Elevator dispatching control method and device, electronic equipment and storage medium

Abstract

The application discloses an elevator scheduling control method and device, electronic equipment and a storage medium, comprising: constructing an elevator operation mathematical model with the operating state parameters of the elevator as the dependent variable and the control parameters of the controller of the elevator as the independent variable, constructing the controller based on the operating state parameters, the controller including a loss function with the number of passengers in the car as the variable, solving the target controller at the minimum of the loss function, and controlling the elevator through the target controller to make the elevator run at the optimal operating speed, which realizes solving the loss function at the minimum energy loss at least through the number of passengers in the car, thereby further solving the target controller, and the energy loss is minimum when the elevator is controlled to run at the optimal operating speed through the target controller, compared with the energy feedback device of the elevator, the application does not need to increase hardware equipment, has low cost, can cope with complex working conditions of different numbers of passengers, and has better energy-saving and power-saving effects.

Description

Technical Field

[0001] This invention relates to the field of elevator control technology, and in particular to an elevator scheduling and control method, device, electronic equipment and storage medium. Background Technology

[0002] With social development and the continuous increase in high-rise buildings, the demand for elevators is growing, which has led people to focus their attention on elevator safety performance and energy consumption.

[0003] While pursuing safety performance, the elevator industry has found it difficult to take into account the energy loss generated during elevator operation. With more than 10 million elevators in my country, elevators account for a significant proportion of electricity consumption. Although the elevator industry has researched elevator energy feedback devices that control traction motor drive, running height, and running speed, these devices are costly and have poor energy-saving effects under complex operating conditions. Summary of the Invention

[0004] This invention provides an elevator scheduling and control method, device, electronic equipment, and storage medium to reduce energy loss during elevator scheduling without affecting elevator ride comfort and performance, thereby saving electricity.

[0005] In a first aspect, the present invention provides an elevator scheduling and control method, comprising:

[0006] A mathematical model for elevator operation is constructed, wherein the operating state parameters of the elevator and the control parameters of the elevator controller are used as independent variables, and the operating state parameters include at least the number of passengers in the elevator car during operation.

[0007] A controller is constructed based on the operating status parameters, and the controller includes a loss function with the number of passengers in the car as a variable;

[0008] Find the target controller that minimizes the loss function;

[0009] The elevator is controlled by the target controller so that it runs at an optimal operating speed.

[0010] Optionally, the mathematical model for the elevator's operation can be expressed as follows:

[0011]

[0012] Where k is the sampling time of the segment, This indicates the distance traveled by the elevator, its speed, acceleration, and the number of passengers in the car. i Let τ represent the elevator controller, where τ is the control coefficient and R is a real number.

[0013] Optionally, before constructing the controller based on the said operating state parameters, the method further includes:

[0014] Set up a switchable communication network and obtain the number of passengers in the car based on the switchable communication network.

[0015] Optionally, the expression for the switching mode of the switchable communication network is as follows:

[0016]

[0017] in, For switching signals, G1…Gβ are switchable communication segments, and n is a natural number.

[0018] Optionally, the constructed controller expression is as follows:

[0019]

[0020] i and j represent the number of people in the elevator car. This represents the expression for the sampling time k after the event triggering mechanism is implemented. Let i be the weighting coefficient assigned to j at time k in the parameter matrix corresponding to the switching signal at time k. This describes the algorithmic steps of the event-triggered mechanism. The functions `sig` and `sign` are the event-triggered functions, `σ` represents a coefficient, and `a` represents a coefficient. i ∈R, y i (k), z i (k), m represents the process quantity, d i The subgradient of the loss function f(x) at i, The loss function f(x) based on the event-triggered mechanism is expressed as follows: The expression for the subgradient at a given point is given, where scalar α>0 is the step size of the controller, and η1, η2, and η3 are coefficients.

[0021] Optionally, the target controller that minimizes the loss function includes:

[0022] Based on the Lyapunov criterion theorem formula Find the optimal solution z for the following loss function:

[0023]

[0024] Among them, f i f(x) represents the single-person loss in the car, f(x) represents the total loss of all people in the car, and n represents the number of people in the car.

[0025] Substituting the optimal solution z obtained from the solution into the expression of the controller yields the target controller.

[0026] Optional, also includes:

[0027] The controller was then incorporated into the control system and verified using MATLAB simulation software.

[0028] In a second aspect, the present invention provides an elevator dispatching and control device, comprising:

[0029] An elevator operation mathematical model construction module is used to construct an elevator operation mathematical model. The operation mathematical model uses the elevator's operation state parameters as independent variables and the control parameters of the elevator's controller as independent variables. The operation state parameters include at least the number of passengers in the elevator car during operation.

[0030] A controller design module is used to construct a controller based on the operating state parameters, wherein the controller includes a loss function with the number of passengers in the car as a variable;

[0031] The solution module is used to solve for the target controller when the loss function is minimized;

[0032] The control module is used to control the elevator through the target controller so that the elevator runs at an optimal operating speed.

[0033] Thirdly, the present invention provides an electronic device, the electronic device comprising:

[0034] At least one processor; and

[0035] A memory communicatively connected to the at least one processor; wherein,

[0036] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the elevator scheduling control method according to any one of the first aspects of the present invention.

[0037] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the elevator scheduling and control method according to any one of the first aspects of the present invention.

[0038] This invention constructs a mathematical model of elevator operation, using at least the number of passengers in the car as the dependent variable and the control parameters of the elevator controller as the independent variable. A controller is further constructed based on the operating state parameters, including a loss function with the number of passengers in the car as the variable. A target controller is found that minimizes the loss function. The elevator is then controlled by this target controller. This achieves the goal of minimizing energy loss by finding the loss function with at least the number of passengers in the car, thereby further solving for the target controller. By controlling the elevator to operate at the optimal speed with minimal energy loss, this invention, compared to an elevator energy feedback device, requires no additional hardware, is low-cost, and can handle complex operating conditions with varying passenger numbers, resulting in better energy-saving performance.

[0039] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart of an elevator scheduling and control method provided in Embodiment 1 of the present invention;

[0042] Figure 2 This is a flowchart of an elevator scheduling and control method provided in Embodiment 2 of the present invention;

[0043] Figure 3 This is a schematic diagram of the speed curve and energy consumption curve;

[0044] Figure 4 This is a schematic diagram of the topology of a communication network;

[0045] Figure 5 This is a schematic diagram of communication segment handover;

[0046] Figure 6 This is a simulation diagram showing the position, velocity, and acceleration in the elevator simulation results;

[0047] Figure 7 This is a schematic diagram of the losses before and after quantization in the elevator simulation results;

[0048] Figure 8 This is a schematic diagram of the structure of an elevator dispatching and control device provided in Embodiment 3 of the present invention;

[0049] Figure 9 This is a schematic diagram of the structure of the electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0050] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0051] Example 1

[0052] Figure 1 This is a flowchart of an elevator scheduling and control method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where elevators are controlled to operate with the lowest energy consumption during elevator scheduling. This method can be executed by an elevator scheduling and control device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the elevator dispatching and control method includes:

[0053] S101. Construct a mathematical model for elevator operation. The mathematical model uses the elevator's operating state parameters as the dependent variable and the elevator controller's control parameters as the independent variable. The operating state parameters include at least the number of passengers in the elevator car during operation.

[0054] The elevator in this embodiment refers to a vertical lifting elevator. The elevator's operating mathematical model can be a mathematical model describing the relationship between various operating parameters of the elevator and the control parameters of the elevator controller. In this embodiment, the elevator's operating state parameters can include the elevator's running distance, speed, acceleration, car weight (related to the number of passengers in the car), and running time. The controller's control parameters can include parameters such as the traction motor's drive current and voltage. The operating mathematical model can be a mathematical model with the control parameters as independent variables and the elevator's operating state parameters as dependent variables, that is, the correspondence between the control parameters output by the controller at different running times k and the elevator's running distance, speed, acceleration, and car weight (related to the number of passengers in the car) at running time k.

[0055] S102. Construct a controller based on the operating state parameters. The controller includes a loss function with the number of passengers in the car as the variable.

[0056] In one embodiment, the controller aims to minimize energy loss and controls elevator operation without affecting elevator ride comfort and performance. The controller reflects the correspondence between energy consumption and control parameters at different running times k when the number of passengers in the car is determined.

[0057] S103, Solve for the target controller when the loss function is minimized.

[0058] Since the number of passengers in the elevator car varies, the weight of the elevator car also varies, and the energy loss during elevator operation also varies. The loss function is a function that describes the energy loss of the elevator when the number of passengers is different. After solving the loss function to obtain the objective solution that minimizes the loss function, the objective solution is substituted into the controller to obtain the target controller.

[0059] S104. Control the elevator through the target controller to make the elevator run at the optimal operating speed.

[0060] After the target controller controls the elevator to run, the elevator runs at the optimal speed to achieve the goal of minimizing energy consumption.

[0061] This invention constructs a mathematical model of elevator operation, using operating state parameters (at least the number of passengers in the car) as the dependent variable and control parameters of the elevator controller as the independent variable. A controller is further constructed based on these operating state parameters, including a loss function with the number of passengers in the car as the variable. A target controller is found that minimizes the loss function. By controlling the elevator operation through this target controller, the loss function, which is calculated at least based on the number of passengers in the car, is minimized. This allows for further calculation of the target controller, which controls the elevator to operate at its optimal speed with minimal energy loss. Compared to elevator energy feedback devices, this invention requires no additional hardware, is low-cost, and can handle complex operating conditions with varying passenger numbers, resulting in better energy-saving performance.

[0062] Example 2

[0063] Figure 2 This is a flowchart of an elevator scheduling and control method provided in Embodiment 2 of the present invention. This embodiment is an optimization based on Embodiment 1 described above, such as... Figure 2 As shown, the elevator dispatching and control method includes:

[0064] S201. Construct a mathematical model for elevator operation. The mathematical model uses the elevator's operating state parameters as the dependent variable and the elevator controller's control parameters as the independent variable. The operating state parameters include at least the number of passengers in the elevator car during operation.

[0065] Specifically, based on the elevator's daily operation, its trajectory can be determined, such as establishing the relationship curve between the elevator's speed and time k. Furthermore, by fitting a large amount of statistical data, the functional relationship between the elevator's energy consumption and its speed can be determined. For example,... Figure 3 This is a schematic diagram of the operating speed curve and energy consumption curve. Figure 3 In the process, the running speed V first accelerates with time t, the elevator energy consumption F changes with speed V, then becomes constant, and finally decelerates. A mathematical model can be established with the elevator's running distance, speed, acceleration, and time as variables.

[0066] Specifically, the mathematical model for elevator operation is expressed as follows:

[0067]

[0068] Where k is the sampling time of the segment, This indicates the elevator's travel distance, speed, acceleration, and number of passengers in the car (car weight, which can be determined by a weight sensor). i Let τ represent the elevator controller, where τ is the control coefficient and R is a real number.

[0069] Formula (1) above describes the correspondence between the control parameters output by the controller at different running times k and the elevator's running distance, speed, acceleration, and car weight (related to the number of passengers in the car) at running time k.

[0070] S202. Set up a switchable communication network and obtain the number of passengers in the car based on the switchable communication network.

[0071] In this embodiment, the controller receives data via a communication network, such as the weight of the car (number of passengers). To ensure the reliability of system communication, a switchable communication network is typically used, such as... Figure 4 The diagram shows different communication network topologies. Figure 5 This is a diagram showing the corresponding number of communication segments.

[0072] The expression for the switching mode of the switchable communication network is as follows:

[0073]

[0074] in, The switching signal is represented by G1…Gβ, which are switchable communication segments, and n is a natural number. In this embodiment, β = 3, which means there are a total of 3 communication segments, including G1, G2 and G3.

[0075] For example, in this embodiment, k is the segment sampling time. Different values ​​of k correspond to different communication topologies. For example, the correspondence between time K and communication topology is as follows:

[0076]

[0077] If communication is interfered with at sampling time k1, causing communication abnormality, the internal system will automatically switch the communication mode to k2.

[0078] S203. Construct a controller based on the operating status parameters. The controller includes a loss function with the number of passengers in the car as the variable.

[0079] In one embodiment, the constructed controller has the following expression:

[0080]

[0081] i and j represent the number of people in the elevator car. This represents the expression for the sampling time k after the event triggering mechanism is implemented. Let i be the weighting coefficient assigned to j at time k in the parameter matrix corresponding to the switching signal at time k. This describes the algorithmic steps of the event-triggered mechanism. The functions `sig` and `sign` are the event-triggered functions, `σ` represents a coefficient, and `a` represents a coefficient. i ∈R, y i (k), z i (k), m represents the process quantity, d i The subgradient of the loss function f(x) at i, The loss function f(x) based on the event-triggered mechanism is expressed as follows: The expression for the subgradient at a given point is given, where scalar α>0 is the step size of the controller, and η1, η2, and η3 are coefficients.

[0082] Wherein, the parameter matrix corresponding to the switching signal at time k As shown below:

[0083]

[0084] S204, Formula based on Lyapunov's criterion theorem Find the optimal solution for the loss function.

[0085] Since elevator losses vary depending on the number and weight of passengers in the car, the total loss is defined as the following loss function:

[0086]

[0087] Among them, f i f(x) represents the individual loss within the car, f(x) represents the total loss of all people within the car, and n represents the number of people within the car.

[0088] As can be seen from the above formula (5), the Lyapunov criterion theorem formula can be used. The solution is to find z that minimizes f(z), where formula (6) represents the process quantities for different elevator operating states. For example, after the number of passengers (car weight) is determined, the process quantities under different operating states such as speed, acceleration, and distance are calculated. Solving formula (6) is essentially solving for the optimal speed, acceleration, and distance that minimize the value of formula (6). Specifically, this can be based on the Lyapunov criterion theorem formula. For a detailed solution, please refer to the method for finding the optimal value based on the Lyapunov criterion theorem. The embodiments of this invention will not be described in detail here.

[0089] S205. Substitute the obtained optimal solution into the expression of the controller to obtain the target controller.

[0090] After solving for the process quantity z that minimizes the value of formula (6), z can be substituted into formulas (3)-(5) to obtain the target controller u. i (k).

[0091] In one embodiment, after solving for the optimal target controller, the controller can be substituted into the control system and verified using MATLAB simulation software. For example, in the MATLAB simulation, assuming there are five people in the elevator car, i.e., n=5, the loss function f for a certain section during elevator scheduling is as follows:

[0092] f = (z i -γ i ) 2 +θ i ;

[0093] Where, z i (0) = [0.2, 0.6, 0.12, 0.74, 0.5] T γ i =[5,-2,7,4,6] T θ i =[20,11,-15,25,-20] T ,d=0.0138.

[0094] Among them, z i (0) represents the initial input value of the process quantity, γ and θ are the set values ​​of the coefficients, and d is the set value of the subgradient.

[0095] like Figure 6 The diagram shows the displacement, velocity, and acceleration results of the elevator operation simulation. Figure 7 The diagram shown illustrates the losses during elevator operation simulation. The simulation reveals that... Figure 6 The displacement, velocity, and acceleration in the simulation all eventually converge. Figure 7The power consumption of theoretical calculations and simulation calculations is similar before and after quantization.

[0096] S206. Control the elevator through the target controller to make the elevator run at the optimal operating speed.

[0097] In determining the target controller u i After (k), the output of the controller can be determined by the operating mathematical model expressed by formula (1). After controlling the elevator to run at the optimal operating speed by the controller output, the energy consumption of the elevator is minimized.

[0098] This invention constructs a mathematical model for elevator operation, using elevator operating state parameters as dependent variables and elevator controller control parameters as independent variables. The operating state parameters include at least the number of passengers in the elevator car during operation. A switchable communication network is set up, and the number of passengers in the car is obtained based on this network. A controller is constructed based on the operating state parameters, including a loss function with the number of passengers in the car as the variable. The optimal solution of the loss function is solved based on the Lyapunov criterion theorem. Substituting the obtained optimal solution into the controller's expression yields the target controller. The elevator is controlled by the target controller to operate at the optimal speed. This achieves the goal of minimizing energy loss by solving the loss function at least through the number of passengers in the car, thereby further solving for the target controller. By controlling the elevator to operate at the optimal speed with the minimum energy loss, this invention, compared to an elevator energy feedback device, requires no additional hardware, has low cost, and can handle complex operating conditions with varying passenger numbers, resulting in better energy saving.

[0099] Furthermore, due to the introduction of a switchable communication network, when one communication segment is interfered with, it automatically switches to another segment with good communication to obtain data, thus improving the stability of data transmission.

[0100] Example 3

[0101] Figure 8 This is a schematic diagram of the structure of an elevator dispatching and control device provided in Embodiment 3 of the present invention. Figure 8 As shown, the elevator dispatch control device includes:

[0102] Elevator operation mathematical model construction module 801 is used to construct an elevator operation mathematical model. The operation mathematical model uses the elevator operation state parameters as dependent variables and the control parameters of the elevator controller as independent variables. The operation state parameters include at least the number of passengers in the elevator car when the elevator is running.

[0103] The controller design module 802 is used to construct a controller based on the operating state parameters, and the controller includes a loss function with the number of passengers in the car as a variable;

[0104] Solver module 803 is used to solve for the target controller when the loss function is minimized;

[0105] The control module 804 is used to control the elevator through the target controller so that the elevator runs at an optimal operating speed.

[0106] Optionally, the mathematical model for the elevator's operation can be expressed as follows:

[0107]

[0108] Where k is the sampling time of the segment, This indicates the distance traveled by the elevator, its speed, acceleration, and the number of passengers in the car. i Let τ represent the elevator controller, where τ is the control coefficient and R is a real number.

[0109] Optional, also includes:

[0110] The communication network setting module is used to set a switchable communication network and obtain the number of passengers in the car based on the switchable communication network.

[0111] Optionally, the expression for the switching mode of the switchable communication network is as follows:

[0112]

[0113] in, For switching signals, G1…Gβ are switchable communication segments, and n is a natural number.

[0114] Optionally, the constructed controller expression is as follows:

[0115]

[0116] i and j represent the number of people in the elevator car. This represents the expression for the sampling time k after the event triggering mechanism is implemented. Let i be the weighting coefficient assigned to j at time k in the parameter matrix corresponding to the switching signal at time k. This describes the algorithmic steps of the event-triggered mechanism. The functions `sig` and `sign` are the event-triggered functions, `σ` represents a coefficient, and `a` represents a coefficient. i ∈R, y i (k), z i (k), m represents the process quantity, d i The subgradient of the loss function f(x) at i, The loss function f(x) based on the event-triggered mechanism is expressed as follows: The expression for the subgradient at a given point is given, where scalar α>0 is the step size of the controller, and η1, η2, and η3 are coefficients.

[0117] Optionally, the solver module 803 includes:

[0118] The optimal solution solving unit is used for solving the Lyapunov criterion theorem formula. Find the optimal solution z for the following loss function:

[0119]

[0120] Among them, f i f(x) represents the single-person loss in the car, f(x) represents the total loss of all people in the car, and n represents the number of people in the car.

[0121] The controller solving unit is used to substitute the optimal solution z obtained from the solution into the expression of the controller to obtain the target controller.

[0122] Optional, also includes:

[0123] The simulation module is used to integrate the controller into the control system and verify it using MATLAB simulation software.

[0124] The elevator scheduling and control device provided in the embodiments of the present invention can execute the elevator scheduling and control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0125] Example 4

[0126] Figure 9 A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0127] like Figure 9As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded into the RAM 43 from storage unit 48. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0128] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0129] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as elevator scheduling control methods.

[0130] In some embodiments, the elevator scheduling control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the elevator scheduling control method described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to perform the elevator scheduling control method by any other suitable means (e.g., by means of firmware).

[0131] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0132] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0133] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0134] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0135] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0136] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0137] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0138] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An elevator dispatching and control method, characterized in that, include: A mathematical model for elevator operation is constructed, wherein the elevator's operating state parameters are the dependent variables and the control parameters of the elevator's controller are the independent variables, and the operating state parameters include at least the number of passengers in the elevator car during operation. A controller is constructed based on the operating state parameters. The controller includes a loss function with the number of passengers in the car as a variable. The loss function represents the relationship between the energy consumption of the elevator and the control parameters at different operating times k when the number of passengers in the car is determined. The target controller aims to minimize energy consumption by finding the minimum loss function at least by considering the number of passengers in the car. Solving the loss function is essentially finding the optimal operating speed, acceleration, and distance that minimize the value of the loss function. The elevator is controlled by the target controller so that it runs at an optimal operating speed.

2. The method according to claim 1, characterized in that, The mathematical model for elevator operation is expressed as follows: ； Where k is the sampling time of the segment, This indicates the distance the elevator travels, its speed, acceleration, and the number of passengers in the car. This refers to the elevator controller. This is the control factor.

3. The method according to claim 1, characterized in that, Before constructing the controller based on the aforementioned operating status parameters, the following steps are also included: Set up a switchable communication network and obtain the number of passengers in the car based on the switchable communication network.

4. The method according to claim 3, characterized in that, The expression for the switching mode of the switchable communication network is as follows: ； in, For switching signals, G1…Gβ are switchable communication segments, and n is a natural number.

5. The method according to claim 3, characterized in that, The expression for the constructed controller is as follows: ； ； ； i and j represent the number of people in the elevator car. This represents the expression for the sampling time k after the event triggering mechanism is implemented. In the parameter matrix corresponding to the switching signal at time k, i is assigned to... The weighting coefficients, This represents the algorithmic steps of the event-triggered mechanism, where the functions `sig` and `sign` are the functions that trigger the event. Represents the coefficient, coefficient R is a real number. , , m represents the process quantity, Let f(x) be the subgradient of the loss function at i. The loss function f(x) based on the event-triggered mechanism is represented in... The expression of the subgradient at a given point, scalar The step size of the controller, is a coefficient.

6. The method according to claim 5, characterized in that, The target controller, which aims to minimize energy consumption by solving for the minimum loss function with at least the number of passengers in the car, includes: Based on the Lyapunov criterion theorem formula Find the optimal solution z for the following loss function: ； in, f(x) represents the individual loss within the elevator car, f(x) represents the total loss of all people within the elevator car, n represents the number of people within the elevator car, and z represents the process quantity for different operating states of the elevator. Substituting the optimal solution z obtained from the solution into the expression of the controller yields the target controller.

7. The method according to any one of claims 1-6, characterized in that, Also includes: The controller was then incorporated into the control system and verified using MATLAB simulation software.

8. An elevator dispatching and control device, characterized in that, include: An elevator operation mathematical model construction module is used to construct an elevator operation mathematical model. The operation mathematical model uses the elevator's operation state parameters as dependent variables and the control parameters of the elevator's controller as independent variables. The operation state parameters include at least the number of passengers in the elevator car during operation. The controller design module is used to construct a controller based on the operating state parameters. The controller includes a loss function with the number of passengers in the car as a variable. The loss function represents the relationship between the energy consumption of the elevator and the control parameters at different operating times k when the number of passengers in the car is determined. The solution module is used to solve the target controller that minimizes the loss function with the goal of minimizing energy consumption, based on at least the number of passengers in the car. Solving the loss function is essentially solving for the optimal operating speed, acceleration, and distance that minimize the value of the loss function. The control module is used to control the elevator through the target controller so that the elevator runs at an optimal operating speed.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the elevator scheduling control method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the elevator scheduling and control method according to any one of claims 1-7.

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