A Novel Data-Driven Control Approach for a Class of Discrete-Time Nonlinear Systems

被引：605

作者：

Hou, Zhongsheng ^{[1
]}

Jin, Shangtai ^{[1
]}

机构：

[1] Beijing Jiaotong Univ, Adv Control Syst Lab, Sch Elect & Informat Engn, Beijing 100044, Peoples R China

来源：

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | 2011年 / 19卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Adaptive control; compact form dynamic linearization (CFDL); data-driven control; model-free adaptive control (MFAC); partial form dynamic linearization (PFDL); pseudo-partial derivative (PDD); three-tank system; ADAPTIVE-CONTROL; PREDICTIVE CONTROL; LEARNING CONTROL; CONTROL DESIGN; OPTIMIZATION; HORIZON;

D O I：

10.1109/TCST.2010.2093136

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this work, a novel data-driven control approach, model-free adaptive control, is presented based on a new dynamic linearization technique for a class of discrete-time single-input and single-output nonlinear systems. The main feature of the approach is that the controller design depends merely on the input and the output measurement data of the controlled plant. The theoretical analysis shows that the approach guarantees the bounded input and bounded output stability and tracking error monotonic convergence. The comparison experiments verify the effectiveness of the proposed approach.

引用

页码：1549 / 1558

页数：10

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