Abstract
Modern process plants are highly integrated and as a result, decentralized PID control loops are often strongly interactive. The currently used sequential tuning approach is not only time consuming, but does also not achieve optimal performance of the inherently multivariable control system. This paper describes a method and a software tool which allows a control engineer to calculate optimal PID controller settings for multiloop systems. It is based on the identification of a state space model of the multivariable system, and it uses constrained nonlinear optimization techniques to find the controller parameters. The solution is tailored to the specific control system and PID algorithm to be used. The methodology has been successfully applied in several industrial advanced control projects. The tuning results which have been achieved for interacting PID control loops in the stabilizing section of an industrial Gasoline Treatment Unit at SABIC Petrochemicals are presented.
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