The PFDL-Model-Free Adaptive Predictive Control for a Class of Discrete-Time Nonlinear Systems
Systems and Control
2020-12-04 v2 Systems and Control
Abstract
In this paper, a novel partial form dynamic linearization (PFDL) data-driven model-free adaptive predictive control (MFAPC) method is proposed for a class of discrete-time single-input single-output nonlinear systems. The main contributions of this paper are that we combine the concept of MPC with MFAC together to propose a novel MFAPC method. We prove the bounded-input bounded-output stability and tracking error monotonic convergence of the proposed method; Moreover, we discuss the possible relationship between the current PFDL-MFAC and the proposed PFDL-MFAPC. The simulation and experiment are carried out to verify the effectiveness of the proposed MFAPC.
Keywords
Cite
@article{arxiv.1910.09961,
title = {The PFDL-Model-Free Adaptive Predictive Control for a Class of Discrete-Time Nonlinear Systems},
author = {Feilong Zhang},
journal= {arXiv preprint arXiv:1910.09961},
year = {2020}
}
Comments
8 pages,3 figures. arXiv admin note: substantial text overlap with arXiv:1910.08321