AI RESEARCH
Dual Control of Linear Systems from Bilinear Observations with Belief Space Model Predictive Control
arXiv CS.LG
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ArXi:2604.24663v1 Announce Type: cross We study finite-horizon quadratic control of linear systems with bilinear observations, in which the control input affects not only the state dynamics but also the partial observations of the state. In this setting, the separation principle can fail because control inputs influence the future quality of state estimates. State estimation requires an input-dependent Kalman filter whose gain and error covariance evolve as functions of the control inputs.