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山东大学学报 (工学版) ›› 2020, Vol. 50 ›› Issue (1): 35-48.doi: 10.6040/j.issn.1672-3961.0.2019.039

• 控制科学与工程 • 上一篇    下一篇

一类非仿射非线性大系统的结构在线扩展

曹小洁(),李小华*(),刘辉   

  1. 辽宁科技大学电子与信息工程学院, 辽宁 鞍山 114051
  • 收稿日期:2019-01-23 出版日期:2020-02-20 发布日期:2020-02-14
  • 通讯作者: 李小华 E-mail:1085515524@qq.com;lixiaohua6412@163.com
  • 作者简介:曹小洁(1994-),女,辽宁大连人,硕士研究生,主要研究方向为非线性系统的控制问题. E-mail: 1085515524@qq.com
  • 基金资助:
    辽宁省科技厅自然科学基金(20180550319)

Construction expansion online for a class of nonaffine nonlinear large-scale systems

Xiaojie CAO(),Xiaohua LI*(),Hui LIU   

  1. School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051, Liaoning, China
  • Received:2019-01-23 Online:2020-02-20 Published:2020-02-14
  • Contact: Xiaohua LI E-mail:1085515524@qq.com;lixiaohua6412@163.com
  • Supported by:
    辽宁省科技厅自然科学基金(20180550319)

摘要:

研究一类非仿射非线性互联大系统的结构在线扩展问题。基于backstepping技术提出一种大系统在线结构扩展的自适应神经分散关联镇定控制方法。在原结构系统控制器保持不变的前提下,利用神经网络自适应技术设计新加入子系统的分散控制律和自适应律,将新加入子系统后原结构系统产生的互联部分放在新子系统的控制器中处理,从而获得新扩展子系统的自适应分散关联镇定控制器。该控制器可以保证新加入的闭环非仿射非线性子系统及整个扩展后的闭环大系统中所有信号是一致最终关联有界的。仿真结果验证了所提控制方法的有效性。

关键词: 非仿射大系统, 结构在线扩展, 神经网络自适应技术, 分散关联控制, backstepping技术

Abstract:

The problem of construction expansion online was studied for a class of nonaffine nonlinear interconnected large-scale systems. An adaptive neural decentralized connective stabilization method was proposed for expansion online of large-scale systems based on backstepping technique. By using neural network adaptive technique, the decentralized controller of the newly added subsystem was designed under the condition that the decentralized control laws and adaptive laws of the original system were kept to be unchanged. The interconnection parts caused the a new subsystem were dealt with in the controller of the new subsystem. An adaptive decentralized connective stabilization controller for the newly added subsystem was obtained. The controller could ensure that all the signals both in the newly added closed-loop nonaffine subsystem and the resultant expanded closed-loop large-scale system were uniformly ultimately connective bounded. The simulation results were given to verify the effectiveness of the proposed control method.

Key words: nonaffine large-scale systems, construction expansion online, neural network adaptive technique, decentralized connective control, backstepping technique

中图分类号: 

  • TP273

图1

由弹簧连接的耦合倒立摆系统"

图2

耦合倒立摆系统y1, y2的仿真结果"

图3

耦合倒立摆系统的状态轨迹x1, 2, x2, 2的仿真结果"

图4

耦合倒立摆系统的自适应参数${\hat \theta _1}$, ${\hat \theta _2}$的仿真结果"

图5

耦合倒立摆系统的控制输入u1, u2的仿真结果"

图6

扩展倒立摆系统的y1, y2, y3的仿真结果"

图7

扩展倒立摆系统的状态轨迹x1, 2, x2, 2, x3, 2的仿真结果"

图8

扩展倒立摆系统的自适应参数${\hat \theta _1}$, ${\hat \theta _2}$, ${\hat \theta _3}$的仿真结果"

图9

扩展倒立摆系统的控制输入u1, u2, u3的仿真结果"

图10

移除互联项后扩展倒立摆系统的y1, y2, y3的仿真结果"

图11

移除互联项后扩展倒立摆系统的状态x1, 2, x2, 2, x3, 2的仿真结果"

图12

移除互联项后扩展倒立摆系统自适应参数${\hat \theta _1}$, ${\hat \theta _2}$, ${\hat \theta _3}$的仿真结果"

图13

移除互联项后扩展倒立摆系统控制输入u1, u2, u3的仿真结果"

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