NONLINEAR MODEL-BASED CONTROL USING 2ND-ORDER VOLTERRA MODELS

A nonlinear controller synthesis scheme is presented that retains the original spirit and characteristics of conventional (linear) model predictive control (MPC) while extending its capabilities to nonlinear systems. The scheme employs a Volterra model-a simple and convenient nonlinear extension of the linear convolution model employed by conventional MPC-and gives rise to a controller composed of a conventional linear controller augmented by an auxiliary loop of nonlinear 'corrections'. Simulation case studies involving two different examples representative of the typical spectrum of nonlinear behavior in real chemical processes-an industrial polymerization reactor and an isothermal reactor exhibiting inverse response-are used to demonstrate the practical utility of the control scheme and to evaluate its performance.