Error Estimates for Finite-Dimensional Approximations in Control of Distributed Parameter Systems
Distributed parameter systems such as elastic multibody systems or heat and mass transfer processes are described by partial differential equations. However, for the control design of such systems, finite-dimensional approximations are usually applied. To derive accurate control strategies both for stabilization of fixed operating points and tracking control, it is essential to quantify deviations between the exact dynamics and its finite-dimensional approximation. Using experimental data, modeling uncertainties are estimated in real time for a finite-dimensional mathematical representation of the motion of an elastic beam employing a continuous-time Luenberger-type observer and a discrete-time stochastic filtering approach.
KeywordsExtend Kalman Filter Model Predictive Control Algebraic Riccati Equation Distribute Parameter System Quadratic Cost Function
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