Laser particle size analyzer assisted feeding quantity self-adaptive compensation control method

Abstract

This invention discloses a laser particle size analyzer-assisted adaptive compensation control method for feeding quantity, comprising: S1, acquiring the real-time laser particle size signal of the material and the dynamic characteristic parameters of the feeding actuator during the feeding process; S2, constructing a dual-channel collaborative control architecture including a main channel and a secondary channel; S3, implementing closed-loop control based on the real-time laser particle size signal through the main channel to dynamically adjust the feeding rate. This invention relates to the field of industrial automation control technology. This laser particle size analyzer-assisted adaptive compensation control method for feeding quantity achieves real-time acquisition of the laser particle size signal of the material and combines it with the dynamic characteristic parameters of the feeding actuator, enabling dynamic adjustment of the feeding rate, ensuring the accuracy and stability of the feeding process. By adopting a main-secondary channel collaborative control architecture and coupling and fusing the feeding adjustment amount through an adaptive weight fusion algorithm, it can adaptively compensate for fluctuations and errors during the feeding process, improving the system's adaptability.

Description

Technical Field

[0001] This invention relates to the field of industrial automation control, and more specifically, to a laser particle size analyzer-assisted adaptive compensation control method for feeding amount. Background Technology

[0002] In many industrial production processes, precise material feeding is crucial for product quality and production efficiency. Traditional feeding control systems typically rely on simple measuring instruments and preset feeding rates, lacking the ability to adjust in real time to changes in material properties. Especially when material properties such as particle size and flowability are greatly affected by environmental factors, traditional control methods often fail to meet production demands, leading to inaccurate feeding amounts, or even overfeeding or underfeeding.

[0003] In recent years, laser particle size analyzers, as non-contact, real-time instruments for detecting material particle size, have been increasingly applied in feeding process control. However, relying solely on particle size signals obtained from laser particle size analyzers for feeding adjustment still has certain limitations. Material particle size variations are influenced by various factors, and the feeding actuator itself possesses complex dynamic characteristics, such as response time, the relationship between flow rate and opening degree, and the correspondence between rotational speed and feed rate. These factors directly affect the stability and accuracy of the feeding rate.

[0004] Existing technologies typically use a single control channel to adjust the feeding amount, neglecting the complexity of the feeding process and the dynamic characteristics of the feeding actuator. Such systems have poor accuracy and robustness, cannot effectively cope with fluctuations in material particle size and lag in actuator response, and lack adaptive capabilities in the adjustment process. Summary of the Invention

[0005] The purpose of this invention is to provide a laser particle size analyzer-assisted adaptive compensation control method for feeding amount, which solves the problem that existing technologies generally use a single control channel to adjust the feeding amount, neglecting the complexity of the feeding process and the dynamic characteristics of the feeding actuator. Such systems have poor accuracy and robustness, cannot effectively cope with fluctuations in material particle size and the lag in the response of the actuator, and lack adaptive capability in the adjustment process.

[0006] This invention achieves the above objective through the following technical solution: a laser particle size analyzer-assisted adaptive compensation control method for feed rate, comprising:

[0007] S1. Acquire the real-time laser particle size signal of the material and the dynamic characteristic parameters of the feeding actuator during the feeding process;

[0008] S2. Construct a dual-channel collaborative control architecture that includes a main channel and a secondary channel;

[0009] S3. The feeding rate is dynamically adjusted by implementing closed-loop control based on real-time laser particle size signal through the main channel;

[0010] S4. Correction and compensation are performed based on dynamic characteristic parameters through the secondary channel to output the actuator adaptation adjustment amount;

[0011] S5. An adaptive weight fusion algorithm is used to couple and fuse the main channel feeding rate adjustment and the secondary channel adaptation adjustment to generate the final feeding control command.

[0012] S6. Send the final feeding control command to the feeding actuator to achieve adaptive compensation control of the feeding amount.

[0013] Furthermore, the real-time laser particle size signal is used to collect particle size distribution data of the material in the feeding channel through a non-contact particle size detection device;

[0014] Construct a laser particle size signal set by extracting at least three particle size feature parameters from the particle size distribution data;

[0015] The particle size characteristic parameters are selected from one or more of the following: particle size mean, particle size standard deviation, and characteristic particle size interval percentage.

[0016] Furthermore, the dynamic characteristic parameters are collected through multiple types of sensors, and the collected data includes:

[0017] At least four of the following: response time of the feeding actuator, relationship between opening degree and flow rate, relationship between rotation speed and feeding amount, and action delay time;

[0018] The collected parameters are organized into a dynamic characteristic parameter set.

[0019] Furthermore, it also includes parameter preprocessing steps:

[0020] Linear normalization is performed on all parameters in the laser particle size signal set and dynamic characteristic parameter set to eliminate the dimensional differences between different parameters.

[0021] The fluctuation amplitude of the laser particle size signal is calculated to characterize the real-time fluctuation of the material particle size.

[0022] Calculate the stability coefficient of the dynamic characteristics of the actuator to characterize the stability of the dynamic characteristics of the actuator.

[0023] Furthermore, the closed-loop control process of the main channel includes:

[0024] Preset target particle size values ​​for materials that match the requirements of the production process;

[0025] Calculate the deviation between the real-time laser particle size signal and the target particle size value;

[0026] A closed-loop control algorithm is used to calculate the deviation and generate the main channel feeding rate adjustment amount;

[0027] The closed-loop control algorithm includes an incremental proportional-integral-derivative control algorithm.

[0028] Furthermore, the correction and compensation process for the secondary channel includes:

[0029] A dynamic characteristic model of the feeding actuator is established, and the theoretical response value of the actuator is calculated based on the model and the feeding rate adjustment amount output by the main channel.

[0030] The difference between the theoretical response value and the actual maximum response value of the actuator is calculated. Combined with the delay compensation amount obtained based on the delay time of the actuator, the secondary channel adaptation adjustment amount is output through a preset correction formula to correct the main channel adjustment amount.

[0031] Furthermore, the execution process of the adaptive weight fusion algorithm includes:

[0032] Stability coefficient based on the fluctuation amplitude of laser particle size signal and the dynamic characteristics of actuator;

[0033] The weighting coefficients of the main channel and the secondary channel are dynamically determined, and the weighting coefficients satisfy the normalization constraint conditions.

[0034] The calculated weighting coefficients are subjected to amplitude limiting to prevent the weight of a single channel from being too high.

[0035] The adjustment values ​​of the two channels are coupled and fused based on the weighted coefficients after the amplitude limit to generate the initial final feeding control command.

[0036] Furthermore, this also includes saturation processing of the initial final feeding control command:

[0037] If the initial control command is greater than the maximum adjustment amount of the feeding actuator, then the maximum adjustment amount shall be taken as the final feeding control command;

[0038] If the initial control command is less than the minimum adjustment amount of the actuator, then the minimum adjustment amount is taken as the final feeding control command;

[0039] The maximum and minimum adjustment amounts are determined by the hardware parameters of the actuator.

[0040] Furthermore, it also includes a feedback correction step for the final feeding control command:

[0041] The actual feeding rate of the feeding actuator after receiving the control command is collected in real time. The target feeding rate is calculated based on the final feeding control command. The deviation between the actual feeding rate and the target feeding rate is calculated.

[0042] When the absolute value of the deviation exceeds the preset deviation threshold, the weight coefficients of the main and secondary channels are corrected a second time using a fuzzy control algorithm.

[0043] The final feeding control command is regenerated and sent based on the corrected weighting coefficients to achieve dynamic iterative correction.

[0044] Furthermore, in the fuzzy control algorithm, the correction coefficient is determined by a preset fuzzy rule table;

[0045] The input to the fuzzy rule table is a fuzzy subset of the deviation between the actual feeding rate and the target feeding rate, and the output is a fuzzy subset of the correction coefficients.

[0046] The fuzzy values ​​output from the fuzzy rule table are defuzzified using the centroid method to obtain the precise values ​​of the correction coefficients, which are then used for secondary correction of the weight coefficients.

[0047] The beneficial effects of this invention are as follows:

[0048] 1. By collecting the laser particle size signal of the material in real time and combining it with the dynamic characteristic parameters of the feeding actuator, the feeding rate can be dynamically adjusted to ensure the accuracy and stability of the feeding process.

[0049] 2. The main and auxiliary channels are coordinated and controlled. The feeding adjustment is coupled and fused through an adaptive weight fusion algorithm, which can adaptively compensate for fluctuations and errors in the feeding process and improve the adaptability of the system.

[0050] 3. By using a dynamic correction and compensation mechanism, the response characteristics of the feeding actuator are compensated in real time to make up for the errors caused by neglecting the dynamic characteristics of the actuator in traditional control methods, thereby improving the system's response speed and control accuracy.

[0051] 4. By real-time feedback correction of feeding control commands and secondary correction of fuzzy control algorithms, the robustness of the system to sudden changes and disturbances is effectively improved, making the feeding process more accurate and stable.

[0052] 5. By precisely controlling the amount of material added, material waste or product defects caused by improper material addition are reduced, thereby improving production efficiency and product quality and resulting in good economic benefits. Attached Figure Description

[0053] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0054] Figure 1 This is an overall flowchart of the present invention;

[0055] Figure 2This is a detailed diagram of the dual-channel collaborative control of the present invention;

[0056] Figure 3 This is the adaptive fusion and feedback correction diagram of the present invention. Detailed Implementation

[0057] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0058] Example 1:

[0059] Please see Figure 1-3 This invention provides a technical solution: a laser particle size analyzer-assisted adaptive compensation control method for feed amount, the method comprising:

[0060] S1. Acquire the real-time laser particle size signal of the material during the feeding process and collect the dynamic characteristic parameters of the feeding actuator;

[0061] Among them, the laser particle size signal is a signal that the laser particle size analyzer uses the principle of laser scattering to measure the size of material particles. When a laser beam shines on a material particle, scattering occurs. Particles of different sizes produce scattered light with different angles and intensities. By detecting the characteristic information of these scattered light beams and processing them through a specific algorithm, a signal representing the particle size distribution of the material is obtained. This signal can reflect the size of the material particles in real time during the feeding process. The feeding actuator is the device responsible for actually performing the feeding action in the feeding system, such as a screw feeder or a vibrating feeder. The dynamic characteristic parameters refer to the characteristic parameters exhibited by the feeding actuator during dynamic operation. They reflect the mechanism's responsiveness to input signals and the changing patterns during its own motion.

[0062] S2. Construct a dual-channel collaborative control architecture for laser particle size signal and feeding actuator, which includes a main channel and a secondary channel;

[0063] The dual-channel collaborative control architecture divides the control process into two cooperating channels. In this method, these two channels are the main channel and the secondary channel, each undertaking different control tasks but cooperating with each other to achieve precise control of the feeding amount. This architecture can fully leverage the advantages of different control strategies and improve the system's control performance and robustness. The main channel, in the dual-channel collaborative control architecture, is primarily responsible for performing core control tasks based on the main control criteria. It dynamically adjusts the feeding rate directly according to the particle size of the material and is the key part for achieving initial control of the feeding amount. The secondary channel is another channel that works in cooperation with the main channel. In this method, it mainly performs correction and compensation based on the dynamic characteristic parameters of the feeding actuator. Its role is to further optimize the control results of the main channel, consider the performance characteristics of the feeding actuator itself, and output the actuator's adaptive adjustment amount to improve the accuracy and stability of the entire feeding control system.

[0064] S3. The feeding rate is dynamically adjusted by using closed-loop control based on real-time laser particle size signal through the main channel;

[0065] Closed-loop control is a control method that feeds the system's output back to the input, compares it with the given input signal, and adjusts the system's control input based on the error signal, thereby making the system's output as close as possible to the given input signal. In this method, the main channel uses real-time laser particle size signal for closed-loop control, which can dynamically adjust the feeding rate according to the real-time changes in material particle size to achieve effective control of material particle size. The dynamic adjustment of the feeding rate is based on the real-time acquired laser particle size signal and other relevant factors, changing the feeding speed of the feeding actuator in real time. When the detected material particle size is too large, the feeding rate is appropriately reduced; when the material particle size is too small, the feeding rate is appropriately increased to ensure that the particle size of the fed material meets the requirements.

[0066] S4. The auxiliary channel performs correction and compensation based on the dynamic characteristic parameters of the feeding actuator, and outputs the actuator adaptation adjustment amount;

[0067] The correction and compensation process further adjusts and optimizes the control results of the main channel. Since the main channel is primarily controlled based on laser particle size signals, it may not fully consider the impact of the dynamic characteristics of the feeding actuator on the feeding amount. The secondary channel performs correction and compensation based on the dynamic characteristic parameters of the feeding actuator, outputting an actuator adaptation adjustment amount to eliminate or reduce this impact and make the feeding amount more accurate. The actuator adaptation adjustment amount is calculated by the secondary channel based on the dynamic characteristic parameters of the feeding actuator and is used to adjust the operating state of the feeding actuator. This adjustment amount aims to enable the feeding actuator to better adapt to various changes in the actual feeding process and ensure that the feeding amount is controlled as expected. For example, if the feeding actuator has problems such as large inertia and slow response, the adaptation adjustment amount can pre-adjust the actuator in advance so that it can perform the feeding operation more timely and accurately.

[0068] S5. Based on the adaptive weight fusion algorithm, the feeding rate adjustment of the main channel and the adaptive adjustment of the secondary channel are coupled and fused to generate the final feeding control command.

[0069] Among them, the adaptive weight fusion algorithm is a fusion algorithm that can automatically adjust the weight values ​​of different input signals according to the real-time status and operation of the system. Through this algorithm, the weights of the main and secondary channel control quantities can be dynamically allocated according to the importance and effectiveness of the control quantities at different times and under different operating conditions. Then, the weighted control quantities are coupled and fused to generate the final feeding control command. This can give full play to the advantages of the main and secondary channels and improve the performance and adaptability of the entire control system. Coupling fusion is to combine two or more different signals or control quantities according to certain rules and algorithms to form a comprehensive control command. In this method, the feeding rate adjustment quantity of the main channel and the adaptive adjustment quantity of the secondary channel are coupled and fused through the adaptive weight fusion algorithm so that they complement each other and work together to generate a more accurate and reasonable final feeding control command to achieve precise control of the feeding quantity.

[0070] S6. Send the final feeding control command to the feeding actuator to achieve adaptive compensation control of the feeding amount;

[0071] The final feeding control command is generated by coupling and fusing the control quantities of the main channel and the secondary channel through an adaptive weight fusion algorithm. This command is used to control the feeding actuator and includes detailed information such as feeding rate and feeding time. The feeding actuator performs the actual feeding operation based on this command, thereby achieving adaptive compensation control of the feeding amount. This ensures that the feeding process can be dynamically adjusted according to the particle size of the material and the characteristics of the feeding actuator to achieve the expected feeding effect. Adaptive compensation control is a method that can automatically adjust the control strategy and parameters according to real-time changes in the system and external disturbances to achieve precise control of the system output. In this method, by acquiring the laser particle size signal and the dynamic characteristic parameters of the feeding actuator in real time, and utilizing a dual-channel collaborative control architecture and an adaptive weight fusion algorithm, the feeding control system can automatically adapt to changes in material particle size and the characteristics of the feeding actuator, performing real-time and accurate compensation control of the feeding amount, thus improving the stability and accuracy of the feeding process.

[0072] It should be noted that during use, by utilizing real-time laser particle size signals, the main channel closed-loop control can dynamically adjust the feeding rate according to the material particle size, respond promptly to particle size changes, ensure that the material particle size meets the requirements, and improve product quality stability. The secondary channel is based on the dynamic characteristic parameters of the feeding actuator for correction and compensation, and outputs an adaptive adjustment amount. It takes into account the influence of the actuator's own characteristics on feeding, eliminates errors caused by its inertia and slow response, and improves feeding accuracy. The adaptive weight fusion algorithm couples and fuses the adjustment amounts of the main and secondary channels, and can automatically allocate weights according to different working conditions, giving full play to the advantages of the two channels and generating more accurate final feeding control commands. The commands are sent to the actuator to achieve adaptive compensation control, so that the entire feeding process can be automatically adjusted according to real-time conditions, enhancing the system's adaptability and robustness, reducing manual intervention costs, and improving production efficiency and economic benefits.

[0073] In one embodiment, the real-time laser particle size signal of the material during the feeding process is acquired, and the dynamic characteristic parameters of the feeding actuator are collected, including:

[0074] The process of acquiring laser particle size signals is as follows: a laser diffraction particle size analyzer is used to perform non-contact detection of the material in the feeding channel, and the particle size distribution histogram data of the material is collected in real time. The particle size mean, particle size standard deviation, and proportion of characteristic particle size intervals are extracted from the distribution data as the core laser particle size signals, and a laser particle size signal set is constructed. ,in The number of particle size characteristic parameters to be selected is determined according to the actual particle size control requirements of the materials produced, and is generally 3-8.

[0075] The process of acquiring the dynamic characteristic parameters of the feeding actuator is as follows: Valve response time, valve opening-flow rate curve, screw speed-feed rate relationship, and actuator action delay time are acquired using displacement sensors, speed sensors, and flow sensors, respectively. These parameters are then compiled into a dynamic characteristic parameter set. ,in Valve response time This is the set of fitting coefficients for the valve opening-flow rate curve. This is the ratio coefficient between screw speed and feed rate. Delay time for the implementing agency;

[0076] To eliminate the influence of dimensional differences between different parameters on subsequent control calculations, the laser particle size signal set was... and dynamic characteristic parameter set All parameters are linearly normalized, and the normalization expression is as follows:

[0077]

[0078] in, These are the original parameter values. This is the minimum value of the parameter under production conditions. This is the maximum value of the parameter under production conditions;

[0079] Fluctuation amplitude of laser particle size signal The specific calculation process is as follows: First, calculate the mean value of the laser particle size signal within the continuous sampling period. ,in The set number of sampling points is typically 50-200. For the first The normalized value of the laser particle size signal from the next sample is used, and then the standard deviation of the laser particle size signal is calculated based on this mean, which is used as the fluctuation amplitude. This value is used to characterize the real-time fluctuation of material particle size;

[0080] Stability coefficient of dynamic characteristics of actuator The specific calculation process is as follows: based on the dynamic characteristic parameter set Calculate the mean of the parameter set. Calculate the relative deviation of each dynamic characteristic parameter from the mean, and finally obtain the stability coefficient by averaging:

[0081]

[0082] The closer the value of this coefficient is to 1, the more stable the dynamic characteristics of the actuator are. The value range is (0,1).

[0083] This design utilizes a laser diffraction particle size analyzer for non-contact material detection, extracting key particle size characteristics to construct a signal set. Multiple sensors then collect and aggregate actuator parameters, normalizing these parameters and calculating signal fluctuation amplitude and actuator stability coefficients. This comprehensive and accurate acquisition of key data provides a reliable basis for subsequent control. Normalization eliminates dimensional differences, allowing different parameters to be calculated under a unified standard. The calculation of fluctuation amplitude and stability coefficients directly reflects the state of the material and actuator, facilitating flexible adjustments to control strategies based on actual conditions and improving control accuracy and adaptability.

[0084] In one embodiment, the feeding rate is dynamically adjusted through closed-loop control of the main channel based on real-time laser particle size signals, including:

[0085] Preset target particle size values ​​for materials according to production process requirements. The target value is determined by process engineers based on product quality standards and entered into the control system. Subsequently, the deviation between the real-time laser particle size signal and the target value is calculated. Among them, the deviation Each dimension component Each component corresponds to the deviation value of a granularity feature parameter;

[0086] To improve the response speed and anti-interference capability of closed-loop control, an incremental proportional-integral-derivative (PID) control algorithm is adopted to control the deviation. Perform calculations to generate the main channel feeding rate adjustment amount. The formula for calculating incremental PID is:

[0087] ,

[0088] ,

[0089] in, This is the proportionality coefficient. The integral coefficient is... These are the differential coefficients, and the three factors were determined using the Ziegler-Nichols method during on-site testing. At the current sampling time, For the previous sampling time, For the first two sampling times, This is the adjustment amount of the main channel feeding rate at the current moment. This is the adjustment amount of the main channel feeding rate at the previous moment. This represents the increment of the adjustment amount at the current moment. The physical meaning of this adjustment amount is the percentage adjustment value of the feeding rate, and the value range is [-30%, 30%].

[0090] This design presets a target particle size value for the material, calculates the deviation from the real-time signal, and uses an incremental PID algorithm to calculate the deviation, generating an adjustment amount for the main channel feeding rate. The preset target value clearly defines the control direction, ensuring that product quality has a standard to follow. The incremental PID algorithm has a fast response speed and strong anti-interference ability, and can adjust the feeding rate in a timely manner according to the particle size deviation, effectively reducing the gap between the actual particle size and the target value, ensuring the stability of the material particle size, and improving the consistency of product quality.

[0091] In one embodiment, the actuator is adjusted and compensated based on the dynamic characteristic parameters of the feeding actuator via a secondary channel, and the resulting adjustment amount is output, including:

[0092] Establish a dynamic characteristic model of the feeding actuator based on the dynamic characteristic parameter set. The valve's response characteristics were curve-fitted using the least squares method, resulting in the following valve response curve:

[0093]

[0094] in This represents the actual flow rate of the valve. Valve response time , For valve opening, The fitting coefficients are obtained by fitting experimental data of the valve's step response.

[0095] By fitting the feeding characteristics of the screw, the screw speed characteristic equation is obtained as follows:

[0096]

[0097] in, This represents the actual feed rate of the screw. screw speed , The fitting coefficients were determined through a screw rotation speed-feed rate calibration experiment.

[0098] Adjust the amount of feed rate based on the output of the main channel. The theoretical response value of the actuator is calculated based on the above dynamic characteristic model. ,in The weighting coefficients for valves and screws are determined based on the type of actuator.

[0099] If the feeding system primarily uses valve-controlled flow, then Take a value of 0.6-0.9, and primarily control the quantity using the screw. Take a value between 0.1 and 0.4;

[0100] Calculate the theoretical response value and the actual maximum response value of the actuator. The difference This difference is used to characterize the load state of the actuator, and the delay compensation amount is calculated based on the actuator's delay time. ,in The delay compensation coefficient is determined experimentally and ranges from 0.8 to 1.2.

[0101] Based on difference and delay compensation amount Calculate the adjustment amount of the secondary channel adaptation. The main channel adjustment amount is corrected using the following formula:

[0102]

[0103] in, , , , , The characteristic adaptation coefficients were calibrated through multiple orthogonal experiments combined with the gradient descent method. The calibration objective was to ensure that the root mean square error between the actual and theoretical response values ​​of the actuator was less than a preset threshold. , This ensures that the correction and compensation of the secondary channel can accurately match the actual characteristics of the actuator.

[0104] This design establishes a dynamic characteristic model to fit the characteristics of the valve and screw, calculates the theoretical response value, and then calculates the adaptive adjustment amount based on the load state and delay time. The established model can accurately grasp the characteristics of the actuator, providing theoretical support for correction and compensation. By calculating the difference between the theoretical response value and the actual maximum response value, as well as the delay compensation amount, the adaptive adjustment amount can be accurately calculated, effectively correcting the main channel adjustment amount, making the feeding control more in line with the actual actuator, and reducing feeding errors caused by the characteristics of the actuator.

[0105] In one embodiment, based on an adaptive weight fusion algorithm, the feeding rate adjustment of the main channel and the adaptive adjustment of the secondary channel are coupled and fused to generate the final feeding control command, including:

[0106] An adaptive weight calculation model is constructed based on the fluctuation amplitude of the laser particle size signal. Stability coefficient of dynamic characteristics of actuator Dynamically adjust the weighting coefficients of the main and secondary channels. and The two weight coefficients satisfy the normalization constraint. This is to ensure the reasonable allocation of control command weights;

[0107] The specific formula for calculating the weighting coefficient is as follows:

[0108]

[0109]

[0110] The design logic of this formula is as follows: when the fluctuation amplitude of the laser particle size signal is large, the weight of the secondary channel is increased to weaken the impact of particle size fluctuation on control;

[0111] When the actuator has high stability, the weight of the main channel is increased to enhance the precise control of granular feedback;

[0112] To prevent the control system from becoming unstable due to an excessively high weighting of a single channel, the calculated weighting coefficients are subject to amplitude limiting, with the limiting range set as follows: , This ensures that both channels can participate in control calculations.

[0113] After weight allocation is completed, the final feeding control command is generated through weight coupling and fusion. The formula is:

[0114] ;

[0115] Meanwhile, to prevent control commands from exceeding the physical limits of the feeding actuator, the final feeding control command is... Perform saturation treatment;

[0116] like Then take ;

[0117] like Then take ,in This is the maximum adjustment range of the feeding actuator. The minimum adjustment amount of the feeding actuator is determined by the hardware parameters of the actuator.

[0118] This design constructs an adaptive weight calculation model, dynamically adjusting the weights based on the fluctuation amplitude of the laser particle size signal and the stability coefficient of the actuator. After amplitude limiting, the system is coupled and fused to generate commands and then saturated. The adaptive weight calculation model can dynamically allocate the weights of the main and secondary channels according to the actual situation, making the control more flexible and reasonable. Amplitude limiting avoids the system from becoming unstable due to the excessive weight of a single channel, and saturation prevents the commands from exceeding the limits of the actuator, ensuring the stable operation of the system and improving the reliability and stability of the feeding control.

[0119] In one embodiment, a feedback correction step for the final feeding control command is further included to improve the accuracy of the feeding amount control, specifically:

[0120]

[0121] The control commands received by the feeding actuator are collected in real time by flow sensors and speed sensors. Actual feeding rate after And according to the final control command Calculate the target feeding rate Then, the deviation between the actual feeding rate and the target feeding rate was calculated. ;

[0122] Set deviation threshold This threshold is determined based on the required production precision, and is generally taken as 1%-5% of the target feeding rate;

[0123] when When this occurs, it indicates a significant deviation between the actual action of the actuator and the control command. In this case, a fuzzy control algorithm is used to adjust the weighting coefficients. and A second correction is performed, and the correction formula is as follows:

[0124]

[0125]

[0126] in, This is the fuzzy control correction coefficient, which is based on the deviation. The size is determined by a preset fuzzy rule table, the input of which is... Fuzzy subsets:

[0127]

[0128] The output is Fuzzy subsets:

[0129]

[0130] The fuzzy output is defuzzified using the centroid method to obtain... The precise value;

[0131] Use the corrected weighting coefficients and Recalculate the final feeding control command The corrected control commands are sent to the feeding actuator in real time to achieve dynamic iterative correction of the control commands.

[0132] This design allows for real-time acquisition of the actual and target feeding rates and calculation of the deviation. When the deviation exceeds a threshold, the weight coefficients are corrected a second time using a fuzzy control algorithm. The corrected control commands are then recalculated and sent. The feedback correction mechanism can detect deviations between the actuator's actions and commands in real time and make timely adjustments. The fuzzy control algorithm can flexibly adjust the weights according to the magnitude of the deviation, making the control commands more aligned with actual needs. Through dynamic iterative correction, the feeding control is continuously optimized, effectively improving the accuracy of feeding quantity control and meeting the requirements of high-precision production.

[0133] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A laser particle size analyzer-assisted adaptive compensation control method for feed rate, characterized in that, include: S1. Acquire the real-time laser particle size signal of the material and the dynamic characteristic parameters of the feeding actuator during the feeding process; S2. Construct a dual-channel collaborative control architecture that includes a main channel and a secondary channel; S3. The feeding rate is dynamically adjusted by implementing closed-loop control based on real-time laser particle size signal through the main channel; S4. Correction and compensation are performed based on dynamic characteristic parameters through the secondary channel to output the actuator adaptation adjustment amount; S5. An adaptive weight fusion algorithm is used to couple and fuse the main channel feeding rate adjustment and the secondary channel adaptation adjustment to generate the final feeding control command. S6. Send the final feeding control command to the feeding actuator to achieve adaptive compensation control of the feeding amount.

2. The laser particle size analyzer-assisted adaptive compensation control method for feed quantity according to claim 1, characterized in that: The real-time laser particle size signal is collected by a non-contact particle size detection device to obtain particle size distribution data of the material in the feeding channel; Construct a laser particle size signal set by extracting at least three particle size feature parameters from the particle size distribution data; The particle size characteristic parameters are selected from one or more of the following: particle size mean, particle size standard deviation, and characteristic particle size interval percentage.

3. The laser particle size analyzer-assisted adaptive compensation control method for feed amount according to claim 1, characterized in that, The dynamic characteristic parameters are collected through multiple types of sensors, and the collected data includes: At least four of the following: response time of the feeding actuator, relationship between opening degree and flow rate, relationship between rotation speed and feeding amount, and action delay time; The collected parameters are organized into a dynamic characteristic parameter set.

4. The laser particle size analyzer-assisted adaptive compensation control method for feed amount according to claim 1, characterized in that, It also includes parameter preprocessing steps: Linear normalization is performed on all parameters in the laser particle size signal set and dynamic characteristic parameter set to eliminate the dimensional differences between different parameters. The fluctuation amplitude of the laser particle size signal is calculated to characterize the real-time fluctuation of the material particle size. Calculate the stability coefficient of the dynamic characteristics of the actuator to characterize the stability of the dynamic characteristics of the actuator.

5. The laser particle size analyzer-assisted adaptive compensation control method for feed amount according to claim 1, characterized in that, The closed-loop control process of the main channel includes: Preset target particle size values ​​for materials that match the requirements of the production process; Calculate the deviation between the real-time laser particle size signal and the target particle size value; A closed-loop control algorithm is used to calculate the deviation and generate the main channel feeding rate adjustment amount; The closed-loop control algorithm includes an incremental proportional-integral-derivative control algorithm.

6. The laser particle size analyzer-assisted adaptive compensation control method for feed amount according to claim 1, characterized in that, The correction and compensation process for the secondary channel includes: A dynamic characteristic model of the feeding actuator is established, and the theoretical response value of the actuator is calculated based on the model and the feeding rate adjustment amount output by the main channel. The difference between the theoretical response value and the actual maximum response value of the actuator is calculated. Combined with the delay compensation amount obtained based on the delay time of the actuator, the secondary channel adaptation adjustment amount is output through a preset correction formula to correct the main channel adjustment amount.

7. The laser particle size analyzer-assisted adaptive compensation control method for feed rate according to claim 1, characterized in that, The execution process of the adaptive weight fusion algorithm includes: Stability coefficient based on the fluctuation amplitude of laser particle size signal and the dynamic characteristics of actuator; The weighting coefficients of the main channel and the secondary channel are dynamically determined, and the weighting coefficients satisfy the normalization constraint conditions. The calculated weighting coefficients are subjected to amplitude limiting to prevent the weight of a single channel from being too high. The adjustment values ​​of the two channels are coupled and fused based on the weighted coefficients after the amplitude limit to generate the initial final feeding control command.

8. The laser particle size analyzer-assisted adaptive compensation control method for feed amount according to claim 7, characterized in that, This also includes saturation processing of the initial final feeding control command: If the initial control command is greater than the maximum adjustment amount of the feeding actuator, then the maximum adjustment amount shall be taken as the final feeding control command; If the initial control command is less than the minimum adjustment amount of the actuator, then the minimum adjustment amount is taken as the final feeding control command. The maximum and minimum adjustment amounts are determined by the hardware parameters of the actuator.

9. The laser particle size analyzer-assisted adaptive compensation control method for feed amount according to claim 1, characterized in that, It also includes a feedback correction step for the final feeding control command: The actual feeding rate of the feeding actuator after receiving the control command is collected in real time. The target feeding rate is calculated based on the final feeding control command. The deviation between the actual feeding rate and the target feeding rate is calculated. When the absolute value of the deviation exceeds the preset deviation threshold, the weight coefficients of the main and secondary channels are corrected a second time using a fuzzy control algorithm. The final feeding control command is regenerated and sent based on the corrected weighting coefficients to achieve dynamic iterative correction.

10. The laser particle size analyzer-assisted adaptive compensation control method for feed amount according to claim 9, characterized in that, In the fuzzy control algorithm, the correction coefficient is determined by a preset fuzzy rule table; The input to the fuzzy rule table is a fuzzy subset of the deviation between the actual feeding rate and the target feeding rate, and the output is a fuzzy subset of the correction coefficients. The fuzzy values ​​output from the fuzzy rule table are defuzzified using the centroid method to obtain the precise values ​​of the correction coefficients, which are then used for secondary correction of the weight coefficients.

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