A PID controller parameter optimal setting method based on a differential evolution method

A differential evolution algorithm and control parameter technology, applied in the direction of adaptive control, general control system, control/adjustment system, etc., can solve the problems of poor PID controller parameter tuning, complicated parameter tuning methods, and difficulty in achieving expected results. The effect of fast optimization speed, easy promotion and application, and strong global convergence ability

Inactive Publication Date: 2016-06-22
HENAN UNIV OF URBAN CONSTR
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Problems solved by technology

However, in actual use, due to the troubles of complicated parameter tuning methods, the parameters of the PID con

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  • A PID controller parameter optimal setting method based on a differential evolution method
  • A PID controller parameter optimal setting method based on a differential evolution method
  • A PID controller parameter optimal setting method based on a differential evolution method

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Embodiment Construction

[0032] The present invention will be further described below in conjunction with the accompanying drawings, but not as a limitation of the present invention.

[0033] PID control is one of the earliest developed control strategies. Due to its remarkable advantages of simple algorithm, good robustness and high reliability, it is widely used in industrial process control. However, the complicated and cumbersome tuning process of PID parameters has always troubled engineering technology. Therefore, it is of great theoretical significance and engineering application value to study the simple and practical PID parameter tuning method with excellent tuning effect.

[0034] Differential Evolution (DE) algorithm is a random heuristic search algorithm formed by simulating the evolution law of natural biological populations based on the principle of "survival of the fittest and survival of the fittest". It is a new evolutionary computing technology. Due to its ease of use, good robustne...

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Abstract

The invention discloses a PID controller parameter optimal setting method relating to the field of automatic control and based on swarm intelligence optimization searching technology. Integral performance indexes which can comprehensively measure stability, rapidness and accuracy of an automatic control system are adopted as fitness functions. Through utilization of a global optimization function of a differential evolution algorithm, a proportionality coefficient K[p], an integral coefficient K[I] and a differential coefficient K[D] which can realize global minimization of the performance index function values of a PID control system are searched to be regarded as optimal setting parameters of the PID controller. The PID controller parameter optimal setting method based on the differential evolution method is utilized to carry out simulation experiment direct current motor rotating speed closed loop control system. The experiment result shows that a PID control system obtained after undergoing setting by the method has outstanding advantages of a fast adjusting speed and small overshoot compared with control systems set obtained through a common setting method. The PID controller parameter optimal setting method is a PID controller parameter setting method having a popularization value.

Description

technical field [0001] The invention belongs to the technical field of automatic control, and relates to a PID controller parameter setting technology based on a swarm intelligence optimization algorithm. Background technique [0002] PID control is one of the earliest developed control strategies. It is widely used in industrial process control due to its simple algorithm, good robustness and high reliability. However, in the actual use process, due to the trouble of complicated parameter setting methods, the parameters of the PID controller are often poorly set and the performance is not good, and it is difficult to achieve the expected effect. [0003] Differential Evolution (DE) algorithm is a random heuristic search algorithm formed by simulating the evolutionary development law of natural biological populations based on the principle of "survival of the fittest and survival of the fittest". It is an emerging evolutionary computing technology. [0004] Therefore, it is...

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/04
Inventor 王万召王红阁蒋建飞
Owner HENAN UNIV OF URBAN CONSTR
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