Temperature control method, device, equipment, system, storage medium and program product

Abstract

The invention provides a temperature control method, device, equipment and system, a storage medium and a program product, and relates to the technical field of industrial control, and the method comprises the steps: determining a PID parameter of a temperature controller of a controlled object; and based on the obtained current environment temperature of the controlled object and the target control temperature of the controlled object, carrying out adaptive adjustment on PID parameters of the temperature controller according to a fuzzy PID control algorithm. And the temperature controller is adjusted according to the PID parameters after self-adaptive adjustment, and temperature control is carried out on the controlled object according to the adjusted temperature controller. According to the invention, the PID parameters of the temperature control system are adaptively adjusted according to the fuzzy PID control algorithm, so that the PID parameters can adapt to the dynamic change of the environment temperature of the system, the overshoot of the system can be reduced, the reaction time of the system can be shortened, and the system can accurately control the temperature of the controlled object under the variable working condition or multi-disturbance condition.

Description

Technical Field

[0001] The present application relates to the field of industrial control technology, and in particular to temperature control methods, devices, equipment, systems, storage media and program products. Background Art

[0002] At present, most temperature control methods use PID control. PID control is a control strategy widely used in industrial control systems. It automatically adjusts the controller output by calculating the response of the three basic elements of "proportional", "integral", and "derivative", so that the actual output response of the controlled system reaches or approaches the desired set value.

[0003] PID controller is simple and easy to implement, but in some applications with high precision requirements, its control response speed and overshoot control are often difficult to achieve ideal state. And the parameters (proportional, integral, differential) of PID controller need to be precisely adjusted according to the specific application, which is particularly complicated in variable working conditions or multiple disturbances. Summary of the invention

[0004] The present application provides a temperature control method, device, equipment, system, storage medium and program product, which are used to provide a technical solution that can achieve precise temperature control under variable operating conditions or multiple disturbances.

[0005] In a first aspect, the present application provides a temperature control method for controlling the temperature of a controlled object, the method comprising:

[0006] Determine PID parameters of a temperature controller of the controlled object.

[0007] Based on the acquired current ambient temperature of the controlled object and the target control temperature of the controlled object, the PID parameters of the temperature controller are adaptively adjusted according to a fuzzy PID control algorithm.

[0008] The temperature controller is adjusted according to the adaptively adjusted PID parameters, and the temperature of the controlled object is controlled according to the adjusted temperature controller.

[0009] In a possible implementation manner, determining the PID parameters of the temperature control system of the controlled object includes:

[0010] According to the simulated annealing PID algorithm, the PID parameters of the temperature control system of the controlled object are determined.

[0011] In a possible implementation, in the simulated annealing PID algorithm, the performance index of the current temperature control system is evaluated according to the time-weighted absolute error integral.

[0012] The current temperature control system is a temperature control system determined according to current PID parameters.

[0013] In a possible implementation, in the simulated annealing PID algorithm, based on the Metropolis criterion, the current PID parameters are updated according to the new PID parameters.

[0014] The new PID parameters are PID parameters obtained after randomly perturbing the current PID parameters.

[0015] In a possible implementation, in the simulated annealing PID algorithm, the temperature reduction function is determined to be an exponential temperature reduction function.

[0016] In a possible implementation, the adaptively adjusting the PID parameters of the temperature control system according to the fuzzy PID control algorithm based on the acquired current ambient temperature of the controlled object and the target control temperature of the controlled object includes:

[0017] When the current ambient temperature of the controlled object is different from the target control temperature of the controlled object, the PID parameters of the temperature control system are adaptively adjusted according to the fuzzy PID control algorithm to keep the temperature of the controlled object at the target control temperature.

[0018] In a possible implementation, in the fuzzy PID control algorithm, a current error of the fuzzy PID control algorithm is determined according to a current ambient temperature of the controlled object and a target control temperature of the controlled object;

[0019] And based on at least two of the current errors determined during the temperature control of the controlled object, a current error change rate of the fuzzy PID control algorithm is determined.

[0020] In a possible implementation manner, the membership function of the fuzzy PID control algorithm is determined to be a triangular membership function.

[0021] In a second aspect, the present application provides a temperature control device for controlling the temperature of a controlled object, the device comprising:

[0022] The determination module is used to determine the PID parameters of the temperature control system of the controlled object.

[0023] The adjustment module is used to adaptively adjust the PID parameters of the temperature control system according to a fuzzy PID control algorithm based on the acquired current ambient temperature of the controlled object and the target control temperature of the controlled object.

[0024] The control module adjusts the temperature control system according to the adaptively adjusted PID parameters, and performs temperature control on the controlled object according to the adjusted temperature control system.

[0025] In a third aspect, the present application provides a temperature control device, comprising: a processor, and a memory communicatively connected to the processor;

[0026] The memory stores computer-executable instructions;

[0027] The processor executes the computer-executable instructions stored in the memory to implement the method in the first aspect.

[0028] In a fourth aspect, the present application provides a temperature control system, the system comprising: a controlled object and the temperature control device described in the third aspect, the temperature control device being used to perform temperature control on the controlled object.

[0029] In a fifth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method in the first aspect.

[0030] In a sixth aspect, the present application provides a computer program product, comprising a computer program, which implements the method in the first aspect when executed by a processor.

[0031] The technical solution provided by the present application first determines the PID parameters of the temperature control system of the controlled object, and then uses the temperature control system to control the temperature of the controlled object. During the control process, the present application adaptively adjusts the PID parameters of the temperature control system according to the fuzzy PID control algorithm based on the current ambient temperature of the controlled object and the target control temperature of the controlled object, so that the PID parameters can adapt to the dynamic changes of the system ambient temperature, thereby reducing the overshoot of the system and the reaction time of the system, so that the system can accurately control the temperature of the controlled object under variable operating conditions or multiple disturbances. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0033] Figure 1 A flow chart of a temperature control method provided in an embodiment of the present application;

[0034] Figure 2 A structural diagram of a temperature control device provided in an embodiment of the present application;

[0035] Figure 3 A structural diagram of a temperature control device provided in an embodiment of the present application.

[0036] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0037] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art to which the present application belongs. The terms used herein in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. It is understood that the terms "first", "second", etc. used in the present application can be used to describe various information or data in this article, but these elements are not limited by these terms. These terms are only used to distinguish the first information from another information. For example, without departing from the scope of the present application, the first action information can be referred to as the second action information, and similarly, the second action information can be referred to as the first action information. Both the first action information and the second action information are action information, but they are not the same action information.

[0039] First, the terms involved in this application are explained:

[0040] Simulated annealing PID algorithm: It is a hybrid control algorithm that combines simulated annealing algorithm with traditional PID control. Simulated annealing algorithm is a global optimization algorithm based on physical annealing process, which can effectively avoid local optimal solution and find global optimal solution. Combining it with PID control, the parameters of PID controller can be adjusted dynamically to improve the control performance of the system.

[0041] Fuzzy PID control algorithm: Based on traditional PID control, fuzzy logic is introduced to deal with uncertainty and nonlinear problems. It processes the input signal (error and error change rate) through fuzzification, uses fuzzy rules for reasoning, and then obtains accurate control output through defuzzification to achieve real-time adjustment of PID parameters.

[0042] At present, most temperature control methods use PID control. PID control is a control strategy widely used in industrial control systems. It automatically adjusts the controller output by calculating the response of the three basic elements of "proportional", "integral", and "derivative", so that the actual output response of the controlled system reaches or approaches the desired set value.

[0043] PID controller is simple and easy to implement, but in some applications with high precision requirements, its control response speed and overshoot control are often difficult to achieve ideal state. And the parameters (proportional, integral, differential) of PID controller need to be precisely adjusted according to the specific application, which is particularly complicated in variable working conditions or multiple disturbances.

[0044] Based on this, the embodiments of the present application provide a temperature control method, device, equipment, system, storage medium and program product, which are used to adaptively adjust the temperature control system of the controlled object (referred to as the system) using fuzzy PID control, so that the PID parameters can better adapt to the dynamic changes of the system, reduce the overshoot of the system, and reduce the system response time.

[0045] The structure and principle of the technical solution provided by this application are described in detail below with reference to the accompanying drawings.

[0046] In a first aspect, the present application provides a temperature control method for controlling the temperature of a controlled object.

[0047] Optionally, the controlled object may include a MEMS device, such as a MEMS resonator. The temperature control of the controlled object may be constant temperature control of the controlled object.

[0048] Reference Figure 1 , the above method may include the following steps:

[0049] S101, determining PID parameters of a temperature control system of a controlled object.

[0050] Optionally, the embodiment of the present application may adopt any suitable PID algorithm to determine the PID parameters of the temperature control system of the controlled object.

[0051] It should be understood that the PID algorithm is a classic control method widely used in industrial control systems, which can achieve effective control of the system. Based on this, this embodiment can achieve effective control of the system and further accurately control the temperature of the controlled object.

[0052] S102 , based on the acquired current ambient temperature of the controlled object and the target control temperature of the controlled object, adaptively adjust the PID parameters of the temperature control system according to the fuzzy PID control algorithm.

[0053] It should be understood that the controlled object is usually in an environment with changing temperature. During the process of temperature control of the controlled object, changes in the ambient temperature often affect the accuracy of temperature control of the controlled object.

[0054] Based on this, in the process of using the above-mentioned temperature control system to control the temperature of the controlled object, the present application uses a fuzzy PID control algorithm to adaptively adjust the PID parameters of the temperature control system based on the current ambient temperature of the controlled object and the target control temperature of the controlled object, so that the PID parameters can adapt to the dynamic changes in the ambient temperature of the system, thereby enabling the temperature control system to accurately control the temperature of the controlled object under variable operating conditions or multiple disturbances.

[0055] S103, adjusting the temperature control system according to the adaptively adjusted PID parameters, and performing temperature control on the controlled object according to the adjusted temperature control system.

[0056] Optionally, the PID parameters adjusted after the adaptive adjustment are applied to the PID controller, the control output is calculated using the adjusted PID controller, the control output is applied to the temperature control system, and the power of the heater or cooler is adjusted to change the temperature of the controlled object. Repeat the above steps, adjust the PID parameters and control output in real time, and ensure that the temperature of the controlled object is stable near the target temperature.

[0057] Based on this, the adaptive adjustment of the temperature control system based on the fuzzy PID control algorithm can be realized, and the real-time temperature control of the controlled object can be performed.

[0058] In an optional embodiment, determining the PID parameters of the temperature control system of the controlled object includes: determining the PID parameters of the temperature control system of the controlled object according to a simulated annealing PID algorithm.

[0059] It should be understood that traditional PID control often relies on the experience of engineers for engineering tuning. This embodiment uses the simulated annealing PID algorithm to determine the value of the PID parameter, replacing the engineering tuning method that requires the experience of engineers, and the system stability is also higher.

[0060] Among them, the simulated annealing algorithm (SA) is a heuristic search algorithm that simulates the annealing process of solid materials and performs global optimization search in the search space to find the approximate optimal solution of the problem. The simulated annealing algorithm allows the algorithm to jump out of the local optimal solution during the search process by controlling the change of parameters, so that it is possible to find the global optimal solution. The characteristic of this algorithm is that it can find an approximate optimal solution within a certain computational cost. Although it does not necessarily guarantee the absolute optimal solution, it has shown good results in many practical applications.

[0061] PID controllers are widely used in industrial control systems, but the tuning of their parameters is often a challenge because it is necessary to balance multiple factors such as system stability, response speed, and overshoot. The simulated annealing algorithm sets initial parameters (such as population size, maximum number of iterations, etc.) and defines a fitness function to evaluate the performance of PID parameters, and then iterates and optimizes in the search space until a set of PID parameters that meet the system requirements is found.

[0062] Therefore, the simulated annealing PID algorithm can search in a larger parameter space, avoid falling into the local optimum, and find better PID parameter settings, thereby improving the performance of the control system.

[0063] Based on this, the embodiment of the present application first uses the simulated annealing PID algorithm to determine the values ​​of the initial P, I, and D parameters, and then uses the fuzzy PID algorithm to adaptively control them. In other words, the embodiment of the present application constructs a hybrid control strategy that combines the global search capability of simulated annealing and the strong adaptability and good fault tolerance of fuzzy logic.

[0064] The above content describes the overall structure of the embodiment of the present application, and the following part focuses on a detailed description of the simulated annealing PID algorithm and the fuzzy PID control algorithm.

[0065] First, the simulated annealing PID algorithm is described:

[0066] Optionally, the simulated annealing PID algorithm includes the following steps:

[0067] Step 1: Initialization:

[0068] Set the initial parameters, including the initial PID parameters, initial temperature, cooling efficiency, termination temperature, and maximum number of iterations. The initial PID parameters can be randomly generated or set based on experience. The initial temperature can be set to a higher temperature to allow a larger search range and accept poorer solutions in the early stages of the algorithm. The cooling efficiency is used to determine how the temperature decreases over time. Common cooling efficiencies include exponential decay, linear decay, etc.

[0069] The second step is to evaluate the current PID parameters:

[0070] Calculate performance indicators: Set up the temperature control system using the current PID parameters and evaluate its performance. Performance can be measured in many ways, such as overshoot, rise time, settling time, steady-state error, etc.

[0071] Record the best PID parameters: In each iteration, record and update the determined best PID parameters.

[0072] Generate new PID parameters: Make small random disturbances to the current PID parameters to generate new PID parameters. The disturbance amplitude is controlled by the current "temperature". The higher the temperature, the greater the disturbance allowed.

[0073] Calculate new performance indicators: Calculate new performance indicators of the temperature control system using new PID parameters.

[0074] Conditions for accepting new PID parameters: If the new PID parameters have better performance, then the new PID parameters are accepted, or even if the new PID parameters are not better than the current PID parameters, then the new PID parameters are accepted according to a certain probability.

[0075] Update current parameters and performance indicators: If the new PID parameters are accepted, the current PID parameters are updated according to the new PID parameters, and the current performance indicators are calculated according to the new PID parameters. If the new PID parameters are not accepted, there is no need to update the current PID parameters or recalculate the current performance indicators.

[0076] Update current temperature: Update the current temperature according to the above cooling rate.

[0077] Termination condition: the temperature drops to the termination temperature or the number of iterations reaches the maximum number of iterations.

[0078] The final optimized PID parameters are output. This set of PID parameters is the best parameter for performance evaluation during the entire iteration process.

[0079] In the embodiment of the present application, in the above-mentioned simulated annealing PID algorithm, the performance index of the current temperature control system can be evaluated according to the integral of time-weighted absolute error (ITAE), wherein the current temperature control system is a temperature control system determined according to the current PID parameters.

[0080] The time-weighted absolute error integral is defined as follows: ITAE = ∑T1 × e(t)dt; where T1 is time and e(t) is the error of the system at time t.

[0081] It should be understood that the time-weighted absolute error integral is an indicator for evaluating the performance of a control system. Unlike other performance indicators (such as integrated absolute error IAE, integrated square error ISE, etc.), ITAE adds a time weight on the basis of the error, so that the error of the system in the early stage has a greater impact on the overall performance. This weight mechanism encourages the system to reduce the error as soon as possible, thereby improving the response speed and stability of the system. Therefore, the use of ITAE in the embodiment of the present application can provide the response speed and stability of the temperature control system, thereby achieving more accurate temperature control of the controlled object.

[0082] In one embodiment, in the simulated annealing PID algorithm, based on the Metropolis criterion, the current PID parameters are updated according to the new PID parameters; wherein the new PID parameters are PID parameters obtained after disturbing the current PID parameters.

[0083] Among them, the Metropolis Criterion is an important criterion in the Monte Carlo Method. The basic idea is to explore the state space of a complex system through random sampling, and accept or reject new states according to a certain probability to achieve an equilibrium state or find the global optimal solution.

[0084] Optionally, in this embodiment, if the new PID parameters have better performance, the new PID parameters are accepted; if the new PID parameters are not better than the current PID parameters, the new PID parameters are accepted using the Metropolis criterion.

[0085] The Metropolis criterion can be characterized as: ? ? (? ?, ? ?′, ? ?2) = exp(-(? ?′-? ?) / ? ?2), where ? ?, ? ?′ are the performance indicators of the current PID parameters and the new PID parameters respectively, and ? ?2 is the current temperature.

[0086] It should be understood that the Metropolis criterion can avoid falling into the local optimal solution, and accept the poor solution with a certain probability, so as to have the opportunity to jump out of the local minimum and gradually approach the global optimal solution. Therefore, the PID parameters determined in this embodiment can approach the global optimal PID parameters to perform more accurate temperature control on the controlled object.

[0087] Optionally, in the simulated annealing PID algorithm, the cooling function is an exponential cooling function.

[0088] The expression of the exponential cooling function is: T k =T s α k , where k is the number of iterations, α is the cooling coefficient, Ts is the initial temperature, T k It is the temperature after each iteration.

[0089] The value of α is usually between 0 and 1. Optionally, α is 0.95. s is 1000℃.

[0090] Among them, in each iteration of the exponential cooling function, the temperature will gradually decrease in the form of an exponential function. Selecting the appropriate initial temperature and cooling coefficient is the key to the performance of the algorithm, because too high an initial temperature may cause the algorithm to converge too slowly, and too low an initial temperature may cause the algorithm to fall into a local optimal solution too early. Therefore, this embodiment can ensure that the determined PID parameters are the globally optimal PID parameters.

[0091] Then, the fuzzy PID algorithm is described:

[0092] The fuzzy PID algorithm includes the following steps:

[0093] 1. Model definition

[0094] Determine the input and output, analyze the temperature control system, and determine the input and output of the PID controller. For a PID controller, the input is usually the error e(t) and its rate of change Δe(t). For example: the error e(t) can be the difference between the current ambient temperature and the target control temperature, and the error change rate Δe(t) can be the degree of change of the error.

[0095] The output is the control parameter of the PID controller, which can be P, I, or D gain.

[0096] 2. Design of fuzzy controller

[0097] Determine fuzzy sets: Define fuzzy sets and membership functions for inputs (error and error rate) and outputs (P, I, D gains).

[0098] Formulate fuzzy rules: Based on the performance requirements and control strategies of the temperature control system, formulate a series of fuzzy rules.

[0099] For example, the fuzzy rules may include: if the error is large and the error change rate is large, then increase the control parameter P; if the error is small and the error change rate is small, then reduce the control parameter P. The control parameters I and D may be adjusted in a similar manner, which will not be repeated here.

[0100] 3. Fuzzy reasoning

[0101] Fuzzification: Convert the exact values ​​of real-time error and error change rate into fuzzy values ​​(i.e., membership degree).

[0102] 4. Defuzzification

[0103] Convert the fuzzy value output by the fuzzy controller into precise control action (actual value of P, I, D gain).

[0104] 5. Apply PID control

[0105] Adjust PID parameters: Adjust the response of the PID controller according to the P, I, and D gains output by the fuzzy controller.

[0106] Calculate PID output: Based on the adjusted PID parameters, calculate the output of the controller to drive the temperature control system.

[0107] In an optional embodiment, the temperature control of the controlled object in this embodiment may be a constant temperature control. Based on this, based on the current ambient temperature of the controlled object and the target control temperature of the controlled object, adaptively adjusting the PID parameters of the temperature control system according to the fuzzy PID control algorithm may include:

[0108] When the current ambient temperature of the controlled object is different from the target control temperature of the controlled object, the PID parameters of the temperature control system are adaptively adjusted according to the fuzzy PID control algorithm to keep the temperature of the controlled object at the target control temperature.

[0109] Based on the above technical solution, the controlled object can be kept in a constant temperature state, thereby achieving constant temperature control of the controlled object.

[0110] Exemplarily, in the fuzzy PID control algorithm, the current error of the fuzzy PID control algorithm may be determined according to the current ambient temperature of the controlled object and the target control temperature of the controlled object;

[0111] And based on at least two of the current errors determined during the temperature control of the controlled object, a current error change rate of the fuzzy PID control algorithm is determined.

[0112] The at least two current errors may be current errors in adjacent iterations or current errors in adjacent iterations, and the embodiment of the present application does not impose any special limitation on this.

[0113] Based on the above description, the embodiment of the present application determines the current error of the fuzzy PID control algorithm according to the current ambient temperature and the target control temperature, and determines the current error change rate of the fuzzy PID control algorithm according to at least two of the current errors to set the parameters in the fuzzy PID control algorithm. Therefore, the fuzzy PID control algorithm can perform precise temperature control of the controlled object according to the current environmental parameters of the controlled object.

[0114] Optionally, the membership function of the above fuzzy PID control algorithm is a triangular membership function.

[0115] Among them, the triangle membership function is a fuzzy membership function used to represent fuzzy sets in fuzzy logic systems. Its shape is similar to a triangle, and it is simple, intuitive, and easy to calculate. The triangle membership function can be used in the fuzzification process, that is, converting precise input values ​​into fuzzy sets.

[0116] Based on this, the present application uses triangular membership functions to represent fuzzy sets, which can reduce computational complexity and improve the system response rate.

[0117] Second, refer to Figure 2 The embodiment of the present application further provides a temperature control device for controlling the temperature of a controlled object, the device comprising:

[0118] The determination module 201 is used to determine the PID parameters of the temperature control system of the controlled object.

[0119] The adjustment module 202 is used to adaptively adjust the PID parameters of the temperature control system according to a fuzzy PID control algorithm based on the acquired current ambient temperature of the controlled object and the target control temperature of the controlled object.

[0120] The control module 203 adjusts the temperature control system according to the adaptively adjusted PID parameters, and performs temperature control on the controlled object according to the adjusted temperature control system.

[0121] Optionally, the determination module is specifically used to determine the PID parameters of the temperature control system of the controlled object according to a simulated annealing PID algorithm.

[0122] Optionally, the determination module is specifically used to: in the simulated annealing PID algorithm, evaluate the performance index of the current temperature control system according to the time-weighted absolute error integral. Wherein, the current temperature control system is a temperature control system determined according to the current PID parameters.

[0123] Optionally, the determination module is specifically used to: in the simulated annealing PID algorithm, based on the Metropolis criterion, update the current PID parameters according to the new PID parameters.

[0124] The new PID parameters are PID parameters obtained after randomly perturbing the current PID parameters.

[0125] Optionally, the determination module is specifically used to: in the simulated annealing PID algorithm, determine that the cooling function is an exponential cooling function.

[0126] Optionally, the adjustment module is specifically used to: when the current ambient temperature of the controlled object is different from the target control temperature of the controlled object, adaptively adjust the PID parameters of the temperature control system according to the fuzzy PID control algorithm so that the temperature of the controlled object is maintained at the target control temperature.

[0127] Optionally, the adjustment module is specifically used to: in the fuzzy PID control algorithm, determine the current error of the fuzzy PID control algorithm according to the current ambient temperature of the controlled object and the target control temperature of the controlled object;

[0128] And based on at least two of the current errors determined during the temperature control of the controlled object, a current error change rate of the fuzzy PID control algorithm is determined.

[0129] Optionally, the adjustment module is specifically used to: determine that the membership function of the fuzzy PID control algorithm is a triangular membership function.

[0130] In a third aspect, the present application also provides a temperature control device.

[0131] Figure 3 This is a schematic diagram of the structure of the temperature control device provided in the embodiment of the present application. Figure 3 As shown, the temperature control device may include: a transceiver 121 , a processor 122 , and a memory 123 .

[0132] The processor 122 executes the computer execution instructions stored in the memory, so that the processor 122 executes the temperature control method provided in the above embodiment. The processor 122 can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0133] The memory 123 is connected to the processor 122 via a system bus and completes communication between them. The memory 123 is used to store computer program instructions.

[0134] The transceiver 121 may be used to obtain tasks to be executed and configuration information of the tasks to be executed.

[0135] The system bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The system bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The transceiver is used to realize the communication between the database access device and other computers (such as clients, read-write libraries, and read-only libraries). The memory may include random access memory (RAM) and may also include non-volatile memory.

[0136] An embodiment of the present application also provides a chip for running instructions, which is used to execute the technical solution of the temperature control method in the above embodiment.

[0137] In a fourth aspect, the present application provides a temperature control system, the system comprising: a controlled object and the temperature control device described in the third aspect, the temperature control device being used to perform temperature control on the controlled object.

[0138] In a fifth aspect, an embodiment of the present application further provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed on a computer, the computer executes the technical solution of the temperature control method of the above embodiment.

[0139] In a sixth aspect, in an exemplary embodiment, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, the temperature control method described in any one of the above embodiments is implemented.

[0140] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0141] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

[0142] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The above-mentioned module-composed unit can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0143] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the methods of various embodiments of the present application.

[0144] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.

[0145] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0146] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0147] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0148] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a main control device.

[0149] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0150] The beneficial effects of the second to sixth aspects of this embodiment are the same as the beneficial effects of the temperature control method in the first aspect, and will not be repeated here.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A temperature control method, characterized in that: For controlling the temperature of a controlled object, the method comprises: Determining PID parameters of the temperature control system of the controlled object; Based on the acquired current ambient temperature of the controlled object and the target control temperature of the controlled object, adaptively adjusting the PID parameters of the temperature control system according to a fuzzy PID control algorithm; The temperature control system is adjusted according to the adaptively adjusted PID parameters, and the temperature of the controlled object is controlled according to the adjusted temperature control system.

2. The temperature control method according to claim 1, characterized in that: Determining the PID parameters of the temperature control system of the controlled object includes: According to the simulated annealing PID algorithm, the PID parameters of the temperature control system of the controlled object are determined.

3. The temperature control method according to claim 2, characterized in that: In the simulated annealing PID algorithm, the performance index of the current temperature control system is evaluated according to the time-weighted absolute error integral; Wherein, the current temperature control system is a temperature control system determined according to current PID parameters.

4. The temperature control method according to claim 3, characterized in that: In the simulated annealing PID algorithm, based on the Metropolis criterion, the current PID parameters are updated according to the new PID parameters; The new PID parameters are PID parameters obtained after randomly perturbing the current PID parameters.

5. The temperature control method according to claim 2, characterized in that: In the simulated annealing PID algorithm, the temperature reduction function is determined to be an exponential temperature reduction function.

6. The temperature control method according to any one of claims 1 to 5, characterized in that: The adaptively adjusting the PID parameters of the temperature control system according to the fuzzy PID control algorithm based on the acquired current ambient temperature of the controlled object and the target control temperature of the controlled object includes: When the current ambient temperature of the controlled object is different from the target control temperature of the controlled object, the PID parameters of the temperature control system are adaptively adjusted according to the fuzzy PID control algorithm to keep the temperature of the controlled object at the target control temperature.

7. The temperature control method according to claim 6, characterized in that: In the fuzzy PID control algorithm, a current error of the fuzzy PID control algorithm is determined according to the current ambient temperature of the controlled object and the target control temperature of the controlled object; And based on at least two of the current errors determined during the temperature control of the controlled object, a current error change rate of the fuzzy PID control algorithm is determined.

8. The temperature control method according to claim 6, characterized in that: The membership function of the fuzzy PID control algorithm is determined to be a triangular membership function.

9. A temperature control device, characterized in that: Used to control the temperature of a controlled object, the device comprises: A determination module, used to determine the PID parameters of the temperature control system of the controlled object; an adjustment module, configured to adaptively adjust the PID parameters of the temperature control system according to a fuzzy PID control algorithm based on the acquired current ambient temperature of the controlled object and the target control temperature of the controlled object; The control module adjusts the temperature control system according to the adaptively adjusted PID parameters, and performs temperature control on the controlled object according to the adjusted temperature control system.

10. A temperature control device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 8.

11. A temperature control system, characterized in that: The system comprises: a controlled object and the temperature control device according to claim 10, wherein the temperature control device is used to perform temperature control on the controlled object.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

13. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when being executed by a processor.

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