An electrical control system, method, and medium for a milling robot

Abstract

The application relates to an electrical control system, method and medium of a milling robot, and relates to the technical field of electrical control; the electrical control system of the milling robot comprises a storage and preservation module, which is used for acquiring real-time storage data of brown rice in a storage tank and adjusting to a preset storage environment data interval; a quantitative transmission module, which is used for stage-wise quantitative rice supply from the storage tank according to user demand to obtain a target rice quantity; a milling and bran removal module, which is used for milling brown rice according to the target rice quantity and a whiteness level to obtain milled rice; an intelligent rice cooking module, which is used for completing water addition and milled rice steaming according to a steaming recipe; and a total control module, which is used for analyzing user demand to extract the target rice quantity, identifying rice species and regulating a steaming progress in combination with a steaming curve; through the cooperation of the multiple modules, the whole-process automation of brown rice storage and preservation, on-demand quantitative milling and intelligent steaming is realized, and the rice quality freshness and cooking efficiency are improved.

Description

Technical Field

[0001] This application relates to the field of electrical control technology, and in particular to an electrical control system, method and medium for a grinding and cooking robot. Background Technology

[0002] The electrical control system of rice milling and cooking robots typically uses a high-performance microcontroller (such as the STM32 series) as the main control unit, achieving full-process automation by integrating various sensors and actuators. In the rice milling stage, the system uses a high-precision stepper motor to drive the rice milling mechanism, and combines real-time feedback from the weighing module to achieve precise control of the amount of rice fed and the weight measurement. In the cooking stage, the system monitors the water temperature and pressure inside the pot in real time through temperature sensors, and uses bidirectional thyristors in conjunction with a PID (proportional-integral-derivative) control algorithm to achieve precise adjustment of the heating element power, thereby ensuring that the water temperature changes according to the preset curve and completing the soaking, heating, boiling, and simmering processes. At the same time, the system integrates a flow sensor for water volume detection, a microswitch for detecting the pot status, and a DC motor drive module for material conveying. In terms of human-machine interaction, the control system supports parameter setting and status monitoring through a touch screen or mobile device application (APP), and connects to a cloud platform with the help of Internet of Things (IoT) technology to achieve remote control and data management.

[0003] Existing patents disclose a control system and method for an industrial rice cooker. The method includes: acquiring rice cooking temperature reference curves for different varieties of rice; real-time monitoring of the pot bottom heating temperature, determining the temperature error between the pot bottom heating temperature at each moment and the corresponding desired temperature, wherein the desired temperature is determined based on the rice cooking temperature reference curves; controlling the speed at which a transmission device transports the rice cooker to the rice cooker module based on the temperature error; and controlling the opening of the natural gas regulating valve using a PID fuzzy control algorithm based on the temperature error to achieve closed-loop regulation of the pot bottom heating temperature. This invention determines different rice cooking temperature reference curves for different rice varieties, monitors the pot bottom heating temperature, and uses an intelligent control algorithm to adjust the opening of the automatic natural gas regulating valve, achieving closed-loop control of the pot bottom heating temperature and ensuring efficient and energy-saving industrial rice cooker cooking control.

[0004] The existing technical solutions mentioned above have the following drawbacks: 1. The existing system uses a common motor to control the rice supply and relies on a delayed motor stop. However, the motor has a large inertia after it stops, resulting in low rice supply accuracy. Furthermore, it is impossible to obtain the specific speed and number of revolutions of the motor in real time, so the improvement in accuracy is still limited. 2. The existing system's preservation, milling, proportioning, and cooking of brown rice are mostly decentralized. Each stage consumes a lot of the user's time and cannot guarantee that the user will get the cooked rice with the desired taste. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this application is to provide an electrical control system, method, and medium for a rice milling robot. Through multi-module collaboration, the entire process of brown rice storage and preservation, on-demand quantitative milling, and intelligent cooking is automated, thereby improving rice freshness, cooking efficiency, and user experience consistency.

[0006] This was achieved using the following technical solutions: In a first aspect, this application provides an electrical control system for a grinding and cooking robot, comprising: The storage and preservation module has its signal input terminal connected to the first signal terminal of the main control module and its signal output terminal connected to the signal input terminal of the quantitative transmission module. It is used to acquire real-time storage data of brown rice in the rice storage box and adjust it to the preset storage environment data range. The quantitative transmission module has its signal input end connected to the second signal end of the main control module and its signal output end connected to the signal input end of the milling and chaff removal module. It is used to supply rice from the rice storage box in stages according to user needs to obtain the target amount of rice. The milling and chaff removal module has its signal input terminal connected to the third signal terminal of the main control module and its signal output terminal connected to the signal input terminal of the intelligent rice cooking module. It is used to mill brown rice according to the target rice quantity and whiteness level to obtain refined rice. The intelligent rice cooker module has its signal input terminal connected to the fourth signal terminal of the main control module. It is used to add water according to the cooking recipe and to complete the cooking of refined rice. The main control module is used to analyze user requirements to extract the target amount of rice, identify the type of rice, and adjust the cooking progress in conjunction with the cooking curve.

[0007] By adopting the above technical solutions, based on closed-loop control and precise metering algorithms, the entire process of brown rice storage and preservation, on-demand quantitative milling and intelligent cooking is automated through multi-module collaboration, which significantly improves rice freshness, cooking efficiency and user experience consistency.

[0008] Furthermore, the storage and preservation module includes: The environmental data acquisition unit is used to collect environmental information on the brown rice stored in the rice storage box to obtain real-time storage data, including temperature, humidity and ventilation. The data cleaning unit is used to fill in missing values ​​and remove duplicate values ​​from the real-time stored data according to the collection timestamp, so as to obtain standard stored data. The data correction unit is used to correct the standard storage data based on a preset storage environment data range and a PID algorithm to maintain the stability of the storage environment. The rice quantity monitoring unit is used to monitor the amount of brown rice stored based on a preset rice quantity warning line and the amount used in a single use, determine the remaining rice quantity, and generate a rice quantity replenishment notification. The PID algorithm is as follows: M n =MP n +MI n +MD n ; Among them, M n MP is the calculated value of the loop output at sampling time n. n MI is the proportional term value of the loop output at sampling time n. n The integral term value of the sampling time loop output, MD n This is the differential value of the loop output at sampling time n; MP n =K C *(SP n -PV n ); Among them, K C For loop gain, SP n PV is the set value at sampling time n. n The value of the process variable at sampling time n; MI n =K C *T S / T I *(SP n -PV n )+MX; Among them, T S T is the loop sampling time. I Where MX is the integration time, and MX is the value of the integral term at sampling time n-1; MD n =K C *T D / T S *((SP n -PV n )-(SP n-1 -PV n-1 )); If SP n =SP n-1 MD n =K C *T D / T S *(PV n-1 -PV n ); Among them, T D SP is the differential period of the loop. n-1 PV is the set value at sampling time n-1. n-1 The value of the process variable at sampling time n-1.

[0009] By adopting the above technical solution, based on data cleaning and PID closed-loop control algorithm, multi-source environmental parameters are standardized and dynamically adjusted to a preset stable range. At the same time, combined with rice quantity monitoring and early warning mechanism, intelligent inventory management is realized, which improves the freshness stability and inventory response time of brown rice storage.

[0010] Furthermore, the quantitative transmission module includes: The requirement analysis unit is used to analyze user requirements and extract the target rice quantity and required rice type; The equipment analysis unit is used to collect data from the actuator according to the required rice type to obtain the actuator's operating data; The dynamic transmission unit is used to interpret the stage control signals according to the equipment type to obtain the stage execution parameters and stage transition timestamps; The weighing and detection unit is used to correct the mechanism's operating data according to the stage execution parameters, obtain the initial operating data, and collect the initial meter measurement; The cutoff compensation unit is used to switch the initial operation data according to the stage transition timestamp and collect the final meter reading. If the absolute difference between the final amount of rice and the target amount of rice is within the preset tolerance range, and the absolute difference between the initial amount of rice and the initial rice threshold is within the tolerance range, then the rice supply is considered successful and the current stage execution parameters are the optimal solution. If not, the execution parameters for the current stage will be adjusted to obtain the target meter quantity.

[0011] By adopting the above technical solution, based on demand analysis and closed-loop feedback control algorithm, and through phased execution and real-time weighing detection, combined with deviation compensation and parameter self-correction mechanism, precise meter feeding is achieved, which significantly improves the accuracy, adaptability and execution efficiency of quantitative transmission.

[0012] Furthermore, the overall control module includes: The rice type identification unit is used to collect multi-dimensional data on brown rice, obtain multi-dimensional data on brown rice, and make a comprehensive judgment by combining it with a preset rice type identification model to output the type of brown rice. The verification and judgment unit is used to judge the target amount of rice and the remaining amount of rice based on the required type of rice. If the remaining rice quantity is greater than the target rice quantity, it indicates that the rice quantity is sufficient, and a phased control signal is generated in conjunction with the phased rice supply mechanism. If not, the user will be prompted that there is not enough rice left, and other types of rice will be recommended or the amount of rice to be taken will be reduced based on the similarity of the rice types. The intelligent proportioning unit is used to match the proportion of polished rice according to the type of brown rice and the target amount of rice, and to calculate the target amount of water. The rice milling synchronization unit is used to calculate the total amount of brown rice based on the rice yield and the target amount of rice, and to determine the milling strategy. The milling determination unit is used to optimize the milling strategy based on the whiteness level and the total amount of brown rice, and generate milling parameter curves. The recipe generation unit is used to classify historical cooking data according to brown rice type and cooking altitude to obtain single-category cooking data; The formula optimization unit is used to optimize the cooking rice data based on the required rice type and target rice quantity to obtain the cooking formula and generate the cooking curve. The parameter analysis unit is used to divide the cooking curve into stages and obtain the cooking stage parameters. The signal conversion unit is used to convert the grinding parameter curve, target water volume and cooking stage parameters according to the equipment type to obtain grinding signal, water replenishment signal and cooking stage signal; The signal distribution unit is used to allocate grinding signals, water replenishment signals, and steaming / cooking signals according to the cooking process, and to determine the signal implementation timestamp; The process control unit is used to perform staged processing of brown rice based on the signal implementation timestamp, collect stage data of brown rice, and control the cooking progress in combination with stage standard data.

[0013] By adopting the above technical solutions, intelligent rice type determination is achieved based on multimodal recognition and data fusion algorithms. The milling, water volume and cooking parameters are generated through demand matching and optimization calculations. Signal conversion and closed-loop control technologies are used to precisely control the entire cooking process, which significantly improves the equipment's adaptability, the level of personalized cooking and the stability of the process.

[0014] Furthermore, the process control unit includes: The timing judgment layer is used to perform timing analysis on the cooking process, extract the cooking stages, and determine the parallel cooking timing segments. The time allocation layer is used to pre-allocate time periods for the cooking stage and combine them with signal timestamps to obtain stage transition nodes; The timing correction layer is used to correct the stage transition nodes according to the parallel cooking timing segment to obtain the corrected stage nodes; The stage monitoring layer is used to monitor brown rice according to the correction stage nodes and collect brown rice stage data; The stage simulation layer is used to collect data from cooking equipment and combine it with the equipment wear curve to construct a twin, thereby obtaining a virtual equipment. The stage nodes are then simulated and evolved to obtain the stage standard data range. The progress control layer is used to compare and judge the brown rice stage data based on the stage standard data. If all the brown rice stage data are within the standard stage data range, it indicates that the current signal implementation timestamp is accurate, there is no need to adjust the execution time, and the cooking progress is displayed. If not, then the current signal timestamp is compensated in stages to obtain the corrected timestamp, and the execution time is globally corrected to complete the cooking progress adjustment.

[0015] By adopting the above technical solutions, the cooking process is analyzed and the equipment evolution is simulated based on time series analysis and digital twin modeling algorithms. By collecting stage data in real time and comparing it with standard intervals, the execution progress is dynamically adjusted using deviation compensation and global correction mechanisms, which significantly improves the adaptive adjustment accuracy, stability and user interaction experience of the cooking process.

[0016] Secondly, this application also provides an electrical control method for a grinding and cooking robot, which adopts the following technical solution; An electrical control method for a grinding and cooking robot includes: Collect multidimensional data on brown rice and combine it with a preset rice type recognition model to make a comprehensive judgment and output the type of brown rice; Based on the required type of rice, determine the target amount of rice and the remaining amount of rice, and generate a phased control signal in conjunction with the phased rice supply mechanism; Match the polished rice according to the type of brown rice and the target rice quantity ratio, and calculate the target water quantity; Calculate the total amount of brown rice based on the rice yield and the target amount of rice, and determine the milling strategy. Based on the whiteness level and the total amount of brown rice, the milling strategy is optimized and a milling parameter curve is generated. Based on historical cooking data categorized by brown rice type and cooking altitude, single-category cooking data were obtained. Based on the required type of rice and the target amount of rice, optimize and screen the rice cooking data, generate cooking curves, and divide them into cooking stage parameters. Based on the equipment type, the grinding parameter curves, target water volume, and cooking stage parameters are converted to obtain grinding signals, water replenishment signals, and cooking stage signals. Based on the cooking process, grind signals, water replenishment signals, and steaming / cooking signals are assigned, and the timestamps for signal implementation are determined. Brown rice is processed in stages based on the signal timestamp, stage data of brown rice is collected, and the cooking progress is adjusted in combination with stage standard data.

[0017] By adopting the above technical solutions, intelligent rice type determination is achieved based on multimodal recognition and data fusion algorithms. The milling, water volume and cooking parameters are generated through demand matching and optimization calculations. Signal conversion and closed-loop control technologies are used to precisely control the entire cooking process, which significantly improves the equipment's adaptability, the level of personalized cooking and the stability of the process.

[0018] Thirdly, this application also provides a storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the electrical control method of the grinding and cooking robot as described above.

[0019] In summary, the beneficial technical effects of this application are as follows: Based on closed-loop control and precise metering algorithms, the entire process of brown rice storage and preservation, on-demand quantitative milling and intelligent cooking is automated through multi-module collaboration, which significantly improves rice freshness, cooking efficiency and user experience consistency. Based on time-series analysis and digital twin modeling algorithms, the cooking process is analyzed and the equipment evolution is simulated. By collecting stage data in real time and comparing it with standard intervals, the execution progress is dynamically adjusted using deviation compensation and global correction mechanisms, which significantly improves the adaptive adjustment accuracy, stability and user interaction experience of the cooking process. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the electrical control system of the grinding and cooking robot in this application; Figure 2 This is a schematic diagram of the overall control module in this application; Figure 3 This is a schematic diagram of the process control unit in this application; Figure 4 This is a flowchart illustrating the electrical control method of the grinding and cooking robot in this application. Detailed Implementation

[0021] The present application will be further described in detail below with reference to the accompanying drawings.

[0022] Reference Figure 1 The present application discloses an electrical control system for a grinding and cooking robot, comprising: The storage and preservation module has its signal input terminal connected to the first signal terminal of the main control module and its signal output terminal connected to the signal input terminal of the quantitative transmission module. It is used to acquire real-time storage data of brown rice in the rice storage box and adjust it to the preset storage environment data range. The quantitative transmission module has its signal input end connected to the second signal end of the main control module and its signal output end connected to the signal input end of the milling and chaff removal module. It is used to supply rice from the rice storage box in stages according to user needs to obtain the target amount of rice. Mechanical transmission drives a servo mechanism to precisely control the speed and position of the impeller, thereby achieving high-precision quantitative rice feeding with an error of no more than 5 grams.

[0023] The milling and chaff removal module has its signal input terminal connected to the third signal terminal of the main control module and its signal output terminal connected to the signal input terminal of the intelligent rice cooking module. It is used to mill brown rice according to the target rice quantity and whiteness level to obtain refined rice. The rice milling machine adjusts the rotation speed of the agitator blades based on the amount of rice added at one time and the user's desired whiteness, enabling controlled milling in conjunction with the inner wall of the screen. This not only removes excess bran to improve taste but also maximizes the retention of key nutrients in brown rice, such as dietary fiber and B vitamins, by avoiding over-processing. The intelligent rice cooker module has its signal input terminal connected to the fourth signal terminal of the main control module. It is used to add water according to the cooking recipe and to complete the cooking of refined rice. The intelligent rice cooker system uses intelligent algorithms to precisely control temperature and time, ensuring that different types of rice can be cooked to a full and soft texture, avoiding problems such as undercooked or overcooked rice caused by manual operation.

[0024] Like refrigerators, smart rice cookers use PID control algorithms to achieve precise temperature regulation. Through the coordinated calculation of proportional, integral, and derivative terms, the heating power is dynamically adjusted so that the temperature inside the pot is quickly and stably maintained within the set range, thereby adapting to the cooking curve required for different types of rice and textures. The main control module is used to analyze user requirements to extract the target amount of rice, identify the type of rice, and adjust the cooking progress in conjunction with the cooking curve. The rice type information is obtained through the human-machine interface (HMI), and its intelligent algorithm will automatically call the corresponding scientific rice-water ratio according to the target amount of rice and drive the automatic water replenishment device to complete the precise water distribution. The PLC control unit acquires mixed signals (digital and analog signals) through its input modules, converts and calculates them through internal programs, and finally calculates the start-up timing and working status required by the controlled component. The PLC control unit uses its embedded intelligent algorithm to calculate the system status in real time and issue precise commands to servo, temperature control and mechanical control units accordingly. The recipe database contains a large amount of data, which can automatically search and match the best recipe based on the user's selected parameters using AI. First, the rice milling machine is adjusted synchronously to complete the milling process; then, the rice is automatically delivered to the rice cooker; finally, the rice cooker automatically completes the rice-water ratio and cooking according to the recipe. The entire process is seamless and requires no manual intervention. It also has self-learning capabilities, saving user-set parameters for one-click recall next time.

[0025] By integrating an IoT gateway and connecting to a mobile app based on the ModbusTcp protocol, it supports a series of operations such as remote rice milling control, rice cooking reservation, and rice storage balance inquiry.

[0026] In this embodiment, the types of food that the grinding and cooking robot can prepare include: Grains: millet porridge, eight-treasure porridge, oatmeal porridge, purple rice porridge; Soy products: soy milk, tofu pudding, and tofu curd; Vegetables and fruits: Pumpkin soup, carrot puree, apple puree, vegetable soup; Medicinal and health-preserving dishes: Tremella and lotus seed soup, yam and barley paste, black sesame paste; Infant and toddler complementary foods: rice cereal, mixed fruit and vegetable puree, and meat puree porridge.

[0027] In this embodiment, the user sets a request via a mobile app to "cook brown rice for two people at 7 AM tomorrow, with a preference for a soft and sticky texture." The main control module analyzes this request, automatically extracts the target rice quantity, identifies the rice variety as "Wuchang brown rice," and retrieves the optimal cooking curve for this batch of brown rice from cloud storage. The storage and preservation module monitors the temperature, humidity, and gas composition inside the rice storage box in real time, automatically activating a micro-refrigeration and controlled atmosphere device to adjust the temperature to a preset storage range of 15°C and 65%RH, ensuring the brown rice remains fresh and active before milling. The quantitative transmission module, based on the two-person requirement, precisely outputs 150 grams of brown rice from the storage box to the milling chamber via a screw mechanism, and provides feedback on the actual rice output. The milling and bran removal module, based on the user's preset... The "Whiteness Level 3" setting initiates the grinding process with sand rollers. By dynamically adjusting the grinding pressure based on real-time monitoring of the rice grain surface temperature and grinding current, the brown rice is hulled and polished within 90 seconds. Simultaneously, the generated rice bran is drawn into the bran collection box under negative pressure. After receiving the polished rice, the intelligent rice cooking module automatically calculates and injects purified water in a 1:1.2 ratio according to the cooking recipe, and activates IH electromagnetic heating (bottom heating can also be used, including three-dimensional IH heating, top cover IH / far-infrared heating, and ordinary / flat IH heating). Following the segmented cooking curve issued by the main control module, the module sequentially completes soaking, heating, boiling, and simmering, ultimately presenting users with a pot of crystal-clear, plump, and soft-textured freshly milled and cooked rice at 7:00 AM sharp.

[0028] Preferably, the storage and preservation module includes: The environmental data acquisition unit is used to collect environmental information on the brown rice stored in the rice storage box to obtain real-time storage data, including temperature, humidity and ventilation. The data cleaning unit is used to fill in missing values ​​and remove duplicate values ​​from the real-time stored data according to the collection timestamp, so as to obtain standard stored data. The data correction unit is used to correct the standard storage data based on a preset storage environment data range and a PID algorithm to maintain the stability of the storage environment. The rice quantity monitoring unit is used to monitor the amount of brown rice stored based on a preset rice quantity warning line and the amount used in a single use, determine the remaining rice quantity, and generate a rice quantity replenishment notification. The PID algorithm is as follows: M n=MP n +MI n +MD n ; Among them, M n MP is the calculated value of the loop output at sampling time n. n MI is the proportional term value of the loop output at sampling time n. n The integral term value of the sampling time loop output, MD n This is the differential value of the loop output at sampling time n; MP n =K C *(SP n -PV n ); Among them, K C For loop gain, SP n PV is the set value at sampling time n. n The value of the process variable at sampling time n; MI n =K C *T S / T I *(SP n -PV n )+MX; Among them, T S T is the loop sampling time. I Let MX be the integration time, and MX be the value of the integral term at sampling time n-1. MD n =K C *T D / T S *((SP n -PV n )-(SP n-1 -PV n-1 )); If SP n =SP n-1 MD n =K C *T D / T S *(PV n-1 -PV n ); Among them, T D SP is the differential period of the loop. n-1 PV is the set value at sampling time n-1. n-1 The value of the process variable at sampling time n-1.

[0029] In this embodiment, the environmental acquisition unit of the storage and preservation module monitors the temperature, humidity and ventilation in the rice storage box in real time to obtain real-time storage data of brown rice; the data cleaning unit fills out and removes duplicates based on the acquisition timestamp, generates standard storage data and transmits it to the data correction unit; this unit uses a preset value of 15℃ and 65%RH as the setpoint, calculates the proportional, integral and derivative terms through the PID algorithm, and dynamically controls the semiconductor cooling chip and micro fan to keep the temperature and humidity in the box stable within the target range. Meanwhile, the rice quantity monitoring unit continuously calculates the remaining rice quantity based on the preset 2kg rice quantity warning line and the user's daily cooking rice consumption of 150g. When the remaining quantity is less than 500g, it automatically generates a rice replenishment notification and pushes it to the user's mobile phone to ensure that the brown rice is always in the best condition of being fresh and sufficient when cooking rice in the morning.

[0030] Preferably, the quantitative transmission module includes: The requirement analysis unit is used to analyze user requirements and extract the target rice quantity and required rice type; The equipment analysis unit is used to collect data from the actuator according to the required rice type to obtain the actuator's operating data; The dynamic transmission unit is used to interpret the stage control signals according to the equipment type to obtain the stage execution parameters and stage transition timestamps; The weighing and detection unit is used to correct the mechanism's operating data according to the stage execution parameters, obtain the initial operating data, and collect the initial meter measurement; The cutoff compensation unit is used to switch the initial operation data according to the stage transition timestamp and collect the final meter reading. If the absolute difference between the final amount of rice and the target amount of rice is within the preset tolerance range, and the absolute difference between the initial amount of rice and the initial rice threshold is within the tolerance range, then the rice supply is considered successful and the current stage execution parameters are the optimal solution. If not, the execution parameters for the current stage will be adjusted to obtain the target meter quantity.

[0031] By adopting the above technical solution, based on demand analysis and closed-loop feedback control algorithm, and through phased execution and real-time weighing detection, combined with deviation compensation and parameter self-correction mechanism, precise meter feeding is achieved, which significantly improves the accuracy, adaptability and execution efficiency of quantitative transmission.

[0032] In this embodiment, the user's rice retrieval request is received through a user interface (such as a touch screen, mobile APP, or voice command), including the required amount of rice (such as "take 2 cups of rice" or "300 grams") and the type of rice (such as "long grain rice" or "brown rice"). If the rice storage box has a multi-compartment design.

[0033] If the user input is "number of cups" (such as the measuring cup that comes with the rice cooker), the system converts the number of cups into a mass unit (grams) according to the preset conversion relationship (1 cup ≈ 150 grams, which depends on the density of the rice variety), and uses it as the target rice quantity Qtarget (unit: grams). If the user directly inputs the mass, it is directly adopted.

[0034] If the rice storage box contains multiple independent rice storage grids (for storing different rice varieties respectively), the system determines the ID of the target rice storage grid corresponding to the current rice supply according to the rice type selected by the user.

[0035] Read the real-time remaining quantity data of the target rice storage grid, which is continuously monitored and updated by the weighing sensor (or ultrasonic / photoelectric sensor) at the bottom of the rice storage box. Obtain the current remaining quantity Qstock (unit: grams).

[0036] If Qstock ≥ Qtarget, the remaining quantity is sufficient, and proceed to the next step.

[0037] If Qstock < Qtarget, the remaining quantity is insufficient. Prompt the user through the interface that the remaining quantity is insufficient and needs to be replenished; check whether the rice supply actuator (such as a screw propeller, vibrating feeder, gate) is in the standby state, without jamming or foreign object blockage. If there is an abnormality, trigger an alarm and prompt for maintenance.

[0038] According to the target rice quantity Qtarget and the accuracy requirement, divide the rice supply process into multiple stages. Usually, adopt a two-stage strategy of "coarse supply + fine supply": Coarse supply stage: Quickly release most of the rice (such as 90% of the target quantity), and adopt a high rotation speed or large flow rate mode to improve efficiency.

[0039] Fine supply stage: Slowly and with a small flow rate make up the remaining part to ensure the accuracy of the final rice quantity and avoid overshoot.

[0040] If the target rice quantity is small (such as below the threshold Qthreshold), it can be combined into a single-stage fine supply.

[0041] [[ID=2,6]]The coarse supply target quantity Qrough = Qtarget × 0.9 (the coefficient is adjustable).

[0042] The fine supply target quantity Qfine = Qtarget - Qrough.

[0043] According to the flow characteristics of the actuator (such as the number of grams of rice supplied per revolution of the screw propeller kg / rev), calculate the required operating time or number of revolutions of the actuator for each stage: Control the rice supply actuator of the target rice storage grid to start running at the preset coarse supply rotation speed, and the rice grains fall from the bottom outlet of the rice storage box into the rice receiving container (such as a rice receiving cup).

[0044] The high-precision weighing sensor under the rice receiving container measures the mass Qdispensed(t) of the discharged rice in real time, and the data is fed back to the controller at a high frequency (such as 10Hz).

[0045] When Qdispensed(t) ≥ Qrough, an instruction is immediately issued to switch the actuator to the fine supply mode (reduce the rotation speed or change to intermittent rice supply). During the switching process, the overshoot caused by mechanical inertia needs to be considered, and the switching instruction can be issued in advance by a certain amount (such as in advance by ΔQ).

[0046] The actuator continues to supply rice at a low speed or in a pulsed manner, and the weighing sensor continuously monitors. Calculate the remaining required rice quantity Qremaining = Qtarget - Qdispensed(t) in real time.

[0047] When Qremaining ≤ ϵ (ϵ is the allowed static error, such as ±1 gram), or when Qdispensed(t) ≥ Qtarget, immediately stop the operation of the actuator. To prevent the overshoot caused by mechanical inertia, the stop instruction can be issued in advance when slightly lower than the target value (such as Qtarget - δ), and δ is calibrated according to experience.

[0048] After stopping the rice supply, wait for the rice grains in the rice receiving container to stabilize (usually 1 - 2 seconds), the reading of the weighing sensor no longer fluctuates, and read the final discharged rice quantity Qfinal.

[0049] If |Qfinal - Qtarget| ≤ tolerance (such as ±2 grams), it is determined that the rice supply is successful this time.

[0050] If Qfinal < Qtarget - tolerance (under - quantity), record the difference and enter the supplementary process.

[0051] If Qfinal > Qtarget + tolerance (over - quantity), record the over - quantity value and compensate it during the next rice supply (such as reducing the corresponding amount), or prompt the user to take out the excess part (if operable).

[0052] Display the final rice quantity and the success status on the user interface, and give a voice prompt "Rice taking completed".

[0053] Preferably, referring to Figure 2 , the total control module includes: The rice variety identification unit is used to collect multi - dimensional data of paddy rice, obtain the multi - dimensional data of paddy rice, and make a comprehensive judgment in combination with a preset rice variety identification model, and output the paddy rice variety; The verification and judgment unit is used to judge the target rice quantity and the remaining rice quantity according to the required rice variety; If the remaining rice quantity is greater than the target rice quantity, it indicates that the rice quantity is sufficient, and a phased control signal is generated in conjunction with the phased rice supply mechanism. If not, the user will be prompted that there is not enough rice left, and other types of rice will be recommended or the amount of rice to be taken will be reduced based on the similarity of the rice types. The intelligent proportioning unit is used to match the proportion of polished rice according to the type of brown rice and the target amount of rice, and to calculate the target amount of water. The rice milling synchronization unit is used to calculate the total amount of brown rice based on the rice yield and the target amount of rice, and to determine the milling strategy. The milling determination unit is used to optimize the milling strategy based on the whiteness level and the total amount of brown rice, and generate milling parameter curves. The recipe generation unit is used to classify historical cooking data according to brown rice type and cooking altitude to obtain single-category cooking data; The formula optimization unit is used to optimize the cooking rice data based on the required rice type and target rice quantity to obtain the cooking formula and generate the cooking curve. The parameter analysis unit is used to divide the cooking curve into stages and obtain the cooking stage parameters. The signal conversion unit is used to convert the grinding parameter curve, target water volume and cooking stage parameters according to the equipment type to obtain grinding signal, water replenishment signal and cooking stage signal; The signal distribution unit is used to allocate grinding signals, water replenishment signals, and steaming / cooking signals according to the cooking process, and to determine the signal implementation timestamp; The process control unit is used to perform staged processing of brown rice based on the signal implementation timestamp, collect stage data of brown rice, and control the cooking progress in combination with stage standard data.

[0054] In this embodiment: the cooking curve typically includes multi-stage parameters: Soaking stage: time (e.g., 20 minutes), temperature (room temperature or slight heating).

[0055] Heating stage: heating power, target temperature (e.g., 100℃), heating rate.

[0056] Boiling stage: maintain boiling time (e.g., 10 minutes), power control.

[0057] Cooking stage: time (e.g., 15 minutes), utilization of residual heat or slight heating.

[0058] Insulation stage: Temperature setting (e.g., 65℃).

[0059] After the user sets the desired "cook brown rice for two people at 7 am tomorrow, with a preference for a soft and sticky texture" via the mobile app, the main control module initiates intelligent control of the entire process: First, the rice variety identification unit collects multi-dimensional data such as color, particle size, and moisture content of the brown rice using a multispectral sensor. Combined with a pre-trained convolutional neural network rice variety identification model, it comprehensively determines that the batch of brown rice is "Wuchang Daohuaxiang" and outputs a confidence level of 98%. The verification and judgment unit then obtains the remaining amount of rice in the rice storage box (currently 1800g) and compares it with the user's target amount of 150g. After confirming that the amount of rice is sufficient, it generates a stage control signal for quantitative transmission in conjunction with the staged rice supply mechanism. The intelligent proportioning unit retrieves the optimal water absorption rate curve of the variety from the cloud database based on the identified brown rice variety and the target amount of rice, and calculates the target water volume to be 225ml. The rice milling synchronization unit, based on the standard rice yield of 92% for this variety, deduced that 163g of brown rice is needed to produce 150g of polished rice, and determined to adopt a "light milling and slow grinding" strategy accordingly. The milling judgment unit, based on the user-preset whiteness level 3 and the total amount of 163g of brown rice, optimized the milling strategy and generated a milling parameter curve including the speed of the sand roller, milling pressure, and multiple residence times. The formula generation unit, based on the "Wuchang Daohuaxiang" rice variety and the local altitude of 50 meters, extracted similar data from historical cooking data. The formula optimization unit, targeting the "soft and glutinous" taste requirement and the target amount of 150g of rice, optimized the cooking curve to include soaking for 20 minutes, heating to 100℃, boiling for 10 minutes, simmering for 15 minutes, and keeping warm at 65℃. The parameter analysis unit divides the curve into five cooking stage parameters; the signal conversion unit converts the grinding parameter curve into a grinding signal, the target water volume into a water replenishment signal, and the cooking stage parameters into corresponding cooking segment signals according to the equipment type; the signal distribution unit prioritizes the grinding signal to the grinding and bran removal module (timestamp set to 22:00) and distributes the water replenishment signal and cooking segment signal to the smart rice cooker module (timestamp set to 6:55 the next day) according to the cooking timestamp the next morning; finally, the process control unit strictly follows the signal implementation timestamp the next morning, triggering grinding, water replenishment, and segmented heating in sequence, and collecting the temperature and moisture data of the brown rice in real time at each cooking stage, comparing and controlling it with the stage standard data to ensure that the cooking progress accurately matches the preset curve, presenting users with a pot of freshly milled and cooked rice with a soft and sticky texture and well-preserved nutrients at 7 o'clock sharp.

[0060] Preferably, refer to Figure 3 The process control unit includes: The timing judgment layer is used to perform timing analysis on the cooking process, extract the cooking stages, and determine the parallel cooking timing segments. The time allocation layer is used to pre-allocate time periods for the cooking stage and combine them with signal timestamps to obtain stage transition nodes; The timing correction layer is used to correct the stage transition nodes according to the parallel cooking timing segment to obtain the corrected stage nodes; The stage monitoring layer is used to monitor brown rice according to the correction stage nodes and collect brown rice stage data; The stage simulation layer is used to collect data from cooking equipment and combine it with the equipment wear curve to construct a twin, thereby obtaining a virtual equipment. The stage nodes are then simulated and evolved to obtain the stage standard data range. The progress control layer is used to compare and judge the brown rice stage data based on the stage standard data. If all the brown rice stage data are within the standard stage data range, it indicates that the current signal implementation timestamp is accurate, there is no need to adjust the execution time, and the cooking progress is displayed. If not, then the current signal timestamp is compensated in stages to obtain the corrected timestamp, and the execution time is globally corrected to complete the cooking progress adjustment.

[0061] In this embodiment, the complete intelligent cooking process is broken down into three core stages: Milling stage: from starting the rice milling machine to producing refined rice and delivering it to the rice cooker.

[0062] Water replenishment phase: from the start of water filling to reaching the target water volume.

[0063] Steaming / cooking stage: from the start of heating to the completion of cooking, it is divided into sub-stages such as soaking, heating up, boiling, simmering, and keeping warm.

[0064] Clarify the sequence and parallel possibilities of each stage: milling and water replenishment can be partially parallel (e.g., water volume can be calculated and water replenishment prepared after milling begins, but water must be added after the rice is put into the pot). Steaming must be started after both rice and water are in place.

[0065] Grinding signals include: Start-up signal: includes target rice milling quantity Qtarget, whiteness grade Wdesired, and rice variety information.

[0066] Adjustment signal: An instruction to adjust the roller pressure or speed based on real-time whiteness feedback during the grinding process.

[0067] Completion signal: A confirmation signal that milling is finished and the rice has been delivered to the rice cooker.

[0068] Hydration signals include: Water quantity calculation signal: Rice-to-water ratio instruction generated based on rice type and target rice quantity.

[0069] Water injection control signal: Real-time commands to control the start / stop and flow rate of the water pump.

[0070] Water volume confirmation signal: A stop signal issued after the target water volume has been reached.

[0071] The cooking section signals include: Stage switching signals: such as "Soaking ends → Heating begins", "Heating ends → Boiling begins", etc.

[0072] Parameter adjustment signals: heating power, temperature target, and time setting for each stage.

[0073] Safety monitoring signals: abnormal handling instructions such as temperature exceeding limit and dry burning warning.

[0074] Establish a global timeline with the user confirming the startup time as T0.

[0075] Milling signal timestamp: Tmill_start=T0+Δprep (Δprep is the preparation time, such as feeding time); Based on the estimated milling time Tmill_duration (determined by the amount of rice and whiteness), set the estimated completion time Tmill_end = Tmill_start + Tmill_duration.

[0076] The timestamps for the real-time whiteness feedback trigger adjustment signals are dynamically generated, for example, once every 5 seconds.

[0077] Water replenishment signal timestamp: The water volume calculation signal is generated immediately after T0.

[0078] The water injection start signal is set to Twater_start=Tmill_end−Twater_overlap (which can overlap with the later stage of milling, for example, start water injection 30 seconds before the end of milling, provided that the rice has been delivered).

[0079] The water injection duration Twater_duration is determined by the water volume and flow rate, and the water injection completion signal timestamp is Twater_end = Twater_start + Twater_duration.

[0080] Cooking section signal timestamp: The cooking start signal Tcook_start = max(Tmill_end, Twater_end) + Δsync (ensure that the rice and water are in place).

[0081] The timestamps for each sub-stage are pre-assigned based on the cooking curve: Tsoak_end=Tcook_start+tsoak;Theat_end=Tsoak_end+theat; Tboil_end=Theat_end+tboil; Tsimmer_end=Tboil_end+tsimmer; The heat preservation stage continues until the user picks up the rice.

[0082] When the Tmill_start signal is sent, the rice milling machine starts working according to the preset parameters.

[0083] Whiteness value W(t): Read once every 5 seconds from the whiteness sensor.

[0084] Real-time weight Qrice(t): The weighing sensor in the rice milling chamber monitors the remaining material and calculates the amount of milled rice.

[0085] Motor current I(t): reflects the milling load and indirectly indicates the milling efficiency.

[0086] Dynamic adjustment: The real-time whiteness W(t) is compared with the target whiteness Wdesired. If the deviation exceeds the threshold (e.g., ±0.3 level), an adjustment signal is generated (e.g., increasing pressure or extending time), and the estimated completion time is updated.

[0087] When W(t)≥Wdesired or the maximum allowable time is reached, a milling completion signal is issued, and the actual completion time Tmill_actual and the final amount of milled rice are recorded.

[0088] Calculate the target water volume immediately after T0 and check the status of the water source and pump.

[0089] When a water injection start signal is sent at Twater_start, the water pump starts working, and the flow meter provides real-time feedback on the cumulative water volume V(t).

[0090] Instantaneous flow rate F(t): Used for closed-loop control to adjust the pump speed to stabilize the flow rate.

[0091] Cumulative water volume V(t): Compare with target water volume Vtarget: When V(t) ≥ Vtarget − δ (δ is the lead time to compensate for residual water in the pipeline), issue a deceleration or stop signal to ensure that the final water volume error is < ±1%. Record the actual completion time Twater_actual.

[0092] Before Tcook_start, confirm that the rice has been put into the pot, the water has been added, and the pot lid is closed.

[0093] Soaking stage: Monitor the temperature and humidity inside the pot to ensure the rice grains fully absorb water. If the temperature deviates from the target (e.g., due to excessively high room temperature causing rapid heating), the soaking time can be fine-tuned.

[0094] During the heating phase: Monitor the heating power and heating rate, and compare them with the standard curve. If the heating is too slow, increase the power appropriately; if it is too fast, reduce the power or temporarily pause heating.

[0095] Boiling stage: Monitor whether the temperature is stable at around 100℃ (boiling point needs to be adjusted in high-altitude areas), and the duration of this temperature maintenance. Monitor the boiling intensity using a steam sensor, and adjust the power as needed to maintain adequate boiling.

[0096] During the simmering stage: Monitor the temperature drop curve and continue gelatinization using residual heat. If the temperature drops too quickly, add a small amount of heat.

[0097] At the end of each sub-stage, based on the deviation between the actual collected data and the standard data, a dynamic decision is made on whether to immediately switch to or extend the current stage. For example, if the actual water absorption during the soaking stage is insufficient (through weight changes or model predictions), the soaking time Δt can be extended, and the timestamp of the subsequent stages can be postponed accordingly.

[0098] Load the standard curve data corresponding to the current rice variety and taste from the recipe library, including the ideal temperature, time, and power parameters for each stage.

[0099] Deviation calculation: At each sampling point, calculate the deviation between the actual value and the standard value. eT(t)=Tactual(t)−Ttarget(t); et=tactual_phase−ttarget_phase; Regulatory rules include: Small deviations (e.g., temperature ±2℃): Heating power is finely adjusted via PID control, eliminating the need to adjust the time.

[0100] Moderate deviation (e.g., temperature remains too low): compensate in subsequent stages, such as by appropriately extending the boiling time to ensure sufficient gelatinization; Large deviation (such as temperature runaway): triggers safety protection, suspends heating and alarms.

[0101] Based on the actual execution, adjust the timestamps of the remaining stages in real time and display the updated estimated completion time on the HMI.

[0102] Once all stages have been completed according to the dynamically adjusted time, the system determines that cooking is complete and automatically switches to keep-warm mode. Complete cooking timeline data (actual timestamps of each signal, collected stage data, and control records) is saved to the user's history archive for subsequent analysis and model optimization. A push notification is sent to the user via HMI or app to inform them that the rice is ready.

[0103] Reference Figure 4 The present application discloses an electrical control method for a grinding and cooking robot, comprising: Collect multidimensional data on brown rice and combine it with a preset rice type recognition model to make a comprehensive judgment and output the type of brown rice; Based on the required type of rice, determine the target amount of rice and the remaining amount of rice, and generate a phased control signal in conjunction with the phased rice supply mechanism; Match the polished rice according to the type of brown rice and the target rice quantity ratio, and calculate the target water quantity; Calculate the total amount of brown rice based on the rice yield and the target amount of rice, and determine the milling strategy. Based on the whiteness level and the total amount of brown rice, the milling strategy is optimized and a milling parameter curve is generated. Based on historical cooking data categorized by brown rice type and cooking altitude, single-category cooking data were obtained. Based on the required rice type and target rice quantity, optimize and screen rice cooking data, generate cooking curves, and divide them into cooking stage parameters. Based on the equipment type, the grinding parameter curves, target water volume, and cooking stage parameters are converted to obtain grinding signals, water replenishment signals, and cooking stage signals. Based on the cooking process, grind signals, water replenishment signals, and steaming / cooking signals are assigned, and the timestamps for signal implementation are determined. Brown rice is processed in stages based on the signal timestamp, stage data of brown rice is collected, and the cooking progress is adjusted in combination with stage standard data.

[0104] In this embodiment: Before going to bed, the user sets the desired "cook brown rice for two people at 7 am tomorrow, with a soft and sticky texture" via a mobile app. First, a multi-spectral sensor collects multi-dimensional data such as the color, particle size, and moisture content of the brown rice. Combined with a pre-trained rice identification model, the system determines that the batch is "Wuchang Daohuaxiang" rice. Next, it verifies that the remaining rice amount of 1800g is greater than the required target amount of 150g. After confirming that the rice amount is sufficient, a quantitative transmission control signal is generated in conjunction with the staged rice supply mechanism. Based on the identified brown rice type and target amount, the system retrieves the optimal water absorption rate of the variety from the cloud and calculates the target water volume of 225ml to be injected. Combined with the standard rice yield of 92% for this variety, it is deduced that a total amount of 163g of brown rice needs to be added, and the "light milling and slow grinding" strategy is determined. Based on the user's preset whiteness level 3 and the total amount of 163g of brown rice, a milling parameter curve including the speed of the grinding roller, the milling pressure, and multiple residence times is optimized and generated. Based on the "Wuchang Daohuaxiang" rice variety and the local altitude of 50 meters, similar data were extracted from historical cooking data and optimized for a "soft and glutinous" texture, generating a segmented cooking curve that includes soaking for 20 minutes, heating to 100℃, boiling for 10 minutes, simmering for 15 minutes, and maintaining a temperature of 65℃. This curve was then divided into five cooking stage parameters. Based on the equipment type, the milling parameter curve, target water volume, and cooking stage parameters were converted into milling signals, water replenishment signals, and cooking stage signals, respectively. Following the cooking process, the milling... The grinding signal is assigned to the milling and bran removal module (timestamp set to 23:00), while the water replenishment signal and the cooking segment signal are assigned to the smart rice cooker module (timestamp set to 6:50 the next day). The next morning, the milling, water replenishment, and segmented heating are triggered in sequence according to the signal implementation timestamps. The temperature and moisture data of the brown rice are collected in real time at each cooking stage and compared with the stage standard data for adjustment to ensure that the cooking progress accurately matches the preset curve. At 7 o'clock sharp, a pot of freshly milled and cooked rice with a soft and sticky texture and good nutritional retention is presented to the user.

[0105] This application discloses a storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the electrical control method of the grinding and cooking robot as described above.

[0106] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. An electrical control system for a grinding and cooking robot, characterized in that, include: The storage and preservation module has its signal input terminal connected to the first signal terminal of the main control module and its signal output terminal connected to the signal input terminal of the quantitative transmission module. It is used to acquire real-time storage data of brown rice in the rice storage box and adjust it to the preset storage environment data range. The quantitative transmission module has its signal input terminal connected to the second signal terminal of the main control module and its signal output terminal connected to the signal input terminal of the milling and chaff removal module. It is used to supply rice from the rice storage box in stages according to user needs to obtain the target amount of rice. The milling and chaff removal module has its signal input terminal connected to the third signal terminal of the main control module and its signal output terminal connected to the signal input terminal of the intelligent rice cooking module. It is used to mill brown rice according to the target rice quantity and whiteness level to obtain refined rice. The intelligent rice cooker module has its signal input terminal connected to the fourth signal terminal of the main control module, and is used to add water according to the cooking recipe and complete the cooking of refined rice. The main control module is used to analyze user requirements, extract the target amount of rice, identify the type of rice, and adjust the cooking progress based on the cooking curve.

2. The electrical control system of the grinding and cooking robot according to claim 1, characterized in that, The storage and preservation module includes: An environmental data acquisition unit is used to collect environmental information about the brown rice stored in the rice storage box to obtain real-time storage data; the real-time storage data includes temperature, humidity and ventilation rate. The data cleaning unit is used to fill in missing values ​​and remove duplicate values ​​from the real-time stored data according to the collection timestamp to obtain standard stored data. The data correction unit is used to correct the standard storage data according to a preset storage environment data range and a PID algorithm to maintain the stability of the storage environment. The rice quantity monitoring unit is used to monitor the amount of brown rice stored based on a preset rice quantity warning line and the amount used in a single use, determine the remaining rice quantity, and generate a rice replenishment notification.

3. The electrical control system of the grinding and cooking robot according to claim 2, characterized in that, The PID algorithm is as follows: M n =MP n +MI n +MD n ; Among them, M n MP is the calculated value of the loop output at sampling time n. n MI is the proportional term value of the loop output at sampling time n. n The integral term value of the sampling time loop output, MD n This is the differential value of the loop output at sampling time n; MP n =K C *(SP n -PV n ); Among them, K C For loop gain, SP n PV is the set value at sampling time n. n The value of the process variable at sampling time n; MI n =K C *T S / T I *(SP n -PV n )+MX; Among them, T S T is the loop sampling time. I Where MX is the integration time, and MX is the value of the integral term at sampling time n-1; MD n =K C *T D / T S *((SP n -PV n )-(SP n-1 -PV n-1 )); If SP n =SP n-1 MD n =K C *T D / T S *(PV n-1 -PV n ); Among them, T D SP is the differential period of the loop. n-1 PV is the set value at sampling time n-1. n-1 The value of the process variable at sampling time n-1.

4. The electrical control system of the grinding and cooking robot according to claim 1, characterized in that, The quantitative transmission module includes: The requirement analysis unit is used to analyze user requirements and extract the target rice quantity and required rice type; The equipment analysis unit is used to collect data from the actuator according to the required rice type to obtain the actuator operation data; The dynamic transmission unit is used to interpret the stage control signals according to the equipment type to obtain the stage execution parameters and stage transition timestamps; The weighing and detection unit is used to correct the mechanism's operating data according to the stage execution parameters to obtain initial operating data and collect preliminary meter readings. The cutoff compensation unit is used to switch the initial operation data according to the stage transition timestamp and collect the final meter reading. If the absolute difference between the final amount of rice and the target amount of rice is within the preset tolerance range, and the absolute difference between the initial amount of rice and the initial rice amount threshold is within the tolerance range, then the rice supply is determined to be successful, and the execution parameters at the current stage are the optimal solution. If not, the execution parameters for the current stage are corrected to obtain the target meter value.

5. The electrical control system of the grinding and cooking robot according to claim 1, characterized in that, The main control module includes: The rice type identification unit is used to collect multi-dimensional data on brown rice, obtain multi-dimensional data on brown rice, and make a comprehensive judgment by combining it with a preset rice type identification model to output the type of brown rice. The verification and judgment unit is used to judge the target amount of rice and the remaining amount of rice according to the required type of rice. If the remaining amount of rice is greater than the target amount of rice, it indicates that there is enough rice, and a stage control signal is generated in conjunction with the staged rice supply mechanism. If not, the user will be prompted that there is not enough rice left, and other types of rice will be recommended or the amount of rice to be taken will be reduced based on the similarity of the rice types. The intelligent proportioning unit is used to match the proportion of polished rice according to the type of brown rice and the target rice quantity, and to calculate the target water content; The rice milling synchronization unit is used to calculate the total amount of brown rice based on the rice yield and the target amount of rice, and to determine the milling strategy. The milling determination unit is used to optimize the milling strategy based on the whiteness level and the total amount of brown rice, and generate a milling parameter curve.

6. The electrical control system of the grinding and cooking robot according to claim 1 or 5, characterized in that, The main control module also includes: The recipe generation unit is used to classify historical cooking data according to brown rice type and cooking altitude to obtain single-category cooking data; The formula optimization unit is used to optimize the cooking rice data according to the required rice type and target rice quantity to obtain the cooking formula and generate the cooking curve. The parameter parsing unit is used to divide the cooking curve into stages to obtain cooking stage parameters. The signal conversion unit is used to convert the grinding parameter curve, target water volume and cooking stage parameters according to the equipment type to obtain grinding signal, water replenishment signal and cooking stage signal; The signal distribution unit is used to allocate the grinding signal, the water replenishment signal, and the steaming / cooking segment signal according to the cooking process, and to determine the signal implementation timestamp; The process control unit is used to perform phased processing of brown rice according to the timestamp of the signal, collect phased data of brown rice, and control the cooking progress in combination with the phased standard data.

7. The electrical control system of the grinding and cooking robot according to claim 6, characterized in that, The process control unit includes: The timing judgment layer is used to perform timing analysis on the cooking process, extract the cooking stages, and determine the parallel cooking timing segments. The time allocation layer is used to pre-allocate time periods for the cooking stages and combine them with signals to implement timestamps, thereby obtaining stage transition nodes; A timing correction layer is used to correct the stage transition nodes according to the parallel cooking timing segment to obtain corrected stage nodes; A stage monitoring layer is used to monitor brown rice according to the corrected stage nodes and collect brown rice stage data. The stage simulation layer is used to collect data from cooking equipment and construct a virtual device by combining the equipment wear curve. The stage nodes are then simulated to evolve and obtain the stage standard data range. The progress control layer is used to compare and judge the brown rice stage data based on the stage standard data. If all the brown rice stage data are within the stage standard data range, it indicates that the current signal implementation timestamp is accurate, there is no need to adjust the execution time, and the cooking progress is displayed. If not, then the current signal timestamp is compensated in stages to obtain a corrected timestamp, and the execution time is globally corrected to complete the cooking progress adjustment.

8. An electrical control method for a grinding and cooking robot, applied to the system described in any one of claims 1-7, characterized in that, include: Collect multidimensional data on brown rice and combine it with a preset rice type recognition model to make a comprehensive judgment and output the type of brown rice; Based on the required type of rice, determine the target amount of rice and the remaining amount of rice, and generate a phased control signal in conjunction with the phased rice supply mechanism; The target water content is calculated by matching the polished rice with the brown rice type and the target rice quantity ratio; Based on the rice yield and the target rice quantity, calculate the total amount of brown rice and determine the milling strategy; Based on the whiteness level and the total amount of brown rice, the milling strategy is optimized to generate a milling parameter curve.

9. The electrical control method for the grinding and cooking robot according to claim 8, characterized in that, The electrical control method further includes: Based on historical cooking data categorized by brown rice type and cooking altitude, single-category cooking data were obtained. Based on the required rice type and target rice quantity, the cooking rice data is optimized and screened to generate a cooking curve, which is then divided into cooking stage parameters. Based on the equipment type, the grinding parameter curve, target water volume, and cooking stage parameters are converted to obtain the grinding signal, water replenishment signal, and cooking stage signal. The grinding signal, the water replenishment signal, and the steaming / cooking segment signal are assigned according to the cooking process, and the signal implementation timestamp is determined. Based on the signal, the brown rice is processed in stages according to the timestamp, the brown rice stage data is collected, and the cooking progress is adjusted in combination with the stage standard data.

10. A storage medium storing at least one instruction, at least one program, a code set, or an instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the electrical control method of the grinding and cooking robot as described in any one of claims 8-9.

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