1, it is characterized in that: In Step 1, the steps for establishing the kinematic model and dynamic model of the vehicle-like mobile robot are as follows: The kinematic model of the vehicle-like mobile robot is expressed as: where i ∈ {P, V}, P represents the physical end, and V represents the virtual end, x i (t),y i (t)) is the position of the car-like mobile robot, θ i (t) is the yaw angle of the car-like mobile robot; The dynamic model of the vehicle-like mobile robot is expressed as: Among them, v i (t) and ω i (t) are the linear velocity and yaw rate of the vehicle-like mobile robot, M is the weight of the vehicle, γ is the moment of inertia of the vehicle-like mobile robot, R is the radius of the wheel, and are the motor torques of the rear and front wheels respectively, d f (d r ) is the longitudinal distance between the centre of gravity and the front (rear) wheel; and Where s = r, f is the lateral turning force and the longitudinal friction force respectively; and is given as: Where F is the coefficient of kinetic friction, G s represents the cornering stiffness; considering the motor circuit, and It is expressed as: in is the input voltage to the motor, Indicates the speed of the motor, Ω s , H s , C e and T n are resistance, motor ratio, back EMF constant and torque constant respectively; hence the power system can be rewritten as: where in and is the total disturbance; Definitions i (t) = [υ i (t),ω i (t)] T , The kinetic model is then rewritten as:

3. The trajectory tracking control method of a vehicle-like mobile robot in an unreliable communication environment according to claim 2, characterized in that: In Step 2, the framework for constructing the digital twin platform of the vehicle-like mobile robot includes: the physical vehicle-like mobile robot, the intelligent transportation sand table, the virtual vehicle-like mobile robot, the virtual-real interaction platform, and network communication; The virtual-real interaction platform is used for data processing, status monitoring, and application services; The network communication includes: ROS communication for sending commands from the virtual-real interaction platform to the physical vehicle-like mobile robot, visualization simulation software for realizing the motion visualization of the vehicle-like mobile robot, ROS communication for sending commands from the virtual-real interaction platform to the virtual vehicle-like mobile robot, and ROS topics for transmitting the collected state data of the physical and virtual vehicle-like mobile robots.

4. The trajectory tracking control method of a vehicle-like mobile robot in an unreliable communication environment according to claim 3 is characterized in that: In Step 3, the steps for designing the switching elastic compensator and the proportional derivative plus damping controller are as follows: Step 3.1: Design a switching elastic compensator based on a zero-order hold and a proportional derivative compensator: Among them, for any i∈{P,V}, represents the state information of the car-like mobile robot after compensation, s i (t) is the speed information of the car-like mobile robot, τ i (t) represents random delay, is the compensation coefficient; Step 3.2: According to the received state information of the physical vehicle-like mobile robot and combined with its own state information, design a proportional derivative plus damping controller: where k V ,λ V , ρ V is the controller gain; Step 3.3: Considering the nonlinear characteristics of the vehicle-like mobile robot, external disturbances, and the influence of the unreliable communication environment, design a nonlinear extended observer to estimate the robot state and disturbances: To improve the accuracy of trajectory tracking, and The states s are i (t) and the disturbance d i The estimated value of (t), β i and α i is an adjustable positive constant; Defining the estimation error and The observation error system is expressed as: β i and α i Take appropriate parameters so that the estimated error and Converges to a sufficiently small value with a certain upper bound; Thus, the control input of the dynamic model of the virtual end-type vehicle mobile robot can be obtained.

5. The trajectory tracking control method of a vehicle-like mobile robot in an unreliable communication environment according to claim 4, characterized in that: In Step 4, the steps for designing the double closed-loop control strategy for the physical vehicle-like mobile robot are as follows: Step 4.1: According to the kinematic model of the vehicle-like mobile robot, design a backstepping controller to achieve outer-loop control and ensure that the vehicle-like mobile robot tracks the reference trajectory; Among them, the backstepping controller The design is as follows: Among them, L1, L2, L3 and L4 are adjustable positive definite parameters, and the position error Defined as: H P (t)=F e (q r (t)-q P (t)) Among them, q r (t) = [x r (t),y r (t),θ r (t)] T is the reference trajectory, q P (t) = [x P (t),y P (t),θ P (t)] T is the actual trajectory, Step 4.2: For the physical end, design a switching elastic compensator based on a zero-order hold and a proportional derivative compensator, the same as Step 3.1; Step 4.3: Based on the dynamic model of the vehicle-like mobile robot, design an inner-loop control strategy relying on a weighted averager to achieve high-precision speed tracking; the weighted averager is: where 0 < c1 < 1 and 0 < c2 < 1 are the weighting coefficients satisfying c1 + c2 = 1; Step 4.4: Design a proportional derivative plus damping controller for the inner-loop controller: where k P ,λ P , ρ P is the controller gain; Step 4.5: Design a nonlinear extended observer to estimate the state and disturbances of the physical vehicle-like mobile robot, the same as Step 3.3; From this, we can get the control input of the dynamics model of the physical end car-like mobile robot

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