title: Data-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systems.
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.
authors.affiliation: Advanced Control Systems Laboratory of the School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China. zhshhou@bjtu.edu.cn
authors.forename: Zhongsheng
authors.initials: Z
authors.lastname: Hou
authors.forename: Shangtai
authors.initials: S
authors.lastname: Jin
mesh_terms: D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D005246:Feedback; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted