一类非线性系统模糊自适应固定时间量化反馈控制

王焕清; 陈明; 刘晓平

doi:10.16383/j.aas.c190681

一类非线性系统模糊自适应固定时间量化反馈控制

doi: 10.16383/j.aas.c190681

1.
渤海大学数学科学学院锦州 121007 中国
2.
辽宁科技大学电子与信息工程学院鞍山 114044 中国
3.
湖首大学电子工程系桑德贝 P7G 1A4 加拿大

基金项目: 国家自然科学基金(61773072, 61403177, 62173046), 辽宁省自然基金面上项目(20180550691), 辽宁省教育厅项目(2019LNJC09)资助

详细信息

作者简介:
王焕清：渤海大学数学科学学院教授. 主要研究方向为非线性系统自适应控制, 智能控制.E-mail: ndwhq@163.com

陈明：辽宁科技大学电子与信息工程学院教授. 主要研究方向为非线性系统容错控制, 鲁棒控制. 本文通信作者. E-mail: cm8061@sina.com

刘晓平：加拿大湖首大学教授. 主要研究方向为非线性奇异系统, 非线性自适应控制, 移动机器人, 模糊逻辑控制及神经网络控制.E-mail: xliu2@lakeheadu.ca

计量
- 文章访问数: 1268
- HTML全文浏览量: 421
- PDF下载量: 377
- 被引次数: 0
出版历程
- 收稿日期: 2019-09-29
- 录用日期: 2020-01-17
- 网络出版日期: 2021-10-27
- 刊出日期: 2021-12-23

Fuzzy Adaptive Fixed-time Quantized Feedback Control for a Class of Nonlinear Systems

1.
College of Mathematical Sciences, Bohai University, Jinzhou 121007, China
2.
School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114044, China
3.
Department of Electrical Engineering, Lakehead University, Thunder Bay P7G 1A4, Canada

Funds: Supported by National Natural Science Foundation of China (61773072, 61403177, 62173046), Natural Science Foundation of Liaoning Province (20180550691), and Education Department Project of Liaoning Province (2019LNJC09)

More Information

Author Bio:
WANG Huan-Qing　Professor at the College of Mathematical Sciences, Bohai University. His research interest covers adaptive control and intelligent control

CHEN Ming　Professor at the School of Electronic and Information Engineering, University of Science and Technology Liaoning. Her research interest covers fault-tolerant control and robust control of nonlinear systems. Corresponding author of this paper

LIU Xiao-Ping　Professor in the Department of Electrical Engineering, Lakehead University. His research interest covers nonlinear singular systems, nonlinear adaptive control, walking robots, fuzzy logic control, and neural network control

摘要

摘要: 研究了一类严格反馈不确定非线性系统的模糊自适应实际固定时间量化反馈控制问题. 基于李雅普诺夫有限时间稳定理论、自适应模糊控制理论及反演控制算法, 提出了一种非线性系统模糊自适应实际固定时间量化反馈跟踪控制方案. 所设计的控制方案能够保证闭环系统的输出跟踪误差在固定时间内收敛于原点的一个充分小邻域内, 且闭环系统内所有信号均有界. 最后, 数值示例验证了设计方案的有效性.
- 迟滞量化器 /
- 固定时间控制 /
- 非线性系统 /
- 模糊逻辑系统 /
- 反演控制
Abstract: The problem of fuzzy adaptive practical fixed-time quantized feedback control for a class of strict-feedback nonlinear systems is investigated. Based on the Lyapunov finite-time stability theory, adaptive fuzzy control theory and backstepping algorithm, a fuzzy adaptive practical fixed-time quantized feedback tracking controller is developed, which ensures that the output tracking error converges to a small neighborhood of the origin in a fixed period of time and all the signals in the closed-loop system are bounded. Finally, a numerical example demonstrates the effectiveness of the proposed method.
- Hysteresis quantizer /
- fixed-time control /
- nonlinear systems /
- fuzzy logic systems /
- backstepping control

HTML全文

图 1 期望输出和实际输出曲线

Fig. 1 Trajectories of desired output and practical output

下载: 全尺寸图片幻灯片

图 2 跟踪误差响应曲线

Fig. 2 Response curve of tracking error

下载: 全尺寸图片幻灯片

图 3 状态变量$ x_{2} $响应曲线

Fig. 3 Response curve of $ x_{2} $

下载: 全尺寸图片幻灯片

图 4 控制输入$ u $响应曲线

Fig. 4 Response curve of control input $ u $

下载: 全尺寸图片幻灯片

图 5 量化输出响应曲线

Fig. 5 Response curve of $ Q(u) $

下载: 全尺寸图片幻灯片

图 6 自适应律${\hat{\theta}_{1}}, {\hat{\theta}_{2}}$响应曲线

Fig. 6 Response curves of adaptive control law ${\hat{\theta}_{1}}, {\hat{\theta}_{2}}$

下载: 全尺寸图片幻灯片

参考文献(22)

[1]	秦贞华, 何熊熊, 李刚, 伍益明. 考虑量化输入和输出约束的互联系统自适应分散跟踪控制. 自动化学报, 2019, DOI: 10.16383/j.aas.c180786 Qin Zhen-Hua, He Xiong-Xiong, Li Gang, Wu Yi-Ming. Adaptive Decentralized Tracking Control for Nonlinear Interconnected Systems with Input Quantization and Output Constraints. Acta Automatica Sinica, 2019, DOI: 10.16383/j.aas.c180786
[2]	王隔霞. 一类非线性系统量化反馈控制的几何设计方法. 自动化学报, 2019, DOI: 10.16383/j.aas.c180046 Wang Ge-Xia. Geometrical Method on Quantized Feedback Control Design for A Class of Nonlinear Systems. Acta Automatica Sinica, 2019, DOI: 10.16383/j.aas.c180046
[3]	王隔霞. 一类非线性系统的量化控制器的设计. 自动化学报, 2016, 42(1): 140−144 Wang Ge-Xia. Design of Quantizer for a Class of Nonlinear Systems. Acta Automatica Sinica, 2016, 42(1): 140−144
[4]	刘俊豪, 张皓, 陈启军. 具有均匀量化器的非线性网络控制系统的一致有界性, 控制理论与应用, 2012, 29(11): 1388−1396 Liu Jun-Hao, Zhang Hao, Chen Qi-Jun. Uniformalybounded nonlinear etworked control systems with uniform quantizer. Control Theory and Applications, 2012, 29(11): 1388−1396
[5]	Hayakawa T, Ishii H, Tsumura K. Adaptive quantized controlfornonlinearuncertain systems. Systems and control letters, 2009, 58(9): 625−632 doi: 10.1016/j.sysconle.2008.12.007
[6]	Zhou J, Wen C, Yang G. Adaptive quantized controlfornonlinearuncertain systems. IEEE Transactions on Automatic Control, 2013, 59(2): 460−464
[7]	Polyakov A, Efimov D, Perruquetti W. Finite-time and fixed-time stabilization: Implicit Lyapunov function approach. Automatica, 2015, 51: 332−340 doi: 10.1016/j.automatica.2014.10.082
[8]	Zuo Z. Non-singular fixed-time terminal sliding mode control of non-linear systems. IET control theory and applications, 2014, 7(4): 545−552
[9]	Zuo Z. Nonsingular fixed-time consensus tracking for second-order multi-agent networks. Automatica, 2015, 54: 305−309 doi: 10.1016/j.automatica.2015.01.021
[10]	张骁骏, 袁夏明, 王向阳等. 一种固定时间收敛模型参考终端滑模控制方法, 自动化学报, 2019, DOI: 10.16383/j.aas.c190273 Zhang Xiao-Jun, Yuan Xia-Ming, Wang Xiang-Yang, etc. A model reference terminal sliding mode control method with fixed-time convergence. Acta Automatica Sinica, 2019, DOI: 10.16383/j.aas.c190273
[11]	Jin X. Adaptive fixed-time control for mimo nonlinear systems with asymmetric output constraints using universal barrier functions. IEEE Transactions on Automatic Control, 2018, 64(7): 3046-3053
[12]	Wang H, Liu P X, Li S, Wang D. Adaptive neural outputfeedback control for a class of nonlower triangular nonlinear systems with unmodeled dynamics. IEEE Transactions on Neural Networks and Learning Systems, 2017, 29(8): 3658−3668
[13]	Wang H, Liu P X, Bao J, Xie X, Li S. Adaptive neural output-feedback decentralized control for large-scale nonlinear systems with stochastic disturbances. IEEE transactions on neural networks and learning systems, 2019, DOI: 10.1109/TNNLS.2019.2912082
[14]	Wang H, Liu P X, Shi P. Observer-based fuzzy adaptive output-feedback control of stochastic nonlinear multiple time-delay systems. IEEE Transactions on Cybernetics, 2017, 47(9): 2568−2578 doi: 10.1109/TCYB.2017.2655501
[15]	王桐, 邱剑彬, 高会军. 随机非线性系统基于事件触发机制的自适应神经网络控制, 自动化学报, 2019, DOI 10.16383/j.aas.2018.c180404 doi: 10.16383/j.aas.2018.c180404 Wang Tong, Qiu Jian-Bin, Gao Hui-Jun. Event-triggered Adaptive Neural Network Control for a Class of Stochastic Nonlinear Systems. Acta Automatica Sinica, 2019, DOI 10.16383/j.aas.2018.c180404 doi: 10.16383/j.aas.2018.c180404
[16]	Wang F, Chen B, Lin C, Zhang J, Meng X. Adaptive neural network finite-time output feedback control of quantized nonlinear systems. IEEE Transactions on Cybernetics, 2017, 48(6): 1839−1848
[17]	Liu Z, Wang F, Zhang Y, Chen C.P. Fuzzy adaptive quantized control for a class of stochastic nonlinear uncertain systems. IEEE Transactions on Cybernetics, 2015, 46(2): 524−534
[18]	Zuo Z, Tian B, Defoort M, Ding Z. Fixed-time consensus tracking for multiagent systems with high-order integrator dynamics. IEEE Transactions on Automatic Control, 2017, 63(2): 563−570
[19]	Zhu Z, Xia Y, Fu M. Attitude stabilization of rigid spacecraft with finite-time convergence. International Journal of Robust and Nonlinear Control, 2011, 21(6): 686−702 doi: 10.1002/rnc.1624
[20]	Bhat S P, Bernstein D S. Finite-time stability of continuous autonomous systems. SIAM Journal on Control and Optimization, 2000, 38(3): 751−766 doi: 10.1137/S0363012997321358
[21]	Wang C, Lin Y. Decentralized adaptive tracking control for a class of interconnected nonlinear time-varying systems. Automatica, 2015, 54: 16−24 doi: 10.1016/j.automatica.2015.01.041
[22]	Wang L X, Mendel J M. Fuzzy basis functions, universal approximation, and orthogonal least-squares learning. IEEE transactions on Neural Networks, 1992, 3(5): 807−814 doi: 10.1109/72.159070