Robust Control of Modular Gun Propellant Select Mechanism with Unknown Dead-Zone

Article Preview

Abstract:

Modular gun propellant select mechanism is an important subsystem of the gun automatic loading system, it is used to select desired amount of modular gun propellants, which are placed in a receptacle. The distance between two adjacent propellants is short because of the small storage space, so robust precision control is important and necessary to reliably select the desired amount of propellants. The mathematical model is obtained, and nonlinear characteristics such as nonlinear friction, transmission clearance, and unknown dead-zone and so on are also considered. To simplify the problem, a simplified disturbing force model is used to replace the impulse force when the propellant, which is fastened by a hook, is freed. Considering that the system parameters are time-varying and also the system is influenced by an additional disturbance, a fuzzy sliding mode controller is designed by using the sliding mode control theory and fuzzy control theory together, the sliding mode control forces the system to move along the desired trajectory while the fuzzy control is used to reduce the chattering. Three situations, that are select one, three and five propellants respectively, have been studied, simulation results show that the presented fuzzy sliding mode controller is not only insensitive to the system parameters change and the additional disturbances, but also has high position precision.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

812-817

Citation:

Online since:

August 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Niraj Kumar Shukla, Dr. S K Sinha. Fuzzy and PI Controller Based Performance Evaluation of Separately Excited DC Motor [J]. International Journal of Emerging Trends in Electrical and Electronics, Vol. 2, 12~18(2013).

Google Scholar

[2] Navid Moshtaghi Yazdani. Performance Comparison between Classic and Intelligent Methods for Position Control of DC Motor [J]. 7th SASTech (2013).

Google Scholar

[3] WANG Xing-Song, Chun-Yi Su, Henry Hong. Robust adaptive control of a class of nonlinear systems with unknown dead-zone[J]. Automatic (2004) 407~413.

DOI: 10.1109/cdc.2001.981134

Google Scholar

[4] HU Chuxiong, YAO Bin and WANG Qingfeng. Adaptive Robust Precision Motion Control of Systems with Unknown Input Dead-zone: A Case Study with Comparative Experiments. [J]. IEEE Transactions on Industrial Electronics. 58(6)(2011).

DOI: 10.1109/tie.2010.2066535

Google Scholar

[5] LIU Jin-kun. MATLAB Simulation for Sliding Mode Control[M]. Beijing TSINGHUA University Press, (2005).

Google Scholar

[6] Ilyas Eker. Sliding mode control with PID sliding surface experimental application to an electromechanical plant [J]. ISA Transactions 45, (2006) 109–118.

DOI: 10.1016/s0019-0578(07)60070-6

Google Scholar

[7] ZHANG T. P GE S.S. Adaptive dynamic surface control of nonlinear systems with unknown dead-zone in pure feedback form [J]. Automatic 44(2008) 1895-(1903).

DOI: 10.1016/j.automatica.2007.11.025

Google Scholar

[8] MA Hong-jun, YANG Guang-hong. Adaptive output control of uncertain nonlinear system with non-symmtric dead-zone input [J]. Automatic 46 (2010) 413-420.

DOI: 10.1016/j.automatica.2009.11.010

Google Scholar

[9] ZHU Jing. Fuzzy Control Theory and Its Applications[M]. Beijing: China Machine Press(2005).

Google Scholar

[10] Robust Motion Controller Design for High-Accuracy Positioning Systems [J]. IEEE Transactions on Industrial Electronics. 43(1)(1996).

DOI: 10.1109/41.481407

Google Scholar