Sliding Mode Control of Electro-hydraulic Position Servo System Optimized by Improved PSO Algorithm
-
摘要: 针对电液位置伺服系统因参数不确定性、复杂时变性与非线性而导致控制性能不佳的问题，提出了一种基于改进PSO算法的电液位置伺服系统滑模控制方法。建立电液位置伺服系统的误差状态空间方程，通过设计滑模面和控制律推导出滑模控制器结构，利用李雅普诺夫函数验证了控制器的稳定性，采用柯西变异和自适应速度更新策略改进了PSO算法，并把改进后的PSO算法应用至滑模控制器中进行参数优化，基于AMEsim/MATLAB联合仿真研究了几种方法下系统对位置的跟踪情况。结果表明，相比于PSO算法和APSO算法，改进PSO算法寻优性能更好，从而验证了该方法是有效的；通过对比分析，采用改进PSO算法的滑模控制器极大地提高了系统的控制性能，在抑制抖振的同时实现了系统对状态轨迹的快速精确跟踪。通过现场试验研究，验证了所提方法的应用可行性。Abstract: In view of the problem that the control performance of electro-hydraulic position servo system is poor due to parameter uncertainty, complex time variability and nonlinearity. A sliding mode control method for electro-hydraulic position servo system based on improved particle swarm optimization (PSO) algorithm is proposed. The error state space equation of electro-hydraulic position servo system is established. The sliding mode controller structure is deduced by designing sliding mode surface and control rule. The stability of the controller is verified by Lyapunov function. The PSO algorithm is improved by using Cauchy mutation and adaptive speed update strategy, and the improved PSO algorithm is applied to the parameter optimization of sliding mode controller. Based on AMEsim/MATLAB co-simulation, the position tracking performance of the system for several methods is studied. The results show that the performance of the improved PSO algorithm is better than that of the PSO algorithm and the APSO algorithm, which proves that the improved method is effective. Through the comparison and analysis, the sliding mode controller with improved PSO algorithm is better, which greatly improves the control performance of the system and realizes the fast and accurate tracking of the state trajectory while damping the vibration. The feasibility of the proposed method is verified by experimental results.
-
表 1 电液位置伺服系统AMEsim模型参数
参数名称 数值及单位 液压油密度 850 kg/m3 液压油都动力粘度 0.03 Pa·s 液压泵系统压力 20 MPa 液压泵系统流量 300 L/min 电磁伺服阀额度电流 50 mA 电磁伺服阀固有频率 100 Hz 电磁伺服阀最大开口流量 150 L/min 活塞缸直径 120 mm 活塞直径 95 mm 负载总质量 300 kg 电机转速 1 500 r/min 
下载: 导出CSV
-
[1] Shao J P, Wang Z W, Lin J Y, et al. Model identification and control of electro-hydraulic position servo system[C]//Proceedings of 2009 International Conference on Intelligent Human-Machine Systems and Cybernetics. Hangzhou, Zhejiang, China: IEEE, 2009 [2] 高岗, 郑建明, 章小林, 等.直驱泵控电液位置伺服系统模糊滑模控制仿真与实验研究[J].机械科学与技术, 2015, 34(8):1239-1243 http://jxkx.cbpt.cnki.net/WKA2/WebPublication/paperDigest.aspx?paperID=f4e56c3c-c850-4716-a62d-33e16f25fd0aGao G, Zheng J M, Zhang X L, et al. Simulation and experimental study of fuzzy sliding mode control for direct drive bump-controlled electro-hydraulic position servo system[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(8):1239-1243(in Chinese) http://jxkx.cbpt.cnki.net/WKA2/WebPublication/paperDigest.aspx?paperID=f4e56c3c-c850-4716-a62d-33e16f25fd0a [3] 林浩, 李恩, 梁自泽.具有非线性不确定参数的电液伺服系统自适应backstepping控制[J].控制理论与应用, 2016, 33(2):181-188 http://d.old.wanfangdata.com.cn/Periodical/kzllyyy201602006Lin H, Li E, Liang Z Z. Adaptive backstepping controller for electro-hydraulic servo system with nonlinear uncertain parameters[J]. Control Theory & Application, 2016, 33(2):181-188(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/kzllyyy201602006 [4] Tadesse A, Ma J G. Modeling and simulations on a fuzzy-PID position controller of electro hydraulic servo system[C]//Proceedings of the 12th International Conference on Fuzzy Systems and Knowledge Discovery. Zhangjiajie, China: IEEE, 2016 [5] Yu L K, Zheng J M, Yuan Q L, et al. Fuzzy PID control for direct drive electro-hydraulic position servo system[C]//Proceedings of 2011 International Conference on Consumer Electronics, Communications and Networks. Xianning, China: IEEE, 2011 [6] Mintsa H A, Venugopal R, Kenne J P, et al. Feedback linearization-based position control of an electrohydraulic servo system with supply pressure uncertainty[J]. IEEE Transactions on Control Systems Technology, 2012, 20(4):1092-1099 doi: 10.1109/TCST.2011.2158101 [7] Li L J, Poms U, Thurner T. Accurate position control of a servo-hydraulic test cylinder by iterative learning control technique[C]//Proceedings of 2014 European Modelling Symposium. Pisa, Italy: IEEE, 2014 [8] 靳宝全, 熊诗波, 程珩.电液位置伺服系统的变速趋近律滑模控制抖振抑制[J].机械工程学报, 2013, 49(10):163-169 http://d.old.wanfangdata.com.cn/Periodical/jxgcxb201310023Jin B Q, Xiong S B, Cheng H. Chattering inhibition of variable rate reaching law sliding mode control for electro-hydraulic position servo system[J]. Journal of Mechanical Engineering, 2013, 49(10):163-169(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/jxgcxb201310023 [9] 周向阳, 李玲玲, 赵立波.基于扩张状态观测器的稳定平台非奇异终端滑模控制[J].仪器仪表学报, 2018, 39(5):161-169 http://epub.cnki.net/grid2008/detail.aspx?filename=YQXB201805020&dbname=DKFX2018Zhou X Y, Li L L, Zhao L B. Nonsingular terminal sliding mode control for the ESO-based stabilized platform[J]. Chinese Journal of Scientific Instrument, 2018, 39(5):161-169(in Chinese) http://epub.cnki.net/grid2008/detail.aspx?filename=YQXB201805020&dbname=DKFX2018 [10] Kumar A, Hardas R S. Reduced rate adaptive sliding mode control based robust position tracking for rotatory electro hydraulic servo system[C]//Proceedings of 2015 International Conference on Power and Advanced Control Engineering. Bangalore, India: IEEE, 2015 [11] 王陆峰.基于粒子群算法的重型车辆悬架路面友好性非线性优化[J].振动与冲击, 2018, 37(8):218-224 http://d.old.wanfangdata.com.cn/Periodical/zdycj201808033Wang L F. Road friendliness optimization of heavy vehicle suspension based on particle swarm algorithm[J]. Journal of Vibration and Shock, 2018, 37(8):218-224(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/zdycj201808033 [12] Lai L H. A synchronization position control method based on dynamic particle swarm optimization algorithm in electro-hydraulic servo system[C]//Proceedings of the IET International Conference on Smart and Sustainable City 2013. Shanghai, China: IET, 2013 [13] 刘云峰, 缪栋.电液伺服系统的自适应模糊滑模控制研究[J].中国电机工程学报, 2006, 26(14):140-144 doi: 10.3321/j.issn:0258-8013.2006.14.026Liu Y F, Miao D. Research on adaptive fuzzy sliding mode control for electro-hydraulic servo system[J]. Proceedings of the CSEE, 2006, 26(14):140-144(in Chinese) doi: 10.3321/j.issn:0258-8013.2006.14.026 [14] 石姣姣, 郑建明, 李旭波, 等.直驱泵控压力伺服系统自适应模糊PID控制[J].机械科学与技术, 2017, 36(1):52-57 http://jxkx.cbpt.cnki.net/WKA2/WebPublication/paperDigest.aspx?paperID=1edbbcb8-f507-49b9-8147-d8940ad6b819Shi J J, Zheng J M, Li X B, et al. Adaptive fuzzy PID control of direct drive pump-controlled pressure servo system[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(1):52-57(in Chinese) http://jxkx.cbpt.cnki.net/WKA2/WebPublication/paperDigest.aspx?paperID=1edbbcb8-f507-49b9-8147-d8940ad6b819 [15] Eberhart R, Kennedy J. A new optimizer using particle swarm theory[C]//Proceedings of the 6th International Symposium on Micro Machine and Human Science. Nagoya, Japan: IEEE, 2002 [16] Kennedy J, Eberhart R. Particle swarm optimization[C]//Proceedings of ICNN'95-International Conference on Neural Networks. Perth, WA, Australia: IEEE, 1995: 1942-1948 [17] Ali M, Pant M. Improving the performance of differential evolution algorithm using Cauchy mutation[J]. Soft Computing, 2011, 15(5):991-1007 doi: 10.1007/s00500-010-0655-2 -
点击查看大图
图(12) / 表(1)
计量
- 文章访问数: 433
- HTML全文浏览量: 259
- PDF下载量: 23
- 被引次数: 0
