Linear quadratic Gaussian controller design for plasma current, position and shape control system in ITER

Belyakov, V. A.; Kavin, А.; Kharitonov, Vladimir L.; Misenov, B.A.; Mitrishkin, Yu. V.; Ovsyannikov, Alexander; Ovsyannikov, Dmitri; Rumyantsev, E. N.; Веремей, Е. И.; Zhabko, Alexey P.

doi:10.1016/s0920-3796(98)00431-1

Cited by 34 publications

(14 citation statements)

References 1 publication

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“…Theorem 1: Let us consider the closed-loop system (15) and the polytopic Initial Set P defined by (10). Assume there exists a scalar 0 , a , 1, a positive-definite matrix P and a matrix L such that…”

Section: Resultsmentioning

confidence: 99%

“…These alternative approaches suffer from lack of robustness because the desired properties (stabilisation and performance) are only guaranteed around the equilibrium point. On the other hand, since the sufficient conditions of Theorem 1 are directly applied to the non-linear system (38), they ensure the existence of a linear state-feedback controller, which robustly stabilises the closed-loop system over the assigned set of initial condition having the polytopic structure defined in (10). Therefore such a control law is likely to achieve robust control performance over an adequate operating range of the UAV attitude.…”

Section: Comparison With a Classical Lqr Design Methodsmentioning

confidence: 99%

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Domain of attraction and guaranteed cost control for non‐linear quadratic systems. Part 2: controller design

Amato

Ambrosino

Ariola

et al. 2013

IET Control Theory & Applications

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This study addresses the problem of designing a guaranteed cost controller for non-linear discrete quadratic systems. More specifically, the main contribution concerns a sufficient condition for the existence of a state-feedback controller achieving a certain guaranteed cost, whenever the state trajectories start from a prescribed set of initial conditions. The controller design requires the solution of a convex optimisation problem involving linear matrix inequalities, which can be efficiently solved via available optimisation algorithms. Finally, the proposed design methodology is illustrated via an example concerning the attitude control of an unmanned aerial vehicle.

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Section: Resultsmentioning

confidence: 99%

Section: Comparison With a Classical Lqr Design Methodsmentioning

confidence: 99%

Domain of attraction and guaranteed cost control for non‐linear quadratic systems. Part 2: controller design

Amato

Ambrosino

Ariola

et al. 2013

IET Control Theory & Applications

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“…The MIMO LQG controller K 11Â18 LQG was synthesized by the methodology developed by Belyakov et al (1999) when minimizing the cost function JðK LQG Þ ¼ J 1 þ cJ 2 where…”

Section: Bd-controllersmentioning

confidence: 99%

Plasma multivariable robust control system design and simulation for a thermonuclear tokamak-reactor

Mitrishkin

Kurachi

Kimura

2003

International Journal of Control

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The paper reports results on the design and analysis of the multivariable feedback H 1 robust system for plasma current, position and shape control in the fusion energy advanced tokamak (FEAT) developed in the International Thermonuclear Experimental Reactor (ITER) project. The system contains the fast loop with the SISO plasma vertical speed robust controller and the slow loop with the MIMO plasma current and shape robust controller. The goal is to study the resources of the system robustness to achieve a higher degree of the FEAT operation reliability. Two H 1 block diagonal controllers diagfK SISO ; K MIMO g were designed by a mixed sensitivity approach in the framework of the disturbance rejection configuration. These controllers were compared with block diagonal decoupling, PI and LQG controllers at the set of FEAT key scenario points according to the multiple-criterion: nominal performance at minor disruptions, robust stability and robust performance. The H 1 controllers showed larger multivariable stability margin and better nominal performance.

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“…The application of LQG control to the nuclear science field has appeared. Berkan and Upadhyaya (1989) used the LQG control to accomplish a reactor power regulation and the drum level control; Belyakov et al (1999) utilized the LQG methodology for the ITER plasma current, position and shape control system as well as power derivative management system; Parikh et al (2011) designed the LQG controller to control a nuclear steam generator. However, a LQG controller is calculated and obtained after subjectively choosing decent weighting matrixes in the LQG optimal control.…”

Section: Introductionmentioning

confidence: 99%

Load following control and global stability analysis for PWR core based on multi-model, LQG, IAGA and flexibility idea

Zhao

2013

Progress in Nuclear Energy

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Linear quadratic Gaussian controller design for plasma current, position and shape control system in ITER

Cited by 34 publications

References 1 publication

Domain of attraction and guaranteed cost control for non‐linear quadratic systems. Part 2: controller design

Domain of attraction and guaranteed cost control for non‐linear quadratic systems. Part 2: controller design

Plasma multivariable robust control system design and simulation for a thermonuclear tokamak-reactor

Load following control and global stability analysis for PWR core based on multi-model, LQG, IAGA and flexibility idea

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