Single neuron/PID adaptive compound control and parameter optimization for the inertially stabilized platform

被引：0
|
作者：
Zhou X. [1 ,2 ]
Shi Y. [1 ]
机构：
[1] School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing
[2] Beijing Academy of Quantum Beijing Academy of Quantum Information Sciences, Beijing
来源：
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2019年 / 40卷 / 11期
关键词：
Aerial sensing; Improved bacterial foraging optimization; Inertially stabilized platform; Single neuron/PID(proportion integration differentiation) adaptive control; Stabilization precision;
D O I：
10.19650/j.cnki.cjsi.J1905406
中图分类号：
学科分类号：
摘要：
To meet the requirements of high stability precision control to an inertially stabilized platform (ISP), a single neuron/proportion integration differentiation (PID) adaptive compound control method based on the improved bacterial foraging optimization algorithm is proposed. Firstly, the single neuron and PID control are fused to formulate a single neuron/PID adaptive controller to realize the adaptive control of ISP. In this way, the control accuracy of the ISP is improved. Secondly, to solve the problem that the optimal parameters of the controller are hard to be achieved by the trial method, an improved bacterial foraging optimization algorithm is used to optimize the parameters of the compound controllers. Finally, simulations and experiments are carried out. Experimental results show that the proposed method can significantly improve the system performance such as stability accuracy and disturbance rejection ability. After utilizing the compound control with parameter optimization, the stabilization accuracy of the platform under the condition of static and dynamic base are 0.003 8° and 0.290 4°, which are 19.1% and 39.9% higher than the traditional PID control. © 2019, Science Press. All right reserved.
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页码：189 / 196
页数：7
相关论文
共 15 条
  • [1] Zhou X.Y., Gao H., Zhao B.L., Et al., A GA-based parameters tuning method for an ADRC controller of ISP for aerial remote sensing applications, ISA Transactions, 81, 8, pp. 318-328, (2018)
  • [2] Zhong M.Y., Jiao C.B., Li S.S., Et al., Study on the compensation method for disturbance torque of three-axis inertially stabilized platform based on PMI, Chinese Journal of Scientific Instrument, 35, 4, pp. 781-787, (2014)
  • [3] Wang H.G., Williams T.C., Strategic inertial navigation systems: High-accuracy inertially stabilized platforms for hostile environments, IEEE Control System Magazine, 28, 1, pp. 65-85, (2008)
  • [4] Zhou X.Y., Jia Y., Yue H.X., Et al., MC & OS-based CMAC compound control of inertially stabilized platform for aerial remote sensing, Chinese Journal of Scientific Instrument, 37, 4, pp. 764-771, (2016)
  • [5] Rong Z.G., Zhang S., Yang L.N., Et al., Research on stability control of parallel mechanism based on single neuron PID, Information Technology, 2, pp. 98-101, (2019)
  • [6] Liu G.Q., Li L., Quantification factor self-tuning fuzzy PID controller research for a permanent magnet synchronous motor feeding system, IEEE Control and Decision Conference, pp. 2510-2514, (2012)
  • [7] Jiang J.G., Zhou J.W., Zheng Y.C., Et al., Adaptive bacterial foraging optimization algorithm, Journal of Xidian University(Natural Science), 42, 1, pp. 75-81, (2015)
  • [8] Guan L.H., Zeng Z.G., Bao H.X., Et al., Application of an improved bacterial foraging algorithm to image segmentation, Journal of Hunan University of Technology, 30, 6, pp. 34-38, (2016)
  • [9] Zhao W.G., Wang L.Y., An effective bacterial foraging optimizer for global optimization, Information Sciences, 329, 2, pp. 719-735, (2016)
  • [10] Zhou X.Y., Li L.L., Zhao L.B., Nonsingular terminal sliding mode control for the ESO-based stabilized platform, Chinese Journal of Scientific Instrument, 39, 5, pp. 161-169, (2018)
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