identification for closed-loop two-dimensional (2-d) causal, recursive, and separable-in-denominator (crsd) systems in the Roesser form is discussed in this study. For closed-loop 2-dcrsd systems, under feedback cont...
详细信息
identification for closed-loop two-dimensional (2-d) causal, recursive, and separable-in-denominator (crsd) systems in the Roesser form is discussed in this study. For closed-loop 2-dcrsd systems, under feedback control condition, there exists some correlation between the unknown disturbances and future inputs which offers the fundamental limitation for utilizing standard open-loop 2-dcrsd systems subspace identification methods. In other words, the existing open-loop subspace approaches will result in biased estimates of plant parameters from closed-loopdata. In this study, based on orthogonal projection and principal component analysis, novel 2-dcrsd subspace identification methods are developed, which are applicable to both open-loop andclosed-loopdata. Additionally, the whiteness external excitation case is discussed and subsequently modified instrument variables are adopted to improve the proposed subspace algorithm. An illustrative example of the injection molding process and several numerical examples are used to validate consistency and efficiency of the proposed subspace approaches for 2-dcrsd systems.
暂无评论