Improved Nonminimal State Space Model Predictive Control for Multivariable Processes Using a Non-Zero–Pole Decoupling Formulation
Jianming Zhang
Abstract
Jianming Zhang
Abstract
In this article, a decoupling approach is first formulated, and then a corresponding nonminimal state space predictive control is proposed. The proposed decoupling structure can avoid zero–pole cancellations between the decoupler and the process, and thus, realization is guaranteed. Consequently, a systematic design of nonminimal state space predictive control can be designed in terms of a SISO procedure. Simulation results of a typical multivariable process are provided to demonstrate the effectiveness of the proposed method. In addition, a closed-form transfer function representation that facilitates frequency analysis of the control system is also provided to give further insight into the proposed strategy.
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In this article, a decoupling approach is first formulated, and then a corresponding nonminimal state space predictive control is proposed. The proposed decoupling structure can avoid zero–pole cancellations between the decoupler and the process, and thus, realization is guaranteed. Consequently, a systematic design of nonminimal state space predictive control can be designed in terms of a SISO procedure. Simulation results of a typical multivariable process are provided to demonstrate the effectiveness of the proposed method. In addition, a closed-form transfer function representation that facilitates frequency analysis of the control system is also provided to give further insight into the proposed strategy.
Key concepts: Multivariable calculus, Decoupling (probability), Control theory (sociology), Model predictive control, Realization (probability), State-space representation, Computer science, Representation (politics)