This work focuses on the design and implementation of a nonlinear model-based control system on an experimental reverse-osmosis (RO) membrane water desalination system to address large set-point changes and variations in feedwater salinity. A dynamic nonlinear lumped-parameter model is derived using firstprinciples, and its parameters are computed from experimental data to minimize the error between model predictions and experimental RO system response. This model then is used as the basis for the design of a nonlinear control system, using geometric control techniques. The nonlinear control system is implemented on the experimental RO system, and its set-point tracking and disturbance rejection capabilities are successfully evaluated.
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