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
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