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Stochastic Receding Horizon Control of Constrained Linear Systems With State and Control Multiplicative Noise

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2 Author(s)
Primbs, James A. ; Manage. Sci. & Eng. Dept., Stanford Univ., Stanford, CA ; Chang Hwan Sung

We develop a receding horizon control approach to stochastic linear systems with control and state multiplicative noise that also contain constraints. Our receding horizon formulation is based upon an on-line optimization that utilizes open-loop plus linear feedback and is solved as a semi-definite programming problem. We also provide a characterization of stability, performance, and constraint satisfaction properties of the receding horizon controlled system under a specific choice of terminal weight and terminal constraint. A simple numerical example is used to illustrate the approach.

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Automatic Control, IEEE Transactions on  (Volume:54 ,  Issue: 2 )