This paper describes the use of partial correlation based instrumental variables method for the identification and isolation of weak interaction dynamics between subsystems in decentralized control systems. Unlike the available methods based on the ordinary least square, the proposed method clearly discriminates the interaction channels that have significant contribution to the interconnected subsystem from the ones which do not by reducing the model error that arises due to the process inputs correlation. The efficacy of the proposed method is illustrated through a case study. © 2014 Trans Tech Publications, Switzerland.