• DocumentCode
    3020967
  • Title

    Augmented LQG Optimal Control of Dynamic Performance for ETG System

  • Author

    Zhang, Gui-Chen

  • Author_Institution
    State Key Lab. of Ocean Eng., Shanghai Jiaotong Univ., Shanghai, China
  • Volume
    4
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    446
  • Lastpage
    450
  • Abstract
    Running of unstable speed exhaust turbine generator (ETG) using main engine (ME) waste heat by high turbulence intensities, in order to demand maximization of regenerative energy harvested from the ME waste heat and minimization of damage caused by mechanical losses and fatigue. ALQG control scheme for output power leveling with unknown dynamics is proposed in this paper. The control scheme applies a neurocontroller (NC), regulates rotational speed and generator torque by specifying optimal-load ratio demanded generator output power. SINAMICS technology ensures rated power output of ETG. A second-order power control model and a stochastic exhaust gas field model are established in the analysis; power matching characteristic is analyzed, hardware-in-the-loop simulation is researched. Simulation results indicate the ALQG control scheme effectively harmonizes the relation between rotor speed and the highly turbulent exhaust gas speed thereby regulating shaft moment and maintaining rated power.
  • Keywords
    engines; linear quadratic Gaussian control; machine control; neurocontrollers; power control; torque control; turbogenerators; velocity control; SINAMICS technology; augmented LQG optimal control; exhaust turbine generator; generator torque regulation; hardware-in-the-loop simulation; main engine waste heat; mechanical losses; neurocontroller; power matching characteristic; rotational speed regulation; second-order power control model; stochastic exhaust gas field model; Fatigue; Heat engines; Neurocontrollers; Optimal control; Power control; Power generation; Stochastic processes; Torque control; Turbines; Waste heat; LQG; NC; energy feedback; exhaust turbine generator; hybrid error;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.417
  • Filename
    5376286