Online optimal decoupled sliding mode control based on moving least squares and particle swarm optimization

被引：25

作者：

Mahmoodabadi, M. J. ^{[1
]}

Momennejad, S. ^{[2
]}

Bagheri, A. ^{[3
]}

机构：

[1] Sirjan Univ Technol, Dept Mech Engn, Sirjan, Iran

[2] Islamic Azad Univ, Dept Mech Engn, Langerud Branch, Guilan, Iran

[3] Univ Guilan, Fac Engn, Dept Mech Engn, Rasht, Iran

来源：

INFORMATION SCIENCES | 2014年 / 268卷

关键词：

Decoupled sliding mode control; Particle swarm optimization; Moving least squares; Online optimal control; NEURAL-NETWORK; DESIGN; ALGORITHM; CONVERGENCE;

D O I：

10.1016/j.ins.2014.01.027

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Regulation and tracking of system states to the desired points or trajectories are two common tasks in the field of control engineering. For optimum performance of a controller, the appropriate selection of its parameters is of utmost importance. Furthermore, when the initial conditions of the system change, the controller with the previous parameters would be not optimum in the new conditions. To overcome these obstacles, in this paper, an online optimal Decoupled Sliding Mode Control (DSMC) approach is introduced. Firstly, to determine the optimum parameters of DSMC, an improved Particle Swarm Optimization (PSO) algorithm is applied. Next, to adapt the optimal controller to any initial condition, the Moving Least Squares (MLS) approximation is utilized. Finally, the proposed online optimal DSMC is successfully applied to a ball and beam system. The comparative studies are provided to verify the effectiveness of the proposed control scheme. (c) 2014 Elsevier Inc. All rights reserved.

引用

页码：342 / 356

页数：15

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