Miniature stepping motor of smart home curtain and wireless networking control method

Abstract

The invention relates to the technical field of intelligent control, in particular to a micro stepping motor and wireless networking control method for a smart home curtain, and the method comprises the steps: obtaining the light intensity data and the opening degree data of each curtain at a current moment and at each historical moment under each historical regulation and control operation; obtaining an operation influence coefficient according to the association relationship between the historical regulation and control operation of each curtain and the light intensity data change trend of other curtains at the same historical moment; obtaining an environment difference coefficient according to the difference condition of the opening and closing degree data and the difference condition of the light intensity data of all curtains at the current moment and under each historical regulation and control operation; according to the environment difference coefficient and the light intensity data of each curtain at the current moment, in combination with the operation influence coefficient, obtaining a parameter adjustment coefficient of each curtain at the current moment; therefore, each curtain can be controlled. Opening and closing of the curtain can be stably controlled, and the phenomenon of linkage excessive response or control oscillation caused by blind synchronous action of the curtain is avoided.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a micro stepping motor for smart home curtains and a wireless networking control method. Background Art

[0002] With the popularization of smart home technology, electric curtains, as an important component of intelligent lighting and environmental control systems, are gradually being widely used in homes, office buildings, and public spaces. Currently, most smart curtain systems use micro-stepping motors as drive units. They are characterized by small size, high control precision, and low cost, and are suitable for a variety of curtain loads. Motor control is usually based on a lookup table method to output a fixed step timing, combined with PWM speed regulation to achieve the opening and closing of the curtains. Subdivision control can also be used to improve operational smoothness and reduce mechanical noise. In terms of system communication, an increasing number of curtain control units are beginning to have wireless networking capabilities. They can connect to home gateways via Wi-Fi or Bluetooth to achieve remote control, scene linkage, and timed scheduling, providing users with a more convenient and intelligent user experience.

[0003] Office buildings have multiple windows, and independent curtain control systems for each window operate simultaneously to adjust indoor lighting. However, due to the mutual influence of light obstruction between windows, traditional independent control strategies lack a unified coordinated control mechanism, which can easily lead to chaotic curtain control. For example, if one curtain closes, reducing indoor light intensity, other curtains will open accordingly. These repeated adjustments create control oscillations, which can cause unnecessary wear and tear on the curtain drive system. Summary of the Invention

[0004] In order to solve the technical problem that the existing curtain drive system independently controls the intelligent regulation process of each curtain, which is prone to chaotic regulation, the purpose of the present invention is to provide a micro stepping motor and wireless networking control method for smart home curtains. The technical solutions adopted are as follows:

[0005] In a first aspect, the present invention provides a wireless networking control method for a micro stepping motor of a smart home curtain, comprising:

[0006] Obtain the light intensity data of each curtain at the current moment and at each historical moment under each historical control operation, as well as the opening and closing degree data of each curtain at the current moment and at each historical control operation;

[0007] Based on the correlation between the historical control operation of each curtain and the light intensity data change trend of other curtains at the same historical moment, the influence coefficient of each historical control operation of each curtain on the operation of other curtains is analyzed;

[0008] Based on the difference in the opening and closing degree data of all curtains at the current moment and under each historical control operation, combined with the difference in the light intensity data of all curtains at the current moment and under each historical control operation, the environmental difference coefficient between the current moment and each historical control operation of each curtain is obtained;

[0009] Obtaining a parameter adjustment coefficient for each curtain at the current moment based on the environmental difference coefficient and the light intensity data of each curtain at the current moment, combined with the operation influence coefficient;

[0010] Each curtain is controlled based on the parameter adjustment coefficient and the stepping motor corresponding to each curtain.

[0011] Preferably, the step of analyzing the influence coefficient of each historical control operation of each curtain on the operation of other curtains based on the correlation between the change trend of light intensity data of each curtain under historical control operation and that of other curtains at the same historical moment specifically includes:

[0012] Determine a light intensity difference factor for each curtain at each historical moment based on a difference in light intensity data of each curtain between each historical moment and an adjacent historical moment;

[0013] According to the correlation between the light intensity difference factor of each curtain at each historical moment under each historical control operation and the light intensity difference factors of other curtains at the same historical moment, the influence coefficient of each curtain's historical control operation on the operation of other curtains is obtained.

[0014] Preferably, obtaining the influence coefficient of each curtain's historical control operation on the operation of other curtains based on the correlation between the light intensity difference factor of each curtain at each historical moment under each historical control operation and the light intensity difference factors of other curtains at the same historical moment specifically includes:

[0015] The historical time period corresponding to any historical control operation of any curtain is recorded as the target time period of the target curtain. Based on the ratio between the light intensity difference factor of the target curtain at each historical moment in the target time period and the light intensity difference factor of each other curtain at the same corresponding historical moment, the operation influence coefficient of the historical control operation corresponding to the target curtain in the target time period on each other curtain is determined.

[0016] Preferably, the step of obtaining the environmental difference coefficient between the current moment and each historical control operation of each curtain based on the difference in the opening and closing degree data of all curtains at the current moment and each historical control operation, in combination with the difference in the light intensity data of all curtains at the current moment and each historical control operation, specifically includes:

[0017] Based on the opening and closing data of all curtains at each moment, an opening and closing vector at each moment is constructed; based on the light intensity data of all curtains at each moment, a light intensity vector at each moment is constructed; wherein each moment includes the current moment and each historical moment;

[0018] Based on the difference between the opening and closing degree vector at the current moment and the opening and closing degree vector at the initial historical moment under each historical control operation of each curtain, a first difference factor between the current moment and each historical control operation of each curtain is determined; based on the difference between the light intensity vector at the current moment and the light intensity vector at the initial historical moment under each historical control operation of each curtain, a second difference factor between the current moment and each historical control operation is determined; and in combination with the first difference factor and the second difference factor, an environmental difference coefficient between the current moment and each historical control operation of each curtain is determined.

[0019] Preferably, the parameter adjustment coefficient of each curtain at the current moment is obtained based on the environmental difference coefficient and the light intensity data of each curtain at the current moment, combined with the operation influence coefficient, specifically including:

[0020] Based on the environmental difference coefficient between the current moment and each historical control operation of each curtain, combined with the influence coefficient of each curtain's corresponding historical control operation on other curtains, an impact evaluation index of each curtain's control operation at the current moment on other curtains is obtained;

[0021] Obtain the standard light intensity corresponding to the curtain adjustment operation; obtain the parameter adjustment coefficient of each curtain at the current moment based on the degree to which each curtain is affected by the adjustment operation of other curtains at the current moment and the light intensity data corresponding to other curtains at the current moment combined with the standard light intensity.

[0022] Preferably, the influence evaluation index of each curtain's control operation at the current moment on other curtains is obtained based on the environmental difference coefficient between the current moment and each historical control operation of each curtain, combined with the influence coefficient of the historical control operation corresponding to each curtain on the operation of other curtains, specifically including:

[0023] The environmental difference coefficient between the current moment and each historical control operation of each curtain is negatively correlated and normalized to obtain the environmental weight corresponding to each historical control operation of each curtain; the environmental weight is used to weightedly average the operational influence coefficient of each curtain on other curtains under each historical control operation to obtain the impact evaluation index of each curtain's control operation on other curtains at the current moment.

[0024] Preferably, the step of obtaining the parameter adjustment coefficient of each curtain at the current moment based on the degree to which each curtain is affected by the adjustment operation of other curtains at the current moment and the light intensity data corresponding to other curtains at the current moment combined with the standard light intensity specifically includes:

[0025] Record any one curtain as the selected curtain, and all other curtains except the selected curtain as reference curtains;

[0026] The difference between the light intensity data of each reference curtain at the current moment and the standard light intensity is used as the operation weight of each reference curtain;

[0027] Using the operation weight of each reference curtain, the impact evaluation index of the control operation of each reference curtain at the current moment on the selected curtain is weightedly summed, and the summation result is negatively normalized to obtain the parameter adjustment coefficient of the selected curtain at the current moment; among which, the impact evaluation index of the control operation of each reference curtain at the current moment on the selected curtain represents the degree to which the selected curtain is affected by the adjustment operation of each reference curtain.

[0028] Preferably, the controlling of each curtain based on the parameter adjustment coefficient and the stepping motor corresponding to each curtain specifically includes:

[0029] For each curtain, obtain the PID parameters of the stepper motor at the current moment, and use the product of the parameter adjustment coefficient of each curtain at the current moment and the proportional coefficient in the PID parameter as the adjusted proportional coefficient of each curtain;

[0030] The adjusted integral coefficient and differential coefficient are obtained according to the adjusted proportional coefficient of each curtain, and PID control is performed on each curtain.

[0031] Preferably, the step of obtaining the adjusted integral coefficient and differential coefficient according to the adjusted proportional coefficient of each curtain specifically includes:

[0032] The ratio of the adjusted proportional coefficient of each curtain to the current preset integral time constant is used as the adjusted integral coefficient of each curtain; the product of the adjusted proportional coefficient of each curtain and the current preset differential time constant is used as the adjusted differential coefficient of each curtain.

[0033] In a second aspect, the present invention provides a micro stepping motor for smart home curtains, which is used to receive a control signal from a control unit and execute the steps of controlling each curtain in the wireless networking control method of the micro stepping motor for smart home curtains.

[0034] The embodiments of the present invention have at least the following beneficial effects:

[0035] The present invention first quantifies the impact coefficient of each historical control operation on the operations of other curtains by analyzing the correlation between the historical data changes generated by each curtain and the corresponding data changes generated by other curtains at the same historical time, thereby establishing the mutual influence relationship between different curtains. Then, by fully considering the differences between the environmental factors under each historical control operation and the environmental factors at the current moment, the environmental difference coefficient between the current moment and each historical control operation for each curtain is obtained, and the environmental correlation relationship between the current and historical moments is established. Furthermore, by integrating the results of multiple feature analysis aspects, the final parameter adjustment coefficient is determined. This fully considers the correlation and difference between historical light intensity and current environmental changes, and can adaptively control the opening and closing of curtains based on the stepper motor corresponding to each curtain, thereby improving the system's adaptability to light changes in multi-source disturbance environments. By considering the impact of the micro-stepping motors corresponding to multiple curtains in a smart home on indoor light intensity, the present invention adjusts the network control method of multiple stepper motors in real time to ensure the stability of curtain opening and closing under light intensity changes in the smart home, avoiding chain over-response or control oscillation caused by blindly synchronized curtain operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 This is a flowchart of the steps of a wireless networking control method for a micro stepping motor of a smart home curtain provided by the present invention;

[0038] Figure 2 This is a schematic diagram of the installation of a light intensity sensor corresponding to a window provided by the present invention;

[0039] Figure 3 Schematic diagram of the data curve of the light intensity corresponding to the curtain provided by the present invention before and after smoothing;

[0040] Figure 4 is a flowchart of the steps of the method for obtaining the operation influence coefficient provided by the present invention;

[0041] Figure 5 It is a schematic diagram of a curve showing the change in light intensity data corresponding to the curtains corresponding to the windows provided by the present invention over a period of time. DETAILED DESCRIPTION

[0042] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the following, in combination with the accompanying drawings and preferred embodiments, describes in detail the specific implementation method, structure, characteristics and effects of a micro stepping motor and wireless networking control method for smart home curtains proposed by the present invention.

[0043] Before introducing the specific solutions provided in the embodiments of the present application, some of the terms in the present application are explained to facilitate understanding by those skilled in the art, and are not intended to limit the use in the present application.

[0044] The following are the main components of the smart curtain system:

[0045] (1) Control Unit (MCU): Responsible for receiving sensor data, running the light analysis and control algorithm, and outputting drive signals to the stepper motor. This module has local computing power and wireless communication capabilities, and can interact with other curtain nodes or cloud platforms through protocols such as MQTT.

[0046] (2) Light intensity sensor: installed in key locations indoors (such as near windows or in the center of the room), used to collect real-time indoor natural light intensity, support sampling at a set frequency and store historical data.

[0047] (3) Micro stepper motor: responsible for the specific execution of the curtain opening and closing action. Each motor is connected to a set of curtain fabrics, that is, corresponding to a window, and completes the opening and closing action of the specified angle according to the control signal sent by the main control unit.

[0048] In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0049] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0050] The following describes in detail a micro stepping motor and wireless networking control method for smart home curtains provided by the present invention in conjunction with the accompanying drawings.

[0051] See also Figure 1 , which shows a flowchart of a wireless networking control method for a micro stepping motor of a smart home curtain provided by one embodiment of the present invention, the method comprising the following steps:

[0052] Step S100: Obtain the light intensity data of each curtain at the current moment and at each historical moment under each historical control operation, and the opening and closing degree data of each curtain at the current moment and at each historical control operation.

[0053] It should be understood that each window corresponds to a curtain, a light intensity sensor and a micro stepper motor, and the curtains corresponding to all windows are collaboratively controlled by the MCU control unit, such as Figure 2 , which shows a schematic diagram of the installation of a light intensity sensor corresponding to a window.

[0054] First, the light intensity data collected by the light intensity sensor at each moment during the real-time monitoring of each curtain is obtained, where each moment includes a historical moment and a current moment.

[0055] In some embodiments, considering that the change in light intensity corresponding to each curtain is not only caused by the change in the degree of opening and closing of the curtain, but also due to factors such as the movement of people and changes in lighting in the current scene, it is necessary to pre-process the data collected by the sensor before analyzing the mutual influence of multiple curtains. As a specific example, the light intensity collected by the sensor is processed by mean filtering, such as Figure 3 , which shows the data curve of the light intensity collected by the sensor for a certain curtain during a period of time before and after smoothing.

[0056] The historical control process of the curtain stepper motor includes multiple different control modes, including intelligent control based on light intensity and manual opening and closing of individual curtains. Considering each complete curtain opening or closing process as a historical control operation, it should be understood that the complete opening and closing process of a curtain in a historical control operation takes a certain amount of time. Therefore, when collecting sensor data, it is necessary to obtain the light intensity data of each window at each historical moment in each historical control operation.

[0057] Furthermore, to measure the opening and closing state of each curtain at different moments, the number of steps of the micro-stepping motor can be used to measure the opening degree of each curtain, intuitively reflecting the actual opening and closing position of the curtain. Specifically, for any curtain at any moment, the number of steps of the corresponding micro-stepping motor is obtained, and the ratio between the number of steps and the maximum number of steps that the micro-stepping motor can control is used as the opening and closing data of the curtain at that moment. The opening and closing data reflects the actual opening and closing state of the curtain at each moment. Using the same method, the opening and closing data of each curtain at the current moment and the opening and closing data of each curtain at each historical moment under each historical control operation can be obtained.

[0058] It should be noted that to prevent the dimensionality of the collected data from affecting the subsequent feature analysis process, the light intensity data in this embodiment is normalized. The normalization method is well known and will not be further described here. It should be understood that representing the opening and closing state of the curtains by the proportion of the micro-stepping motor's steps can not only avoid the influence of dimensionality, but also facilitate unified control across all curtains.

[0059] Step S200 , analyzing the influence coefficient of each historical control operation of each curtain on the operations of other curtains based on the correlation between the historical control operations of each curtain and the light intensity data change trends of other curtains at the same historical moment.

[0060] In the collaborative control strategy of the smart curtain system, accurately quantifying the light intensity coupling effect between each curtain is key to achieving global optimization. When the smart curtain system is in single-motor independent control mode, changes in light intensity of curtains in other areas are mainly due to light changes caused by the operation of the controlled curtain. In other words, considering that the control of smart curtains tends to be stable, when controlling a single curtain, the mutual influence between different curtain operations should be fully considered. Based on this consideration, the changes in ambient light intensity between each curtain in the historical control operations are analyzed to evaluate the potential influence relationship between historical control operations.

[0061] In some embodiments, as Figure 4 As shown, the method for obtaining the operation influence coefficient can be implemented by step S201 and step S202.

[0062] Step S201 : determining a light intensity difference factor of each curtain at each historical moment based on the difference in light intensity data of each curtain between each historical moment and an adjacent historical moment.

[0063] Specifically, the difference in light intensity data between each curtain at each historical moment and the adjacent previous historical moment is used as the light intensity difference factor for each curtain at each historical moment. It should be noted that the analysis is not performed for the case where the first historical moment cannot be calculated.

[0064] In other embodiments, the light intensity data of each curtain at all historical moments under each historical control operation are first constructed into a light intensity sequence of each curtain under each historical control operation in chronological order, and a first-order difference value of each light intensity sequence is calculated. Each first-order difference value corresponds to a light intensity difference factor of each curtain at each historical moment except the first historical moment under each historical control operation.

[0065] The light intensity difference factor characterizes the change in ambient light intensity at each historical moment relative to its adjacent moments.

[0066] Step S202 , obtaining the influence coefficient of each curtain's historical control operation on other curtains based on the correlation between the light intensity difference factor of each curtain at each historical moment under each historical control operation and the light intensity difference factors of other curtains at the same historical moment.

[0067] Specifically, the historical time period corresponding to any historical control operation of any curtain is recorded as the target time period of the target curtain. Based on the ratio between the light intensity difference factor of the target curtain at each historical moment in the target time period and the light intensity difference factor of each other curtain at the same corresponding historical moment, the operational influence coefficient of the historical control operation corresponding to the target curtain in the target time period on each other curtain is determined.

[0068] As a specific example, the i-th curtain is taken as the target curtain, and the historical time period consisting of all historical moments of the r-th historical control operation of the i-th curtain is taken as the target time period of the target curtain. Where i = 1, 2, ..., N1, r = 1, 2, ..., N i , N1 represents the total number of curtains, N i represents the total number of historical control operations for the i-th curtain. Furthermore, taking the m-th curtain other than the i-th curtain as an example, the influence coefficient of the i-th curtain on the m-th curtain under the r-th historical control operation can be expressed as:

[0069]

[0070] Among them, F i,r (m) represents the influence coefficient of the i-th curtain on the m-th other curtain under the r-th historical control operation, that is, the influence coefficient of the historical control operation corresponding to the target curtain in the target time period on the m-th other curtain. i,r represents the total number of all historical moments contained in the rth historical control operation of the i-th curtain, ΔX i,r (t) represents the light intensity difference factor at the tth historical moment under the rth historical control operation of the i-th curtain, ΔX i,r (m, t) represents the light intensity difference factor of the mth other curtains corresponding to the target curtain at the same tth historical moment.

[0071] The influence coefficient of the historical control operation of the target curtain corresponding to the target time period on the operation of the mth other curtain reflects the degree of influence of the target curtain on the mth other curtain when the curtain is opened and closed. When the value is larger, it means that the opening and closing operation of the target curtain significantly drives the degree of synchronous change of the light intensity in the area where the mth other curtain is located.

[0072] like Figure 5, which shows a schematic diagram of the light intensity data change curve corresponding to the curtains of 5 windows over a period of time, Figure 5 As can be seen, when the curtain opening of Window 4 changes, the lighting conditions in the area surrounding Window 5 also change synchronously, while the lighting conditions in the other windows do not. This indicates that changes in the lighting environment around Window 4 have a greater impact on the curtains of Window 5. It should be noted that in order to more intuitively illustrate the changing trends in the light intensity data, non-standardized data is used in the curve diagram.

[0073] Step S300 , based on the difference in the opening and closing degree data of all curtains at the current moment and under each historical control operation, combined with the difference in the light intensity data of all curtains at the current moment and under each historical control operation, obtains the environmental difference coefficient between the current moment and each historical control operation of each curtain.

[0074] During the coordinated control of smart curtains, there are certain differences in ambient light intensity at different time nodes. For example, when the curtains of the same window are controlled at different times, the natural ambient light in the morning and afternoon will change over time. Based on this consideration, when performing intelligent control on the window opening and closing degree at the current moment, in order to make the environmental impact of historical control operations more accurate, we further combine the differences and similarities between the ambient light intensity at the current moment and each historical control operation to perform feature analysis, and evaluate the degree of difference in the environmental dimension between the current moment and each historical control operation under the correlation of the time dimension.

[0075] The first step is to construct an opening degree vector for each moment based on the opening degree data of all curtains at each moment, and to construct a light intensity vector for each moment based on the light intensity data of all curtains at each moment; wherein each moment includes the current moment and each historical moment.

[0076] It should be understood that the vector acquisition method for the current moment and for each historical moment in each historical control operation is exactly the same. Taking any given moment as an example, the opening and closing degree data for all curtains at that moment are combined in a preset order to form the opening and closing degree vector for that moment. Similarly, the light intensity data for all curtains at that moment are combined in the same order to form the light intensity vector for that moment. The preset order can be customized by the implementer based on the specific implementation scenario, as long as all corresponding vector elements belong to the same curtain.

[0077] Based on this, the current moment corresponds to an opening and closing degree vector and a light intensity vector. At the same time, since other curtains may not necessarily change at the same moment when each curtain is controlled, the environmental changes of each historical control operation are analyzed for each corresponding curtain, that is, the environmental parameters before the curtains need to be intelligently controlled are fully considered.

[0078] Specifically, taking the target curtain as an example, when there is an r-th historical control operation for the target curtain, the data distribution of the target curtain and all other curtains at the initial historical moment of the r-th historical control operation is obtained to form the opening and closing degree vector and light intensity vector of the target curtain at the initial historical moment of the r-th historical control operation. The initial historical moment refers to the first historical moment of a historical control operation, reflecting the time state when the control operation has not yet started or is about to start.

[0079] In the second step, based on the difference between the opening and closing degree vector at the current moment and the opening and closing degree vector at the initial historical moment under each historical control operation of each curtain, a first difference factor between the current moment and each historical control operation of each curtain is determined; based on the difference between the light intensity vector at the current moment and the light intensity vector at the initial historical moment under each historical control operation of each curtain, a second difference factor between the current moment and each historical control operation is determined; and by combining the first difference factor and the second difference factor, an environmental difference coefficient between the current moment and each historical control operation of each curtain is determined.

[0080] As a specific example, taking the rth historical control operation of the i-th curtain as an example, the environmental difference coefficient between the current moment and the rth historical control operation of the i-th curtain can be expressed as:

[0081]

[0082] Among them, Y i,r represents the environmental difference coefficient between the current moment and the rth historical control operation of the i-th curtain, Represents the opening and closing degree vector at the current moment, Ψ i,r represents the opening and closing degree vector of the rth historical control operation of the i-th curtain at the initial historical moment, Represents the light intensity vector at the current moment, X i,r represents the light intensity vector at the initial historical moment of the rth historical control operation of the i-th curtain, and ‖‖2 represents the L2 norm of the vector.

[0083] is the first difference factor, which represents the Euclidean distance between two opening and closing degree vectors; is the second difference factor, representing the Euclidean distance between the two light intensity vectors. The environmental differences in both opening and closing degree and light intensity comprehensively represent the environmental differences between the current moment and the historical control operations.

[0084] In other embodiments, when analyzing environmental differences, the difference analysis results of environmental data in other dimensions can also be added for comprehensive evaluation. Specifically, the solar altitude angle at each moment is obtained, which indirectly reflects the performance of the natural environment at the corresponding moment. The absolute value of the difference between the solar altitude angle at the current moment and the solar altitude angle at the first historical moment under each historical control operation of each curtain is further calculated as the third difference factor between the current moment and each historical control operation of each curtain. The cumulative sum of the first difference factor, the second difference factor, and the third difference factor is used as the corresponding environmental difference, which can more comprehensively measure the difference in the corresponding lighting environment between different time nodes. It should be noted that in order to avoid the influence of the dimension on the data analysis results, the solar altitude angle needs to be normalized before the difference calculation is performed. At the same time, the method for obtaining the solar altitude angle is also a well-known technology and will not be described in detail here.

[0085] Step S400 , obtaining a parameter adjustment coefficient for each curtain at the current moment based on the environment difference coefficient and the light intensity data of each curtain at the current moment in combination with the operation influence coefficient.

[0086] The environmental difference coefficient reflects the comprehensive difference in the lighting environment and window opening and closing environment of each curtain at the current moment and the corresponding historical control operation. The operational impact coefficient of each historical control operation on other curtains reflects the extent to which the opening and closing action of one curtain triggers or affects the opening and closing actions of other curtains under the condition of a certain historical control operation. This impact has a temporal condition, that is, it corresponds to the impact at the moment of the historical adjustment operation. In order to predict and evaluate whether the current opening and closing action of a curtain will have a significant impact on other curtains, when analyzing historical control operations, it is also necessary to consider whether there is a certain difference between the environment at the current moment and the time node of the corresponding historical control operation. The greater the difference between the two, the greater the difference between the historical control operation environment and the current operating environment, and the smaller the operational impact between curtains. Based on this, the environmental difference coefficient is first used to construct the operational impact relationship between different windows at the current moment.

[0087] Step S401 , based on the environmental difference coefficient between the current moment and each historical control operation of each curtain, combined with the operational impact coefficient of each curtain's corresponding historical control operation on other curtains, obtain an impact evaluation index of each curtain's control operation on other curtains at the current moment.

[0088] Specifically, negative correlation normalization processing is performed on the environmental difference coefficient between the current moment and each historical control operation of each curtain to obtain the environmental weight corresponding to each historical control operation of each curtain; the environmental weight is used to weightedly average the operational influence coefficient of each curtain on other curtains under each historical control operation to obtain the impact evaluation index of each curtain's control operation on other curtains at the current moment.

[0089] As a specific example, taking the i-th curtain and the m-th other curtain as examples, the calculation method of the evaluation index of the impact of the control operation of the i-th curtain on the m-th other curtain at the current moment can be expressed as:

[0090]

[0091] Among them, F′ i,m N represents the impact evaluation index of the control operation of the i-th curtain on the m-th other curtain at the current moment, i represents the total number of historical control operations of the i-th curtain, Y i,r represents the environmental difference coefficient between the current moment and the rth historical control operation of the i-th curtain, F i,r (m) represents the operational influence coefficient of the i-th curtain on the m-th other curtain under the r-th historical control operation, and Norm represents the normalization function.

[0092] [1-Norm(Y i,r )] is the environmental weight corresponding to the rth historical control operation of the i-th curtain. A larger value indicates a smaller corresponding environmental difference and a greater reference value for evaluating the impact of the upcoming control operation of the r-th window on other windows at the current moment. The impact assessment index is obtained by taking a weighted average, reflecting the degree of influence of each curtain's control operation on all other curtains at the current moment.

[0093] Step S402, obtaining the standard light intensity corresponding to the curtain adjustment operation; obtaining the parameter adjustment coefficient of each curtain at the current moment based on the degree to which each curtain is affected by the other curtain adjustment operations at the current moment and the light intensity data corresponding to the other curtains at the current moment combined with the standard light intensity.

[0094] The adjustment of each curtain not only affects the ambient light intensity in the area surrounding its own window, but also, due to certain objective factors, affects the ambient light intensity in the areas surrounding other windows. For example, if window 1 is closed, it may cause the windows in adjacent areas to detect insufficient ambient light intensity, requiring the corresponding curtains to be opened wider. The adjustment of multiple curtains may have a cumulative impact on the area surrounding the same window. Therefore, when analyzing the need for adjustment of each curtain at the current moment, the cumulative impact of all other curtain operations should be considered. In other words, the adjustment of each curtain should comprehensively consider the status of other curtains and their impact on itself, which can effectively suppress the oscillation caused by multiple curtain control operations.

[0095] Specifically, any curtain is recorded as the selected curtain, and all other curtains except the selected curtain are recorded as reference curtains; the difference between the light intensity data of each reference curtain at the current moment and the standard light intensity is used as the operation weight of each reference curtain; using the operation weight of each reference curtain, the influence evaluation index of the control operation of each reference curtain at the current moment on the selected curtain is weightedly summed, and the summation result is negatively correlated and normalized to obtain the parameter adjustment coefficient of the selected curtain at the current moment.

[0096] It should be understood that the influence of the opening and closing operations of the curtains is mutual, that is, the adjustment operation of each curtain may have a greater or lesser influence on each other curtain, and for each curtain, each curtain will also be affected to a greater or lesser extent by the other curtains with adjustment operations. Based on this, the impact evaluation index of the adjustment operation of each reference curtain at the current moment on the selected curtain also represents the degree to which the selected curtain is affected by the adjustment operation of each reference curtain.

[0097] As a specific example, the nth curtain is recorded as the selected curtain. Taking the selected curtain as an example for explanation, the parameter adjustment coefficient of the nth curtain at the current moment can be expressed as:

[0098]

[0099] Among them, R n represents the parameter adjustment coefficient of the nth curtain at the current moment, N1 represents the total number of curtains, F′ k,n represents the impact evaluation index of the control operation of the kth reference curtain on the nth curtain at the current moment, ΔL n,k It represents the difference between the light intensity data of the kth reference curtain corresponding to the nth curtain at the current moment and the standard light intensity, that is, the operation weight, and Norm represents the normalization function.

[0100] It should be noted that standard light intensity refers to the target value or target range of indoor light intensity that is expected to be maintained during a specific time period. Implementers need to set this value based on the specific implementation scenario. It can be a single value or a range of values. Considering that natural light intensity varies at different times of the day, in order to maximize the use of natural light, the intelligent system can preset different standard light intensities for different times of the day, such as morning, noon, and afternoon. No further restrictions are imposed here.

[0101] It should be understood that when the standard light intensity is the target value, the absolute value of the difference between the light intensity data of the kth reference curtain corresponding to the nth curtain at the current moment and the target value is calculated to obtain the corresponding operation weight ΔL n,k When the standard light intensity is the target interval, calculate the minimum absolute value of the difference between the light intensity data of the kth reference curtain corresponding to the nth curtain at the current moment and the light intensity in the target interval, and obtain the corresponding operation weight ΔL n,k .

[0102] The operation weight represents the urgency of the adjustment demand of the corresponding reference curtain at the current moment. When the value of the operation weight is larger, it means that the adjustment demand of the reference curtain at the current moment is more urgent. At this time, the adjustment operation of the reference curtain has a greater impact on the selected curtain, that is, the nth curtain. The adjustment of the reference curtain may significantly change the ambient light intensity of the area where the selected curtain is located. At this time, it is necessary to relatively reduce the controllable response degree of the area where the selected curtain is located to avoid the oscillation of the selected curtain caused by the adjustment of the reference curtain. That is, the larger the value of the corresponding parameter adjustment coefficient is.

[0103] The parameter adjustment coefficient of the selected curtain at the current moment reflects the situation in which the response level of the selected curtain needs to be reduced at the current moment. That is, the parameter adjustment coefficient is used to represent that the system can dynamically reduce the response gain of the curtain in high-interference scenarios to avoid overshoot and oscillation caused by chain reactions.

[0104] Step S500: Control each curtain based on the parameter adjustment coefficient and the stepping motor corresponding to each curtain.

[0105] Specifically, for each curtain, the PID parameters of the stepper motor at the current moment are obtained, and the product of the parameter adjustment coefficient of each curtain at the current moment and the proportional coefficient in the PID parameters is used as the adjusted proportional coefficient of each curtain. Based on the adjusted proportional coefficient of each curtain, the adjusted integral coefficient and differential coefficient are obtained, and PID control is performed on each curtain. The adjusted integral coefficient and differential coefficient are obtained by: using the ratio of the adjusted proportional coefficient of each curtain and the currently preset integral time constant as the adjusted integral coefficient of each curtain; and using the product of the adjusted proportional coefficient of each curtain and the currently preset differential time constant as the adjusted differential coefficient of each curtain.

[0106] More intuitively, the adjusted PID parameters can be expressed as follows: K P,n =R n ×K P , K D,n =K P,n ×T D , where R n Indicates the parameter adjustment coefficient of the nth curtain at the current moment, K P Indicates the proportional coefficient before adjustment in the PID parameter of the current moment corresponding to the nth curtain, K P,n , K I,n and K D,n They represent the proportional coefficient, integral coefficient and differential coefficient of the nth curtain after adjustment at the current moment, T I represents a preset integral time constant, which is exemplarily set to 10 in this embodiment. D represents a preset differential time constant, which is exemplarily set to 1.5 in this embodiment.

[0107] The movement of other curtains significantly interferes with the nth curtain (such as light intensity superposition or shading effect). The smaller the value of the corresponding parameter adjustment coefficient is, the lower the proportional gain is. This can reduce the excessive adjustment of the nth curtain caused by the environment and suppress oscillation.

[0108] Based on this, according to the adjusted PID parameters, the system can dynamically allocate proportional gains during the adjustment process. For curtains that are less affected by light intensity, a higher proportional coefficient is assigned to improve their response sensitivity to light changes and quickly compensate for small-scale disturbances. For curtains in areas of strong disturbance, their proportional terms are appropriately reduced to slow down the response speed and avoid system oscillations caused by excessive adjustment, thereby enhancing the stability and anti-disturbance capability of the overall system.

[0109] Finally, at the current moment, each curtain corresponds to an adjusted proportional coefficient, integral coefficient and differential coefficient, that is, the adjusted PID parameters. Based on the adjusted PID parameters, the PID algorithm is used to generate the PID control signal corresponding to each window, and then the PID control signal of each curtain is output to the motor corresponding to each curtain, driving the motor to adjust the opening and closing degree of the curtain.

[0110] At the motor drive level, each stepper motor is controlled by a high-precision drive module. The pulse frequency and stepping direction are adjusted in real time based on the PID control signal output at the current moment, enabling fine-tuning of the curtain fabric or continuous opening and closing. The drive process utilizes a micro-control and speed gradient mechanism to ensure smooth and jitter-free adjustment, effectively extending the life of mechanical components. It should be understood that the PID control algorithm and stepper motor drive method are well-known technologies and will not be further elaborated here.

[0111] The networking control module is centrally managed by the master control unit and maintains periodic state synchronization with each curtain node based on wireless or bus communication protocols. The system supports a distributed PID parameter update mechanism and a motor cascade control strategy. While ensuring local response at each node, it calculates global illumination deviation by integrating data from all light intensity sensors, further guiding coordinated parameter adjustment and motor scheduling. Ultimately, through a dynamic trade-off between local control and global illumination goals, an intelligent curtain control strategy is achieved that unifies illumination balance, energy optimization, and multi-motor coordinated motion.

[0112] In summary, the present invention can adaptively adjust the PID control parameters of each curtain motor based on historical light intensity and current environmental changes, thereby improving the system's adaptability to light changes in a multi-source disturbance environment. By calculating the degree of influence of each curtain on indoor light intensity in real time and building a prediction model, the system can achieve differentiated regulation and priority control, avoiding excessive response or energy waste caused by blind synchronous action. Compared with the traditional static parameter control method, the present invention has higher lighting control accuracy, stronger anti-interference ability and lower overall energy consumption while ensuring indoor lighting comfort. In addition, the system supports wireless networking and dynamic parameter coordination between motors, which is easy to deploy and expand, and is suitable for the intelligent lighting management needs of complex home or office scenarios such as multiple rooms and multiple windows.

[0113] An embodiment of the present invention also provides a micro stepper motor for smart home curtains, which is used to receive a control signal from a control unit, that is, to receive a control signal generated by the control unit based on the adjusted PID parameters, and to execute the step of controlling each curtain in the wireless networking control method of the micro stepper motor for smart home curtains.

[0114] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A wireless networking control method for a micro stepping motor of a smart home curtain, characterized in that: The method comprises the following steps: Obtain the light intensity data of each curtain at the current moment and at each historical moment under each historical control operation, as well as the opening and closing degree data of each curtain at the current moment and at each historical control operation; Based on the correlation between the historical control operation of each curtain and the light intensity data change trend of other curtains at the same historical moment, the influence coefficient of each historical control operation of each curtain on the operation of other curtains is analyzed; Based on the difference in the opening and closing degree data of all curtains at the current moment and under each historical control operation, combined with the difference in the light intensity data of all curtains at the current moment and under each historical control operation, the environmental difference coefficient between the current moment and each historical control operation of each curtain is obtained; Obtaining a parameter adjustment coefficient for each curtain at the current moment based on the environmental difference coefficient and the light intensity data of each curtain at the current moment, combined with the operation influence coefficient; Each curtain is controlled based on the parameter adjustment coefficient and the stepping motor corresponding to each curtain.

2. The wireless networking control method for a micro stepping motor of a smart home curtain according to claim 1, characterized in that: The analysis of the influence coefficient of each historical control operation of each curtain on the operation of other curtains based on the correlation between the change trend of the light intensity data of each curtain under the historical control operation and other curtains at the same historical moment specifically includes: Determine a light intensity difference factor for each curtain at each historical moment based on a difference in light intensity data of each curtain between each historical moment and an adjacent historical moment; According to the correlation between the light intensity difference factor of each curtain at each historical moment under each historical control operation and the light intensity difference factors of other curtains at the same historical moment, the influence coefficient of each curtain's historical control operation on the operation of other curtains is obtained.

3. The wireless networking control method for a micro stepping motor of a smart home curtain according to claim 2, characterized in that: Obtaining the influence coefficient of each curtain's historical control operation on other curtains based on the correlation between the light intensity difference factor of each curtain at each historical moment under each historical control operation and the light intensity difference factors of other curtains at the same historical moment specifically includes: The historical time period corresponding to any historical control operation of any curtain is recorded as the target time period of the target curtain. Based on the ratio between the light intensity difference factor of the target curtain at each historical moment in the target time period and the light intensity difference factor of each other curtain at the same corresponding historical moment, the operation influence coefficient of the historical control operation corresponding to the target curtain in the target time period on each other curtain is determined.

4. The wireless networking control method for a micro stepping motor of a smart home curtain according to claim 1, characterized in that: The environmental difference coefficient between the current moment and each historical control operation of each curtain is obtained based on the difference in the opening and closing degree data of all curtains at the current moment and each historical control operation, combined with the difference in the light intensity data of all curtains at the current moment and each historical control operation. Specifically, the difference coefficient includes: Based on the opening and closing data of all curtains at each moment, an opening and closing vector at each moment is constructed; based on the light intensity data of all curtains at each moment, a light intensity vector at each moment is constructed; wherein each moment includes the current moment and each historical moment; Based on the difference between the opening and closing degree vector at the current moment and the opening and closing degree vector at the initial historical moment under each historical control operation of each curtain, a first difference factor between the current moment and each historical control operation of each curtain is determined; based on the difference between the light intensity vector at the current moment and the light intensity vector at the initial historical moment under each historical control operation of each curtain, a second difference factor between the current moment and each historical control operation is determined; and in combination with the first difference factor and the second difference factor, an environmental difference coefficient between the current moment and each historical control operation of each curtain is determined.

5. The wireless networking control method for a micro stepping motor of a smart home curtain according to claim 1, characterized in that: The parameter adjustment coefficient of each curtain at the current moment is obtained based on the environmental difference coefficient and the light intensity data of each curtain at the current moment, combined with the operation influence coefficient, specifically including: Based on the environmental difference coefficient between the current moment and each historical control operation of each curtain, combined with the influence coefficient of each curtain's corresponding historical control operation on other curtains, an impact evaluation index of each curtain's control operation at the current moment on other curtains is obtained; Obtain the standard light intensity corresponding to the curtain adjustment operation; obtain the parameter adjustment coefficient of each curtain at the current moment based on the degree to which each curtain is affected by the adjustment operation of other curtains at the current moment and the light intensity data corresponding to other curtains at the current moment combined with the standard light intensity.

6. The wireless networking control method for a micro stepping motor of a smart home curtain according to claim 5, characterized in that: The impact evaluation index of each curtain's control operation at the current moment on other curtains is obtained based on the environmental difference coefficient between the current moment and each historical control operation of each curtain, combined with the operational impact coefficient of each curtain's corresponding historical control operation on other curtains. Specifically, it includes: The environmental difference coefficient between the current moment and each historical control operation of each curtain is negatively correlated and normalized to obtain the environmental weight corresponding to each historical control operation of each curtain; the environmental weight is used to weightedly average the operational influence coefficient of each curtain on other curtains under each historical control operation to obtain the impact evaluation index of each curtain's control operation on other curtains at the current moment.

7. The wireless networking control method for a micro stepping motor of a smart home curtain according to claim 5, characterized in that: The parameter adjustment coefficient of each curtain at the current moment is obtained based on the degree to which each curtain is affected by the adjustment operation of other curtains at the current moment and the light intensity data of other curtains at the current moment combined with the standard light intensity, specifically including: Record any one curtain as the selected curtain, and all other curtains except the selected curtain as reference curtains; The difference between the light intensity data of each reference curtain at the current moment and the standard light intensity is used as the operation weight of each reference curtain; Using the operation weight of each reference curtain, the impact evaluation index of the control operation of each reference curtain at the current moment on the selected curtain is weightedly summed, and the summation result is negatively normalized to obtain the parameter adjustment coefficient of the selected curtain at the current moment; among which, the impact evaluation index of the control operation of each reference curtain at the current moment on the selected curtain represents the degree to which the selected curtain is affected by the adjustment operation of each reference curtain.

8. The wireless networking control method for a micro stepping motor of a smart home curtain according to claim 1, characterized in that: The controlling of each curtain based on the parameter adjustment coefficient and the stepping motor corresponding to each curtain specifically includes: For each curtain, obtain the PID parameters of the stepper motor at the current moment, and use the product of the parameter adjustment coefficient of each curtain at the current moment and the proportional coefficient in the PID parameter as the adjusted proportional coefficient of each curtain; The adjusted integral coefficient and differential coefficient are obtained according to the adjusted proportional coefficient of each curtain, and PID control is performed on each curtain.

9. The wireless networking control method for a micro stepping motor of a smart home curtain according to claim 8, characterized in that: The step of obtaining the adjusted integral coefficient and differential coefficient according to the adjusted proportional coefficient of each curtain specifically includes: The ratio of the adjusted proportional coefficient of each curtain to the current preset integral time constant is used as the adjusted integral coefficient of each curtain; the product of the adjusted proportional coefficient of each curtain and the current preset differential time constant is used as the adjusted differential coefficient of each curtain.

10. A micro stepping motor for smart home curtains, characterized in that: Used to receive the control signal of the control unit and execute the step of controlling each curtain in the wireless networking control method of the micro stepping motor of the smart home curtain as claimed in claim 1.

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