Control method and device, electronic equipment, readable storage medium and chip

Abstract

The application provides a control method, device, electronic equipment, readable storage medium and chip, and the method comprises the following steps: acquiring first input and output data of each first control loop under at least one working condition; determining first optimal parameters of a second controller located in a second control loop under at least one working condition according to the first input and output data; acquiring importance levels corresponding to all first devices and control strategies corresponding to each importance level; adjusting the second control loop corresponding to the first device to a third control loop according to the importance level and the control strategy corresponding to the importance level, wherein the third control loop comprises at least one second controller; acquiring third input and output data of each third control loop under at least one working condition; determining second optimal parameters of the second controller under at least one working condition according to the third input and output data; and controlling at least one first device through the third control loop according to the second optimal parameters.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ship power system, in particular to a control method and device, electronic equipment, readable storage medium and chip. BACKGROUND

[0002] At present, the ship power system mainly adopts PID control, but due to the defects of the PID controller itself, the control difficulty of the system coupling and multiple disturbance conditions is large. SUMMARY

[0003] Therefore, the present application aims to solve the problem of large control difficulty of system coupling and multiple disturbance conditions.

[0004] Specifically, the present application is realized by the following technical solutions:

[0005] The embodiment of the first aspect of the present application provides a control method.

[0006] The embodiment of the second aspect of the present application provides a control device.

[0007] The embodiment of the third aspect of the present application provides an electronic equipment.

[0008] The embodiment of the fourth aspect of the present application provides a readable storage medium.

[0009] The embodiment of the fifth aspect of the present application provides a chip.

[0010] The control method provided by the present application comprises: obtaining first input and output data of each first control loop under at least one working condition, wherein the first input and output data comprises a control signal of a first controller and an output signal of a first device controlled by the first control loop; determining first optimal parameters of a second controller located in a second control loop under at least one working condition according to the first input and output data, wherein the second controller is used to control the first device; obtaining importance levels corresponding to all first devices and control strategies corresponding to each importance level; adjusting the second control loop corresponding to the first device to a third control loop according to the importance level and the control strategy corresponding to the importance level, the third control loop comprising at least one second controller; obtaining third input and output data of each third control loop under at least one working condition, wherein the third input and output data comprises a control signal of the third control loop and an output signal of the first device controlled by the third control loop; determining second optimal parameters of the second controller under at least one working condition according to the third input and output data; and controlling at least one first device through the third control loop according to the second optimal parameters.

[0011] In some embodiments, the determining the first optimal parameter of the second controller under the at least one working condition according to the first input-output data comprises: determining a transfer function under a working condition corresponding to the first input-output data; determining the first optimal parameter of the second controller under the working condition corresponding to the transfer function; and adjusting the first optimal parameter according to the first optimal parameters corresponding to the plurality of working conditions by a piecewise function.

[0012] In some embodiments, the adjusting the second control loop corresponding to the first device into the third control loop according to the importance level and the control strategy corresponding to the importance level comprises: obtaining the second control loop for controlling the first device; determining a control strategy for the second control loop for controlling the first device according to the importance level corresponding to the first device, wherein the importance level of the second control loop is the same as the importance level of the first device; and adjusting the second control loop into the third control loop according to the control strategy.

[0013] In some embodiments, the obtaining the third input-output data of each third control loop under the at least one working condition comprises: determining an obtaining sequence of the third input-output data of the third control loop according to the importance level corresponding to the third control loop, wherein the importance level of the third control loop is the same as the importance level of the second control loop; and obtaining the third input-output data of all third control loops under the at least one working condition according to the obtaining sequence.

[0014] In some embodiments, the first controller is a PID controller, and the second controller is an ADRC controller.

[0015] In some embodiments, the determining the transfer function under the at least one working condition according to the first input-output data comprises: determining the transfer function under the at least one working condition by a PSO algorithm according to the first input-output data.

[0016] In some embodiments, the determining the first optimal parameter of the second controller under the at least one working condition according to the transfer function comprises: determining the first optimal parameter of the second controller under the at least one working condition by a GA algorithm according to the transfer function.

[0017] The second aspect of the present application provides a control device, which comprises:

[0018] The acquisition module is further configured to acquire third input-output data of each third control loop under at least one working condition, wherein the third input-output data comprises a control signal of the third control loop and an output signal of the first device controlled by the third control loop; the parameter determination module is further configured to determine second optimal parameters of the second controller under the at least one working condition according to the third input-output data; and the control module is configured to control the at least one first device through the third control loop according to the second optimal parameters.

[0019] Embodiments of the third aspect of the present application provide an electronic device, comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor, and the program or instruction is executed by the processor to implement the steps of the control method in the first aspect.

[0020] Embodiments of the fourth aspect of the present application provide a readable storage medium, and the readable storage medium stores a program or instruction, and the program or instruction is executed by the processor to implement the steps in the first aspect.

[0021] Embodiments of the fifth aspect of the present application provide a chip, comprising a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run a program or instruction to implement the steps in the first aspect.

[0022] The technical solutions provided by the present application at least bring the following beneficial effects:

[0023] 1) Each control loop of the ship power system is coupled and interferes with each other, and the ADRC has strong anti-disturbance performance, so that the application of the ADRC in the ship power system can effectively improve the stability of the system, and further improve the comprehensive performance of the system.

[0024] 2) The distribution of the PID controller of the existing device in the ship power system is not changed, and the ADRC can be directly used to replace the PID controller at the corresponding position.

[0025] 3) A control method specially for solving the problem of ship power system, there is no inapplicable situation caused by the change of application scene, the existing ship power system operation data is directly used for identification of the dynamic model transfer function of the controlled object, and the reliability is strong and the pertinence is strong.

[0026] 4) The importance of different equipment indexes in the ship power system is fully considered according to the actual situation, and the control levels are divided, and different control levels can be directly seated according to the number, and the optimized ADRC control system is gradually applied to the actual coordinated control system. BRIEF DESCRIPTION OF DRAWINGS

[0027] The accompanying drawings incorporated in and forming a part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application.

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or related description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without creative labor.

[0029] Figure 1 The flowchart of the control method provided by the embodiment of the present application is shown in the figure;

[0030] Figure 2 The flowchart of the control method provided by the embodiment of the present application is shown in the figure;

[0031] Figure 3 The flowchart of the control method provided by the embodiment of the present application is shown in the figure;

[0032] Figure 4 The flowchart of the control method provided by the embodiment of the present application is shown in the figure;

[0033] Figure 5 The structure diagram of the control device provided by the embodiment of the present application is shown in the figure;

[0034] Figure 6 The structure diagram of the electronic device provided by the embodiment of the present application is shown in the figure;

[0035] Figure 7 The schematic diagram of the ADRC controller provided by the embodiment of the present application is shown in the figure;

[0036] Figure 8 The control strategy diagram of the device provided by the embodiment of the present application is shown in the figure;

[0037] Figure 9 The control strategy diagram of the device provided by the embodiment of the present application is shown in the figure;

[0038] Figure 10 A control strategy diagram of the device provided by the embodiment of the present application is provided;

[0039] Figure 11 A transfer function optimization target function diagram provided by the embodiment of the present application is provided;

[0040] Figure 12 A flowchart of the PSO algorithm optimization provided by the embodiment of the present application is provided;

[0041] Figure 13 A flowchart of the genetic algorithm optimization ADRC controller parameter provided by the embodiment of the present application is provided;

[0042] Figure 14 A schematic diagram of the ship power system provided by the embodiment of the present application is provided.

[0043] In the figure, the correspondence between the names and labels of the parts is as follows:

[0044] 900: control device; 901: acquisition module; 902: parameter determination module; 903: adjustment module; 904: control module; 700: ship power system; 701: first device; 702: first control loop; 703: first controller; 1000: electronic device; 1109: memory; 1110: processor. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0046] Referring to Figure 1 , the first aspect of the present application provides a control method, comprising the following steps:

[0047] Step S102: acquiring first input-output data of each first control loop under at least one working condition, wherein the first input-output data comprises a control signal of the first controller and an output signal of the first device controlled by the first control loop;

[0048] Step S104: determining first optimal parameters of a second controller located in a second control loop under at least one working condition according to the first input-output data, wherein the second controller is used to control the first device;

[0049] Step S106: Obtain the importance level corresponding to each first device and the control strategy corresponding to each importance level;

[0050] Step S108: Adjust the second control loop corresponding to the first device to a third control loop according to the importance level and the control strategy corresponding to the importance level, the third control loop comprising at least one second controller;

[0051] Step S110: Obtain third input-output data of each third control loop under at least one working condition, wherein the third input-output data comprises a control signal of the third control loop and an output signal of the first device controlled by the third control loop;

[0052] Step S112: Determine second optimal parameters of the second controller under at least one working condition according to the third input-output data;

[0053] Step S114: Control at least one first device through the third control loop according to the second optimal parameters.

[0054] The control method provided by the present application is mainly used for Figure 14 As shown in the ship power system 700 for providing propulsion and operating energy for the ship, the system comprises a first control loop 702 which is a closed-loop control system for managing and controlling a specific device or subsystem, each first control loop 702 usually comprises a sensor, an actuator and one or more controllers for monitoring the operating state (such as speed, pressure, temperature, etc.) of the first device 701 and adjusting the control signal according to the set target value to achieve precise control. The first controller 703 is the core component embedded in the first control loop 702, which is responsible for receiving the actual operating data of the first device 701 fed back by the sensor and comparing it with the set target value to generate the corresponding control signal to adjust the operating state of the first device 701, wherein the first controller 703 can adopt various control algorithms such as PID controller (proportional-integral-derivative controller), ADRC controller (active disturbance rejection controller) and the like. In general, the ship power system 700 precisely controls at least one first device 701 through multiple independent first control loops 702, wherein each loop is equipped with at least one first controller 703.

[0055] In the application of the control method, first, a plurality of sets of first input and output data of each first control loop under different operating conditions are obtained. Under a certain operating condition, the first input and output data specifically include the control signal sent by the first controller and the output signal generated after the first device responds to the control signal. It can be understood that the output signal is the actual operating data of the first device and can be fed back to the first controller through a sensor. The first controller can compare these data with the target value, calculate the error, and adjust the control signal through an algorithm, so as to control the first device to operate as expected. It should be noted that the first input and output data are data related to the first controller. By analyzing the first input and output data, not only can the adjustment performance and response speed of the first controller be evaluated, but also a basis can be provided for the design of a controller with better performance: when the first controller (such as a PID controller) has limitations under nonlinear and strong coupling conditions, the first controller can be replaced by a second controller (such as an ADRC controller). It should be noted that the second controller adopts a more advanced control strategy, and when facing external disturbances, the second controller can more quickly and effectively offset the influence of disturbances on the system, and has stronger anti-interference performance than the first controller. Specifically, according to the distribution of the existing first controllers in the system, the second controller can be used to replace the first controller one by one at the corresponding position, and the parameters of the second controller can be optimized after the replacement is completed. It can be understood that the first input and output data obtained previously can guide the design and parameter optimization of the second controller, including: using the first input and output data and through a modeling method to determine the dynamic characteristics of the first device, to provide an accurate mathematical model for the design of the second controller; based on the performance data of the first controller, determining the specific performance indicators that need to be improved for the second controller; using the first input and output data to determine the parameters of the first controller, and using the parameters as the initial reference of the optimization algorithm of the second controller, so as to shorten the subsequent optimization convergence time. Overall, in order to improve the anti-disturbance and self-adaptability of the system, the original first controller can be replaced by a second controller with better performance, and according to the input and output data of the first controller under different operating conditions, the optimal parameters of the second controller, i.e., the first optimal parameters, are determined. It should be noted that the second control loop corresponding to the second controller has the same line structure as the first control loop corresponding to the first controller, and only the controller in the line is replaced, which ensures that the different control loops can cooperate seamlessly.

[0056] To further improve the anti-disturbance performance of the system, after completing the optimization of the individual control loops, i.e., replacing the controllers with poor performance with controllers with better performance, the coupling problem between devices also needs to be considered. Different devices are controlled by different control loops. Based on the importance level of the devices, the control loops corresponding to some devices can be adjusted to have stronger anti-disturbance performance, thereby achieving higher-level control optimization. First, according to the importance level of the devices, the control strategies corresponding to different importance levels are determined. The devices with high importance levels need higher-level control strategies, i.e., the control loops with stronger anti-disturbance performance. At this time, the devices with the lowest importance level are still configured with the previous control loops, but the devices with higher importance levels will no longer be controlled by the previous control loops. The previous control loops will be adjusted to more complex control loops according to the higher-level control strategies. The new control loops are similar in structure to the previous control loops, but may include more controllers or more complex control algorithms to meet higher control requirements.

[0057] The third input-output data of each third control loop includes the control signal generated by the control loop and the output signal of the first device controlled by the control loop when the system is actually running. The process of obtaining these data first involves exciting and monitoring the third control loop under different operating conditions to ensure that the dynamic relationship between the control signal and the device response can be fully captured under each operating condition. After obtaining the input-output data collected under at least one operating condition, advanced optimization algorithms such as genetic algorithm (GA) or particle swarm optimization algorithm (PSO) are applied to optimize the parameters of the second controller. These algorithms simulate the process of natural selection and group cooperation to gradually adjust the parameters of the controller so that it can achieve the best control performance under a specific operating condition. After determining the optimal parameters of the second controller, the next step is to apply these parameters to the third control loop and input the optimized parameters into the second controller so that it can generate more accurate and efficient control signals to adjust the operating state of the first device, and ultimately achieve precise control of the devices in the system through the third control loop.

[0058] In general, this method does not change the distribution of the existing controllers corresponding to the devices in the system, directly replaces the new controllers in the corresponding positions, and does not have the inapplicable situation caused by the change of application scenarios. Moreover, the parameters of the new controllers are directly determined using the existing running data of the ship power system, which has strong reliability and strong pertinence. Finally, the actual situation is fully considered, the control levels are divided according to the importance of different device indicators in the ship power system, and the corresponding control loops are set for the devices according to different control levels, which greatly enhances the anti-disturbance performance of the system.

[0059] In one specific embodiment, in the case of a ship power system as shown in FIG. 1, the first control loop 101 is configured to control the first device 102, the second control loop 103 is configured to control the second device 104, and the third control loop 105 is configured to control the third device 106. Figure 14The ship power system shown can use an ADRC controller as a second controller to replace the first controller (such as a DIP controller).

[0060] The PID controller adjusts the system output through the linear combination of the three links of proportionality (P), integration (I), and differentiation (D) to achieve accurate control of the controlled variable. Among them, the proportional control provides basic response ability, the integral control eliminates steady-state error, and the differential control enhances the dynamic performance of the system, which can adapt to most linear systems and deterministic scenarios. However, compared with the active disturbance rejection controller (ADRC), the PID controller has significant disadvantages, such as: strong dependence on system model, difficult to adapt to complex nonlinear or time-varying systems; weak suppression ability to external disturbances, especially in the case of frequent changes in disturbance; complex parameter tuning and lack of flexibility, not as good as ADRC in real-time adjustment. Therefore, although the PID controller is still widely used in engineering practice, in dealing with complex dynamic systems, ADRC usually has more superior robustness and adaptability. For example Figure 7 The working principle of the ADRC controller is shown in the figure, specifically:

[0061] Step.1: LADRC is composed of linear state error feedback (LSEF) and linear expansion state observer (LESO). It is assumed that the controlled object model is in integral series form, that is, formula 1:

[0062] y (n) =b0u+f

[0063] In the formula, b0 is the input gain of the controlled object u; u is the input of the controlled object; f is the generalized disturbance, including internal, external and uncertain disturbance; y (n) is the n-th derivative of the output signal y.

[0064] Step.2: Formula 1 is converted into a state space differential expression as formula 2:

[0065]

[0066] y=x1

[0067] In the formula, x is the state variable; x k =y (k-1) , k = 1, 2, …, n-1; x n =y (n-1) ; is the first derivative of x k , is the first derivative of xn First derivative, is the estimate of x n+1 First derivative.

[0068] Step.3:According to formula 2, design LESO as:

[0069]

[0070] In the formula, z is the estimate of x;β is the gain coefficient of LESO; is the estimate of y is the first derivative of z k First derivative, is the first derivative of z n First derivative, is the first derivative of z n+1 First derivative.

[0071] Step.3:Design LSEF expression as:

[0072]

[0073] γ is the gain coefficient of LSEF, u0 is the output of LSEF, and r is the set value.

[0074] Step.4:The LADRC control law is formula 5:

[0075]

[0076] The basic principle of LADRC anti-disturbance is: formula 5 is brought into formula 1 to obtain:

[0077] y (n) =u0+(f-z n+1 )

[0078] When the disturbance observation value z n+1 =f, the disturbance elimination is realized.

[0079] Since each control loop of the ship power system is coupled and interferes with each other, and the ADRC has strong anti-disturbance performance, applying it to the ship power system can effectively improve the stability of the system, and further improve the comprehensive performance of the system.

[0080] In some embodiments, optionally, as Figure 2 shown, determining, according to the first input-output data, the first optimal parameter of the second controller in at least one working condition comprises:

[0081] Step S1042: determining a transfer function in a working condition corresponding to the first input-output data;

[0082] Step S1044: determining the first optimal parameters of the second controller in the working condition corresponding to the transfer function;

[0083] Step S1046: adjusting the first optimal parameters by a piecewise function according to the first optimal parameters corresponding to the multiple working conditions.

[0084] In this embodiment, the core idea is to determine the transfer function corresponding to each working condition through the first input-output data in each working condition. Specifically, first, collect the input-output data of the control loop in each different working condition, which fully reflects the dynamic characteristics and response behavior of the control loop in the specific working condition. By analyzing and modeling these data, a transfer function model is established for the working condition, which can accurately describe the input-output relationship of the control loop in this working condition, laying a solid foundation for subsequent controller parameter optimization.

[0085] Next, using the determined transfer function, the first optimal parameters of the second controller in the working condition corresponding to the transfer function are determined. This step is achieved through optimization algorithms or parameter adjustment methods, aiming to find the optimal parameter combination for the controller performance. Through optimization, the controller can achieve the best control effect in the specific working condition, thereby improving the overall performance of the system.

[0086] However, the system often experiences multiple different working conditions in actual operation, and the dynamic characteristics and optimal control parameters of the system in each working condition may differ significantly. To solve this problem, the invention proposes a method of adjusting the first optimal parameters by a piecewise function according to the working condition. Specifically, according to the first optimal parameters obtained in each working condition, a piecewise function is designed, which can adjust the parameters of the controller in real time according to the current working condition. The piecewise function organically combines the optimal parameters in different working conditions to form a continuous parameter adjustment curve, so that the controller parameters can be smoothly adjusted with the change of the working condition.

[0087] This piecewise function can be a piecewise linear function, a nonlinear function or other suitable mathematical function based on the working condition variable. The purpose is to achieve smooth transition of parameters between different working conditions, avoiding instability or performance degradation of the system due to parameter mutation. Through the application of the piecewise function, the adjustment of the controller parameters is no longer discrete and abrupt, but continuous and smooth. This method improves the adaptability and robustness of the control system to changes in working conditions, ensuring that the system maintains excellent performance in various working conditions.

[0088] Overall, by collecting the first input-output data under each working condition, the corresponding transfer function is determined, and then the first optimal parameters of the second controller are determined. Then, the optimal parameters are adjusted by piecewise function under different working conditions, so as to realize the continuous and smooth adjustment of the controller parameters.

[0089] In a specific embodiment, after obtaining the first input-output data, ADRC is used to replace each one according to the existing device PID controller distribution at the corresponding position. The specific method is:

[0090] 1) By calling the PID output and the output of the controlled object under different working conditions of the ship power system, the subsequent dynamic model transfer function of the controlled object is facilitated;

[0091] 2) The transfer function under different working conditions of the input and output is identified by the PSO algorithm.

[0092] 3) According to the identified transfer function under different working conditions, the GA algorithm is used to optimize and adjust the ADRC, and ITAE is used as the optimization target. The calculation formula of the objective function J is:

[0093]

[0094] In the formula, e(t) is the system output error, u(t) is the ADRC controller input, ρ1 and ρ2 are weight values, J PID is the objective function, and t is the time variable.

[0095] 4) According to the optimal parameters of ADRC under different working conditions, the piecewise f(x) function is used to adjust the ADRC parameters under different working conditions.

[0096] In some embodiments, as Figure 3 shown, according to the importance level and the control strategy corresponding to the importance level, the second control loop corresponding to the first device is adjusted to a third control loop, and the third control loop includes at least one second controller, including:

[0097] Step S1082: Obtain the second control loop for controlling the first device;

[0098] Step S1084: According to the importance level corresponding to the first device, determine the control strategy of the second control loop for controlling the first device, wherein the importance level of the second control loop is the same as the importance level of the first device;

[0099] Step S1086: Adjust the second control loop to a third control loop according to the control strategy.

[0100] In this embodiment, the system first acquires a second control loop corresponding to at least one first device, wherein the second control loop is used to control the operating state of the first device. It can be understood that each device is controlled by at least one control loop, and by acquiring the second control loop, the system can directly affect the operation of the first device, thereby laying the foundation for subsequent adjustment and optimization. Then, the system determines the corresponding importance level and the corresponding control strategy of the second control loop according to the importance level of the first device and the control strategy associated with the importance level. It can be understood that the importance of the device determines the importance of the control loop that controls the device. It is emphasized that the importance level of the second control loop is the same as the importance level of the first device, and this correspondence ensures the unity and pertinence of the control strategy, so that the control loop can accurately reflect the importance of the device and thus take appropriate control methods.

[0101] After determining the importance level and control strategy of the second control loop, the system adjusts the second control loop to a third control loop according to the control strategy. The importance level of the third control loop is the same as that of the second control loop, maintaining the consistency of the importance level. The key of this step is to adjust the control loop by applying a specific control strategy to meet the control needs of the system for devices of different importance levels. For example, for devices with a higher importance level, a more stringent control strategy may be needed to ensure the reliability and safety of their operation; for devices with a lower importance level, a relatively relaxed control strategy can be used to improve the flexibility and resource utilization of the system.

[0102] By adjusting the second control loop to the third control loop, the system realizes the specific application of the control strategy at the control loop level. The third control loop controls the first device according to the pre-set control strategy, ensuring that the operating state of the device meets the overall goal of the system. This adjustment not only improves the response speed and control accuracy of the system, but also enhances the robustness and adaptability of the system.

[0103] In a specific embodiment, three levels can be set according to the importance of the device index, i.e., a single loop control scheme is used for level 1 devices as shown in Figure 8 , a single loop plus feedforward scheme is used for level 2 devices as shown in Figure 9 , and a cascade plus feedforward scheme is used for level 3 devices as shown in Figure 10 , which further improves the response index of the system to realize primary and secondary coordinated optimization control of the device.

[0104] It should be noted that the single-loop control scheme is a basic automatic control design method, which adjusts a single controlled variable through a control loop to achieve stable control of the target value, mainly composed of controlled object, sensor, controller and actuator. The sensor measures the actual value of the controlled variable and transmits it to the controller, which compares the actual value with the target value, calculates the control signal based on the control algorithm, and instructs the actuator to adjust the controlled object, finally making the controlled variable reach the set target. This scheme is simple and efficient, and is suitable for control scenarios with relatively single object.

[0105] The single-loop plus feedforward control scheme is an improved control strategy, which adds feedforward control signal to the traditional single-loop feedback control to improve the response speed and disturbance rejection ability of the system. In this scheme, the feedforward control directly calculates the compensation signal based on the known disturbance variable or the change of the set value, and combines it with the feedback control signal to act on the controlled object, thereby reducing the response time of the system to disturbance. The advantage of feedforward control is that it can adjust the system in time when disturbance occurs, while feedback control is used to correct the inaccuracy of feedforward, both complement each other, further improve the stability and accuracy of the control system, especially suitable for scenes with clear and predictable disturbance.

[0106] The cascade plus feedforward control scheme is a comprehensive control strategy that combines cascade control and feedforward control to further improve the control performance of the system. Cascade control sets up a main control loop and an auxiliary control loop, where the main loop controls the final key variable, and the auxiliary loop quickly responds to the change of internal variable, thereby enhancing the dynamic performance and anti-disturbance ability of the system. On this basis, feedforward control is added to directly generate compensation signal using known disturbance information or set value change to correct the disturbance in advance and act on the auxiliary loop or main loop to reduce the dependence on feedback adjustment. This method combines the rapidity of feedforward and the delicacy of cascade control, and is suitable for complex, disturbance significant or multi-variable coupling control systems, which can achieve more accurate and stable control of target variables.

[0107] In some embodiments, as shown in Figure 4 the third input-output data of each third control loop under at least one working condition is obtained, including:

[0108] Step S1102: According to the importance level corresponding to each third control loop, the acquisition order of the third control loop to obtain the third input-output data is determined, wherein the importance level of the third control loop is the same as the importance level of the second control loop;

[0109] Step S1104: According to the acquisition order, the third input-output data of all third control loops under at least one working condition is obtained.

[0110] In this embodiment, according to the importance level of each third control loop, the order of each third control loop and the device it controls to access the actual working scene can be determined. It can be understood that according to the importance level of the device (control loop), the devices and their control loops are applied to the scene in importance level from low to high, so as to obtain the actual working data, that is, the third input-output data, and to determine the parameters, which can reduce the uncertainty and risk that may be caused by one-time overall replacement. It can be understood that if the control loop of the highest level is directly applied to the entire system, unexpected problems may occur due to complexity or differences in actual site conditions. It can be said that the gradual advancement of the hierarchical level helps to discover and solve local problems and avoid the expansion of problems.

[0111] In some embodiments, optionally, the first controller is a PID controller, and the second controller is an ADRC controller.

[0112] In this embodiment, the first controller is set as a PID (Proportional-Integral-Derivative) controller, and the second controller is an ADRC (Active Disturbance Rejection Controller) controller. Compared with the PID controller, the ADRC has significant advantages. First, the ADRC estimates and compensates the uncertainties and external disturbances within the system in real time through the extended state observer (ESO), with stronger robustness and anti-interference ability, while the PID controller is more sensitive to disturbances. Second, the ADRC has lower dependence on system models and does not require accurate modeling, making it suitable for handling nonlinear, time-varying or complex systems, while the PID controller relies on the accuracy of the model. In addition, the ADRC can effectively suppress overshoot while achieving fast dynamic response, with better dynamic performance than the PID controller. More importantly, the ADRC has strong adaptability and universality, which can cope with changes in working conditions or system characteristics, reducing the workload of on-site debugging, while the PID usually needs to be re-tuned in these cases. Therefore, the application advantage of ADRC in complex systems and severe working conditions is particularly prominent.

[0113] In some embodiments, optionally, according to the first input-output data, the transfer function under at least one working condition is determined by a PSO algorithm.

[0114] In this embodiment, in at least one working condition, the method for determining the transfer function by the first input and output data using the particle swarm optimization (PSO) algorithm can effectively solve the problems of nonlinearity and uncertainty in complex system modeling. The core idea of this method is to use the global optimization ability of the PSO algorithm to extract the dynamic characteristics of the system from the input and output data of the actual working condition, so as to construct a mathematical model that can reflect the behavior of the system. Specifically, first, the input signal and the corresponding output signal of the system are collected as the initial data set, which can reflect the dynamic response characteristics of the system under certain working conditions and is the basis for subsequent modeling. Then, the target form of the system transfer function is defined, such as determining the order of the transfer function and its general structure, including the distribution form of the zero and pole and the parameter range, etc. Then, the PSO algorithm is used to optimize these parameters, and the optimal transfer function is searched by minimizing the objective function (such as the sum of squares of errors between input and output or related performance indicators). The PSO algorithm is based on population and can avoid falling into local optimum through the cooperation of multiple particles, thereby improving the optimization efficiency and accuracy. This method has high robustness, and even if the dynamic characteristics of the system are complex or the input and output data contain noise, it can still obtain a transfer function that approximates the real system behavior. This modeling method is not only suitable for linear systems, but also can be extended to a nonlinear framework. The transfer function determined by this method can provide an accurate mathematical basis for subsequent controller parameter determination and system performance optimization.

[0115] As shown in Figure 11 , it is a schematic diagram of the transfer function optimization objective function. T discrete control output u(t) and controlled object output y(t) sequences are extracted from the ship power system. Second, select the type of controlled object estimation model, common controlled object types include: high-order inertia, high-order inertia time delay, high-order inertia integral link. Third, according to the estimation model and the original data, the fitness function of the model is calculated, and the calculation formula is:

[0116]

[0117] In the formula, t is a series of discrete time sequences from 1 to T, is the system output sequence corresponding to the transfer function parameters obtained after the kth iteration of particle swarm optimization, is the fitness of the ith particle in the kth iteration.

[0118] As shown in Figure 12 , it is a PSO optimization flow chart, specifically:

[0119] Step S202: initialize the particle swarm parameters, including determining the particle swarm size N, the particle dimension D, the iteration number K, the inertia weight W, the learning factor S, and the iteration step range L;

[0120] Step S204: randomly initializing the position and velocity of each particle; the specific outputs include: individual historical optimal position, group historical optimal position, individual historical optimal fitness, group historical optimal fitness;

[0121] Step S206: judging whether the maximum iteration number is reached or the minimum difference of fitness between two iterations, i.e. judging whether J is less than J max If yes, go to step S218: outputting the optimal transfer function type, parameters, fitting curve, error curve, and finally ending the operation; otherwise, go to step S208.

[0122] Step S208: updating the position and velocity of each particle;

[0123] Step S210: calculating the fitness of each particle;

[0124] Step S212: updating the individual historical optimal fitness and position of each particle;

[0125] Step S214: updating the group historical optimal fitness and position;

[0126] Step S216: updating other parameters, such as inertia weight, iteration number, etc.

[0127] wherein, the velocity updating formula is:

[0128]

[0129] In the formula, vi(k+1) is the velocity vector of particle i in the d-th dimension in the k+1th iteration; vi(k) is the historical optimal position of particle i in the d-th dimension in the kth iteration; ω is the inertia weight; xi(k) is the current position; r1, r2 are randomly set values; c1, c2 are set learning factors; xg(k) is the global optimal position of the particle group in the d-th dimension in the kth iteration. The position updating formula is:

[0130]

[0131]

[0132] In some embodiments, optionally, according to the transfer function, the first optimal parameters of the second controller under at least one working condition are determined through the GA algorithm.

[0133] ​The basic flow of the method is to find the optimal parameter set of the controller that meets the control performance requirements based on the known system transfer function, combined with the actual working condition requirements, and using the global optimization capability of genetic algorithm. First, the system transfer function provides a mathematical description of the dynamic characteristics of the system, which is an important basis for controller design. By analyzing the transfer function, the stability, response speed, and dynamic characteristics of the system can be determined. Next, the target performance indicators of the second controller are set according to the specific working conditions. Then, the genetic algorithm is used to optimize the parameters of the second controller. Genetic algorithm (GA algorithm) is based on population, and the parameters to be optimized of the controller are represented as gene sequences through coding, and the population is initialized. Through selection, crossover, mutation and other operations, genetic algorithm iteratively optimizes in the parameter search space, constantly approaching the optimal solution. In each iteration, the controller parameters are decoded and applied to the system transfer function to calculate the objective function value, such as the performance indicator error based on the working condition requirements, which is used as the fitness function to evaluate each solution. The global search mechanism of genetic algorithm can effectively avoid local optimal traps, especially when the parameter space is complex or there are multiple peaks, its advantage is particularly significant. Through multiple iterations, genetic algorithm gradually converges to the optimal parameter solution, thus obtaining the first optimal parameter set that meets the working condition requirements. This method is highly adaptable and can be used not only for linear controller parameter adjustment, but also for nonlinear controller optimization.

[0134] As shown in Figure 13 , it is the GA optimization flow chart of ADRC parameters, the specific process is as follows: starting from the "start" node, first encode the problem and initialize the population, and set the generation number k = 1; then calculate the target fitness value of the population, and judge whether the current target fitness meets the set optimization condition, if the condition is not met, perform selection, crossover and mutation operations on the population, and check whether the generation number reaches the maximum value kmax; if not, update the generation number k = k + 1 and loop iteration until the condition is met; finally, decode the population and output the result, and the process ends.

[0135] The specific implementation is as follows:

[0136] Step.1: Calculate the fitness f(i = 1, 2, …, N) of each individual in the population, N is the population size;

[0137] Step.2: Calculate the probability of each individual being inherited into the next generation population:

[0138]

[0139] In the formula, P(x i ) is the probability of each individual being inherited into the next generation population, f(x i ) is the fitness of i particles, f(x j) is the fitness of j particle, N is the population size.

[0140] Step.3: Calculate the cumulative probability of each individual:

[0141]

[0142] Step.4: Generate a pseudo-random number r in the interval [0, 1] with uniform distribution;

[0143] Step.5: If r < q[1], select individual 1, otherwise, select individual k, so that: q[k-1]<r≤q[k] is established;

[0144] Step.6: Repeat Step.4 and Step.5 N times.

[0145] As Figure 5 shown, the second aspect of the present application provides a control device 900, comprising: an acquisition module 901, configured to acquire first input and output data of each first control loop under at least one working condition, wherein the first input and output data comprises a control signal of a first controller and an output signal of a first device controlled by the first control loop; a parameter determination module 902, configured to determine first optimal parameters of a second controller under at least one working condition according to the first input and output data, wherein the second control loop comprises at least one second controller; the acquisition module 901 is further configured to acquire importance levels corresponding to all first devices and control strategies corresponding to each importance level, wherein the second control loop controls at least one first device; an adjustment module 903, configured to adjust the second control loop corresponding to the first device to a third control loop according to the importance level and the control strategy corresponding to the importance level, the third control loop comprising at least one second controller; the acquisition module 901 is further configured to acquire third input and output data of each third control loop under at least one working condition, wherein the third input and output data comprises a control signal of the third control loop and an output signal of the first device controlled by the third control loop; the parameter determination module 902 is further configured to determine second optimal parameters of the second controller under at least one working condition according to the third input and output data; and a control module 904, configured to control at least one first device through the third control loop according to the second optimal parameters.

[0146] As Figure 6 shown, the third aspect of the present application provides an electronic device 1000, comprising a processor 1110, a memory 1109, a program or instruction stored on the memory 1109 and executable on the processor 1110, the program or instruction being executed by the processor 1110 to implement each process of the above-mentioned control method and achieve the same technical effect, to avoid repetition, which will not be repeated here.

[0147] The processor 1110 is configured to: acquire first input-output data of each first control loop under at least one working condition, wherein the first input-output data comprises a control signal of a first controller and an output signal of a first device controlled by the first control loop; determine first optimal parameters of a second controller located in a second control loop under the at least one working condition according to the first input-output data, wherein the second controller is configured to control the first device; acquire an importance level corresponding to all the first devices and a control strategy corresponding to each importance level; adjust a second control loop corresponding to the first device to a third control loop according to the importance level and the control strategy corresponding to the importance level, wherein the third control loop comprises at least one second controller; acquire third input-output data of each third control loop under the at least one working condition, wherein the third input-output data comprises a control signal of the third control loop and an output signal of the first device controlled by the third control loop; determine second optimal parameters of the second controller under the at least one working condition according to the third input-output data; and control the at least one first device through the third control loop according to the second optimal parameters.

[0148] Optionally, the processor 1110 is further configured to: determine a transfer function under a working condition corresponding to the first input-output data; determine the first optimal parameters of the second controller under a working condition corresponding to the transfer function; and adjust the first optimal parameters by piecewise functions according to the first optimal parameters corresponding to the plurality of working conditions.

[0149] Optionally, the processor 1110 is further configured to: acquire a second control loop configured to control the first device; determine a control strategy of the second control loop configured to control the first device according to an importance level corresponding to the first device, wherein the importance level of the second control loop is the same as the importance level of the first device; and adjust the second control loop to a third control loop according to the control strategy.

[0150] Optionally, the processor 1110 is further configured to: determine an acquisition order of the third control loop for acquiring the third input-output data according to an importance level corresponding to each third control loop, wherein the importance level of the third control loop is the same as the importance level of the second control loop; and acquire the third input-output data of all the third control loops under the at least one working condition according to the acquisition order.

[0151] The fourth aspect of the present application provides a readable storage medium, and the readable storage medium stores a program or instructions, the program or instructions are executed by a processor to realize each process of the embodiment of the above control method, and the same technical effects can be achieved, and details are not repeated here.

[0152] The methods can be implemented in various ways, and with various features, and / or examples. For example, these methods can be implemented by a combination of hardware, firmware, and / or software. For example, in hardware implementations, a processor can be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, micro-controllers, microprocessors, electronic devices, other devices units that perform the above-described functions, and / or a combination thereof.

[0153] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, and any suitable combination of the foregoing. Computer readable storage media, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media, or electrical signals through a wire, digital or analog communication links, wireless communications links, and / or like.

[0154] The processor is a processor in the electronic device in the above embodiments. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and the like.

[0155] The fifth aspect of the present application provides a chip, which includes a processor and a communication interface, the communication interface is coupled with the processor, the processor is used to run programs or instructions, to realize each process of the above-mentioned control method embodiments, and to achieve the same technical effects. To avoid repetition, details are not repeated here.

[0156] While this specification contains many specifics, these should not be construed as limitations on the scope of any invention or on the scope of what can be claimed, but rather as descriptions of particular implementations of certain embodiments. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features can be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination and the claimed combination can be directed to a subcombination or variation of a subcombination.

[0157] Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring or implying that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing can be advantageous. Moreover, the separation of various system modules and components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated in a single software product or packaged into multiple software products.

[0158] Accordingly, particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve the desired results. In some implementations, multitasking and parallel processing can be advantageous.

[0159] It is noted that, in this document, the terms "first", "second", etc. are used merely as label, and are not necessarily to be taken in a literal sense unless specifically stated to be so. Moreover, the terms "comprise", "comprises", "comprising" or any variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. In other words, unless expressly stated to the contrary, the process, method, article, or apparatus that "comprises" or "comprising" a list of elements does not include only those elements in the list, but can include additional elements not expressly listed or inherent to such process, method, article, or apparatus.

[0160] The foregoing is considered as illustrative only of the principles of the application. Numerous modifications and changes will readily occur to those skilled in the art, and it is intended to embrace all such modifications and changes that fall within the scope of the application. Accordingly, the application is not to be restricted in scope to the specific embodiments disclosed herein but is to be accorded the full scope that the principles and novel features request appropriately granted.

Claims

1. A control method characterized by, The application relates to a control method for a ship power system, the ship power system comprising a plurality of first control loops, the first control loops controlling at least one first device, the first control loops comprising at least one first controller, the control method comprising: obtaining first input-output data of each of the first control loops under at least one working condition, wherein the first input-output data comprises a control signal of the first controller and an output signal of the first device controlled by the first control loop; determining first optimal parameters of a second controller located in a second control loop under at least one working condition according to the first input-output data, wherein the second controller is used for controlling the first device; obtaining an importance level corresponding to all the first devices and a control strategy corresponding to each of the importance levels; adjusting the second control loop corresponding to the first device to a third control loop according to the importance level and the control strategy corresponding to the importance level, wherein the third control loop comprises at least one second controller; obtaining third input-output data of each of the third control loops under at least one working condition, wherein the third input-output data comprises a control signal of the third control loop and an output signal of the first device controlled by the third control loop; determining second optimal parameters of the second controller under at least one working condition according to the third input-output data; controlling at least one of the first devices through the third control loop according to the second optimal parameters.

2. The control method according to claim 1, characterized by, The method comprises the following steps: determining a transfer function under a working condition corresponding to the first input-output data; determining first optimal parameters of the second controller under a working condition corresponding to the transfer function; adjusting the first optimal parameters through a piecewise function according to the first optimal parameters corresponding to a plurality of working conditions.

3. The control method according to claim 1, characterized by, The method comprises the following steps: obtaining a second control loop for controlling the first device; determining a control strategy of the second control loop for controlling the first device according to an importance level corresponding to the first device, wherein the importance level of the second control loop is the same as the importance level of the first device; adjusting the second control loop to the third control loop according to the control strategy.

4. The control method according to claim 1, characterized by, The method comprises the following steps: determining an acquisition order of the third input-output data acquired by the third control loop according to an importance level corresponding to each of the third control loops, wherein the importance level of the third control loop is the same as the importance level of the second control loop. According to the acquisition sequence, third input-output data of all the third control loops in at least one working condition is acquired.

5. The control method according to claim 1, wherein the first controller is a PID controller, and the second controller is an ADRC controller. The first controller is a PID controller, and the second controller is an ADRC controller.

6. The control method according to claim 2, characterized by The determining of the transfer function in the working condition corresponding to the first input-output data comprises: According to the first input-output data, the transfer function in at least one working condition is determined by a PSO algorithm.

7. The control method according to claim 2, characterized by, The determining of the first optimal parameter of the second controller in the working condition corresponding to the transfer function comprises: According to the transfer function, the first optimal parameter of the second controller in at least one working condition is determined by a GA algorithm.

8. A control device characterized by comprising: Comprise: The acquisition module is configured to acquire first input-output data of each first control loop in at least one working condition, wherein the first input-output data comprises a control signal of the first controller and an output signal of the first device controlled by the first control loop. The parameter determination module is configured to determine, according to the first input-output data, a first optimal parameter of a second controller located in a second control loop in at least one working condition, wherein the second controller is configured to control the first device. The acquisition module is further configured to acquire an importance level corresponding to each first device and a control strategy corresponding to each importance level. The adjustment module is configured to adjust the second control loop corresponding to the first device to a third control loop according to the importance level and the control strategy corresponding to the importance level, wherein the third control loop comprises at least one second controller. The acquisition module is further configured to acquire third input-output data of each third control loop in at least one working condition, wherein the third input-output data comprises a control signal of the third control loop and an output signal of the first device controlled by the third control loop. The parameter determination module is further configured to determine, according to the third input-output data, a second optimal parameter of the second controller in at least one working condition. The control module is configured to control at least one first device by the third control loop according to the second optimal parameter.

9. An electronic device, comprising: The program or instructions stored in the memory and executable on the processor implement the steps of the method according to any one of claims 1 to 7.

10. A readable storage medium, characterized by, The program or instructions stored in the memory and executable on the processor implement the steps of the method according to any one of claims 1 to 7.

11. A chip, characterized by The chip comprises a processor and a communication interface, the communication interface and the processor are coupled, and the processor is configured to run a program or instructions to implement the steps of the method according to any one of claims 1 to 7.

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