LQG — Linear Quadratic Gaussian control.
hardAnswer
- Extension of LQR to noisy partial observations.
- Optimal controller = Kalman filter (state estimation) + LQR (control).
- Certainty equivalence: LQ control on filtered state estimate is optimal.
- Bridge between control theory + POMDP-RL.
- Modern: neural networks approximate both filter + controller.
- Foundation of classical control theory taught in every EE / ME curriculum.
Check yourself — multiple choice
- Same as LQR
- LQR + Kalman filter for noisy partial obs; certainty equivalence: LQ control on filtered estimate is optimal; classical control foundation extended to POMDP-RL
- Random
- Not real
LQG: Kalman filter + LQR; certainty equivalence; classical control bridge.
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Practise Reinforcement Learning
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