This work proposes a method to construct a state-shared model for multiple-input multiple-output （MIMO） systems. A state-shared model is defined as a linear time invariant state-space structure that is driven by mea...This work proposes a method to construct a state-shared model for multiple-input multiple-output （MIMO） systems. A state-shared model is defined as a linear time invariant state-space structure that is driven by measurement signals-the plant outputs and the manipulated variables, but shared by different multiple input/output models. The genesis of the state-shared model is based on a particular reduced non minimal realization. Any such realization necessarily fulfills the requirement that the output of the state-shared model is an asymptotically correct estimate of the output of the plant, if the process model is selected appropriately. The approach is demomtrated on a nonlinear MIMO system - a physiological model of calcium fluxes that controls muscle contraction and relaxation in human cardiac myocytes.展开更多
文摘This work proposes a method to construct a state-shared model for multiple-input multiple-output （MIMO） systems. A state-shared model is defined as a linear time invariant state-space structure that is driven by measurement signals-the plant outputs and the manipulated variables, but shared by different multiple input/output models. The genesis of the state-shared model is based on a particular reduced non minimal realization. Any such realization necessarily fulfills the requirement that the output of the state-shared model is an asymptotically correct estimate of the output of the plant, if the process model is selected appropriately. The approach is demomtrated on a nonlinear MIMO system - a physiological model of calcium fluxes that controls muscle contraction and relaxation in human cardiac myocytes.
