A New Model-Free Method for MIMO Systems and Discussion on Model-Free or Model-Based

TL;DR

This paper introduces a novel model-free adaptive predictive control method for MIMO systems that effectively handles time delays by utilizing an equivalent-dynamic-linearization model, extending applicability beyond existing methods.

Contribution

The paper proposes a new MFAPC approach based on EDLM, relaxing previous assumptions and broadening the control input matrix and pseudo-order ranges for improved performance.

Findings

Enhanced handling of time delays in MIMO systems

Extended control input matrix applicability

Simplified performance analysis and parameter selection

Abstract

Current model-free adaptive control (MFAC) can hardly deal with the time delay problem in multiple-input multiple-output (MIMO) systems. To solve this problem, a novel model-free adaptive predictive control (MFAPC) method is proposed. Compared to the current MFAC, i) the proposed method is based on a kind of prediction model which derives from the equivalent-dynamic-linearization model (EDLM); ii) the previous assumptions are relaxed and the application range of MFAPC are extended. The leading coefficient of the control input vector in system description is no more restricted to the diagonally dominant square matrix and the permissible ranges of pseudo orders Ly and Lu are extended; iii) the performance analysis and the issue of how to choose the matrix {\lambda} are completed by an easy manner of analyzing the function of the closed-loop poles, however, both problems may not be realized by the previous contraction mapping method.