Model predictive control of nonlinear singularly perturbed systems: Application to a large-scale process network

Nonlinear model predictive control of energy-integrated process systems

“…result in nonlinear systems theory allows us to exploit this stability property to design a controller for the entire system in the slow time scale, based solely on the slow model (20), following the composite control paradigm [15] (see also [21,22]). We formulate the system-wide control problem as the following Nonlinear Model Predictive Controller (NMPC), aimed at computing the optimal inputs ν s * (t) that provide exponential stability to the slow dynamics (20).…”

An Integrated Approach to Global Synchronization and State Estimation for Nonlinear Singularly Perturbed Complex Networks

“…Furthermore, the neural network based control and observer design problems have been investigated in [22] for a class of singularly perturbed nonlinear systems with guaranteed H ∞ control performance. In [4], the model predictive control problem has been handled for nonlinear singularly perturbed systems with application on a large-scale nonlinear reactorseparator process network which exhibits two-time-scale behavior. Unfortunately, a literature search reveals that little work has been devoted towards the dynamics analysis issue of the singularly perturbed complex networks especially when the singular perturbation phenomenon occurs on each node system.…”

Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes

“…Nonlinear model predictive control (NMPC) has been received great attentions since 1990s in both industries and academia [1][2][3][4], especially in chemical processes [5][6][7][8][9]. In general, NMPC uses a model of plants to predict their future evolutions and a control input is determined by online optimization to minimize a certain performance criterion subject to the state and/or the control constraints.…”

“…In many MPC applications to chemical processes [5][6][7][8][9], not only one but a number of different performance criteria should be taken into account for the controlled system design. At the same time, chemical processes are usually characterized by nonlinear behavior and strong coupling of various process variables.…”