Input–output pairing analysis for uncertain multivariable processes

Abstract

Decentralized control structure is widely employed in many industrial multivariable processes. In this approach, control structure design and in particular input–output pairing is a vital stage in the design procedure. There are several powerful methods to select the appropriate input–output pair in linear multivariable plants. However, in the face of plant uncertainties, the input–output pairs can change. Input–output pairing problem, in the presence of uncertainties, and its consequences on the pairing problem have not been widely addressed. In this paper, Hankel interaction index array is used to choose the appropriate input–output pair and a new method is proposed to compute Hankel interaction index array, which reduces the computational load. Also, a theorem will be presented to show the effect of additive uncertainties on input–output pairing of the process. An upper bound on the element variations of Hankel interaction index array of the additive uncertainties in state space framework is given to show the possible change in input–output pairing. Finally, two typical processes are employed to show the main points of the proposed methodology.