Predictive control method, device, equipment and storage medium for remote control model

Abstract

The present application provides a predictive control method, device, equipment and storage medium for a remote control model. The method includes: in response to receiving a first channel value sent by a remote control at a first time point, the first channel value is added to a first channel value curve, and a target curve segment in the first channel value curve is input into a predictive control algorithm to obtain a second channel value output by the predictive control algorithm; the first channel value curve is constructed based on the channel value received by the remote control model, the target curve segment is composed of the first channel value and a specified number of channel values ​​last received by the remote control model, the specified number is less than or equal to the total number of channel values ​​used to construct the first channel value curve, the second channel value represents the channel value sent by the predicted remote control at a second time point, and the second time point is the time point when the predictive control algorithm outputs the second channel value; the model is controlled according to the second channel value. The method provided by the present application can reduce delays in the process of operating and controlling the remote control model.

Description

Technical Field

[0001] The present application relates to the field of machine control, and in particular, to a predictive control method, device, equipment and storage medium for a remote control model. Background Art

[0002] At present, in the operation process of remote control models, the operator first receives the images and sounds generated by the model through sensory organs such as human eyes and ears. This information is transmitted to the brain for analysis and processing, and then the operator's brain controls the body to make corresponding actions to operate the controls of the remote control. The electronic part of the remote control samples the actions of these controls and converts them into digital signals. The software part then calculates the channel values ​​based on the operator's settings and the sampled digital signals. Then, the radio frequency module of the remote control modulates these channel values ​​into wireless signals and sends them out. After receiving the wireless signal, the receiver demodulates it into digital signal channel values ​​and transmits the control information to the controlled device through wired signals or wired protocols. The controlled device performs corresponding actions according to the received control information, and the linkage of multiple controlled devices finally achieves the control effect expected by the operator, that is, generates new model images and sounds and other information. In the entire control system, the receiver and the controlled device together constitute the receiving end of the control signal, and the operator inputs the operation instructions through the controls of the remote control, and the remote control sends the corresponding control signal, thereby completing the entire control process.

[0003] However, for model remote control scenarios, when the operator is manipulating the model in real time, there is often a delay from the time the operator generates an operation idea to the time the model completes the corresponding action, which makes the model unable to complete some tasks with high time accuracy requirements.

[0004] Therefore, the present application provides a predictive control method, device, equipment and storage medium for a remote control model to solve one of the above technical problems. Summary of the invention

[0005] The purpose of this application is to provide a predictive control method, device, equipment and storage medium for a remote control model, which can solve at least one of the technical problems mentioned above. The specific solution is as follows:

[0006] According to a specific implementation of the present application, in a first aspect, the present application provides a predictive control method for a remote control model, which is applied to the remote control model and includes:

[0007] In response to receiving a first channel value sent by a remote control at a first time point, the first channel value is added to a first channel value curve, and a target curve segment in the first channel value curve is input into a predictive control algorithm to obtain a second channel value output by the predictive control algorithm; wherein, the first channel value curve is constructed based on the channel value received by the remote control model, the target curve segment is composed of the first channel value and a specified number of channel values ​​last received by the remote control model, the specified number is less than or equal to the total number of channel values ​​used to construct the first channel value curve, the second channel value represents the channel value predicted to be sent by the remote control at a second time point, and the second time point is the time point when the predictive control algorithm outputs the second channel value; model control is performed according to the second channel value.

[0008] In one embodiment, the predictive control algorithm is used to predict the delay generated from the remote control completing control data sampling to obtain a digital signal to the remote control model receiving and completing channel value parsing; the predictive control algorithm is trained based on multiple groups of different value data, each group of value data includes a channel value received by the remote control model and a channel value sent by the remote control at the same time point, and the channel value sent by the remote control is obtained based on the control value of the remote control.

[0009] In one embodiment, the predictive control algorithm is used to predict the delay from the operator generating an operation idea to the remote control model receiving and completing the channel value parsing; the predictive control algorithm is trained based on multiple groups of different value data, each group of the value data includes a channel value received by the remote control model and a channel value sent by the remote control collected at the same time point, and the channel value sent by the remote control is obtained based on the sum of the control value of the remote control and the control value increment input by the operator.

[0010] In one embodiment, the input of the predictive control algorithm also includes an adjustable parameter based on the operator input, and the adjustable parameter is used to replace the existing parameters of the predictive control algorithm, or to change the operation mode of the predictive control algorithm, so as to increase or decrease the delay predicted by the predictive control algorithm, and / or make the channel value predicted by the predictive control algorithm fit or move away from the second channel value curve constructed by the channel value sent by the remote control; the method also includes: inputting the target curve segment and the adjustable parameter into the predictive control algorithm to obtain a third channel value output by the predictive control algorithm; wherein the third channel value represents the channel value predicted to be sent by the remote control at a second time point, and the third channel value is the same as or different from the second channel value; in response to the second time point, performing model control according to the third channel value.

[0011] In one embodiment, the predictive control algorithm includes at least one of the following: derivative, anti-derivative algorithm; proportional-integral-differential algorithm; proportional-integral-differential deformation algorithm; big data model algorithm.

[0012] According to a specific embodiment of the present application, in a second aspect, the present application provides a predictive control device for a remote control model, comprising:

[0013] An input-output unit, in response to receiving a first channel value sent by a remote control at a first time point, fills the first channel value into a first channel value curve, and inputs a target curve segment in the first channel value curve into a predictive control algorithm to obtain a second channel value output by the predictive control algorithm; wherein the first channel value curve is constructed based on the channel value received by the remote control model, the target curve segment is composed of the first channel value and a specified number of channel values ​​last received by the remote control model, the specified number is less than or equal to the total number of channel values ​​used to construct the first channel value curve, the second channel value represents the channel value predicted to be sent by the remote control at a second time point, and the second time point is the time point when the predictive control algorithm outputs the second channel value; a control unit, performing model control according to the second channel value.

[0014] In one embodiment, the predictive control algorithm is used to predict the delay from the operator generating an operation idea to the remote control model receiving and completing the channel value parsing; the predictive control algorithm is trained based on multiple groups of different value data, each group of the value data includes a channel value received by the remote control model and a channel value sent by the remote control collected at the same time point, and the channel value sent by the remote control is obtained based on the sum of the control value of the remote control and the control value increment input by the operator.

[0015] In one embodiment, the input of the predictive control algorithm also includes adjustable parameters based on the operator input, and the adjustable parameters are used to replace the existing parameters of the predictive control algorithm, or to change the operation mode of the predictive control algorithm, so as to increase or decrease the delay predicted by the predictive control algorithm, and / or make the channel value predicted by the predictive control algorithm fit or move away from the second channel value curve constructed by the channel value sent by the remote control; the input-output unit is also used to: input the target curve segment and the adjustable parameters into the predictive control algorithm to obtain a third channel value output by the predictive control algorithm; wherein the third channel value represents the channel value predicted to be sent by the remote control at the second time point, and the third channel value is the same as or different from the second channel value; the control unit is also used to: perform model control according to the third channel value.

[0016] According to a specific implementation of the present application, in a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement any one of the methods described in the first aspect.

[0017] According to the specific implementation of the present application, in a fourth aspect, the present application provides a computer-readable storage medium having a computer program / instruction stored thereon, which, when executed by a processor, implements the method described in any one of the first aspects.

[0018] Compared with the prior art, the above scheme of the embodiment of the present application has at least the following beneficial effects: the present application provides a predictive control method for a remote control model, which receives a first channel value sent by a remote control at a first time point and inputs it into a predictive control algorithm to obtain a predicted second channel value, thereby performing model control at a second time point. This method can effectively reduce the delay between the operator's operation idea and the model's response, and improve the operator's real-time sense and experience of operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flow chart showing a predictive control method for a remote control model is shown;

[0020] Figure 2 A schematic diagram showing the timing relationship of each time point in the model control process is shown.

[0021] Figure 3 A schematic diagram of training a predictive control algorithm is shown;

[0022] Figure 4 Another schematic diagram for training a predictive control algorithm is shown;

[0023] Figure 5 A flow chart showing another predictive control method for a remote control model is shown;

[0024] Figure 6 A schematic diagram showing the effect of channel value processing in the related art is shown;

[0025] Figure 7 A schematic diagram showing the channel value processing effect of the present application is shown;

[0026] Figure 8 A unit block diagram of a predictive control device for a remote control model according to an embodiment of the present application is shown;

[0027] Fig. 9 The invention is a block diagram of an electronic device for predictive control of a remote control model according to an exemplary embodiment. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0029] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0030] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0031] It should be understood that although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0032] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0033] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0034] It should be particularly noted that any symbols and / or numbers in the specification that are not marked in the accompanying drawings are not drawing marks.

[0035] At present, in the operation process of remote control models, the operator first receives the images and sounds generated by the model through sensory organs such as human eyes and ears. This information is transmitted to the brain for analysis and processing, and then the operator's brain controls the body to make corresponding actions to operate the controls of the remote control. The electronic part of the remote control samples the actions of these controls and converts them into digital signals. The software part then calculates the channel values ​​based on the operator's settings and the sampled digital signals. Then, the radio frequency module of the remote control modulates these channel values ​​into wireless signals and sends them out. After receiving the wireless signal, the receiver demodulates it into digital signal channel values ​​and transmits the control information to the controlled device through wired signals or wired protocols. The controlled device performs corresponding actions according to the received control information, and the linkage of multiple controlled devices finally achieves the control effect expected by the operator, that is, generates new model images and sounds and other information. In the entire control system, the receiver and the controlled device together constitute the receiving end of the control signal, and the operator inputs the operation instructions through the controls of the remote control, and the remote control sends the corresponding control signal, thereby completing the entire control process.

[0036] However, for model remote control scenarios, when the operator is manipulating the model in real time, there is often a delay from the time the operator generates an operation idea to the time the model completes the corresponding action, which makes the model unable to complete some tasks with high time accuracy requirements.

[0037] In view of this, the present application provides a predictive control method for a remote control model to propose corresponding solutions to different causes of time delay in model remote control scenarios, thereby keeping the remote control model actions and the operator's thoughts synchronized in the time dimension.

[0038] The optional embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0039] The embodiment provided in this application is an embodiment of a predictive control method for a remote control model.

[0040] Combine the following Figure 1 The embodiments of the present application are described in detail.

[0041] Figure 1 A flow chart of a predictive control method for a remote control model is shown, Figure 1 As shown, the method is applied to a remote control model, and includes the following steps S101 to S102.

[0042] Step S101, in response to receiving a first channel value sent by a remote control at a first time point, the first channel value is added to a first channel value curve, and a target curve segment in the first channel value curve is input to a predictive control algorithm to obtain a second channel value output by the predictive control algorithm.

[0043] Among them, the first channel value curve is constructed based on the channel value received by the remote control model, the target curve segment is composed of the first channel value and a specified number of channel values ​​last received by the remote control model, the specified number is less than or equal to the total number of channel values ​​used to construct the first channel value curve, the second channel value represents the channel value sent by the predicted remote control at a second time point, and the second time point is the time point when the prediction control algorithm outputs the second channel value.

[0044] Step S102: performing model control according to the second channel value.

[0045] The present application provides a predictive control method for a remote control model, which receives a first channel value sent by a remote control at a first time point and inputs it into a predictive control algorithm to obtain a predicted second channel value, thereby performing model control at a second time point. This method can effectively reduce the delay between the operator's operation idea and the model's response, and improve the operator's real-time sense and experience of operation.

[0046] Figure 2 A schematic diagram showing the timing relationship of each time point in the model control process is shown.

[0047] For example, suppose that the operator operates the remote control at the first time point to send the channel value for the nth time, and the first channel value sent is C1. After the channel value C1 is received by the receiver, it is input into the predictive control algorithm. Based on historical data and current input, the predictive control algorithm predicts that the remote control will send the second channel value C2 at the second time point. Then, the model controls according to the predicted channel value C2 at the second time point. In this way, if the n+1th channel transmission occurs at the second time point, and the channel value sent for the n+1th time arrives after the second time point, the model can also react in advance, reducing the operation delay. However, in the actual control process, the second time point is the time point when the predictive control algorithm outputs the second channel value. At this time, the remote control may but will not necessarily make the n+1th transmission action at the second time point. For example, Figure 2As shown, the remote control may have sent the channel value for the n+1th time before the second time point, or even before the remote control model receives the first channel value. Alternatively, the channel value may be sent for the n+1th time only after the second time point. In the present application, the predictive control algorithm outputs the second channel value at the second time point and performs model control with the second channel value, aiming to assume that the remote control has sent a new channel value at the second time point, and then predict and respond to the channel value sent at the second time point. On this basis, even if the time point at which the remote control sends the channel value for the n+1th time is earlier or later than the second time point, in the entire model control process, the model can still express a better response speed, and the delay problem can be significantly improved.

[0048] In the embodiment of the present application, the predictive control algorithm is used to predict the delay generated from the remote control completing the control data sampling to obtain the digital signal to the remote control model receiving and completing the channel value analysis.

[0049] Figure 3 A schematic diagram of training a predictive control algorithm is shown.

[0050] For example, Figure 3 As shown, the predictive control algorithm is trained based on multiple groups of different value data. Each group of value data includes a channel value received by a remote control model receiver and a channel value sent by a remote control collected at the same time point. The channel value sent by the remote control is obtained based on the control value of the remote control.

[0051] On this basis, the channel value received by the receiver is used as the input information of the predictive control algorithm, and the channel value corresponding to the measured remote control control value is used as the target value of the predictive control algorithm. The algorithm predicts the channel value that the receiver needs to output at the current moment, and compares the output channel value with the target value to adjust the predictive control algorithm. When the predictive control algorithm completes training, the channel value output by the predictive control algorithm can be used to reduce or even offset the delay generated from the remote control completing the control data sampling to obtain the digital signal to the remote control model receiving and completing the channel value analysis, so as to achieve the effect of eliminating the delay.

[0052] In the embodiment of the present application, the predictive control algorithm is used to predict the delay generated from the operator generating an operation idea to the remote control model receiving and completing the channel value analysis.

[0053] Figure 4 Another schematic diagram for training a predictive control algorithm is shown.

[0054] For example, Figure 4As shown, the predictive control algorithm is trained based on multiple groups of different value data, each group of value data includes a channel value received by a remote control model and a channel value sent by a remote control collected at the same time point, and the channel value sent by the remote control is obtained based on the sum of the control value of the remote control and the control value increment entered by the operator.

[0055] On this basis, the channel value received by the receiver is used as the input information of the predictive control algorithm. Based on the measured control value of the remote control, a certain amount of advance is added as the channel value corresponding to the operation effect when the operator's brain generates the idea, which is used as the target value of the predictive control algorithm. The algorithm predicts the channel value that the receiver needs to output at the current moment, and compares the output channel value with the target value to adjust the predictive control algorithm. When the predictive control algorithm completes the training, the channel value output by the predictive control algorithm can be used to reduce or even offset the delay generated from the operator generating the operation idea to the remote control model receiving and completing the channel value analysis, so as to achieve the effect of eliminating the delay, improve the operator's sense of real-time operation, and operate as soon as he thinks.

[0056] In addition, the operator can also adjust the predicted value through the parameters provided by the algorithm (increase or decrease of delay, deviation of the predicted channel from or closer to the target value) to make it more in line with the operator's feel and improve the operator's operating effect and performance.

[0057] In the embodiment of the present application, there are many possible factors that may cause delays in the process of model remote control, such as the operator controlling the body to operate the remote control control action, the remote control electronic part sampling the control action and converting it into a digital signal, the software part performing calculations (calculating the channel value based on the user settings and the sampled digital signal), the frequency module modulating the channel value calculated into a wireless signal, the remote control model receiving the wireless signal and demodulating it into a digital signal channel value, and sending the control information to the controlled device through a wired signal / wired protocol. Based on the training method provided in the above embodiment, the overall estimation of the above delay can be achieved to optimize the timeliness of model control.

[0058] In the embodiment of the present application, the input of the predictive control algorithm also includes an adjustable parameter based on the operator input, and the adjustable parameter is used to replace the existing parameters of the predictive control algorithm, or to change the operation mode of the predictive control algorithm, so as to increase or decrease the delay predicted by the predictive control algorithm, and / or make the channel value predicted by the predictive control algorithm fit or move away from the second channel value curve constructed by the channel value sent by the remote control. On this basis, the present application further provides a channel value prediction based on operator correction.

[0059] Figure 5 A flowchart of another predictive control method for a remote control model is shown. Figure 5 As shown, the method is applied to a remote control model, and includes the following steps S501 to S503.

[0060] Step S501, in response to receiving a first channel value sent by a remote controller at a first time point, adding the first channel value to a first channel value curve.

[0061] Step S502: input the target curve segment and the adjustable parameters into the predictive control algorithm to obtain the third channel value output by the predictive control algorithm.

[0062] The third channel value represents the channel value sent by the predicted remote controller at the second time point, and the third channel value is the same as or different from the second channel value.

[0063] Step S503: performing model control according to the third channel value.

[0064] The embodiment of the present application introduces adjustable parameters so that the predictive control algorithm can be adjusted according to the individual needs of the operator. This increases the flexibility and adaptability of the predictive control algorithm, allowing different operators to adjust the prediction delay according to their own operating habits, thereby improving the operating effect and performance.

[0065] In the embodiments of the present application, when the adjustable parameters are used to replace the existing parameters of the predictive control algorithm, it is equivalent to adjusting the existing operation structure in the predictive control algorithm. In addition, the predictive control algorithm can also be configured with at least two operation modes. When the adjustable parameters are used to change the operation mode of the predictive control algorithm, it indicates that a switch has been made among several operation modes that have been configured for the predictive control algorithm. In addition to the above embodiments, the present application can also use other methods to modify the predictive control algorithm, which are not described in detail in this application.

[0066] Illustratively, the predictive control algorithm in the present application includes at least one of the following.

[0067] ① Derivative and anti-derivative algorithms.

[0068] ②Proportional-integral-derivative (PID) algorithm.

[0069] ③Proportional-integral-differential deformation algorithm.

[0070] ④Big data model algorithm.

[0071] The above optional algorithms have their own characteristics and applicable scenarios, and this application can select one or several of them for use. Among them, for the scenario of selecting several of them as predictive control algorithms, this application can exemplarily use different algorithms to obtain prediction results respectively, and then give corresponding weights by verifying the authenticity of the results, so as to obtain the final predicted channel value by weighting the results. Of course, this is only an exemplary description, and the actual application method is not unique.

[0072] In addition, for the scenario where one of the two algorithms is selected as the predictive control algorithm, the present application provides implementation details of two of the algorithms. Figure 6 An exemplary description is given.

[0073] Figure 6 A schematic diagram of the channel value processing effect in the related art is shown.

[0074] Figure 7 A schematic diagram of the channel value processing effect of the present application is shown.

[0075] For example, Figure 6 As shown, the related technology adopts the method of directly outputting the channel value received by the receiver, and the channel value output by the related technology is consistent with the channel value received by the receiver. Since there is a delay from the operator's operation idea to the control remote control sending the channel value, and there is a communication delay in the channel value transmission, there is a delay between the operator's operation idea and the remote control model completing the corresponding action. This delay can be Figure 6 The difference between the target value curve of the algorithm and the value curve of the relevant output channel in the vertical direction is reflected. In this regard, consider debugging the predictive control algorithm. For example, Figure 7 As shown, the algorithm target value in this application is the channel value corresponding to the remote control control value, and the algorithm input data is the channel value received by the receiver. On this basis, the predictive control algorithm predicts the delay from the operator generating the operation idea to the remote control model completing the corresponding action, and outputs the predicted channel value used to reduce the delay. And, further, the present application can adjust the predictive control algorithm through adjustable parameters, and by setting and adjusting the adjustable parameters, the output result of the predictive control algorithm can be optimized. For example, the output data of Algorithm 1 and Algorithm 2 are the channel values ​​processed by the predictive control algorithm. The difference is that the adjustable parameters are different. The curve output by Algorithm 2 is smoother and more complete, which better meets user needs and can improve the real-time operation and user experience.

[0076] As one feasible embodiment, the present application may use derivative and anti-derivative methods to implement a predictive control algorithm.

[0077] First, prepare for algorithm debugging. Use an oscilloscope to measure the remote control control value (under normal operator control model conditions), use the remote control channel operation to convert it into a channel value, read the channel value received by the receiver through the program, and adjust the algorithm to make the algorithm output value closer to the algorithm target value. Further, the algorithm core solution is used to obtain the operation curve. Assume that the number of channel values ​​used in the algorithm operation is 3, for example, Figure 7As an example, three points t0, t1, and t2 are selected, and three points x0, x1, and x2 are used as the channel values ​​for the target curve segment, where x2 can be regarded as the first channel value. Assuming that the delay time is known to be m, the time and value correspondence of "remote control value corresponding to channel value" is: t0-m corresponds to value x0, t1-m corresponds to value x1, and t2-m corresponds to value x2. This correspondence can be used to find the corresponding channel value sent by the transmitter when training the algorithm. Calculate the derivative:

[0078] Calculation of actual output value of t2:

[0079] The calculation of k value can also be done by other methods, as long as the ultimate goal is to make the output curve closer to the target curve. After the budget is completed, all the calculation results are calculated to form a line segment. Furthermore, the output data curve obtained by the current algorithm and the input data curve operated by the operator are checked to adjust the k value calculation formula by the algorithm, such as using multi-order derivative calculation methods. Adjust the final data formula:

[0080] a and b are constant values ​​added. Adjust the number of "channel values ​​received by the receiver" used in the calculation, such as adjusting to 4, 10, or 100. The delay time is the value of m, such as 0.001s, 0.0011s (the delay time can also be measured). Add safety mechanisms in the calculation. If there is a large deviation between the predicted value and the actual value received later, correct it immediately and restart the calculation. Let the operator perform multiple operations, use the algorithm to simulate the output, and verify the accuracy of the algorithm operation. Finally, the operator adjusts the parameters. The operator can adjust the predicted value (increase or decrease the delay, predict the channel to deviate from or get closer to the target value) through the parameters provided by the algorithm to make it more in line with the operator's feel, improve the operator's operating effect and performance, and open parameter items. Switch the calculation formula of the k value and the final data formula: The a and b in the calculation use the "channel value received by the receiver" quantity.

[0081] As another feasible embodiment, the present application may adopt a big data model algorithm to implement a predictive control algorithm.

[0082] First, data collection is performed. The operator is asked to operate the remote control for a long time and multiple times, read the remote control control value through the program, use the channel operation in the remote control to convert it into the channel value, and read the channel value received by the receiver through the program. Secondly, model training is performed, and the collected data is put into the big data model, so that the big data model can continue to learn and simulate to find a suitable algorithm, such as setting an accuracy of 99% within the error range of 0.5% of the data. Finally, the operator adjusts the parameters. The calculation results are provided to the operator for adjustment to meet his or her operating feel adaptation.

[0083] The present application also provides an apparatus embodiment that is consistent with the above embodiment, which is used to implement the method steps of the above embodiment. The explanation based on the same name meaning is the same as the above embodiment, and has the same technical effect as the above embodiment, which will not be repeated here.

[0084] like Figure 8 As shown, the present application provides a predictive control device 800 for a remote control model, comprising:

[0085] The input-output unit 801, in response to receiving the first channel value sent by the remote control at the first time point, fills the first channel value into the first channel value curve, and inputs the target curve segment in the first channel value curve into the predictive control algorithm to obtain the second channel value output by the predictive control algorithm. The first channel value curve is constructed based on the channel value received by the remote control model, the target curve segment is composed of the first channel value and the specified number of channel values ​​last received by the remote control model, the specified number is less than or equal to the total number of channel values ​​used to construct the first channel value curve, the second channel value represents the channel value sent by the predicted remote control at the second time point, and the second time point is the time point when the predictive control algorithm outputs the second channel value. The control unit 802 performs model control according to the second channel value.

[0086] In one embodiment, the predictive control algorithm is used to predict the delay from the operator generating an operation idea to the remote control model receiving and completing the channel value analysis. The predictive control algorithm is trained based on multiple sets of different value data, each set of value data includes a channel value received by the remote control model and a channel value sent by the remote control collected at the same time point, and the channel value sent by the remote control is obtained based on the sum of the control value of the remote control and the control value increment input by the operator.

[0087] In one embodiment, the input of the predictive control algorithm also includes adjustable parameters based on operator input, and the adjustable parameters are used to replace existing parameters of the predictive control algorithm, or to change the operation mode of the predictive control algorithm, so that the delay predicted by the predictive control algorithm increases or decreases, and / or the channel value predicted by the predictive control algorithm fits or moves away from the second channel value curve constructed by the channel value sent by the remote control. The input and output unit 801 is also used to: input the target curve segment and the adjustable parameters into the predictive control algorithm to obtain the third channel value output by the predictive control algorithm. The third channel value represents the channel value sent by the predicted remote control at the second time point, and the third channel value is the same as or different from the second channel value. The control unit 802 is also used to: perform model control according to the third channel value.

[0088] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0089] Fig. 9 It is a block diagram of an electronic device 900 for predictive control of a remote control model according to an exemplary embodiment.

[0090] like Fig. 9 As shown, one embodiment of the present application provides an electronic device 900. The electronic device 900 includes a memory 901, a processor 902, and an input / output (I / O) interface 903. The memory 901 is used to store instructions. The processor 902 is used to call the instructions stored in the memory 901 to execute the method for predictive control of a remote control model in an embodiment of the present application. The processor 902 is connected to the memory 901 and the I / O interface 903, respectively, for example, through a bus system and / or other forms of connection mechanisms (not shown). The memory 901 can be used to store programs and data, including the program of the method for predictive control of a remote control model involved in the embodiment of the present application, and the processor 902 executes various functional applications and data processing of the electronic device 900 by running the program stored in the memory 901.

[0091] In the embodiment of the present application, the processor 902 can be implemented in at least one hardware form of a digital signal processor (Digital Signal Processing, DSP), a field programmable gate array (Field Programmable Gate Array, FPGA), and a programmable logic array (Programmable Logic Array, PLA). The processor 902 can be a central processing unit (Central Processing Unit, CPU) or one or a combination of other forms of processing units with data processing capabilities and / or instruction execution capabilities.

[0092] The memory 901 in the embodiment of the present application may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD), etc.

[0093] In the embodiment of the present application, the I / O interface 903 may be used to receive input instructions (such as digital or character information, and to generate key signal input related to operator settings and function control of the electronic device 900, etc.), and may also output various information to the outside (such as images or sounds, etc.). In the embodiment of the present application, the I / O interface 903 may include one or more of a physical keyboard, a function key (such as a volume control key, a switch key, etc.), a mouse, a joystick, a trackball, a microphone, a speaker, and a touch panel, etc.

[0094] In some embodiments, the present application provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, any of the methods described above is performed.

[0095] In some embodiments, the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, any of the methods described above is performed.

[0096] Although operations are described in a particular order in the drawings, this should not be understood as requiring that the operations be performed in the particular order shown or in serial order, or that all shown operations be performed to achieve desired results. In certain circumstances, multitasking and parallel processing may be advantageous.

[0097] The methods and devices of the present application can be implemented using standard programming techniques, using rule-based logic or other logic to implement various method steps. It should also be noted that the words "device" and "module" used herein and in the claims are intended to include implementations using one or more lines of software code and / or hardware implementations and / or devices for receiving input.

[0098] Any steps, operations or procedures described herein may be performed or implemented using one or more hardware or software modules, either alone or in combination with other devices. In one embodiment, the software module is implemented using a computer program product including a computer-readable medium containing computer program code, which can be executed by a computer processor to perform any or all of the described steps, operations or procedures.

[0099] The foregoing description of the implementation of the present application has been given for the purpose of illustration and description. The foregoing description is not exhaustive nor is it intended to limit the present application to the exact form disclosed, and various variations and modifications may exist according to the above teachings or may be obtained from the practice of the present application. These embodiments are selected and described in order to illustrate the principles of the present application and its practical application, so that those skilled in the art can utilize the present application in various embodiments and various modifications suitable for the specific purpose contemplated.

[0100] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0101] It can be further understood that, unless otherwise specified, “connection” includes a direct connection without other components between the two, and also includes an indirect connection with other components between the two.

[0102] It is further understood that, although the operations are described in a specific order in the drawings in the embodiments of the present application, it should not be understood as requiring the operations to be performed in the specific order or serial order shown, or requiring the execution of all the operations shown to obtain the desired results. In certain environments, multitasking and parallel processing may be advantageous.

[0103] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to encompass any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the field of the present application that are not disclosed in the present application. The specification and embodiments are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following scope of rights.

[0104] It should be understood that the present application is not limited to the precise structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the scope of the appended claims.

[0105] The above 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. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A predictive control method for a remote control model, characterized in that: Applied to remote control models, including the following steps: In response to receiving a first channel value sent by the remote controller at a first time point, the first channel value is added to a first channel value curve, and a target curve segment in the first channel value curve is input to a predictive control algorithm to obtain a second channel value output by the predictive control algorithm; Wherein, the first channel value curve is constructed based on the channel value received by the remote control model, the target curve segment is composed of the first channel value and a specified number of channel values ​​last received by the remote control model, the specified number is less than or equal to the total number of channel values ​​used to construct the first channel value curve, the second channel value represents the channel value predicted to be sent by the remote control at a second time point, and the second time point is the time point when the predictive control algorithm outputs the second channel value; Performing model control according to the second channel value; The input of the predictive control algorithm further includes an adjustable parameter based on the operator input, wherein the adjustable parameter is used to replace the existing parameters of the predictive control algorithm, or to change the operation mode of the predictive control algorithm, so as to increase or decrease the delay predicted by the predictive control algorithm, and / or make the channel value predicted by the predictive control algorithm fit in with or move away from the second channel value curve constructed by the channel value sent by the remote controller; The method further comprises: Inputting the target curve segment and the adjustable parameter into the predictive control algorithm to obtain a third channel value output by the predictive control algorithm; wherein the third channel value represents a channel value predicted to be sent by the remote controller at a second time point, and the third channel value is the same as or different from the second channel value; Model control is performed according to the third channel value.

2. The predictive control method according to claim 1, characterized in that: The predictive control algorithm is used to predict the delay generated from the remote controller completing control data sampling to obtain a digital signal to the remote control model receiving and completing channel value analysis; The predictive control algorithm is trained based on multiple groups of different value data, each group of value data includes a channel value received by the remote control model and a channel value sent by the remote control at the same time point, and the channel value sent by the remote control is obtained based on the control value of the remote control.

3. The predictive control method according to claim 1, characterized in that: The predictive control algorithm is used to predict the delay from the operator generating an operation idea to the remote control model receiving and completing the channel value analysis; The predictive control algorithm is trained based on multiple groups of different value data, each group of value data includes a channel value received by the remote control model and a channel value sent by the remote control collected at the same time point, and the channel value sent by the remote control is obtained based on the sum of the control value of the remote control and the control value increment input by the operator.

4. The predictive control method according to any one of claims 1 to 3, characterized in that: The predictive control algorithm includes at least one of the following: Derivative and antiderivative algorithms; Proportional-integral-derivative algorithm; Proportional-integral-derivative deformation algorithm; Big data model algorithms.

5. A predictive control device for a remote control model, characterized in that: include: an input-output unit, in response to receiving a first channel value sent by the remote control at a first time point, filling the first channel value into a first channel value curve, and inputting a target curve segment in the first channel value curve into a predictive control algorithm, to obtain a second channel value output by the predictive control algorithm; wherein the first channel value curve is constructed based on the channel value received by the remote control model, the target curve segment is composed of the first channel value and a specified number of channel values ​​last received by the remote control model, the specified number is less than or equal to the total number of channel values ​​used to construct the first channel value curve, the second channel value represents a channel value predicted to be sent by the remote control at a second time point, and the second time point is a time point when the predictive control algorithm outputs the second channel value; A control unit performs model control according to the second channel value; The input of the predictive control algorithm further includes an adjustable parameter based on the operator input, wherein the adjustable parameter is used to replace the existing parameters of the predictive control algorithm, or to change the operation mode of the predictive control algorithm, so as to increase or decrease the delay predicted by the predictive control algorithm, and / or make the channel value predicted by the predictive control algorithm fit in with or move away from the second channel value curve constructed by the channel value sent by the remote controller; The input-output unit is further used to: input the target curve segment and the adjustable parameter into the predictive control algorithm to obtain a third channel value output by the predictive control algorithm; wherein the third channel value represents a channel value predicted to be sent by the remote controller at a second time point, and the third channel value is the same as or different from the second channel value; The control unit is further used to perform model control according to the third channel value.

6. The predictive control device according to claim 5, characterized in that: The predictive control algorithm is used to predict the delay from the operator generating an operation idea to the remote control model receiving and completing the channel value analysis; The predictive control algorithm is trained based on multiple groups of different value data, each group of value data includes a channel value received by the remote control model and a channel value sent by the remote control collected at the same time point, and the channel value sent by the remote control is obtained based on the sum of the control value of the remote control and the control value increment input by the operator.

7. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the method according to any one of claims 1 to 4.

8. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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