Litcius/Paper detail

Model-free <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e230" altimg="si4.svg"> <mml:msub> <mml:mrow> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>∞</mml:mi> </mml:mrow> </mml:msub> </mml:math> tracking control for de-oiling hydrocyclone systems via off-policy reinforcement learning

Shaobao Li, Petar Durdevic, Zhenyu Yang

2021Automatica27 citationsDOI

Topics & Concepts

Separator (oil production)HydrocycloneComputer scienceSCADAMetering modeAlgorithmEngineeringMechanical engineeringMechanicsThermodynamicsElectrical engineeringPhysicsMechanical Circulatory Support DevicesAdaptive Dynamic Programming ControlSmart Grid Energy Management
Model-free <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e230" altimg="si4.svg"> <mml:msub> <mml:mrow> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>∞</mml:mi> </mml:mrow> </mml:msub> </mml:math> tracking control for de-oiling hydrocyclone systems via off-policy reinforcement learning | Litcius