Multilinear model decomposition of MIMO nonlinear systems and its implication for multilinear model-based control

a b s t r a c t In order to accomplish the multilinear model decomposition of MIMO nonlinear processes with multiple scheduling variables, a systematic division algorithm based on gap metric together with a supporting dichotomy gridding algorithm is proposed by using the gap metric as a measuring tool. For a prescribed distance level, this gap metric based division algorithm effectively decomposes a MIMO nonlinear system into a set of linear subsystems which provide enough model information for multilinear model-based controller design without linear model redundancy. Based on the linear models, a set of linear MPC con- trollers are designed and combined into a global controller for setpoint tracking control. Two benchmark nonlinear processes are studied to demonstrate the effectiveness of the proposed method.

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