Control method, device and equipment of unloading system, medium and program product

Abstract

The invention relates to a control method, device and equipment of an unloading system, a medium and a program product. The method comprises the following steps: acquiring a target association relationship between control input data and motion state data of target unloading equipment; acquiring first reference state data of the target unloading equipment and second reference state data of associated unloading equipment of the target unloading equipment; determining comprehensive difference value data according to a state data difference value between the first reference state data and each piece of second reference state data; determining a time-varying parameter of the current time based on a preset time-varying function; the preset time-varying function is a monotone increasing function in a time period less than a preset time threshold, and is a constant function in a time period not less than the preset time threshold; and according to the comprehensive difference data and the time-varying parameters, reference motion data of the target unloading equipment is determined, so that control input data of the target unloading equipment is determined, and the motion state of the target unloading equipment is controlled through the control input data. According to the method, the control flexibility and the control efficiency are improved.

Description

Technical Field

[0001] The present application relates to the technical field of unloading system control, and in particular to a control method, device, equipment, medium and program product for an unloading system. Background Art

[0002] As rail transport becomes increasingly important in the logistics sector, automated unloading technology for bulk cargo is gaining increasing attention. Traditional unloading methods rely primarily on manual labor, which is not only inefficient but also poses safety risks and high costs. To address these challenges, intelligent unloading systems have emerged. By controlling the unloading device, intelligent unloading systems transform unloading methods and improve unloading efficiency.

[0003] Due to the complex and changeable distribution of cargo and the different unloading conditions at the unloading site, it is usually necessary to carry out round-up control of the unloading device. However, traditional control methods generally have the problems of low control flexibility and poor round-up effect. Summary of the Invention

[0004] Based on this, it is necessary to provide a control method, device, equipment, medium and program product for an unloading system to address the above technical problems, so as to improve the control effect of the unloading system.

[0005] In a first aspect, the present application provides a control method for a vehicle unloading system, comprising:

[0006] For a target unloading device in the unloading system, obtaining a target association relationship between control input data of the target unloading device and motion state data of the target unloading device;

[0007] Acquire first reference state data of a target unloading device and second reference state data of an associated unloading device of the target unloading device in the unloading system;

[0008] determining comprehensive difference data based on a state data difference between the first reference state data and each second reference state data;

[0009] Determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold;

[0010] Determine the reference motion data of the target unloading equipment based on the comprehensive difference data and time-varying parameters;

[0011] Based on the target association relationship and the reference motion data, control input data of the target unloading device is determined, and the motion state of the target unloading device is controlled by the control input data.

[0012] In one embodiment, reference motion data is determined based on the comprehensive difference data and the time-varying parameters, including: obtaining the parameter change rate of the time-varying parameters; determining the ratio of the parameter change rate to the time-varying parameters to obtain the relative change rate of the time-varying parameters; and determining the reference motion data based on the relative change rate of the time-varying parameters and the comprehensive difference data.

[0013] In one embodiment, reference motion data is determined based on the relative change rate of the time-varying parameter and the comprehensive difference data, including: determining the product of the relative change rate of the time-varying parameter and a preset time-varying gain to obtain an initial coupling coefficient; determining the sum of the initial coupling coefficient and a preset basic gain to obtain a target coupling coefficient; and determining the reference motion data based on the target coupling coefficient and the comprehensive difference data.

[0014] In one embodiment, based on a preset time-varying function, a time-varying parameter corresponding to the current time is determined, including: when the current time is less than a preset time threshold, determining a first time length between the current time and a preset initial time; determining a time length difference between the preset time length and the first time length; using the ratio of the preset time length to the time length difference as a reference parameter; and determining the time-varying parameter based on the reference parameter and a preset parameter adjustment gain.

[0015] In one embodiment, the target association relationship is an association relationship between the motion state data of the target unloading equipment, the external disturbance data and the control input data of the target unloading equipment; accordingly, based on the target association relationship and the reference motion data, the control input data of the target unloading equipment is determined, including: obtaining an external disturbance estimate of the target unloading equipment as the external disturbance data; and determining the control input data of the target unloading equipment based on the target association relationship, the reference motion data and the external disturbance data.

[0016] In one embodiment, control input data of a target unloading device is determined based on a target association relationship, reference motion data, and external disturbance data, including: determining a tracking error based on the reference motion data and motion state data; determining a sliding surface corresponding to the target unloading device based on the tracking error; and determining the control input data of the target unloading device based on the sliding surface, the target association relationship, and the external disturbance data.

[0017] In a second aspect, the present application further provides a control device for an unloading system, comprising:

[0018] The first acquisition module is used to acquire, for a target unloading device in the unloading system, a target association relationship between control input data of the target unloading device and motion state data of the target unloading device;

[0019] A second acquisition module is used to acquire first reference state data of the target unloading device and second reference state data of the unloading device associated with the target unloading device in the unloading system;

[0020] a first determining module, configured to determine comprehensive difference data based on a state data difference between the first reference state data and each second reference state data;

[0021] A second determining module is configured to determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold;

[0022] A third determination module is used to determine reference motion data of the target unloading equipment based on the comprehensive difference data and the time-varying parameters;

[0023] The fourth determination module is used to determine the control input data of the target unloading device based on the target association relationship and the reference motion data, and control the motion state of the target unloading device through the control input data.

[0024] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0025] For a target unloading device in the unloading system, obtaining a target association relationship between control input data of the target unloading device and motion state data of the target unloading device;

[0026] Acquire first reference state data of a target unloading device and second reference state data of an associated unloading device of the target unloading device in the unloading system;

[0027] determining comprehensive difference data based on a state data difference between the first reference state data and each second reference state data;

[0028] Determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold;

[0029] Determine the reference motion data of the target unloading equipment based on the comprehensive difference data and time-varying parameters;

[0030] Based on the target association relationship and the reference motion data, control input data of the target unloading device is determined, and the motion state of the target unloading device is controlled by the control input data.

[0031] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0032] For a target unloading device in the unloading system, obtaining a target association relationship between control input data of the target unloading device and motion state data of the target unloading device;

[0033] Acquire first reference state data of a target unloading device and second reference state data of an associated unloading device of the target unloading device in the unloading system;

[0034] determining comprehensive difference data based on a state data difference between the first reference state data and each second reference state data;

[0035] Determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold;

[0036] Determine the reference motion data of the target unloading equipment based on the comprehensive difference data and time-varying parameters;

[0037] Based on the target association relationship and the reference motion data, control input data of the target unloading device is determined, and the motion state of the target unloading device is controlled by the control input data.

[0038] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0039] For a target unloading device in the unloading system, obtaining a target association relationship between control input data of the target unloading device and motion state data of the target unloading device;

[0040] Acquire first reference state data of a target unloading device and second reference state data of an associated unloading device of the target unloading device in the unloading system;

[0041] determining comprehensive difference data based on a state data difference between the first reference state data and each second reference state data;

[0042] Determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold;

[0043] Determine the reference motion data of the target unloading equipment based on the comprehensive difference data and time-varying parameters;

[0044] Based on the target association relationship and the reference motion data, control input data of the target unloading device is determined, and the motion state of the target unloading device is controlled by the control input data.

[0045] The control method, apparatus, device, medium, and program product for the unloading system described above obtain a target association between the control input data of a target unloading device and its motion state data for a target unloading device in the unloading system, thereby providing a basis for subsequently determining the control input data of the target unloading device. By introducing associated unloading devices, the target unloading device is associated with its associated unloading devices. Furthermore, by obtaining first reference state data of the target unloading device and second reference state data of associated unloading devices of the target unloading device in the unloading system, the original data basis for the subsequent reference motion data of the target unloading device is provided. Based on the state data difference between the first reference state data and each second reference state data, comprehensive difference data is determined, thereby determining the state difference between the target unloading device and its associated unloading devices. By introducing a preset time-varying function, which is a monotonically increasing function in a first period less than a preset time threshold and a constant function in a second period not less than the preset time threshold, the corresponding time-varying parameter can be adaptively determined based on the current time. According to the comprehensive difference data and time-varying parameters, the reference motion data of the target unloading equipment is determined, and based on the target association relationship and the reference motion data, the control input data of the target unloading equipment is determined. The motion state of the target unloading equipment is controlled by controlling the input data, so that the target unloading equipment can effectively achieve state unification with the associated unloading equipment within a preset time threshold, that is, the capture of the unloading equipment is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1A Schematic diagram of a flow chart of a control method of a vehicle unloading system in one embodiment;

[0048] Figure 1B A schematic diagram of the communication topology of a truck unloading system in one embodiment;

[0049] Figure 2 A flowchart of a step of determining control input data in one embodiment;

[0050] Figure 3A A schematic diagram of a reference trajectory of an unloading system in one embodiment;

[0051] Figure 3B A schematic diagram of the position trajectory of an unloading system in one embodiment;

[0052] Figure 3C A schematic diagram of the speed trajectory of an unloading system in one embodiment;

[0053] Figure 3D A schematic diagram of tracking error of a vehicle unloading system in one embodiment;

[0054] Figure 3E Schematic diagram of estimation error of an extended state observer in one embodiment;

[0055] Figure 4 A schematic flow chart of a control method for a vehicle unloading system in another embodiment;

[0056] Figure 5 is a structural block diagram of a control device of an unloading system in one embodiment;

[0057] Figure 6 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0059] In one embodiment, Figure 1A As shown, a control method for a vehicle unloading system is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, or to a system including a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0060] S110 , for a target unloading device in the unloading system, obtaining a target association relationship between control input data of the target unloading device and motion state data of the target unloading device.

[0061] The unloading system may include at least one unloading device. When controlling each unloading device, the unloading device may be used as a target unloading device.

[0062] The motion state data may include at least one of displacement state data, velocity state data, acceleration state data, and the like.

[0063] In an optional embodiment, at least one unloading device can be divided into a leading agent and a following agent; the leading agent can be understood as an unloading device used to guide the following agent to follow, and the following agent can be understood as an unloading device used to follow the leading agent and / or follow other following agents.

[0064] For example, the target association relationship between the control input data of the follower agent and the motion state data of the follower agent can be expressed as:

[0065]

[0066] in, and They represent the displacement state and velocity state of the i1th following agent respectively; represents a bounded differentiable uncertain term; represents a bounded and differentiable external perturbation; represents the control input data for the i-th follower agent; N represents the number of follower agents.

[0067] For example, the target association relationship between the control input data of the leader agent and the motion state data of the follower agent can be expressed as:

[0068]

[0069] in, and Represent the displacement state and velocity state of the i2th leader agent, represents the control input data for the jth leader agent; M represents the number of leader agents.

[0070] Among them, i1 represents the index of the following agent in the unloading system, i2 represents the index of the leading agent in the unloading system; i represents the global index, and index i includes index i1 and index i2, that is, i = 1,...,N+M.

[0071] S120: Acquire first reference status data of the target unloading device and second reference status data of unloading devices associated with the target unloading device in the unloading system.

[0072] The first reference state data may be a reference state vector of a target unloading device; and the second reference state data may be a reference state vector of an associated unloading device.

[0073] It is understandable that, when the target unloading device can receive communication data of the preset unloading device, the preset unloading device is the associated unloading device of the target unloading device. The associated unloading device can be allocated to the target unloading device in advance.

[0074] Optionally, for each following agent, the associated unloading device of the following agent may be the leading agent and / or other following agents.

[0075] Optionally, for each leader agent, the leader agent's associated unloading device may be another leader agent. Alternatively, the leader agent may not be provided with an associated unloading device. This application does not impose any limitation on this.

[0076] For further explanation, refer to Figure 1B The communication topology diagram of the unloading system is shown. Figure 1B The unloading system shown in FIG includes six follower agents (F1 to F6) and three leader agents (L7 to L9).

[0077] Among them, the three leading intelligent agents move according to the corresponding reference trajectories respectively, and no corresponding associated unloading equipment is set; the associated unloading equipment of the following intelligent agent F1 includes the leading intelligent agent L7, the following intelligent agent F4, and the following intelligent agent F6; the associated unloading equipment of the following intelligent agent F2 includes the following intelligent agent F3, the following intelligent agent F4 and the following intelligent agent F5.

[0078] Continue to refer Figure 1B , the associated unloading equipment of follower agent F3 includes leader agent L9 and follower agent F2; the associated unloading equipment of follower agent F4 includes follower agent F1 and follower agent F2; the associated unloading equipment of follower agent F5 includes leader agent L8, follower agent F2, and follower agent F6; and the associated unloading equipment of follower agent F6 includes follower agent F1 and follower agent F5. It is worth noting that this application does not impose any restrictions on the specific communication topology of the unloading system, nor does it impose any restrictions on the specific type and specific number of associated unloading equipment corresponding to the target unloading equipment.

[0079] In an optional embodiment, in order to more conveniently and quantifiably represent the association relationship between different unloading equipment, an association matrix A can be introduced. ij The matrix element a in ij Indicates the association between the i-th unloading device and the j-th unloading device. If the j-th unloading device is the associated unloading device of the i-th unloading device, that is, the i-th unloading device can receive the communication data of the j-th unloading device, then a ij =1; otherwise a ij = 0. Where, i = 1, ..., N + M; j = 1, ..., N + M.

[0080] S130 , determining comprehensive difference data according to the state data difference between the first reference state data and each second reference state data.

[0081] In an optional embodiment, the state data difference between the first reference state data and each second reference state data may be determined; and the state data differences may be summed to obtain comprehensive difference data.

[0082] In another optional embodiment, the comprehensive difference data can be expressed as:

[0083]

[0084] Among them, a ij represents the association between the i-th unloading equipment and the j-th unloading equipment; ζ i represents the reference state vector of the i-th unloading device, that is, the reference state data of the i-th unloading device; ζ j Represents the reference state vector of the j-th unloading equipment, that is, the reference state data of the j-th unloading equipment.

[0085] It can be understood that for the target unloading equipment among the N+M unloading equipment, the reference state data corresponding to the target unloading equipment is the above-mentioned first reference state data; correspondingly, the reference state data of the associated unloading equipment corresponding to the target unloading equipment among the N+M unloading equipment is the above-mentioned second reference state data.

[0086] It can be understood that for the i-th unloading device, if the communication data of the j-th unloading device can be received, it means that the j-th unloading device is the associated unloading device of the i-th unloading device. At this time, the matrix element a ij =1, it is included in the summation process of the state data difference; otherwise, if there is no correlation, the matrix element a ij =0, thereby realizing the determination of comprehensive difference data.

[0087] S140. Determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold.

[0088] The time-varying function can be understood as a function that changes with time, and is a monotonically increasing function in a first period that is less than a preset time threshold, and is a constant function in a second period that is not less than the preset time threshold.

[0089] In an optional embodiment, the first time period is a time period in which the current time is not less than the preset initial time and less than the preset time threshold; the second time period is a time period in which the current time is not less than the preset time threshold.

[0090] Optionally, when the current time is less than a preset time threshold, the first time length between the current time and the preset initial time can be determined; the time length difference between the preset time length and the first time length can be determined; the ratio of the preset time length to the time length difference can be used as a reference parameter; and the time-varying parameter can be determined based on the reference parameter and the preset parameter adjustment gain.

[0091] Optionally, the constant function may be 1. It is worth noting that this application does not impose any limitation on the specific function expression of the constant function.

[0092] In an optional embodiment, the preset time-varying function η(t) can be expressed as:

[0093]

[0094] Among them, t represents the current time; T represents the preset time length; t0 represents the preset initial time; t1 represents the preset time threshold; c represents the preset parameter gain, c>2.

[0095] It can be understood that when the current time is in the first period, that is, t∈[t0,t1), as the current time t increases, η(t) gradually increases. When the current time is in the second period, that is, t∈[t1,∞), η(t) is in a stable state, that is, the output is 1.

[0096] S150: Determine reference motion data of the target unloading equipment based on the comprehensive difference data and the time-varying parameters.

[0097] In an optional embodiment, the integrated difference data may be multiplied by a time-varying parameter to determine reference motion data of the target unloading equipment.

[0098] In another optional embodiment, the reference motion data of the target unloading equipment may be determined based on a preset time stability theorem and in accordance with the integrated difference data and the time-varying parameters.

[0099] Among them, the preset time stability theorem, that is, the preset time contains control: for the system χ(0)=χ0, χ is the system state, there exists a continuously differentiable function V(χ(t),t) that satisfies: within the domain Δ-{0}, V(0,t)=0, V(χ(t),t)>0 and within the domain Δ, k>0, then the system χ(0) = χ0 is stable within a preset time length T, t∈[t0,∞).

[0100] In an optional embodiment, the parameter change rate of the time-varying parameter can be obtained; the ratio of the parameter change rate to the time-varying parameter can be determined to obtain the relative change rate of the time-varying parameter; and the reference motion data can be determined based on the relative change rate of the time-varying parameter and the comprehensive difference data.

[0101] Optionally, the product of the relative change rate of the time-varying parameter and the preset time-varying gain can be determined to obtain the initial coupling coefficient; the sum of the initial coupling coefficient and the preset basic gain can be determined to obtain the target coupling coefficient; and the reference motion data can be determined based on the target coupling coefficient and the comprehensive difference data.

[0102] For example, the reference motion data corresponding to the i-th unloading device is It can be determined according to the following formula:

[0103]

[0104] Wherein, k represents the initial coupling coefficient, k>0; a represents the preset time-varying gain, a>0; η represents the time-varying parameter; represents the parameter change rate of the time-varying parameter; a ij represents the association relationship between the i-th unloading equipment and the j-th unloading equipment; ζ i represents the reference state data of the i-th unloading equipment; ζ j Represents the reference status data of the j-th unloading equipment.

[0105] It can be understood that when the current time t is in the first period, as the current time t increases, the time-varying parameter The ratio of the time-varying parameter to the target coupling coefficient increases continuously; when the current time is in the second period, the time-varying parameter The ratio of the time-varying parameter remains unchanged, and the target coupling coefficient is stable. In this way, based on this reference motion data, the unloading equipment can be controlled within the preset time length T, that is, the state consistency of the target unloading equipment and the corresponding associated unloading equipment is achieved.

[0106] Optionally, the reference motion data can be determined by a virtual multi-agent as a signal generator, that is:

[0107]

[0108] Among them, α i Represents the control input of the virtual multi-agent.

[0109] S160: Determine control input data of the target unloading device based on the target association relationship and the reference motion data, and control the motion state of the target unloading device through the control input data.

[0110] In an optional embodiment, a tracking error may be determined based on the reference motion data and the motion state data; and control input data of the target unloading device may be determined based on the tracking error and the target association relationship.

[0111] The tracking error may include a displacement tracking error and a velocity tracking error, and the motion state data may include a displacement state data and a velocity state data.

[0112] Alternatively, the tracking error of the following agent can be expressed as:

[0113]

[0114] Among them, e fxi1 represents the displacement tracking error of the i1th following agent; represents the displacement state data of the i1th following agent; e fvi1 represents the speed tracking error of the i1th following agent; Represents the speed state data of the i1th following agent.

[0115] Similarly, the tracking error of the leader agent can be expressed as:

[0116]

[0117] Among them, e lxi2 represents the displacement tracking error of the i2th leader agent; represents the displacement state data of the i2th leader agent; e lvi2 represents the speed tracking error of the i2th leader agent; Represents the speed state data of the i2th leader agent.

[0118] In an optional embodiment, the sliding surface corresponding to the target unloading device can be determined based on the tracking error; and the control input data of the target unloading device can be determined based on the sliding surface, the target association relationship, and the external disturbance data. Optionally, the process of determining the corresponding sliding surface based on the tracking error can adopt a traditional sliding surface determination method, and this application does not impose any restrictions on this. The sliding surface can be understood as a hyperplane or surface in the state space, which is used to enable the system state to slide along the sliding surface after reaching the sliding surface, and finally reach the desired equilibrium point or trajectory, thereby achieving robustness and stability of control.

[0119] The control method for the unloading system described above obtains a target association between the control input data of the target unloading device and the motion state data of the target unloading device for the target unloading device in the unloading system, thereby providing a basis for subsequently determining the control input data of the target unloading device. By introducing associated unloading devices, the target unloading device is associated with the associated unloading devices. At the same time, by obtaining first reference state data of the target unloading device and second reference state data of the associated unloading devices of the target unloading device in the unloading system, the original data basis for the subsequent reference motion data of the target unloading device is provided. Based on the state data difference between the first reference state data and each second reference state data, comprehensive difference data is determined, thereby determining the state difference between the target unloading device and its associated unloading devices. By introducing a preset time-varying function, which is a monotonically increasing function in a first period less than a preset time threshold and a constant function in a second period not less than the preset time threshold, the corresponding time-varying parameters can be adaptively determined based on the current time. According to the comprehensive difference data and time-varying parameters, the reference motion data of the target unloading equipment is determined, and based on the target association relationship and the reference motion data, the control input data of the target unloading equipment is determined. The motion state of the target unloading equipment is controlled by controlling the input data, so that the target unloading equipment can achieve state unification with the associated unloading equipment within a preset time threshold, that is, the capture of the unloading equipment is achieved.

[0120] Based on the above embodiments, some embodiments refine the step of determining the control input data, wherein the target association relationship is the association relationship between the motion state data of the target unloading device, the external disturbance data, and the control input data of the target unloading device.

[0121] refer to Figure 2 The flowchart of the steps for determining the control input data is shown, including:

[0122] S210: Obtain an external disturbance estimate of the target unloading equipment as external disturbance data.

[0123] S230: Determine control input data of the target unloading equipment based on the target association relationship, reference motion data, and external disturbance data.

[0124] In an optional embodiment, a tracking error can be determined based on reference motion data and motion state data; a sliding surface corresponding to the target unloading equipment can be determined based on the tracking error; and control input data of the target unloading equipment can be determined based on the sliding surface, target association relationship and external disturbance data.

[0125] In an optional embodiment, for the following agent, the target association relationship corresponding to the following agent is the association relationship between the motion state data of the following agent, the external disturbance data and the control input data of the following agent. Can include bounded differentiable external perturbations and bounded differentiable uncertainties That is, referring to the above, the target association relationship corresponding to the following agent can be expressed as:

[0126]

[0127]

[0128] in, and They represent the displacement state and velocity state of the i1th following agent respectively; represents a bounded differentiable uncertain term; represents a bounded and differentiable external perturbation; represents the control input data for the i-th follower agent; N represents the number of follower agents.

[0129] In an optional embodiment, for the leader agent, the external disturbance data can be 0. That is, referring to the above, the target association relationship corresponding to the leader agent can be expressed as:

[0130]

[0131] in, and Represent the displacement state and velocity state of the i2th leader agent, represents the control input data for the jth leader agent; M represents the number of leader agents.

[0132] For example, the displacement state corresponding to the i1th follower agent can be determined based on the extended state observer. The estimated displacement state The speed state of the i1th following agent The velocity state estimate And the external disturbance data corresponding to the i1th follower agent The estimated value of external disturbance Among them, the extended state observer can be expressed as:

[0133]

[0134] in, They are The estimated value of ω0>0 is the only parameter gain of the extended state observer.

[0135] Furthermore, the displacement state observation error can be determined by the following formula: Speed ​​state observation error and external disturbance observation error

[0136]

[0137] in, satisfy

[0138] As mentioned above, the tracking error of the following agent can be expressed as:

[0139]

[0140] Among them, e fxi1 represents the displacement tracking error of the i1th following agent; represents the displacement state data of the i1th following agent; e fvi1 represents the speed tracking error of the i1th following agent; Represents the speed state data of the i1th following agent.

[0141] As mentioned above, the tracking error of the leader agent can be expressed as:

[0142]

[0143] Among them, e lxi2 represents the displacement tracking error of the i2th leader agent; represents the displacement state data of the i2th leader agent; e lvi2 represents the speed tracking error of the i2th leader agent; Represents the speed state data of the i2th leader agent.

[0144] Therefore, the sliding surface of the follower agent and the leader agent, and their first-order differentials can be determined according to the following formula:

[0145]

[0146] Here, ρ can be a preset value, and ρ>0.

[0147] Among them, s fi1 represents the sliding surface of the i1th following agent; e fxi1 represents the displacement tracking error of the i1th following agent; e fvi1 represents the speed tracking error of the i1th following agent; Represents the speed state data of the i1th following agent; Represents the reference state data of the i1th following agent.

[0148] Among them, s li2 represents the sliding surface of the i2th leader agent; e lxi2 represents the displacement tracking error of the i2th leader agent; e lvi2 represents the speed tracking error of the i2th leader agent; Represents the speed state data of the i2th leader agent; Represents the reference state data of the i2th leader agent.

[0149] In an optional embodiment, the control input data of the target unloading equipment can be expressed as:

[0150]

[0151] Among them, k1 and k2 are preset parameters, k1>0, k2>0.

[0152] in, represents the control input data of the i1th following agent; represents the external disturbance estimate of the i1th following agent; represents the reference state data of the i1th following agent; e fvi1 represents the speed tracking error of the i1th following agent; s fi1 represents the sliding surface of the i1th following agent.

[0153] in, represents the control input data of the i2th leader agent; represents the reference state data of the i2th leader agent; e lvi2 represents the speed tracking error of the i2th leader agent; s li2 represents the sliding surface of the i2th leader agent.

[0154] Based on the above embodiment, a verification embodiment is provided, which verifies the control method of the above unloading system.

[0155] Based on the aforementioned preset time stability theorem, stability proof is performed:

[0156]

[0157] Finally, to meet the system stability, e fxi1 ,e fvi1 ,e lxi2 ,e lvi2 Converges to 0.

[0158] Below is Figure 1B The communication topology diagram of the unloading system is used as an example for simulation. The reference trajectory of the leader agent is set as: ζ7 = sint, ζ8 = sint+1, ζ9 = sint-1.

[0159] The initial state of the signal generator is set as:

[0160] ζ(0)=[0,1,-1,4.5,2.5,0.5,-1,-3,-3.5] T

[0161] The initial state of the unloading system is set as:

[0162] x(0)=[0,1,-1,4.5,2.5,0.5,-1,-3,-3.5] T

[0163] v(0)=[1,1,1,3.5,1.5,0,2,4,2.5] T

[0164] Other parameters are as follows: T=1s; c=3; k=3; a=2; ω0=5; ρ=3; k1=k2=5.

[0165] refer to Figure 3A Shown is a schematic diagram of the reference trajectory of the unloading system. Figure 3A The reference trajectories of three leading agents and six following agents are shown in .

[0166] refer to Figure 3B Shown is a schematic diagram of the position trajectory of the unloading system. Figure 3B The black lines represent the trajectories of the three leading agents, and the remaining colors represent the trajectories of the following agents. Figure 3B It can be seen intuitively that the leader agent effectively controls the followers within the preset time length of 1 second, that is, all follower agents enter the capture area of ​​the leader agent.

[0167] refer to Figure 3C The figure shows the velocity trajectory of the unloading system. It can be seen that the velocities of the various unloading devices in the unloading system eventually converge.

[0168] refer to Figure 3D Figure 2 shows the tracking error diagram of the unloading system. As can be seen, all errors converge to 0, verifying the effectiveness of the control method based on the extended state observer.

[0169] refer to Figure 3E Figure 2 shows the estimated error diagram of the extended state observer. It is clear that all the estimated errors converge to a region close to 0, thus verifying the efficiency of the designed extended state observer.

[0170] Based on the above embodiments, the control method of the unloading system is described in detail.

[0171] See also Figure 4 FIG2 is a flow chart of a control method of a vehicle unloading system in another embodiment, comprising:

[0172] S401 : For a target unloading device in an unloading system, obtain a target association relationship between control input data of the target unloading device and motion state data of the target unloading device.

[0173] S402: Acquire first reference status data of a target unloading device and second reference status data of an associated unloading device of the target unloading device in the unloading system.

[0174] S403 : Determine comprehensive difference data according to the state data difference between the first reference state data and each second reference state data.

[0175] S404. Determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold.

[0176] S405: Obtain the parameter change rate of the time-varying parameter.

[0177] S406: Determine the ratio of the parameter change rate to the time-varying parameter to obtain the relative change rate of the time-varying parameter.

[0178] S407 : Determine the product of the relative change rate of the time-varying parameter and the preset time-varying gain to obtain an initial coupling coefficient.

[0179] S408: Determine the sum of the initial coupling coefficient and the preset basic gain to obtain the target coupling coefficient.

[0180] S409: Determine reference motion data according to the target coupling coefficient and the comprehensive difference data.

[0181] S410: Determine a tracking error based on the reference motion data and the motion state data.

[0182] S411. Determine the sliding surface corresponding to the target unloading equipment based on the tracking error.

[0183] S412: Determine control input data of the target unloading device according to the sliding surface, the target association relationship, and the external disturbance data, and control the motion state of the target unloading device through the control input data.

[0184] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0185] Based on the same inventive concept, embodiments of the present application further provide a control device for a vehicle unloading system for implementing the aforementioned control method for a vehicle unloading system. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the control device for a vehicle unloading system provided below can be found in the aforementioned limitations of the control method for a vehicle unloading system, and will not be further elaborated here.

[0186] In an exemplary embodiment, Figure 5 As shown, a control device for a vehicle unloading system is provided, comprising: a first acquisition module 510, a second acquisition module 520, a first determination module 530, a second determination module 540, a third determination module 550, and a fourth determination module 560, wherein:

[0187] The first acquisition module 510 is used to acquire, for a target unloading device in the unloading system, a target association relationship between control input data of the target unloading device and motion state data of the target unloading device;

[0188] A second acquisition module 520 is configured to acquire first reference state data of a target unloading device and second reference state data of an associated unloading device of the target unloading device in the unloading system;

[0189] A first determining module 530 is configured to determine comprehensive difference data based on a state data difference between the first reference state data and each second reference state data;

[0190] A second determining module 540 is configured to determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first period less than a preset time threshold, and is a constant function in a second period not less than the preset time threshold;

[0191] The third determining module 550 is used to determine the reference motion data of the target unloading equipment based on the comprehensive difference data and the time-varying parameters;

[0192] The fourth determining module 560 is configured to determine control input data of the target unloading device based on the target association relationship and the reference motion data, and to control the motion state of the target unloading device through the control input data.

[0193] In one embodiment, the third determination module 550 includes: a first acquisition unit, used to obtain the parameter change rate of the time-varying parameter; a first determination unit, used to determine the ratio of the parameter change rate to the time-varying parameter to obtain the relative change rate of the time-varying parameter; a second determination unit, used to determine the reference motion data based on the relative change rate of the time-varying parameter and the comprehensive difference data.

[0194] In one embodiment, the second determination unit includes: a first determination subunit, used to determine the product of the relative change rate of the time-varying parameter and the preset time-varying gain to obtain an initial coupling coefficient; a second determination subunit, used to determine the sum of the initial coupling coefficient and the preset basic gain to obtain a target coupling coefficient; and a third determination subunit, used to determine the reference motion data based on the target coupling coefficient and the comprehensive difference data.

[0195] In one embodiment, the second determination module 540 includes: a third determination unit, used to determine the first time length between the current time and the preset initial time when the current time is less than a preset time threshold; a fourth determination unit, used to determine the time length difference between the preset time length and the first time length; a fifth determination unit, used to use the ratio of the preset time length to the time length difference as a reference parameter; and a sixth determination unit, used to determine the time-varying parameter based on the reference parameter and the preset parameter adjustment gain.

[0196] In one embodiment, the target association relationship is the association relationship between the motion state data of the target unloading equipment, the external disturbance data and the control input data of the target unloading equipment; accordingly, the fourth determination module 560 includes: a second acquisition unit, used to obtain the external disturbance estimate of the target unloading equipment as the external disturbance data; a seventh determination unit, used to determine the control input data of the target unloading equipment based on the target association relationship, the reference motion data and the external disturbance data.

[0197] In one embodiment, the seventh determination unit includes: a fourth determination subunit, used to determine the tracking error based on reference motion data and motion state data; a fifth determination subunit, used to determine the sliding surface corresponding to the target unloading equipment based on the tracking error; and a sixth determination subunit, used to determine the control input data of the target unloading equipment based on the sliding surface, the target association relationship and the external disturbance data.

[0198] Each module in the control device of the above-mentioned unloading system can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0199] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface, the display unit and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a control method for an unloading system is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0200] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0201] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0202] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0203] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0204] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile memory and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a programmable logic unit (PLC), a data processing logic unit based on quantum computing, an artificial intelligence (AI) processor, and the like.

[0205] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0206] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A control method for a vehicle unloading system, characterized in that: The method comprises: For a target unloading device in the unloading system, obtaining a target association relationship between control input data of the target unloading device and motion state data of the target unloading device; Acquire first reference state data of the target unloading device and second reference state data of an associated unloading device of the target unloading device in the unloading system; determining comprehensive difference data according to a state data difference between the first reference state data and each of the second reference state data; Determining a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold; Determining reference motion data of the target unloading equipment based on the comprehensive difference data and the time-varying parameters; Based on the target association relationship and the reference motion data, control input data of the target unloading device is determined, and the motion state of the target unloading device is controlled by the control input data.

2. The method according to claim 1, characterized in that The determining of reference motion data according to the integrated difference data and the time-varying parameter includes: Obtaining a parameter change rate of the time-varying parameter; Determining the ratio of the parameter change rate to the time-varying parameter to obtain a relative change rate of the time-varying parameter; The reference motion data is determined according to the relative change rate of the time-varying parameter and the comprehensive difference data.

3. The method according to claim 2, characterized in that The determining the reference motion data according to the relative change rate of the time-varying parameter and the comprehensive difference data includes: Determine the product of the relative change rate of the time-varying parameter and a preset time-varying gain to obtain an initial coupling coefficient; Determine the sum of the initial coupling coefficient and a preset basic gain to obtain a target coupling coefficient; The reference motion data is determined according to the target coupling coefficient and the comprehensive difference data.

4. The method according to claim 1, wherein The determining of the time-varying parameter corresponding to the current time based on the preset time-varying function includes: When the current time is less than the preset time threshold, determining a first time length between the current time and a preset initial time; Determining a time difference between a preset time length and the first time length; The ratio of the preset time length to the time length difference is used as a reference parameter; The time-varying parameters are determined based on the reference parameters and the preset parameter adjustment gain.

5. The method according to any one of claims 1 to 4, characterized in that The target association relationship is an association relationship between the motion state data of the target unloading device, the external disturbance data, and the control input data of the target unloading device; accordingly, determining the control input data of the target unloading device based on the target association relationship and the reference motion data includes: obtaining an external disturbance estimate of the target unloading equipment as the external disturbance data; Based on the target association relationship, the reference motion data and the external disturbance data, control input data of the target unloading equipment is determined.

6. The method according to claim 5, characterized in that The determining of the control input data of the target unloading equipment based on the target association relationship, the reference motion data, and the external disturbance data includes: determining a tracking error based on the reference motion data and the motion state data; determining a sliding surface corresponding to the target unloading equipment according to the tracking error; Control input data of the target unloading equipment is determined according to the sliding surface, the target association relationship and the external disturbance data.

7. A control device for a vehicle unloading system, characterized in that: The device comprises: A first acquisition module is configured to acquire, for a target unloading device in the unloading system, a target association relationship between control input data of the target unloading device and motion state data of the target unloading device; A second acquisition module is used to acquire first reference state data of the target unloading device and second reference state data of unloading devices associated with the target unloading device in the unloading system; a first determining module, configured to determine comprehensive difference data based on a state data difference between the first reference state data and each of the second reference state data; A second determining module is configured to determine a time-varying parameter corresponding to the current time based on a preset time-varying function; wherein the preset time-varying function is a monotonically increasing function in a first time period less than a preset time threshold, and is a constant function in a second time period not less than the preset time threshold; A third determining module is configured to determine reference motion data of the target unloading equipment based on the comprehensive difference data and the time-varying parameter; A fourth determination module is configured to determine control input data of the target unloading device based on the target association relationship and the reference motion data, and to control the motion state of the target unloading device through the control input data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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