The goal of this paper is to identify and control multi-input multi-output (MIMO) processes by means of the dynamic partial least squares (PLS) model, which consists of a memoryless PLS model connected in series with linear dynamic models. Unlike the traditional decoupling MIMO process, the dynamic PLS model can decompose the MIMO process into a multiloop control system in a reduced subspace. Without the decoupler design, the optimal tuning multiloop PID controller based on the concept of general minimum variance and the constrained criteria can be directly and separately applied to each control loop under the proposed PLS modeling structure. Several potential applications using this technique are demonstrated.
Qin SJ, McAvoy TJ, A Data-Based Process Modeling Approach and Its Applications, in Proceedings of the 3rd IFAC Symposium on Dynamic and Control of Chemical Reactors, Distillation Columns, and Batch Process, Pergamon, Oxford, 1992