Abstract
pH control is recognized as an industrially important, yet notoriously difficult control problem. It is proposed, however, that Wiener models, consisting of a linear dynamic element followed in series by a static nonlinear element, are ideal for representing this and several other nonlinear processes. They are relatively simple models, requiring little more effort in development than a standard linear step response model, yet offer superior characterization of systems with highly nonlinear gains. In this paper Wiener model predictive control is compared experimentally to both PID and linear MPC, with the effects of output constraints and modeling error also being considered.
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