A state-shared model predictive control approach to transition control of a multi-input multi-output system

Transition control over a large operating space presents a challenging problem, especially for nonlinear multiple-input multiple-output (MIMO) constrained systems. This work proposes and develops a transition control approach based on the development of a state-shared model in a model-predictive control (MPC) framework. The genesis of the state-shared model is based on an identifier-based nonlinear realization. The method is demonstrated on a nonlinear physiological system that transitions from a pathological state to a normal state.