Intelligent non-linearity PID controlling parameter tuning based on self-adapting ant colony

Abstract

The present invention provides a non-linear PID control parameter setting method based on self adaptive ant colony intelligent. The method includes the steps as follows: first, the optimum relation range of undetermined coefficient in a non-linear PID controller; second, a gridding is made in a variable region which is divided into a plurality of space regions; third, an initial parameter and a taboo table index indicating hand, every two ants are used as a partner to choose a certain node as the starting point; fourth, two ants choose the optimum relation space node according to the state transition probability and go forwards; fifth, the taboo table index indicating hand is amended, according to the route passed by the ants, the non-linear PID control undetermined coefficient corresponding to the route is calculated, and the objective function corresponding to the ants is calculated, as well as the ITAE minimal performance index in the cycle period is recorded; finally, the non-linear PID control parameter corresponding to the minimal performance index is stored in a control coefficient, at the same time, the pheromone residual coefficient adjusted in the self-adaption way, and the pheromone rail on each route is renovated. The steps are circled till an optimum result is obtained.

Description

(1) Technical field [0001] The performance of any proportional-differential-integral (Proportional-Integral-Differential, PID) controller depends entirely on the optimization of its control parameters. Non-Linear Proportional-Derivative-Integral (Non-Linear PID, NLPID) controller is a new type of controller, its parameter optimization methods and technologies have been in continuous development, and the use of bionic intelligent methods to optimize NLPID parameters has gradually become a A key technology in the field of PID. [0002] Ant colony algorithm is an emerging artificial intelligence algorithm, which has been well solved many NP problems by applying ant colony algorithm. Aiming at the parameter optimization problem of a new type of NLPID controller, we invented a control parameter tuning method based on adaptive ant colony intelligence. The invention is an effective technical way to solve the problem of NLPID parameter setting, and at the same time, the method can a...

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Problems solved by technology

[0005] (1) For conventional PID controllers in practical applications, due to the troubles of parameter optimization methods, they are often poorly optimized and have poor performance;

[0006] (2) Conventional PID parameter optimization currently adopts methods such as empirical method and trial-and-error method in engineering. These methods are time-consuming and laborious, and often have poor optimization results;

[0007] (3) As a linear control method, conventional PID control is often difficult to obtain good control effects for noise interference and complex nonlinear systems

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