Neural Network Based Control of Four-Bar Mechanism with Variable Input Velocity

被引：1

作者：

Peon-Escalante, R. ^{[1
]}

Flota-Banuelos, Manuel ^{[1
]}

Quintal-Palomo, Roberto ^{[1
]}

Ricalde, Luis J. ^{[1
]}

Penunuri, F. ^{[1
]}

Jimenez, B. Cruz ^{[1
]}

Vinas, J. Aviles ^{[1
]}

机构：

[1] Univ Yucatan, Fac Engn, Merida 97000, Mexico

来源：

MATHEMATICS | 2023年 / 11卷 / 09期

关键词：

four-bar mechanism; variable input-velocity; trajectory tracking; PID neural network controller; FUZZY-LOGIC; DESIGN; DRIVEN; TRACKING; SYSTEM;

D O I：

10.3390/math11092148

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

For control applications, the angular velocity of the drive crank of a four-bar mechanism is traditionally assumed to be constant. In this paper, we propose control of variable velocity of the drive crank to obtain the desired output motions for the coupler point. To estimate the reference trajectory for the crank velocity, a neural network is trained with data from the kinematic model. The control law is designed from feedback linearization of the tracking error dynamics and a Proportional-Integral-Derivative (PID) controller. The applicability of the proposed scheme is validated through simulations for three variable speed profiles, obtaining excellent results from the system.

引用

页数：17

共 32 条

[1]

Al-Jarrah Ahmad, 2015, WSEAS Transactions on Systems and Control, V10, P584

[2] Application of moving sliding mode control for a DC motor driven four-bar mechanism [J].