Robust Control Systems Design Using Matlab

In general, robustness does not “come for free” from a controller designed via optima control and estimation theory (observer design): a controller designed for a nominal process model generally works fine for the nominal plant model, but may fail for even a “nearby” plant model. An important point of all feedback control synthesis methods is the control engineer’s awareness of inherent trade–offs : increasing the robustness will generally make the controller“less aggressive”, and will thereby decrease system performance.Robust control allows to specify more or less directly the plant uncertainty, and allows to predict the possible trade–offs between robustness and closed–loop performance.

Robust water quality controller for a reverse osmosis desalination system

This paper presents two-degree-of-freedom (2-DOF) robust loop-shaping control methodology to stabilize a reverse osmosis (RO) desalination system operating under significant uncertainties, external disturbances and measurement noises, and to reduce product water cost. This method has the advantages that no information about the plant uncertainty is required and it can deal with external disturbance and noise simultaneously. The controlled RO plant is a multi-input multi-output (MIMO) system. The two controlled variables are product water flow and product water salinity, which are fundamental in water desalination. The result shows that the achieved controller has very good performance which can deal with up to 52% uncertainty, and eliminate 60% of disturbance and 70% of noise, while common existing controllers in RO desalination can't cover the uncertainty and disturbance or can only deal with small values of these factors. Now that the software and hardware in the RO plant are sufficiently robust, it is possible to use this powerful method for better water quality control of RO systems.