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| - Robust Model Predictive Control for Integrating Linear Systemswith Bounded Parameters
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| - This paper presents two robust model predictive control (MPC) algorithms for linear integratingplants described by a state-space model. The first formulation focuses on steady-state offsetwhereas the second minimizes output deviations over the entire prediction horizon. The inputmatrix parameters of the plant are assumed to lie in a set defined by an ellipsoidal bound.Robustness is achieved through the addition of constraints that prevent the sequence of theoptimal controller costs from increasing for the true plant. The resulting optimization problemssolved at each time step are convex and highly structured. A simulation example compares theperformance of these algorithms with those based on minimizing the worst-case controller cost.
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