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In this paper, we present a robust multivariate statistical process control chart using kernel principal component analysis. The proposed control chart is effective in the detection of outliers, and its control limits are derived from the eigenanalysis of the Gaussian kernel matrix in the Hilbert feature space. Our experimental results show the much improved performance of the proposed control chart...
Sliding mode control of a chemical process is considered in this paper. The process is nonlinear and the dynamics is highly involved due to the strong interdependencies between the variables involved. The considered process has two state variables named dimensionless concentration and temperature. The goal is to maintain a desired concentration level by suitably altering the coolant temperature. The...
In this paper we design two controllers: a sliding mode controller and a new designed adaptive controller for an under actuated process with important dry friction. The two controllers are compared. Simulations and experiments are performed to evaluate the efficiency of the designed controllers.
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