Suppr超能文献

基于观测器的自适应神经网络控制用于一类具有非对称输入饱和的不确定非线性系统。

Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation.

出版信息

IEEE Trans Neural Netw Learn Syst. 2017 Jul;28(7):1520-1530. doi: 10.1109/TNNLS.2016.2529843. Epub 2016 Mar 8.

Abstract

This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.

摘要

本文针对一类具有非对称输入饱和和不可测状态的不确定非线性系统的自适应跟踪控制问题进行了研究。利用神经网络(NN)的径向基函数来逼近未知函数,并设计了一个 NN 状态观测器来估计不可测状态。为了分析输入饱和的影响,引入了一个辅助系统。通过自适应反推技术,提出了一种自适应跟踪控制方法。在所提出的自适应跟踪控制器下,闭环系统中所有信号的有界性得以实现。此外,与大多数现有参考文献不同的是,跟踪误差可以通过设计参数和饱和输入误差的显式函数来进行约束。最后,通过一个实例验证了所提出方法的有效性。

相似文献

1
Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation.
IEEE Trans Neural Netw Learn Syst. 2017 Jul;28(7):1520-1530. doi: 10.1109/TNNLS.2016.2529843. Epub 2016 Mar 8.
2
Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form.
IEEE Trans Neural Netw Learn Syst. 2016 Jan;27(1):89-98. doi: 10.1109/TNNLS.2015.2412121. Epub 2015 Mar 25.
3
Adaptive neural network decentralized backstepping output-feedback control for nonlinear large-scale systems with time delays.
IEEE Trans Neural Netw. 2011 Jul;22(7):1073-86. doi: 10.1109/TNN.2011.2146274. Epub 2011 Jun 2.
4
Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities.
IEEE Trans Neural Netw. 2010 May;21(5):796-812. doi: 10.1109/TNN.2010.2042611. Epub 2010 Mar 15.
5
Composite Adaptive Fuzzy Output Feedback Control Design for Uncertain Nonlinear Strict-Feedback Systems With Input Saturation.
IEEE Trans Cybern. 2015 Oct;45(10):2299-308. doi: 10.1109/TCYB.2014.2370645. Epub 2014 Nov 25.
6
Observer-Based Adaptive Fuzzy Backstepping Dynamic Surface Control for a Class of MIMO Nonlinear Systems.
IEEE Trans Syst Man Cybern B Cybern. 2011 Aug;41(4):1124-35. doi: 10.1109/TSMCB.2011.2108283. Epub 2011 Feb 10.
7
8
Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints.
IEEE Trans Neural Netw Learn Syst. 2017 Jun;28(6):1318-1330. doi: 10.1109/TNNLS.2016.2538779. Epub 2016 Mar 17.
9
Observer-Based NN Control for Nonlinear Systems With Full-State Constraints and External Disturbances.
IEEE Trans Neural Netw Learn Syst. 2022 Sep;33(9):4322-4331. doi: 10.1109/TNNLS.2021.3056524. Epub 2022 Aug 31.
10
Adaptive output feedback tracking of nonlinear systems with uncertain nonsymmetric dead-zone input.
ISA Trans. 2019 Dec;95:35-44. doi: 10.1016/j.isatra.2019.05.020. Epub 2019 May 24.

引用本文的文献

1
Finite-Time Dynamic Tracking Control of Parallel Robots with Uncertainties and Input Saturation.
Sensors (Basel). 2021 Apr 24;21(9):2996. doi: 10.3390/s21092996.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验