Abstract
The robustness of asymptotic stability with respect to measurement noise for discrete-time feedback control systems is discussed. It is observed that, when attempting to achieve obstacle avoidance or regulation to a disconnected set of points for a continuous-time system using sample and hold state feedback, the noise robustness margin necessarily vanishes with the sampling period. With this in mind, we propose two modifications to standard model predictive control (MPC) to enhance robustness to measurement noise. The modifications involve the addition of dynamical states that make large jumps. Thus, they have a hybrid flavor. The proposed algorithms are well suited for the situation where one wants to use a control algorithm that responds quickly to large changes in operating conditions and is not easily confused by moderately large measurement noise and similar disturbances.
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Tuna, S.E., Sanfelice, R.G., Messina, M.J., Teel, A.R. (2007). Hybrid MPC: Open-Minded but Not Easily Swayed. In: Findeisen, R., Allgöwer, F., Biegler, L.T. (eds) Assessment and Future Directions of Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72699-9_2
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DOI: https://doi.org/10.1007/978-3-540-72699-9_2
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