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Method, device and storage medium for parameter tuning of sliding mode controller based on sfcs algorithm

A parameter setting and controller technology, applied in the directions of adaptive control, general control system, control/regulation system, etc., can solve the problems of large control effect, low convergence accuracy, slow convergence speed, etc., to achieve good control effect, Save the time of manual parameter adjustment, improve the effect of convergence speed and accuracy

Active Publication Date: 2022-06-21
WUYI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Sliding mode control has been widely used in the control of underactuated systems due to its fast response, simple design, and strong robustness. However, the parameter tuning process of the sliding mode controller is complicated, and the tuning results have a great influence on the control effect.
Most of the parameters of sliding mode controllers for bridge cranes rely on manual debugging. Due to the certain coupling between the parameters of the controllers, the adjustment process of the parameters is complicated and cumbersome, and the final parameters are often not good in control effect. not ideal
Some scholars use the traditional optimization algorithm to tune the parameters of the sliding mode controller, but the traditional optimization algorithm has the problems of slow convergence speed, low convergence accuracy and easy to fall into the local optimal solution, resulting in poor parameter tuning results

Method used

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  • Method, device and storage medium for parameter tuning of sliding mode controller based on sfcs algorithm
  • Method, device and storage medium for parameter tuning of sliding mode controller based on sfcs algorithm
  • Method, device and storage medium for parameter tuning of sliding mode controller based on sfcs algorithm

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Embodiment 1

[0076] refer to figure 1 , the first embodiment of the present invention provides a sliding mode controller parameter tuning method based on the SFCS algorithm, an embodiment of which includes but is not limited to the following steps:

[0077] Step S100, initialize parameters and population, first set evolutionary algebra G, maximum evolutionary algebra Gmax, number of bird's nests n, search space dimension D, discovery probability Pa, upper limit u and lower limit l of search space.

[0078] In this embodiment, in this step, the parameters and the population are initialized first, and preconditions are prepared for the parameter tuning and optimization process.

[0079] Step S200, randomly generate n bird nest positions and calculate the fitness value of each bird nest position.

[0080] In this embodiment, this step prepares for the subsequent operation of the improved cuckoo search algorithm.

[0081] Step S300, update the position of each bird's nest and calculate the f...

Embodiment 2

[0114] refer to image 3 , the second embodiment of the present invention provides a sliding mode controller parameter setting device 1000 based on the SFCS algorithm, including:

[0115] The initialization unit 1100 is used to initialize parameters and populations, firstly setting the evolutionary algebra G, the maximum evolutionary algebra Gmax, the number of bird's nests n, the dimension of the search space D, the probability of being found Pa, the upper limit u and the lower limit l of the search space;

[0116] an operation unit 1200 for randomly generating n bird nest positions and calculating the fitness value of each bird nest position;

[0117] The first processing unit is used to update the position of each bird's nest and calculate the fitness of the new bird's nest position by using the inertia weight decreasing algorithm based on the sigmoid function, compare the existing bird's nest with the position of the previous generation bird's nest, and select the one with...

Embodiment 3

[0126] Embodiment 3 of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores executable instructions of the SFCS algorithm-based sliding mode controller parameter tuning device, and the SFCS algorithm-based sliding mode controller parameter tuning The device-executable instructions are used to cause the SFCS algorithm-based sliding mode controller parameter tuning device to perform the above-mentioned SFCS algorithm-based sliding mode controller parameter tuning method, for example, to perform the above-described sliding mode controller parameter tuning method. figure 1 The method steps S100 to S500 in the image 3 functions in units 1000-1420.

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Abstract

The invention discloses a sliding mode controller parameter setting method, device and storage medium based on the SFCS algorithm. An explosion operator with self-adaptive ability and a reverse learning strategy based on the worst solution of the population are added to the traditional CS algorithm, so that the They can communicate with each other, which can further guide the evolution of the population towards the optimal solution; in terms of convergence, the population growth curve balances the influence of the explosion operator and the Levy flight on the candidate solutions generated by the algorithm, and balances the global exploration of the algorithm and local development capabilities; in addition, in the later stage of the algorithm iteration, the explosion operator dominates, effectively improving the convergence speed and accuracy of the algorithm; and applying the SFCS algorithm to the parameter tuning of the sliding mode controller, it is well realized The optimal setting of parameters is realized, thereby saving the time of manually adjusting parameters and obtaining better control effects.

Description

technical field [0001] The invention relates to the field of bridge crane sliding mode controllers, in particular to a parameter setting method, device and storage medium of a sliding mode controller based on an SFCS algorithm. Background technique [0002] The overhead crane system is often used in various heavy industrial sites and port cargo transportation. When working, the load is pulled to the designated position by the hanging rope suspended by the trolley. safety level. Because the control quantity dimension of the overhead crane is less than its degree of freedom, and the precise positioning of the trolley and the suppression of load swing are required during the operation process, the control difficulty is greatly increased. Sliding mode control has been widely used in the control of underactuated systems due to its fast response, simple design and strong robustness. Most of the parameters of the bridge crane sliding mode controller rely on manual debugging. Due ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 王天雷余焱江邱炯智张京玲张昕黄尊地郑宇杰邓亦佳
Owner WUYI UNIV