Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems

Authors:
Zhongsheng Hou;Shangtai Jin
Affiliations:
Advanced Control Systems Laboratory of the School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China;Advanced Control Systems Laboratory of the School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China
Venue:
IEEE Transactions on Neural Networks - Part 2
Year:
2011

Citing 0
Cited 2

A multivariable predictive fuzzy PID control system

Applied Soft Computing
From model-based control to data-driven control: Survey, classification and perspective

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT includes compact form dynamic linearization, partial form dynamic linearization, and full form dynamic linearization. The main feature of the approach is that the controller design depends only on the measured input/output data of the controlled plant. Analysis and extensive simulations have shown that MFAC guarantees the bounded-input bounded-output stability and the tracking error convergence.