基于分数阶神经滑模的某顶置火炮调炮控制

doi:10.3969/j.issn.1000-1093.2013.10.018

兵工学报 ›› 2013, Vol. 34 ›› Issue (10): 1311-1317.doi: 10.3969/j.issn.1000-1093.2013.10.018

基于分数阶神经滑模的某顶置火炮调炮控制

高强¹, 侯润民¹, 杨国来¹, 毛斌², 侯远龙¹

1. 南京理工大学机械工程学院, 江苏南京210094; 2. 北方重工业集团科研所, 内蒙古包头014033

收稿日期:2012-05-16 修回日期:2012-05-16 上线日期:2013-12-16
作者简介:高强(1979—),男,讲师,硕士生导师。
基金资助:
国家重点基础研究发展计划项目(61311603)

Adjustment and Control of a Certain Top-mounted Gun Based on a Novel Fractional Order Neural Sliding Mode Strategy

GAO Qiang¹, HOU Run-min¹, YANG Guo-lai¹,MAO Bin²,HOU Yuan-long¹

1. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China; 2. Research Institute, North Heavy Industries Group, Baotou 014033, Inner Mongolia, China

Received:2012-05-16 Revised:2012-05-16 Online:2013-12-16

摘要/Abstract

摘要： 针对某顶置火炮高低向调炮控制系统存在的强非线性特征,提出了一种分数阶神经网络滑模控制(FNSMC)策略。引入分数阶微积分(FOC),设计了分数阶PID 型滑模面,获得了用于火炮控制的具有分数阶动力学特征的等效控制量。采用饱和函数作为切换函数,基于RBF 神经网络对其切换增℃进行在线动态调节,以获得动态最优性能。通过数值仿真分析比较了引入FOC 后滑模控制系统的动静态特性,结果表明:分数阶滑模控制(FSMC)系统能够更为快速平滑的趋近稳态,这将有效抑制抖振现象,减小控制系统响应时间。半实物仿真试验结果表明:所提出的FNSMC 策略明显优于传统整数阶神经网络滑模控制( CNSMC),具有更强的鲁棒性及更高的控制精度,可以很好实现预期的快速、平稳和高精度调炮。

关键词: 自动控制技术, 炮控系统, 滑模控制, 分数阶微积分, RBF 神经网络

Abstract: A novel fractional order neural sliding mode control (FNSMC) strategy is proposed for the nonlinearities of a gun control system (GCS) which is used to control the elevation of a certain topmounted gun. A fractional order PID type sliding surface is especially designed by introducing the fractional order calculus, and an equivalent control discipline with fractional order dynamics is induced. The saturation function is employed as switch function. To achieve the best control performances, a dynamic adjustment approach of the switch gain is introduced based on RBF neural network. The dynamic and static characteristics of the fractional order sliding mode control (FSMC) system are analyzed by numerical simulation, demonstrating that FSMC can reach up to the steady state more smoothly, which significantly suppresses the chatter effects and enhances the response rate of the control system. Finally, a series of experiments on a semi-physics simulation platform are conducted to investigate the performances of control system. The results show that the proposed FNSMC is of more excellence than the conventional integer order neural SMC(CNSMC). The FNSMC-based control system is of better tracking accuracy as well as high robustness, and the fast, smooth and accurate adjustments of the gun can be achieved.

Key words: automatic control technology, gun control system, sliding mode control, fractional order cal- culus, RBF neural network

中图分类号:

TP273

高强, 侯润民, 杨国来, 毛斌, 侯远龙. 基于分数阶神经滑模的某顶置火炮调炮控制[J]. 兵工学报, 2013, 34(10): 1311-1317.

GAO Qiang, HOU Run-min, YANG Guo-lai,MAO Bin,HOU Yuan-long. Adjustment and Control of a Certain Top-mounted Gun Based on a Novel Fractional Order Neural Sliding Mode Strategy[J]. Acta Armamentarii, 2013, 34(10): 1311-1317.

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基于分数阶神经滑模的某顶置火炮调炮控制

Adjustment and Control of a Certain Top-mounted Gun Based on a Novel Fractional Order Neural Sliding Mode Strategy

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