A stage mechanical equipment synchronous control method with dynamic optimization of state parameters

Abstract

The application discloses a stage mechanical equipment synchronous control method for dynamic optimization of state parameters, which comprises the following steps: obtaining the motion state parameters of all the equipment in synchronous linkage, and obtaining a coupling mathematical state model by performing improved state space mathematical modeling on all the equipment in synchronous motion; performing online updating on time-varying parameters in the coupling mathematical state model, and predicting the state space of the equipment; meanwhile, defining a global synchronization index based on the position synchronization error and the speed synchronization error of the equipment, so as to construct an objective function; defining a cost function of the entire state space of the equipment based on the predicted state space and the objective function; obtaining a control strategy of the equipment based on the cost function of the entire state space of the equipment, and adaptively and dynamically adjusting the control parameters of the equipment by using the control strategy. The method has the advantages that the problem of different synchronization of equipment linkage caused by position and speed deviation is reduced, the synchronous control precision among multiple equipment is improved, and the fluency and comfort of the performance are ensured.

Description

Technical Field

[0001] This invention relates to the field of motion control optimization technology for stage equipment, and in particular to a synchronous control method for stage machinery equipment with dynamic optimization of state parameters. Background Technology

[0002] With rapid economic development and the iterative upgrading of residents' cultural consumption needs, the performance market is ushering in an unprecedented period of high-quality development.

[0003] As we all know, the perfect collaboration between stage machinery and performers is a necessary prerequisite for creating outstanding artistic effects. Among them, the precise coordination of multiple stage machinery devices is the core element for enhancing artistic effects. The precise dynamic collaboration of stage equipment can not only interpret the creative ideas of the performance and enhance the artistic appeal, but also create the overall aesthetics of the stage and enhance the visual impact through the linkage between the equipment.

[0004] Currently, synchronized operation of numerous devices has become a common performance technique in captivating stage performances. Whether it's a large-scale performance or other art forms, synchronized collaboration between devices is indispensable. However, achieving precise and accurate synchronized movement of multiple devices is often constrained by several factors. First, different devices have their own independent communication and attributes, making inter-device linkage difficult. Second, stage space, the environment, and load conditions can also affect the accuracy and stability of synchronized movement. This is especially true for device formations assembled at any given moment during a performance, requiring synchronized operation to complement lighting or combined real-world artistic effects. Even minor synchronization errors or misaligned communication timing can cause deviations between the actual movement position and the target position, reducing the effectiveness of synchronized control and disrupting the overall viewing experience. Even with similar equipment, configured with the same motion parameters, and using the same control processes, there is generally good synchronization and cooperation performance in the initial time cycle. However, common factors such as sudden load changes, network congestion, slow response, or control system disturbances can cause lag or misalignment in the subsequent time cycle. For example, equipment that should have arrived at the target position simultaneously may have developed linkage errors, or equipment that should have started reverse movement simultaneously may no longer have the simultaneous start marker. Because the performance effect is sensitive to positional synchronization, these situations seriously affect the overall artistic expression of the performance. Summary of the Invention

[0005] The purpose of this invention is to provide a synchronous control method for stage machinery with dynamically optimized state parameters, thereby solving the aforementioned problems in the prior art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for synchronous control of stage machinery with dynamically optimized state parameters includes the following steps:

[0008] S1. Obtain the motion status parameters of all synchronously linked devices;

[0009] S2. Based on motion state parameters, improve the state-space mathematical modeling of all synchronously moving devices to obtain a coupled mathematical state model;

[0010] S3. Update the time-varying parameters in the coupled mathematical state model online to predict the state space of the device; at the same time, define a global synchronization index based on the device's position synchronization error and speed synchronization error to construct the objective function.

[0011] S4. Define the cost function of the entire state space of the device based on the predicted device state space and objective function; obtain the control strategy of the device according to the cost function, and use the control strategy to adaptively and dynamically adjust the control parameters of the device.

[0012] Preferably, in step S1, the motion parameters of each device include a description of the sum of position and velocity.

[0013]

[0014] in, for A set of motion parameters for a synchronously linked device; A subset of location data; A subset of velocity data; For the first Location parameters of each device; For the first Speed ​​parameters of each device; , It is a set of positive integers.

[0015] Preferably, step S2 specifically involves introducing coupling relationships between devices and adaptive parameters based on the characteristics of each device to adapt to dynamic changes in the devices, thereby constructing a coupled mathematical state model; the coupled mathematical state model is represented as follows.

[0016]

[0017]

[0018]

[0019]

[0020]

[0021] in, for The first derivative with respect to time; and The first and the The state vector of each device; For the first State transition matrix of each device; For the first Time-varying control input matrix for each device; For the first The equivalent stiffness of each device; For the first The torque of each device; The discrete time step; for The time-varying parameter at time t, and the influence factor of this parameter is: ; The moment of inertia of the equipment; The equivalent stiffness of the equipment; The torque of the equipment; For communication time delay; For the first Control status input for each device; To coordinate the first and the Coupled terms of relative motion between devices; For the first and the The coupling matrix of each device; The position coupling coefficient; This is the velocity coupling coefficient.

[0022] Preferably, step S3 specifically includes the following:

[0023] S31. Adjust the time-varying parameters of the model based on the dynamic changes of the control system. Perform online updates;

[0024]

[0025]

[0026] in, These are the time-varying parameters of the updated model; For the first Parameter vectors for various application scenarios; for The time control system is in the first The probability of various application scenarios; for The time control system is in the first The probability of various application scenarios; This represents the total number of application scenarios. For sensor observation noise, This is the actual sensor feedback value;

[0027] S32. Utilize the updated time-varying parameters Predict the state space of the device;

[0028]

[0029]

[0030]

[0031] in, For the predicted The state space of the time device; for The state space of the time device; for The control input of the device at any given time; This is the coupling state matrix; for Updated predictive control input matrix; Basic stiffness; Stiffness for the initial state; and The first and Moment of inertia of the device; The coupling coefficient between device 1 and device 2; The coupling coefficient between device 2 and device 1;

[0032] S33. Determine the global synchronization index based on the device's position synchronization error and speed synchronization error to construct the objective function;

[0033]

[0034]

[0035]

[0036]

[0037] in, This refers to the position synchronization error; For speed synchronization error; For global synchronization indicators; The objective function is... Speed ​​weights; For device connection topology; The threshold parameter for the global synchronization metric.

[0038] Preferably, step S4 specifically includes the following:

[0039] S41. Based on the predicted device state space and objective function, define the cost function for the entire state space;

[0040]

[0041]

[0042] in, The cost function for the entire empty state space; Dynamic weights used to adjust positional deviations between devices; and These represent the current state and the desired state of the device, respectively. To control input indicators; The step size for prediction; To synchronize weights; These are adaptive coefficients;

[0043] The constraint condition for the cost function of the entire state space is as follows.

[0044]

[0045] in, It's a speed limit; To synchronize the global position of the linked devices; , These are the weight matrices for state and control, respectively, used to balance tracking error and control input.

[0046] S42. Based on the cost function of the entire state space, obtain a control strategy that can adaptively and dynamically adjust the control parameters, and use the control strategy to dynamically adjust the control parameters of the corresponding equipment.

[0047]

[0048]

[0049] in, For adaptive control input; Initialize the input value for adaptive input; For the first The device is Time-based control input.

[0050] The beneficial effects of this invention are as follows: 1. The method of this invention utilizes the mutual influence between synchronously linked devices to establish an improved state-space mathematical model, introduces a multi-device coupling matrix relationship, and solves the spatial coordination problem of moving devices. 2. Taking into account communication delays and interference from other external factors, the method of this invention can identify the control parameters of devices in different application scenarios in real time, iteratively update the control input and optimize the control commands, minimize the problem of device synchronization due to position and speed deviations, improve the synchronization control accuracy between multiple devices, and ensure the smoothness and comfort of the performance. 3. The method of this invention has the characteristics of low cost, high precision, ease of implementation, adaptability to different device formations, and applicability to different performances. It can reduce the workload of operators due to device synchronization issues, while enhancing the real-time synchronous artistic effect of the performance. Attached Figure Description

[0051] Figure 1 This is a technical roadmap of the synchronization control method in the embodiments of the present invention. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0053] To address the disorder caused by asynchronous linkage of stage equipment, a synchronous control method for stage machinery with dynamically optimized state parameters is provided, specifically including the following:

[0054] I. Acquisition of Motion State Parameters

[0055] Obtain the motion status parameters of all synchronously linked devices.

[0056] Specifically: adopt synchronous linkage The position and velocity parameters of each device are used to construct a motion data set, which is represented as follows:

[0057]

[0058] The motion parameters of each device include a sum of position and velocity information, which can be expressed as follows:

[0059]

[0060] in, for A set of motion parameters for a synchronously linked device; A subset of location data; A subset of velocity data; For the first Location parameters of each device; For the first Speed ​​parameters of each device; , It is a set of positive integers.

[0061] II. Establishment of Coupled Mathematical State Model

[0062] An improved state-space mathematical model is obtained by using motion state parameters to perform synchronous motion on all devices, thereby obtaining a coupled mathematical state model.

[0063] Specifically, based on the system's physical characteristics, for the above-mentioned synchronous operation... An improved state-space mathematical model is used for each formation device. Based on the characteristics of each device, coupling relationships between devices and adaptive parameters are introduced to adapt to dynamic changes in the devices. This can be represented as follows:

[0064]

[0065]

[0066]

[0067]

[0068]

[0069] in, for The first derivative with respect to time; and The first and the The state vector of each device; For the first State transition matrix of each device; For the first Time-varying control input matrix for each device; For the first The equivalent stiffness of each device; For the first The torque of each device; The discrete time step; for The time-varying parameter at time t, and the influence factor of this parameter is: ; The moment of inertia of the equipment; The equivalent stiffness of the equipment; The torque of the equipment; For communication time delay; For the first Control status input for each device; To coordinate the first and the Coupled terms of relative motion between devices; For the first and the The coupling matrix of each device; The position coupling coefficient; This is the velocity coupling coefficient.

[0070] In traditional state spaces, parameters are statically acquired and dynamically used. This can lead to devices being unable to make timely adjustments during operation to obtain state values ​​that are closer to the real environment. This can further amplify the synchronization deviation between devices, causing them to operate out of sync with each other in terms of position and speed.

[0071] III. Parameter Update, State Prediction, and Objective Function Construction

[0072] The time-varying parameters in the coupled mathematical state model are updated online to predict the state space of the device. At the same time, a global synchronization index is defined based on the device's position synchronization error and speed synchronization error to construct the objective function.

[0073] 3.1 To adapt to different application scenarios where the equipment operates synchronously, the time-varying parameters of the coupled mathematical state model are... To enable online updates based on dynamic changes in the system, the preset model set is as follows: The model probabilities are updated as follows:

[0074]

[0075] The time-varying parameter update formula is as follows:

[0076]

[0077] in, These are the time-varying parameters of the updated model; For the first Parameter vectors for various application scenarios; for The time control system is in the first The probability of various application scenarios; for The time control system is in the first The probability of various application scenarios; This represents the total number of application scenarios. For sensor observation noise, This is the actual sensor feedback value.

[0078] 3.2 Next, the updated time-varying parameters are used to predict the state space of the device, expressed as:

[0079]

[0080]

[0081]

[0082] in, For the predicted The state space of the time device; for The state space of the time device; for The control input of the device at any given time; This is the coupling state matrix; for Updated predictive control input matrix; Basic stiffness; Stiffness for the initial state; and The first and Moment of inertia of the device; The coupling coefficient between device 1 and device 2; This is the coupling coefficient between device 2 and device 1.

[0083] 3.3. Define a global synchronization index based on the device's position synchronization error and speed synchronization error, and construct an objective function.

[0084] Let the position synchronization error be,

[0085]

[0086] The speed synchronization error is,

[0087]

[0088] The global synchronization metric is,

[0089]

[0090] Therefore, the objective function is constructed as follows:

[0091]

[0092] in, This refers to the position synchronization error; For speed synchronization error; For global synchronization indicators; The objective function is... Speed ​​weights; For device connection topology; The threshold parameter for the global synchronization metric.

[0093] IV. Control Strategy Acquisition

[0094] The cost function of the entire state space of the device is defined based on the predicted state space and objective function; the control strategy of the device is obtained based on the cost function of the entire state space of the device, and the control parameters of the device are adaptively and dynamically adjusted using the control strategy.

[0095] 4.1. Based on the predicted device state space and objective function, the total state space cost function is defined as follows:

[0096]

[0097]

[0098] in, The cost function for the entire empty state space; Dynamic weights used to adjust positional deviations between devices; and These represent the current state and the desired state of the device, respectively. To control input indicators; The step size for prediction; To synchronize weights; These are adaptive coefficients;

[0099] The constraints of the cost function are:

[0100]

[0101] in, For the predicted step size, It is a synchronization weight. It is an adaptive coefficient. It's a speed limit. To control the state input limit, This refers to the global position synchronization of linked devices. , It is the weight matrix for state and control, used to balance tracking error and control input.

[0102] 3.3 The control strategy can be obtained from the cost function of the entire state space, expressed as follows:

[0103]

[0104] This allows for adaptive and dynamic adjustment of control parameters for the corresponding devices using control strategies, ensuring system stability. It also resolves issues such as errors in synchronous linkage.

[0105]

[0106] in, For adaptive control input; Initialize the input value for adaptive input; For the first The device is Time-based control input.

[0107] In this embodiment, through the above steps, the system can use this method to solve the position and speed errors caused by coupling between devices and interference factors, improve the accuracy and stability of synchronous linkage, and maximize the artistic effect of stage performance.

[0108] By adopting the above-disclosed technical solution of this invention, the following beneficial effects are obtained:

[0109] This invention provides a method for the synchronous control of stage machinery with dynamically optimized state parameters. This method utilizes the mutual influence between synchronously linked devices to establish an improved state-space mathematical model, introducing a multi-device coupling matrix relationship to solve the spatial coordination problem of moving equipment. Taking into account communication delays and interference from other external factors, this method can identify the control parameters of the equipment in different application scenarios in real time, iteratively update the control input and optimize the control commands, minimizing the problem of asynchronous device linkage caused by position and speed deviations, improving the synchronous control accuracy between multiple devices, and ensuring the smoothness and comfort of the performance. This method is characterized by low cost, high precision, ease of implementation, adaptability to different equipment formations, and applicability to different performances. It can reduce the workload of operators due to equipment asynchrony while enhancing the real-time synchronous artistic effect of the performance.

[0110] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for synchronous control of stage machinery with dynamically optimized state parameters, characterized in that: Includes the following steps, S1. Obtain the motion status parameters of all synchronously linked devices; S2. Based on the motion state parameters, improve the state-space mathematical modeling of all synchronously moving devices to obtain a coupled mathematical state model; specifically, step S2 involves introducing coupling relationships between devices and adaptive parameters according to the characteristics of each device to adapt to the dynamic changes of the devices, in order to construct a coupled mathematical state model; the coupled mathematical state model is represented as follows. ； ； ； ； ； in, for The first derivative with respect to time; and The first and the The state vector of each device; For the first State transition matrix of each device; For the first Time-varying control input matrix for each device; For the first The equivalent stiffness of each device; For the first The torque of each device; The discrete time step; for The time-varying parameter at time t, and the influence factor of this parameter is: ; The moment of inertia of the equipment; The equivalent stiffness of the equipment; The torque of the equipment; For communication time delay; For the first Control status input for each device; To coordinate the first and the Coupled terms of relative motion between devices; For the first and the The coupling matrix of each device; The position coupling coefficient; The velocity coupling coefficient; S3. Update the time-varying parameters in the coupled mathematical state model online to predict the state space of the device; simultaneously, define a global synchronization index based on the device's position synchronization error and speed synchronization error to construct the objective function; step S3 specifically includes the following: S31. Adjust the time-varying parameters of the model based on the dynamic changes of the control system. Perform online updates; ； ； in, These are the time-varying parameters of the updated model; For the first Parameter vectors for various application scenarios; for The time control system is in the first The probability of various application scenarios; for The time control system is in the first The probability of various application scenarios; This represents the total number of application scenarios. For sensor observation noise, This is the actual sensor feedback value; S32. Utilize the updated time-varying parameters Predict the state space of the device; ； ； ； in, For the predicted The state space of the time device; for The state space of the time device; for The control input of the device at any given time; This is the coupling state matrix; for Updated predictive control input matrix; Basic stiffness; Stiffness for the initial state; and The first and Moment of inertia of the device; The coupling coefficient between device 1 and device 2; The coupling coefficient between device 2 and device 1; S33. Determine the global synchronization index based on the device's position synchronization error and speed synchronization error to construct the objective function; ； ； ； ； in, This refers to the position synchronization error; For speed synchronization error; For global synchronization indicators; The objective function is... Speed ​​weights; For device connection topology; The parameter threshold for the global synchronization indicator; S4. Define the cost function of the entire state space of the device based on the predicted device state space and objective function; obtain the control strategy of the device according to the cost function, and use the control strategy to adaptively and dynamically adjust the control parameters of the device.

2. The synchronous control method for stage machinery equipment with dynamic optimization of state parameters according to claim 1, characterized in that: In step S1, the motion parameters of each device include a description of the sum of position and velocity. ； in, for A set of motion parameters for a synchronously linked device; A subset of location data; A subset of velocity data; For the first Location parameters of each device; For the first Speed ​​parameters of each device; , It is a set of positive integers.

3. The synchronous control method for stage machinery equipment with dynamic optimization of state parameters according to claim 2, characterized in that: Step S4 specifically includes the following: S41. Based on the predicted device state space and objective function, define the cost function for the entire state space; ； ； in, The cost function for the entire empty state space; Dynamic weights used to adjust positional deviations between devices; and These represent the current state and the desired state of the device, respectively. To control input indicators; The step size for prediction; To synchronize weights; These are adaptive coefficients; The constraint condition for the cost function of the entire state space is as follows. ； in, It's a speed limit; To synchronize the global position of the linked devices; , These are the weight matrices for state and control, respectively, used to balance tracking error and control input. S42. Based on the cost function of the entire state space, obtain a control strategy that can adaptively and dynamically adjust the control parameters, and use the control strategy to dynamically adjust the control parameters of the corresponding equipment. ； ； in, For adaptive control input; Initialize the input value for adaptive input; For the first The device is Time-based control input.

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