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Model predictive control (MPC) is the dominant control technology for constrained, multivariable chemical processes. Performance assessment of MPC controllers is an important problem that has received little attention. Most multivariable controller assessment techniques are based on comparing the actual performance to that achievable under minimum variance control (MVC). MVC measures not well suited...
A variety of controller design techniques for nonlinear systems are available. Many methods completely neglect one of the most important types of nonlinearity encountered in process control applications: constraints. We provide a critical review of constraint compensation techniques for nonlinear control systems with an emphasis on methods which have been successfully applied to process control problems...
A linear model predictive control (LMPC) strategy is developed for large-scale gas pipeline networks. A nonlinear dynamic model of a representative pipeline is derived from mass balances and the Virial equation of state. Because the full-order model is ill-conditioned, reduced-order models are constructed using time-scale decomposition arguments. The first reduced-order model is used to represent...
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