Abstract
A robust control algorithm which uses partial state feedback is designed for a class of biochemical processes in the presence of modeling uncertainties. To design the controller, the model uncertainty and the nonmeasurable state are combined into a new state variable. A sliding mode state observer is used to obtain on-line estimates of this new state. A practical stabilizer is obtained by combining the observer with an input–output linearizing controller. The practical convergence of the observer and the controller are proved. The performance of the sliding mode observer and the closed-loop behavior is illustrated through numerical simulations.
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