Optimal control of fuel processing system using generalized linear quadratic Gaussian and loop transfer recovery method

2010 ◽  
Vol 12 (5) ◽  
pp. 597-606 ◽  
Author(s):  
Huan-Liang Tsai ◽  
Jium-Ming Lin
Keyword(s):  
Optimal Control ◽  
Processing System ◽  
Linear Quadratic ◽  
Fuel Processing ◽  
Linear Quadratic Gaussian ◽  
Recovery Method ◽  
Loop Transfer Recovery

Optimal Control of a Nuclear Reactor in Load Follow Based on LQG/LTR

2012 ◽  
Vol 591-593 ◽  
pp. 1563-1566
Author(s):  
Hua Chu Liu
Keyword(s):  
Optimal Control ◽  
Spatial Distribution ◽  
Control Strategy ◽  
Nuclear Reactor ◽  
Control Method ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Load Following ◽  
Loop Transfer Recovery ◽  
Special Factors

Load follow is necessary in the operation of a power plant due to the need of power changing with time. In the load following of a nuclear plant, many special factors have to be considered, which makes the control strategy particularly difficult as well as important. Among many strategies, Linear Quadratic Gaussian and Loop Transfer Recovery (LQG/LTR) design approach is an efficient method for L-F, and is applied to a model of a practical nuclear reactor. The simulation shows the robust control method LQG/LTR meet the control requirements of the neutron flux spatial distribution during load following. And a Kalman-filter based feedback control is also applied in this approach to eliminate the oscillations caused by Xenon poisoning within the nuclear reactor.

scholarly journals Modified LQG/LTR Control Methodology in Active Structural Control

2003 ◽  
Vol 22 (2) ◽  
pp. 97-108 ◽  
Author(s):  
Yan Sheng ◽  
Chao Wang ◽  
Ying Pan ◽  
Xinhua Zhang
Keyword(s):  
Structural Control ◽  
Signal To Noise Ratio ◽  
Open Loop ◽  
Control Force ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Control Approach ◽  
Active Structural Control ◽  
Loop Transfer Recovery ◽  
Control Methodology

This paper presents a new active structural control design methodology comparing the conventional linear-quadratic-Gaussian synthesis with a loop-transfer-recovery (LQG/LTR) control approach for structures subjected to ground excitations. It results in an open-loop stable controller. Also the closed-loop stability can be guaranteed. More importantly, the value of the controller's gain required for a given degree of LTR is orders of magnitude less than what is required in the conventional LQG/LTR approach. Additionally, for the same value of gain, the proposed controller achieves a much better degree of recovery than the LQG/LTR-based controller. Once this controller is obtained, the problems of control force saturation are either eliminated or at least dampened, and the controller band-width is reduced and consequently the control signal to noise ratio at the input point of the dynamic system is increased. Finally, numerical examples illustrate the above advantages.

Linear Quadratic Gaussian Optimal Control for Human Eye Aberration Correction

2014 ◽  
Vol 51 (4) ◽  
pp. 041102
Author(s):  
王波 Wang Bo ◽  
钮赛赛 Niu Saisai ◽  
吴卫明 Wu Weiming
Keyword(s):  
Optimal Control ◽  
Aberration Correction ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Human Eye

Theoretical modeling and vibration control for pre-twisted composite blade based on LLI controller

2019 ◽  
Vol 42 (7) ◽  
pp. 1255-1270
Author(s):  
Ting-Rui Liu ◽  
Ai-Ling Gong
Keyword(s):  
Vibration Control ◽  
Theoretical Modeling ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Flutter Suppression ◽  
Hamilton Variational Principle ◽  
Composite Blade ◽  
Loop Transfer Recovery ◽  
Blade Section ◽  
Blade Tip

Theoretical modeling and vibration control for divergent motion of thin-walled pre-twisted wind turbine blade have been investigated based on “linear quadratic Gaussian (LQG) controller using loop transfer recovery (LTR) at plant input” (LLI). The blade section is a single-celled composite structure with symmetric layup configuration of circumferentially uniform stiffness (CUS), exhibiting displacements of vertical/lateral bending coupling. Flutter suppression for divergent instability is investigated, with blade driven by nonlinear aerodynamic forces. Theoretical modeling of CUS-based structure is implemented based on Hamilton variational principle of elasticity theory. The discretization of aeroelastic equations is solved by Galerkin method, with blade tip responses demonstrated. The LLI controller is characterized by LTR at the plant input. The effects of LLI controller are achieved and illustrated by displacement responses, controller responses and frequency spectrum analysis, respectively.

Sign in / Sign up

Export Citation Format

Share Document