Variable universe fuzzy control AGV (Automatic Guided Vehicle) correction method based on self-adaptive telescopic factor

Abstract

The invention relates to a variable universe fuzzy control AGV (Automatic Guided Vehicle) correction method based on a self-adaptive telescopic factor, which comprises the following steps of: carrying out kinematics analysis on an AGV, and determining an initial universe range in fuzzy control; giving a function expression of a parameter tau in a function type telescopic factor in variable universe fuzzy control; substituting the function expression of the parameter tau into the expression of the function type scaling factor, so that the value of the tau in the function type scaling factor can be adjusted in real time according to the deviation, and obtaining universe scaling factors a1, alpha2 and beta according to the tau, the position deviation e1 and the angle deviation e2; and a1, alpha2 and beta are utilized to adjust the initially set domain of input and output fuzzy variables of the fuzzy controller, the steering angle of the operation center of the AGV body is obtained by utilizing the fuzzy controller according to e1 and e2, and then deviation correction control of the AGV is achieved on the basis of kinematics analysis of the AGV. The adaptive change of fuzzy control is realized, the control rule of the control system is more perfect, and the control effect of the AGV deviation correction controller is improved.

Description

technical field [0001] The invention relates to the field of path planning, in particular to a method for correcting deviations of an automatic guided vehicle (AGV) based on a variable universe fuzzy control based on an adaptive scaling factor. Background technique [0002] The variable universe fuzzy algorithm is an improved optimization algorithm based on the fuzzy algorithm. It maintains the control method that the fuzzy control is closer to human thinking than the traditional control, and can achieve a more accurate ideal control effect through an imprecise model. On the basis of , refine the control rules to improve the control effect. AGV correction control belongs to discrete control, which has the characteristics of nonlinearity, uncertainty of model and environment, and inaccuracy of measurement. Therefore, variable universe fuzzy algorithm can play a better role in AGV correction control. The variable universe fuzzy algorithm is used. Since the selection of such a...

AI Technical Summary

Problems solved by technology

[0004] In the functional expansion factor, ε is a sufficiently small positive number to prevent the variable universe from tending to 0, and there is an artificially selected fixed value τ, and the value of τ is often an artificially selected fixed value based on expert experience , it is difficult to find the optimal value, which makes the expansion factor not intelligent due to the fixed parameters, which ultimately restricts its control efficiency and affects the effect of AGV correction control

Images