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LQG Optimal Control
Proof of Main Theorem
1 other sections not shown
2k Tr AkT Sk+1 Chapter chosen with magnitudes class of problems Contr control law control variable uk Cornell University difference equations Dot product dynamic programming equals estimation error covariance Evolution of d.p.-state gains are chosen global optimum Hk Pk Hk xk IEEE IEEE Trans independent set constraints INDUCTIVE STEP Information Structures Information Theory invertible joojj JX k2 Ken Kishi large as possible LOG problem Logical flow magnitudes as large main theorem Markov Chains matrices are selected matrix inversion lemma measurement information affects measurement row gains MEASUREMENT SUBSYSTEM DESIGN min[H objective function oniatqua Optimal Control optimal row gains parameterize the measurement partial derivative Pk+1 plant Proof selected subject Sk+1T standard LOG standard LQG problem Structures in Optimal subject to box-constraints subject to independent T+kS j^V Team Decision Theory Theory and Information Tr Lk Pk Tr LN_1 vector Vj(Pj Zi,k