Temperature error compensation method and system for multi-heating-section coffee machine

Abstract

The invention relates to the technical field of temperature control, and discloses a temperature error compensation method and system for a multi-heating-section coffee maker, and the method comprises the steps: synchronously collecting the real-time temperature value of each heating section, and calculating a temperature error index; constructing a thermal coupling interference model based on the physical distance between adjacent sections and the heat conduction characteristic of the medium; generating a dynamic decoupling compensation parameter according to the model and the error index (including constructing a symmetric interference matrix, calculating a coupling interference component, applying negative feedback and identifying a main interference component); a decoupling parameter is converted into a power adjustment instruction through a multivariable control algorithm (superposition of basic compensation and decoupling compensation, amplitude limiting and phase compensation); and heating output is updated according to the power instruction, and iterative execution is performed based on the error index change trend until the temperatures of all sections reach steady-state balance. The method can effectively model and compensate thermal coupling interference between sections, improves the efficiency of temperature error compensation, and achieves the quick and stable cooperative temperature control of multiple sections.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control, and particularly to a temperature error compensation method and system for a multi-heating section coffee machine. Background Art

[0002] In the prior art, temperature control of a multi-heating section coffee machine (such as a device with an independent extraction area, steam area, insulation area, etc.) faces significant challenges. Since the heating sections are physically adjacent and there are heat conduction media (such as metal components or thermal insulation materials), heat coupling effects inevitably occur between the sections. This means that adjusting the heating power of one section will interfere with the actual temperature of adjacent sections through heat conduction, resulting in mutual influence and cross-interference of temperature errors.

[0003] Traditional temperature control schemes usually adopt a single-section independent control strategy, and only perform proportional-integral (PI) or proportional-integral-derivative (PID) control based on the temperature error of this section. This method fails to effectively model and compensate for the heat coupling interference between adjacent sections, resulting in cross-influence between control variables (power). As a result, when the target temperatures of multiple sections of the coffee machine vary greatly or the load changes, the temperature fluctuates significantly and it takes a long time to reach a stable state. In addition, existing methods often use fixed compensation parameters or models, and cannot adapt to the dynamic changes in heat conduction characteristics caused by factors such as thermal expansion during the operation of the coffee machine, further reducing the overall efficiency of temperature error compensation. Summary of the Invention

[0004] The present invention provides a temperature error compensation method and system for a multi-heating section coffee machine, and its main purpose is to solve the problem of relatively low temperature error compensation efficiency of a multi-heating section coffee machine in the presence of heat coupling interference between sections.

[0005] To achieve the above object, a temperature error compensation method for a multi-heating section coffee machine provided by the present invention includes: S1. Synchronously collect the real-time temperature values of multiple heating sections of the coffee machine, and calculate the temperature error index of each heating section by section in combination with the preset target temperature value; S2. Based on the physical distance between adjacent heating sections and the heat conduction characteristics of the medium, construct a heat coupling interference model; S3. Generate dynamic decoupling compensation parameters according to the heat coupling interference model and the temperature error index; S4. Convert the dynamic decoupling compensation parameters into power adjustment instructions for each heating section through a multivariable control algorithm, where the multivariable control algorithm compensates for the cross-interference of control variables caused by heat coupling; S5. Update the heating output of the coffee machine according to the power adjustment instruction, and iteratively execute steps S1 - S4 based on the change trend of the temperature error index until the temperatures of all the heating sections reach a steady - state balance.

[0006] Optionally, constructing a thermal coupling interference model based on the physical distance between adjacent heating sections and the thermal conduction characteristics of the medium includes: Obtain the thickness parameter of the heat - conducting medium between adjacent heating sections, and calculate the equivalent thermal resistance value of the heat - conduction path according to the thickness parameter; Establish a heat - flow transfer function based on the equivalent thermal resistance value; Discretize the heat - flow transfer function into a thermal interference intensity matrix as the thermal coupling interference model.

[0007] Optionally, the obtaining the thickness parameter of the heat - conducting medium between adjacent heating sections includes: Monitor the thermal expansion deformation amount during the operation of the coffee machine, and dynamically correct the equivalent thermal resistance value according to the thermal expansion deformation amount; Establish a non - linear mapping relationship table between the equivalent thermal resistance value and temperature, and update the coefficient of the heat - flow transfer function in real time by looking up the table.

[0008] Optionally, the dynamically correcting the equivalent thermal resistance value according to the thermal expansion deformation amount includes: Inject a step test signal during the pre - heating stage of the coffee machine, and collect the response delay of each heating section to the step test signal; Back - calculate the actual thermal conduction characteristics of the heat - conducting medium according to the response delay; Perform cross - verification on the back - calculated result and the non - linear mapping relationship table.

[0009] Optionally, generating dynamic decoupling compensation parameters according to the thermal coupling interference model and the temperature error index includes: Convert the thermal coupling interference model into a symmetric interference matrix; Construct the temperature error index as a column vector; Calculate the product of the symmetric interference matrix and the column vector through matrix multiplication operation to generate a coupled interference component; Apply a negative - feedback operation to the coupled interference component to generate dynamic decoupling compensation parameters.

[0010] Optionally, the applying a negative - feedback operation to the coupled interference component to generate dynamic decoupling compensation parameters includes: Decompose the coupled interference component into orthogonal modes; Identify the main interference components with the greatest contribution to temperature fluctuation in each orthogonal mode; Apply variable gain compensation to the main interference component, and recombine the compensated main interference component into an optimized decoupling parameter.

[0011] Optionally, the identifying the main interference component with the greatest contribution to temperature fluctuations in each orthogonal mode includes: Construct a covariance matrix of the temperature error index, perform singular value decomposition on the covariance matrix to generate a singular value matrix; Extract the eigenvector corresponding to the largest singular value in the singular value matrix as the main interference component.

[0012] Optionally, the converting the dynamic decoupling compensation parameter into a power adjustment instruction for each heating section by a multivariable control algorithm includes: Input the temperature error index into a proportional controller to generate a basic power compensation amount; Superimpose the dynamic decoupling compensation parameter on the basic power compensation amount to generate a total compensation vector; Perform saturation limiting processing on the total compensation vector to generate an intermediate power instruction; Perform phase compensation on the intermediate power instruction according to the thermal inertia delay characteristic to generate a power adjustment instruction for each heating section.

[0013] Optionally, the iteratively executing steps S1 - S4 based on the change trend of the temperature error index until the temperatures of all the heating sections reach a steady - state balance includes: Calculate the difference metric value of the temperature error index in adjacent iteration cycles; When the difference metric value is greater than the convergence threshold, trigger a new round of compensation parameter calculation; When the difference metric value is continuously less than the convergence threshold, determine that the steady - state balance state is entered, and in the steady - state balance state, switch the coffee machine to the maintenance power output mode.

[0014] To solve the above problems, the present invention also provides a temperature error compensation system for a multi - heating - section coffee machine, and the system includes: A temperature error index generation module, configured to synchronously collect real - time temperature values of multiple heating sections of the coffee machine, and calculate the temperature error index of each heating section by sections in combination with a preset target temperature value; A thermal coupling interference model construction module, configured to construct a thermal coupling interference model based on the physical distance between adjacent heating sections and the medium heat conduction characteristic; A decoupling compensation parameter generation module, configured to generate a dynamic decoupling compensation parameter according to the thermal coupling interference model and the temperature error index; A power adjustment instruction generation module, which is used to convert the dynamic decoupling compensation parameters into power adjustment instructions for each heating section through a multivariable control algorithm, where the multivariable control algorithm compensates for the cross-interference of control variables caused by thermal coupling; A temperature steady-state balance module, which is used to update the heating output of the coffee machine according to the power adjustment instruction, and iteratively execute steps S1 - S4 based on the change trend of the temperature error index until the temperatures of all the heating sections reach a steady-state balance.

[0015] Compared with the prior art, the present invention has the following beneficial effects: By constructing a thermal coupling interference model (such as discretizing it into a thermal interference intensity matrix) based on the physical distance between adjacent heating sections and the medium heat conduction characteristics (including dynamically monitoring the thermal expansion deformation amount and correcting the equivalent thermal resistance), and using this model to generate dynamic decoupling compensation parameters in combination with the temperature error index calculated in real time (such as by constructing a symmetric interference matrix, calculating the coupling interference components and performing negative feedback operations, especially using singular value decomposition to identify the main interference components and applying variable gain compensation), the accurate quantification and active cancellation of complex thermal coupling interference between multiple sections are realized, effectively solving the problem of cross-interference of control variables caused by ignoring thermal coupling in the traditional single-section independent control strategy, significantly improving the pertinence and dynamic adaptability of compensation, thereby accelerating the response speed, reducing temperature overshoot and fluctuations; Using a multivariable control algorithm (superimposing the basic power compensation amount and the dynamic decoupling compensation parameters, and passing through saturation limiting and phase compensation) to convert the decoupling parameters into power adjustment instructions, and performing iterative execution and steady-state determination in combination with the change trend of the temperature error index (such as calculating the difference metric value between adjacent iteration cycles and comparing it with the convergence threshold), forming a closed-loop optimization control, not only compensating for the phase lag caused by thermal inertia delay and ensuring the synchronization of power adjustment and temperature response, but also significantly shortening the time required for the system to reach the temperature steady-state balance of all heating sections through dynamic iterative optimization and automatic switching of the maintenance mode, while avoiding energy waste caused by overcompensation, and finally realizing efficient multi-section collaborative temperature control. Brief Description of the Drawings

[0016] Figure 1 It is a schematic flowchart of the temperature error compensation method for a multi-heating section coffee machine provided by an embodiment of the present invention; Figure 2 It is a functional module diagram of the temperature error compensation system for a multi-heating section coffee machine provided by an embodiment of the present invention; The realization, functional characteristics and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the drawings. Detailed Embodiments

[0017] It should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0018] An embodiment of the present application provides a temperature error compensation method for a multi-heating section coffee machine. The execution subject of the temperature error compensation method for the multi-heating section coffee machine includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the temperature error compensation method for the multi-heating section coffee machine can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0019] Refer to Figure 1 As shown, it is a schematic flowchart of the temperature error compensation method for a multi-heating section coffee machine provided by an embodiment of the present invention. In this embodiment, the temperature error compensation method for the multi-heating section coffee machine includes: S1. Synchronously collect the real-time temperature values of multiple heating sections of the coffee machine, and calculate the temperature error index of each heating section by section in combination with a preset target temperature value.

[0020] In an embodiment of the present invention, the synchronously collecting the real-time temperature values of multiple heating sections of the coffee machine includes: Obtain the original temperature signals of each heating section of the coffee machine through a distributed temperature sensor array; Perform a moving average filtering process on the original temperature signals to generate real-time temperature values.

[0021] In an embodiment of the present invention, the calculating the temperature error index of each heating section by section in combination with a preset target temperature value includes: Compare the real-time temperature values with the preset target temperature values of the corresponding sections one by one to generate instantaneous temperature errors; Perform a time integral operation on the instantaneous temperature errors to generate a temperature error index including historical error characteristics.

[0022] Specifically, the distributed temperature sensor array is a sensing system in which multiple temperature sensors are installed in each heating section of the coffee machine according to a specific layout, and it can sense the temperature changes in different regions in real time and output electrical signals.

[0023] Specifically, the moving average filtering process is a signal smoothing technique that reduces the interference of noise on temperature data by taking the arithmetic mean of the original temperature signal over a continuous period of time.

[0024] Specifically, the preset target temperature value is an ideal temperature reference value preset according to the process requirements of different functional sections of the coffee machine. For example, the extraction section is usually set to 90 - 95 °C, and the insulation section is set to 60 - 70 °C. The instantaneous temperature error refers to the difference between the real-time temperature value of each heating section at a certain moment and the corresponding preset target temperature value, which is used to characterize the degree of deviation of the current temperature.

[0025] Specifically, the temperature error index is a comprehensive parameter obtained by integrating the instantaneous temperature error over time. It combines the amplitude and duration information of the temperature deviation and can comprehensively reflect the deviation state of temperature control.

[0026] Specifically, the process of synchronously collecting the real-time temperature values of multiple heating sections of the coffee machine is as follows: First, deploy distributed temperature sensor arrays in multiple heating sections such as the extraction chamber, steam pipe, and warming plate of the coffee machine. Each sensor uses a PT100 thermal resistor with a measurement accuracy of up to ±0.5 °C, which can accurately capture the temperature changes in each area. These sensors synchronously collect temperature data at a sampling frequency of 100 ms, convert the temperature signal into a change in resistance value, and then convert it into a voltage signal through a signal conditioning circuit to form the original temperature signal.

[0027] Further, when performing moving average filtering on the original temperature signal, set a time window containing 10 sampling points. For example, for the original signal sequence at time t , calculate its average value , and use this as the real-time temperature value at that moment. This filtering method can effectively suppress high-frequency noise, make the temperature data smoother, and provide a reliable basis for subsequent error calculation.

[0028] Specifically, when calculating the temperature error index by combining the preset target temperature value in different sections, first compare the real-time temperature value of each heating section with the preset target temperature value of the corresponding section one by one. For example, for the extraction section, the preset target temperature value is 92 °C. If the real-time temperature value at a certain moment is 90 °C, then the instantaneous temperature error is 92 - 90 = 2 °C. Then, perform a time integral operation on this instantaneous temperature error. The integration interval is from the start time of heating to the current time t, and the integration formula is , where, is the instantaneous temperature error at time

[0029] Generally speaking, through the synchronous acquisition and moving average filtering process of the distributed temperature sensor array, this step ensures the accuracy and reliability of the real-time temperature value, and solves the problems of incomplete temperature monitoring and large noise interference caused by single-point temperature measurement in the prior art. By calculating the temperature error index in sections and combining the instantaneous error with the historical error, it can more comprehensively reflect the temperature deviation state of each heating section, providing accurate input parameters for subsequent thermal coupling interference analysis and dynamic decoupling compensation, thus improving the pertinence and effectiveness of temperature error compensation and solving the technical problems of single error index and inability to comprehensively reflect temperature deviation in traditional methods.

[0030] Generally speaking, in this step, the original temperature signal collected by the distributed temperature sensor array is the basis for all subsequent processing. The real-time temperature value obtained after the moving average filtering process provides accurate data for the calculation of the instantaneous temperature error, and the temperature error index generated by the time integration operation of the instantaneous temperature error serves as an important input parameter for constructing the thermal coupling interference model in the subsequent step S2. At the same time, the accuracy of the temperature error index directly affects the generation of subsequent dynamic decoupling compensation parameters and the calculation of power adjustment instructions, forming a complete data link from temperature data acquisition to error analysis and then to compensation control, ensuring the coherence and effectiveness of the entire temperature error compensation system.

[0031] S2. Construct a thermal coupling interference model based on the physical distance between adjacent heating sections and the thermal conduction characteristics of the medium.

[0032] In the embodiment of the present invention, the constructing a thermal coupling interference model based on the physical distance between adjacent heating sections and the thermal conduction characteristics of the medium includes: Obtain the thickness parameter of the heat-conducting medium between adjacent heating sections, and calculate the equivalent thermal resistance value of the heat conduction path according to the thickness parameter; Establish a heat flow transfer function based on the equivalent thermal resistance value; Discretize the heat flow transfer function into a thermal interference intensity matrix as the thermal coupling interference model.

[0033] Specifically, the obtaining the thickness parameter of the heat-conducting medium between adjacent heating sections includes: Monitor the thermal expansion deformation amount during the operation of the coffee machine, and dynamically correct the equivalent thermal resistance value according to the thermal expansion deformation amount; Establish a non-linear mapping relationship table between the equivalent thermal resistance value and the temperature, and update the coefficient of the heat flow transfer function in real time by looking up the table.

[0034] Specifically, the dynamically correcting the equivalent thermal resistance value according to the thermal expansion deformation amount includes: Inject a step test signal during the preheating stage of the coffee machine, and collect the response delay of each heating section to the step test signal; Back-calculate the actual heat conduction characteristics of the heat-conducting medium based on the response time delay; Cross-verify the back-calculated result with the non-linear mapping relation table.

[0035] Specifically, the heat-conducting medium is a material layer located between adjacent heating sections, whose function is to conduct heat. Common materials include metal partitions or heat-insulating materials, and its thickness and heat conduction characteristics directly affect the heat coupling strength between heating sections.

[0036] Specifically, the equivalent thermal resistance value is a physical quantity characterizing the ability of the heat-conducting medium to impede heat flow transfer. By simplifying the complex heat conduction path into a single thermal resistance parameter, it is convenient to establish a heat conduction mathematical model.

[0037] Specifically, the heat flow transfer function is a function describing the dynamic relationship between heat flow input and temperature output, usually constructed based on Laplace transform, and is used to analyze the time-varying characteristics in the heat conduction process.

[0038] Specifically, the heat interference intensity matrix is a matrix model obtained by discretizing the heat flow transfer function. The elements in the matrix characterize the intensity and direction of heat coupling between each heating section, and it is the core data structure for multi-section heat interference analysis.

[0039] Specifically, the thermal expansion deformation amount refers to the physical deformation of the heat-conducting medium caused by temperature change when the coffee machine is working. This deformation amount will cause the thickness of the medium to change, thereby affecting the heat conduction characteristics.

[0040] Specifically, the step test signal is an instantaneously input temperature excitation signal, used to test the heat response characteristics between heating sections. By analyzing the signal response time delay, the actual heat conduction parameters of the heat-conducting medium are back-calculated.

[0041] Specifically, the non-linear mapping relation table is a pre-established correspondence table between the equivalent thermal resistance value and temperature, obtained by fitting experimental data, and is used to query the equivalent thermal resistance correction value at different temperatures in real time.

[0042] Specifically, the process of obtaining the thickness parameter of the heat-conducting medium between adjacent heating sections and calculating the equivalent thermal resistance is as follows: First, deploy distributed strain gauge sensors on the surface of the heat-conducting medium between adjacent heating sections of the coffee machine. The measurement accuracy of this sensor can reach 1μm, and it can continuously monitor the thermal expansion deformation amount of the medium caused by temperature change. When the coffee machine is started, the sensor continuously collects deformation amount data and transmits it to the microcontroller. The microcontroller dynamically corrects the medium thickness according to the initially set initial thickness d0 of the medium (such as 0.005m) and the real-time deformation amount ΔL through the formula d = d0 + ΔL. For example, when the monitored deformation amount is +5μm, the actual thickness d is updated to 0.005m + 0.000005m = 0.005005m.

[0043] Further, when calculating the equivalent thermal resistance, the formula is used, where k is the thermal conductivity of the heat-conducting medium (unit: W / (m·°C), for example, for stainless steel, k = 16.3), A is the heat conduction area (unit: m 2 , such as 0.01 m 2 ), substituting the corrected thickness d into the formula, the equivalent thermal resistance can be obtained. For example, when d = 0.005005 m, = 0.005005 / (16.3×0.01)≈0.0307 °C / W.

[0044] Specifically, the process of establishing the heat flow transfer function based on the equivalent thermal resistance is as follows: The heat flow transfer function adopts a first-order lag model , where C is the heat capacity (unit: J / °C), which is determined through calorimetry experiments. For example, for a certain section, the heat capacity C = 500 J / °C, then the transfer function is H(s)=1 / (0.0307×500·s + 1)=1 / (15.35s + 1). This function describes the frequency-domain relationship between the heat flow input and the temperature output and is used for subsequent dynamic analysis. [[ID=***]]

[0045] Further, the heat flow transfer function is discretized into a heat interference intensity matrix: The transfer function is discretized using the backward Euler method, and the sampling period is set to 1 s. After converting the continuous system into a difference equation, for n heating sections, an n×n matrix M is constructed. The matrix element represents the heat interference intensity of section i on section j, which is determined by calculating the heat flow transfer coefficient between adjacent sections at discrete time points. For example, in a 3-section system, represents the heat interference intensity of section 1 on section 2, and the coefficients after discretization of H(s) are filled into the matrix to form the initial heat interference intensity matrix.

[0046] Specifically, the process of dynamically correcting the equivalent thermal resistance based on the thermal expansion deformation amount includes: During the preheating stage of the coffee machine (the temperature rises from 25 °C to 90 °C), a step test signal is injected into the heating section (such as a sudden 10 °C rise in the target temperature), and the response delay of each section is collected through a temperature sensor (i.e., the time when the temperature rises to 63.2% of the stable value). For example, after injecting a step signal into section 1, the response delay of section 2 is 5 s. According to the heat conduction theory, the delay is positively correlated with the equivalent thermal resistance. Through the inverse formula , the actual equivalent thermal resistance can be obtained.

[0047] Further, the inverse derivation result is cross-validated with the non-linear mapping relationship table: The non-linear mapping relationship table is established through pre-experiments and records the theoretical values of the equivalent thermal resistance at different temperatures. For example, when the temperature is 90 °C, in the table The theoretical value is 0.0105 °C / W, and the error from the back-calculated value of 0.01 °C / W is within 5%, so the verification result is valid. If the error exceeds 10%, the model will trigger self-adaptive correction to update the coefficients in the mapping table to ensure the dynamic accuracy of the equivalent thermal resistance.

[0048] Generally speaking, this step solves the problem of model deviation caused by using fixed thermal resistance parameters in traditional methods by dynamically monitoring the thermal expansion deformation and correcting the equivalent thermal resistance. Traditional technologies do not consider the influence of temperature changes on the thickness of the heat-conducting medium, resulting in a mismatch between the thermal coupling model and the actual working conditions and low compensation accuracy. However, this step makes the heat flow transfer function and the thermal interference intensity matrix more in line with the actual heat conduction process by real-time correcting the equivalent thermal resistance, thereby improving the dynamic adaptability of temperature error compensation. For example, in scenarios where the coffee machine starts and stops frequently or the temperature changes suddenly, the model can more accurately capture the thermal interference between sections, providing a reliable basis for subsequent decoupling compensation and effectively solving problems such as temperature overshoot and compensation lag caused by inaccurate thermal coupling models.

[0049] Generally speaking, the dynamic acquisition of the heat-conducting medium thickness parameter is the basis for calculating the equivalent thermal resistance, and the accuracy of the equivalent thermal resistance directly affects the establishment of the heat flow transfer function. The thermal interference intensity matrix obtained by discretizing the heat flow transfer function serves as the core input for generating dynamic decoupling compensation parameters in subsequent steps. At the same time, the process of dynamically correcting the equivalent thermal resistance (step test, response time delay back-calculation, look-up table verification) forms the self-calibration mechanism of the model to ensure that the thermal coupling interference model is updated in real time with temperature changes. The coherence of this data link enables the entire process from thickness monitoring to matrix generation to form a closed loop, laying the foundation for the precise calculation of subsequent power adjustment instructions and ultimately achieving the coordinated control of multi-section temperatures.

[0050] S3. Generate dynamic decoupling compensation parameters according to the thermal coupling interference model and the temperature error index.

[0051] In the embodiment of the present invention, the generating dynamic decoupling compensation parameters according to the thermal coupling interference model and the temperature error index includes: Convert the thermal coupling interference model into a symmetric interference matrix; Construct the temperature error index as a column vector; Calculate the product of the symmetric interference matrix and the column vector through matrix multiplication operation to generate a coupled interference component; Apply a negative feedback operation to the coupled interference component to generate dynamic decoupling compensation parameters.

[0052] Specifically, the applying a negative feedback operation to the coupled interference component to generate dynamic decoupling compensation parameters includes: Decompose the coupled interference component into orthogonal modes; Identify the main interference component with the largest contribution to temperature fluctuation in each orthogonal mode; Apply variable gain compensation to the main interference component and recombine the compensated main interference component into an optimized decoupling parameter.

[0053] Specifically, the identification of the main interference component with the largest contribution to temperature fluctuation in each orthogonal mode includes: Construct the covariance matrix of the temperature error index, perform singular value decomposition on the covariance matrix, and generate a singular value matrix; Extract the eigenvector corresponding to the largest singular value in the singular value matrix as the main interference component.

[0054] Specifically, the symmetric interference matrix is a matrix converted from a thermal coupling interference model, and its elements satisfy , which characterizes the symmetry of the bidirectional thermal interference between adjacent heating sections and facilitates the analysis of multi-section coupling relationships through matrix operations.

[0055] Specifically, the coupled interference component is a parameter vector obtained by multiplying the symmetric interference matrix by the column vector of the temperature error index, and its elements reflect the comprehensive thermal interference influence values received by each heating section.

[0056] Specifically, the negative feedback operation refers to a control strategy that cancels the thermal coupling effect by applying a compensation amount opposite to the coupled interference component. The core is to adjust the compensation intensity through the feedback gain.

[0057] Specifically, the orthogonal mode decomposes the coupled interference component into a set of mutually independent eigenvectors, and each mode is orthogonal (i.e., the inner product is zero), which facilitates the separation of the influences of different interference factors.

[0058] Specifically, the main interference component is the eigenvector with the largest contribution to temperature fluctuation in the orthogonal mode, and its corresponding singular value is the maximum value in the matrix. Focusing on this component can effectively suppress the main thermal coupling interference.

[0059] Specifically, the covariance matrix is used to describe the correlation between the components of the temperature error index, and the matrix element represents the covariance value between the i-th and j-th temperature error indices, reflecting the distribution characteristics of the data.

[0060] Specifically, singular value decomposition (SVD) decomposes the covariance matrix into the form of , where is a diagonal matrix, and the diagonal elements are singular values, which are used to extract the main characteristic components in the data.

[0061] Specifically, the process of converting the thermal coupling interference model into a symmetric interference matrix is as follows: The initial thermal coupling interference model is an n×n thermal interference intensity matrix M, where the non-diagonal elements Indicates the thermal interference intensity of section i on section j. To simplify the calculation, a new matrix S is generated through symmetrization. The specific rule is: if the original matrix M is asymmetric, then take , so that the matrix satisfies . For example, when , , thus constructing the symmetric interference matrix S, which retains the main coupling relationships of the original model and is convenient for subsequent matrix operations.

[0062] Furthermore, the temperature error index is constructed as a column vector: The temperature error index E is the integral value of the error of each section calculated in step S1. For example, , where Eᵢ is the temperature error index of the i-th heating section. Convert it into the form of an n×1 column vector. For example, in a 3-section system, the column vector is , providing a standard input format for subsequent matrix multiplication.

[0063] Specifically, the coupled interference components are calculated through matrix multiplication: The product operation rule of the symmetric interference matrix S and the temperature error column vector E is: C = S・E, where C is an n×1 column vector of coupled interference components, and its i-th element (j ranges from 1 to n). For example, if S is a 3×3 matrix and E is , then , this operation quantifies the superposition effect of the thermal interference of adjacent sections on each section, providing a basis for subsequent compensation.

[0064] Furthermore, a negative feedback operation is applied to the coupled interference components: The dynamic decoupling compensation parameter K is generated using the formula K = -λ・C, where λ is the feedback gain (the value range is 0.1~0.5), and it needs to be adjusted according to the system response characteristics. For example, when , and λ = 0.2, , the negative sign indicates that the compensation direction is opposite to the interference direction, and the influence of thermal coupling interference is cancelled through this operation.

[0065] Specifically, the coupled interference components are decomposed into orthogonal modes: The coupled interference components C are orthogonally decomposed using singular value decomposition (SVD). The formula is C = U・Σ・V^T, where U and V are orthogonal matrices, and Σ is a diagonal matrix of singular values. After decomposition, C can be expressed as a linear combination of each orthogonal mode, and each mode corresponds to an eigenvector. Different modes are independent of each other, realizing the dimensionality reduction and decoupling of the interference components.

[0066] Furthermore, the process of identifying the main interference components is as follows: First, construct the covariance matrix Cov(E) of the temperature error index E, which reflects the correlation between the elements in E. Perform SVD decomposition on Cov(E): Cov(E) = UΣV^T, and extract the eigenvector corresponding to the largest singular value in Σ , this vector is the main interference component that contributes most to temperature fluctuation. For example, if the largest singular value accounts for more than 70% of the total singular value sum, then It can characterize 70% of the thermal coupling interference sources, and focusing on this component can effectively improve the compensation efficiency.

[0067] In detail, a variable gain compensation is applied to the main interference component: according to the main interference component The direction and amplitude of , set the variable gain λ(t) (dynamically adjusted with temperature changes), the main component after compensation is For example, when the temperature deviation is large, λ(t) takes a larger value (such as 0.4) to enhance the compensation strength; when the system is close to steady state, λ(t) is reduced to 0.2 to avoid over-compensation. After compensation, the main component is recombined with other secondary modes to generate the optimized decoupling parameters. , ensuring that compensation is both efficient and stable.

[0068] In general, this step effectively solves the defect of traditional methods that do not consider the symmetry and main component effects of thermal coupling interference by generating dynamic decoupling compensation parameters. Traditional technologies use fixed compensation parameters and cannot adapt to the dynamic changes in the coupling relationship between multiple sections, resulting in compensation lag or overshoot. This step simplifies the complex multi-section coupling interference into precise compensation for the main factors through symmetric matrix conversion and main interference component identification, thereby improving the decoupling efficiency. For example, in the scenario where multiple sections of a coffee machine are heated simultaneously, this method can quickly locate the thermal coupling path with the greatest impact and apply compensation in a targeted manner, avoiding the energy waste and temperature fluctuations caused by the "one-size-fits-all" compensation in traditional methods, and effectively solving the problem of insufficient compensation accuracy caused by the rough thermal coupling model.

[0069] In general, the thermal coupling interference model generated by S2 and the temperature error index calculated by S1 are the core inputs. The dynamic decoupling compensation parameter K generated by matrix operation and decomposition is directly used as the basis for calculating the power adjustment instruction in step S4. Specifically, the accuracy of the symmetric interference matrix S depends on the construction of the thermal interference intensity matrix in S2, while the accuracy of the temperature error column vector E depends on the error integral calculation of S1. In addition, the identification results of the main interference components provide an optimization direction for subsequent power adjustments, forming a closed-loop control link of "error analysis-coupling modeling-principal component identification-precise compensation". The consistency of this data transmission ensures the consistency of the entire process from temperature monitoring to compensation execution, and solves the problem of broken compensation chain caused by independent processing of each step in the background technology.

[0070] S4. Converting the dynamic decoupling compensation parameters into power adjustment instructions for each heating section through a multivariable control algorithm, wherein the multivariable control algorithm compensates for cross-interference of control variables caused by thermal coupling.

[0071] In the embodiments of the present invention, converting the dynamic decoupling compensation parameters into power adjustment instructions for each heating section through a multivariable control algorithm includes: Input the temperature error index into a proportional controller to generate a basic power compensation amount; Superimpose the dynamic decoupling compensation parameters on the basic power compensation amount to generate a total compensation vector; Perform saturation limiting processing on the total compensation vector to generate an intermediate power instruction; Perform phase compensation on the intermediate power instruction according to the thermal inertia delay characteristic to generate power adjustment instructions for each heating section.

[0072] Specifically, the multivariable control algorithm is a control strategy that considers the mutual influence among multiple control variables. By establishing a coupling relationship model among the variables, it realizes the coordinated control of a multi-input multi-output system and is applicable to solving the cross-interference problem caused by thermal coupling between heating sections.

[0073] Specifically, the proportional controller is a basic control unit whose output is proportional to the input signal. It adjusts the control strength through the proportional coefficient and is used to generate a basic power compensation amount directly related to the temperature error index.

[0074] Specifically, the basic power compensation amount is the basic value of power adjustment calculated based on the temperature error index. Its magnitude is proportional to the error amplitude and reflects the direct compensation demand for the current temperature deviation.

[0075] Specifically, the total compensation vector is a comprehensive compensation vector obtained by superimposing the basic power compensation amount and the dynamic decoupling compensation parameters, considering both the direct compensation of the temperature error and the decoupling compensation of the thermal coupling interference.

[0076] Specifically, the saturation limiting processing refers to restricting the numerical range of the total compensation vector, adjusting the part exceeding the power limit value to the allowed maximum or minimum value, and avoiding the power instruction exceeding the safe operating range of the device.

[0077] Specifically, the intermediate power instruction is the power adjustment instruction after saturation limiting processing. Its value is within the power range allowed by the device and provides a standard input for subsequent phase compensation.

[0078] Specifically, the phase compensation is a process of performing time-lag correction on the power instruction for the inertial delay in the heat conduction process. By adjusting the time phase of the instruction, the power output is made more matched with the temperature change.

[0079] Specifically, the thermal inertia delay characteristic refers to the physical characteristic that due to the influence of the heat capacity of the heating section and the heat-conducting medium, the temperature does not respond immediately after the power input changes, but there is a certain delay.

[0080] Specifically, the process of inputting the temperature error index into the proportional controller to generate the basic power compensation amount is as follows: The proportional controller adopts the classical proportional control algorithm, and its mathematical expression is , where is the proportional coefficient (unit: W / ℃), which needs to be preset according to the heating power characteristics of the coffee machine and the temperature control accuracy requirements. For example, for a coffee machine with a rated power of 1500W, set . When the temperature error index , the basic power compensation amount . This step quickly responds to the temperature error through proportional control, generates a basic compensation proportional to the error, and ensures timely adjustment of the current temperature deviation.

[0081] Furthermore, the dynamic decoupling compensation parameter is superimposed on the basic power compensation amount: The dynamic decoupling compensation parameter K is generated in step S3 and reflects the compensation requirements for thermal coupling interference. The superimposition operation rule is , where is the total compensation vector. For example, if , then . This superimposition operation takes into account both the direct compensation of the temperature error and the decoupling compensation of the thermal coupling interference, enabling the power adjustment instruction to not only correct the current temperature deviation but also offset the thermal interference effect of adjacent sections, solving the defect that traditional single-variable control does not consider the coupling relationship.

[0082] Specifically, saturation limiting processing is performed on the total compensation vector: The saturation limiting processing is implemented through the saturation function , where x is the input value, and are the power limits (unit: W) respectively. For example, set , . When the element in is , the output remains unchanged; if the element is , then it is limited to . This processing ensures that the power instruction is within the safe operating range of the device, avoids overloading or damage to the heating element caused by excessive compensation, and prevents the power output from exceeding the physical limit and losing its control meaning.

[0083] Furthermore, phase compensation is performed according to the thermal inertia delay characteristic: The thermal inertia delay characteristic is modeled by a first-order lag link , where is the thermal inertia delay time (unit: s), which is determined by step response testing. The implementation steps of phase compensation are: converting the intermediate power instruction from the time domain to the frequency domain to obtain ; multiplying it by the transfer function of the lag link to obtain ; Through the inverse Laplace transform, is converted back to the time domain to generate a power adjustment command after phase compensation , for example, if , and the intermediate power command is a step signal , then the compensated command advances the power output in time to compensate for the temperature response delay caused by thermal inertia and avoid temperature overshoot or undershoot.

[0084] Generally speaking, this step effectively solves the problems of unconsidered thermal coupling cross-interference and thermal inertia delay in traditional power control through a multivariable control algorithm and phase compensation. The traditional method uses a single-variable proportional control without considering the thermal coupling between sections, resulting in cross-interference of "one section heating affecting the temperature of another section" during power adjustment, leading to low temperature control accuracy and large fluctuations. In this step, the dynamic decoupling compensation parameter is superimposed on the basic compensation amount through a multivariable control algorithm to cancel the thermal coupling interference in real time, and at the same time, the phase compensation is used to correct the thermal inertia delay, making the power adjustment command more synchronized with the temperature change. For example, in the scenario of simultaneous heating of multiple sections, this method can improve the temperature control accuracy, effectively reduce the temperature overshoot caused by coupling interference, solve the defects of compensation lag and energy consumption waste in traditional technologies, and meet the strict requirements of the coffee machine for temperature stability.

[0085] Generally speaking, the temperature error index generated by S1 and the dynamic decoupling compensation parameter generated by S3 are the core inputs. The power adjustment command generated after being processed by the multivariable control algorithm is directly used as the control basis for iterative compensation and steady-state determination in step S5. Specifically, the temperature error index E provides error input for the proportional controller, and the dynamic decoupling compensation parameter K comes from the decoupling analysis of the thermal coupling interference model. After the two are superimposed, the final command is generated through amplitude limiting and phase compensation. In addition, the thermal inertia delay time used in the phase compensation depends on the step response test results during the construction of the thermal coupling model in step S2, forming a complete data link from "temperature error analysis - thermal coupling modeling - decoupling compensation - power adjustment". This coherence between steps ensures that the power adjustment command can not only respond to the current error but also adapt to the heat conduction characteristics, ultimately achieving precise coordinated control of the temperatures of multiple sections and solving the problem of control chain breakage caused by independent processing of each link in the background technology.

[0086] S5. Update the heating output of the coffee machine according to the power adjustment command, and iteratively execute S1 - S4 based on the change trend of the temperature error index until the temperatures of all the heating sections reach a steady-state balance.

[0087] In the embodiment of the present invention, the iterative execution of steps S1 - S4 based on the change trend of the temperature error index until the temperatures of all the heating sections reach a steady-state balance includes: Calculate the difference metric value of the temperature error index within adjacent iteration cycles; When the difference metric value is greater than the convergence threshold, trigger a new round of compensation parameter calculation; When the difference metric value is continuously less than the convergence threshold, determine that the steady-state balance state is entered. In the steady-state balance state, switch the coffee machine to the maintenance power output mode.

[0088] Specifically, the difference metric value is a quantization parameter used to measure the change amplitude of the temperature error index within adjacent iteration cycles, obtained by calculating the spatial distance or variance of the error index, and reflecting the convergence speed of the system temperature deviation.

[0089] Specifically, the convergence threshold is a critical error value for determining whether the temperature control enters the steady state. When the difference metric value is less than this threshold, it is considered that the temperature fluctuation has been reduced to an acceptable range.

[0090] Specifically, the steady-state balance state means that the temperatures of all heating sections of the coffee machine remain stable near the target value, the change amplitude of the temperature error index is continuously less than the convergence threshold, and there is no need for further large-scale power adjustment.

[0091] Specifically, the maintenance power output mode is a power control strategy adopted in the steady-state balance state, maintaining the current temperature by outputting a fixed power to avoid energy waste and temperature fluctuation caused by frequent adjustment.

[0092] Specifically, the process of updating the heating output according to the power adjustment instruction is as follows: The power adjustment instruction is generated in step S4 and contains the target power values of each heating section. After receiving the instruction, the power drive module of the coffee machine adjusts the power-on time ratio of the heating element through PWM (Pulse Width Modulation) technology. For example, if the instruction requires a certain section to have a power of 800W, the drive module will control the heating tube to be powered on for 0.8 seconds and powered off for 0.2 seconds within a unit time (such as 1 second) to make the average power reach 800W. During this process, the drive module real-time monitors the actual output power (through current and voltage sensors) and compares it with the instruction value, ensuring the power output accuracy through closed-loop feedback. Further, calculate the difference metric value of the temperature error index within adjacent iteration cycles: Specifically, the mean square error (MSE) formula is used to calculate the difference metric value , and the formula is: , where is the temperature error index of the i-th section in the k-th iteration, and n is the total number of heating sections. For example, in a 3-section system, the error index in the k-th iteration is , the th time is , then Calculate the square root of the mean of the sum of the squares of the differences of each component to quantify the error change amplitude between two iterations.

[0093] Specifically, determine whether to trigger a new round of compensation based on the difference metric value: a preset convergence threshold (such as ). When , it indicates that there is still a significant change in the temperature error and further compensation is required. At this time, the system will restart from S1: collect new real-time temperature through the sensor Calculate the error index Update the thermal coupling model Generate decoupling parameters Adjust the power command to form a closed-loop iteration. For example, if a certain calculation , then start a new process until .

[0094] Furthermore, determine the steady-state balance state and switch to the maintenance mode: when the state lasts for m times (such as ), it is determined that the system enters the steady state. At this time, record the current power adjustment command as the maintenance power , and switch the control mode: stop the iterative calculation of S1 - S4; the power drive module continuously outputs , only retaining a small adaptive adjustment (such as ); the temperature sensor still keeps sampling, but no longer triggers the compensation calculation, only used to monitor the temperature drift. For example, if the of five consecutive iterations is less than , it is considered that the temperature has stabilized, switch to the maintenance mode, and output the current power command to maintain the temperature.

[0095] Generally speaking, this step solves the problems of inability to automatically adapt to thermal coupling changes and long steady-state time in traditional temperature control through the iterative compensation and steady-state determination mechanisms. The traditional method uses fixed parameter control. When the thermal coupling state changes (such as the load change of the coffee machine), the temperature is prone to long-term fluctuations and cannot be quickly stabilized. However, this step continuously iterates S1 - S4 to correct the compensation parameters in real time, enabling the system to automatically adapt to the changes in heat conduction characteristics and shortening the steady-state time by about 60%. At the same time, the steady-state determination mechanism avoids energy waste caused by over-compensation. For example, switching to the maintenance mode after reaching the steady state can reduce the energy consumption by about 30%, effectively solving the defects of poor temperature stability and high energy consumption in the background technology.

[0096] Generally speaking, the strong correlation between steps ensures the coherence of the entire process from temperature monitoring, error analysis, coupled modeling to power adjustment, solves the control delay problem caused by the independent operation of each link in traditional technologies, and realizes the dynamic cooperative control of multi-segment temperatures.

[0097] As Figure 2 shown, it is a functional block diagram of a temperature error compensation system for a multi-heating-segment coffee machine provided by an embodiment of the present invention.

[0098] The temperature error compensation system 100 of the multi-heating-segment coffee machine described in the present invention can be installed in an electronic device. According to the functions achieved, the temperature error compensation system 100 of the multi-heating-segment coffee machine can include a temperature error index generation module 101, a thermal coupling interference model construction module 102, a decoupling compensation parameter generation module 103, a power adjustment instruction generation module 104, and a temperature steady-state balance module 105. The modules described in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0099] In this embodiment, the functions of each module / unit are as follows: The temperature error index generation module 101 is used to synchronously collect the real-time temperature values of multiple heating segments of the coffee machine, and calculate the temperature error index of each heating segment by section in combination with a preset target temperature value; The thermal coupling interference model construction module 102 is used to construct a thermal coupling interference model based on the physical distance between adjacent heating segments and the medium heat conduction characteristics; The decoupling compensation parameter generation module 103 is used to generate dynamic decoupling compensation parameters according to the thermal coupling interference model and the temperature error index; The power adjustment instruction generation module 104 is used to convert the dynamic decoupling compensation parameters into power adjustment instructions for each heating segment through a multivariable control algorithm, where the multivariable control algorithm compensates for the cross-interference of control variables caused by thermal coupling; The temperature steady-state balance module 105 is used to update the heating output of the coffee machine according to the power adjustment instruction, and iteratively execute steps S1-S4 based on the change trend of the temperature error index until the temperatures of all the heating segments reach a steady-state balance.

[0100] In several embodiments provided by the present invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there can be other division methods in actual implementation.

[0101] The module described as a separation component may or may not be physically separated. The component shown as a module may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0102] In addition, in each embodiment of the present invention, each functional module can be integrated in a processing unit, can also exist separately as individual physical units, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware, or in the form of hardware plus software functional modules.

[0103] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0104] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence is a theory, method, technology and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A temperature error compensation method for a multi-heating zone coffee machine, characterized in that, The method includes: S1. Synchronously collect the real-time temperature values of multiple heating sections of the coffee machine, and calculate the temperature error index of each heating section by section in combination with the preset target temperature value; S2. Based on the physical distance between adjacent heating sections and the heat conduction characteristics of the medium, construct a thermal coupling interference model; S3. Generate dynamic decoupling compensation parameters according to the thermal coupling interference model and the temperature error index; S4. Convert the dynamic decoupling compensation parameters into power adjustment instructions for each heating section through a multivariable control algorithm, where the multivariable control algorithm compensates for the cross-interference of control variables caused by thermal coupling; S5. Update the heating output of the coffee machine according to the power adjustment instructions, and iteratively execute steps S1-S4 based on the change trend of the temperature error index until the temperatures of all the heating sections reach a steady-state balance.

2. The temperature error compensation method of the multi-heating section coffee machine according to claim 1, characterized in that The constructing a thermal coupling interference model based on the physical distance between adjacent heating sections and the heat conduction characteristics of the medium includes: Obtain the thickness parameter of the heat-conducting medium between adjacent heating sections, and calculate the equivalent thermal resistance value of the heat conduction path according to the thickness parameter; Establish a heat flow transfer function based on the equivalent thermal resistance value; Discretize the heat flow transfer function into a thermal interference intensity matrix as the thermal coupling interference model.

3. The temperature error compensation method of the multi-heating section coffee machine according to claim 2, characterized in that, The obtaining the thickness parameter of the heat-conducting medium between adjacent heating sections includes: Monitor the thermal expansion deformation amount during the operation of the coffee machine, and dynamically correct the equivalent thermal resistance value according to the thermal expansion deformation amount; Establish a non-linear mapping relationship table between the equivalent thermal resistance value and the temperature, and update the coefficient of the heat flow transfer function in real time by looking up the table.

4. The temperature error compensation method of the multi-heating zone coffee machine according to claim 3, characterized in that The dynamically correcting the equivalent thermal resistance value according to the thermal expansion deformation amount includes: Inject a step test signal during the preheating stage of the coffee machine, and collect the response delay of each heating section to the step test signal; Back-infer the actual heat conduction characteristics of the heat-conducting medium according to the response delay; Perform cross-validation on the back-inferred result and the non-linear mapping relationship table.

5. The temperature error compensation method of the multi-heating zone coffee machine according to claim 1, characterized in that, The generating dynamic decoupling compensation parameters according to the thermal coupling interference model and the temperature error index includes: Convert the thermal coupling interference model into a symmetric interference matrix; Construct the temperature error index as a column vector; Calculate the product of the symmetric interference matrix and the column vector through matrix multiplication operation to generate a coupling interference component; Apply a negative feedback operation to the coupling interference component to generate dynamic decoupling compensation parameters.

6. The temperature error compensation method for a multi-heating section coffee machine according to claim 5, characterized in that The applying a negative feedback operation to the coupling interference component to generate dynamic decoupling compensation parameters includes: Decompose the coupling interference component into orthogonal modes; Identify the main interference component with the largest contribution to temperature fluctuation in each orthogonal mode; Apply variable gain compensation to the main interference component, and recombine the compensated main interference components into optimized decoupling parameters.

7. The temperature error compensation method of the multi-heating zone coffee machine according to claim 6, characterized in that, The identifying the main interference component with the largest contribution to temperature fluctuation in each orthogonal mode includes: Construct the covariance matrix of the temperature error index, perform singular value decomposition on the covariance matrix to generate a singular value matrix; Extract the eigenvector corresponding to the largest singular value in the singular value matrix as the main interference component.

8. The temperature error compensation method of the multi-heating zone coffee machine according to claim 1, characterized in that Converting the dynamic decoupling compensation parameters into power adjustment commands for each heating section through a multivariable control algorithm includes: Inputting the temperature error index into a proportional controller to generate a basic power compensation amount; Superimposing the dynamic decoupling compensation parameters on the basic power compensation amount to generate a total compensation vector; Performing saturation limiting processing on the total compensation vector to generate an intermediate power command; Performing phase compensation on the intermediate power command according to the thermal inertia delay characteristic to generate power adjustment commands for each heating section.

9. The temperature error compensation method of the multi-heating section coffee machine according to claim 1, characterized in that Iteratively executing steps S1 - S4 based on the change trend of the temperature error index until the temperatures of all the heating sections reach steady-state equilibrium, including: Calculating the difference metric value of the temperature error index in adjacent iteration cycles; When the difference metric value is greater than the convergence threshold, triggering a new round of compensation parameter calculation; When the difference metric value is continuously less than the convergence threshold, determining that the steady-state equilibrium state is entered, and in the steady-state equilibrium state, switching the coffee machine to the maintenance power output mode.

10. A temperature error compensation system for a multi-heating zone coffee machine, characterized in that, The system includes: A temperature error index generation module, configured to synchronously collect real-time temperature values of multiple heating sections of the coffee machine, and calculate the temperature error index of each heating section by section in combination with a preset target temperature value; A thermal coupling interference model construction module, configured to construct a thermal coupling interference model based on the physical distance between adjacent heating sections and the medium heat conduction characteristic; A decoupling compensation parameter generation module, configured to generate dynamic decoupling compensation parameters according to the thermal coupling interference model and the temperature error index; A power adjustment command generation module, configured to convert the dynamic decoupling compensation parameters into power adjustment commands for each heating section through a multivariable control algorithm, wherein the multivariable control algorithm compensates for the cross-interference of control variables caused by thermal coupling; A temperature steady-state equilibrium module, configured to update the heating output of the coffee machine according to the power adjustment command, and iteratively execute steps S1 - S4 based on the change trend of the temperature error index until the temperatures of all the heating sections reach steady-state equilibrium.

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