非线性严格反馈系统自适应非反步输出反馈控制
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作者单位:

昆明理工大学机电工程学院

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中图分类号:

TP273

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


Adaptive Non-backstepping Output-feedback Control of Nonlinear Strict-feedback Systems
Author:
Affiliation:

Kunming University of Science and Technology

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    针对传统反步控制器设计方法存在复杂度爆炸、参数收敛难、控制奇异、需全系统状态已知等问题, 提出一种新的可保证参数收敛的未知系统动态辨识和非反步输出反馈自适应控制方法. 通过定义新的状态变量和系统等价变换, 将严格反馈系统状态反馈控制转化为标准系统的输出反馈控制, 进而设计包含高阶微分器的自适应单步控制器, 避免反步递推设计的问题. 采用两个神经网络对系统集总未知动态进行估计, 避免了传统控制方法在未知控制增益在线估计过零引发的奇异问题. 构造一种新的自适应算法在线更新神经网络权值确保其收敛到真实值, 进而实现对未知系统动态的精准辨识. 基于Lyapunov 定理的分析表明, 跟踪误差和估计误差均可收敛到零点附近紧集. 基于液压伺服系统模型的对比仿真验证了该方法的有效性和优越性.

    Abstract:

    To remedy the issues of "explosion of complexity", nonconvergent parameter estimation, control singularity, and stringent requirement on the full states in the conventional backstepping methods, this paper proposes a new adaptive identification scheme with guaranteed convergence and an adaptive output-feedback control method for nonlinear strict-feedback systems without using backstepping. By defining new state variables and a coordinate transformation, the state-feedback control of strict-feedback systems can be transformed into an output-feedback control of the derived canonical model. Then, an one-step adaptive control with high-order differentiator is designed. Furthermore, two neural networks (NNs) are employed to approximate the lumped unknown dynamics so as to avoid the potential singularity in the existing control designs. To ensure the convergence of parameter estimation, a novel adaptive law is constructed to online update the NN weights. We adopt the Lyapunov method to prove that the tracking error and estimation error can converge to a small compact set around zero. Comparative simulations based on a hydraulic servo system are provided to show the effectiveness and superiority of the proposed methods.

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历史
  • 收稿日期:2021-02-09
  • 最后修改日期:2021-06-18
  • 录用日期:2021-07-05
  • 在线发布日期: 2021-08-01
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