• Title/Summary/Keyword: stochastic LQR control

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INDEFINITE STOCHASTIC OPTIMAL LQR CONTROL WITH CROSS TERM UNDER IQ CONSTRAINTS

  • Luo, Cheng-Xin;Feng, En-Min
    • Journal of applied mathematics & informatics
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    • v.15 no.1_2
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    • pp.185-200
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    • 2004
  • A stochastic optimal LQR control problem under some integral quadratic (IQ) constraints is studied, with cross terms in both the cost and the constraint functionals, allowing all the control weighting matrices being indefinite. Sufficient conditions for the well-posedness of this problem are given. When these conditions are satisfied, the optimal control is explicitly derived via dual theory.

Determination of the Weighting Parameters of the LQR System for Nuclear Reactor Power Control Using the Stochastic Searching Methods

  • Lee, Yoon-Joon;Cho, Kyung-Ho
    • Nuclear Engineering and Technology
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    • v.29 no.1
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    • pp.68-77
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    • 1997
  • The reactor power control system is described in the fashion of the order increased LQR system. To obtain the optimal state feedback gain vectors, the weighting matrix of the performance function should be determined. Since the contentional method has some limitations, stochastic searching methods are investigated to optimize the LQR weighting matrix using the modified genetic algorithm combined with the simulated annealing, a new optimizing tool named the hybrid MGA-SA is developed to determine the weighting parameters of the LQR system. This optimizing tool provides a more systematic approach in designing the LQR system. Since it can be easily incorporated with any forms of the cost function, it also provides the great flexibility in the optimization problems.

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A Simultaneous Perturbation Stochastic Approximation (SPSA)-Based Model Approximation and its Application for Power System Stabilizers

  • Ko, Hee-Sang;Lee, Kwang-Y.;Kim, Ho-Chan
    • International Journal of Control, Automation, and Systems
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    • v.6 no.4
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    • pp.506-514
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    • 2008
  • This paper presents an intelligent model; named as free model, approach for a closed-loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.

Optimal Design of Linear Quadratic Regulator Restrict Maximum Responses of Building Structures Subject to Stochastic Excitation (확률적 가진입력을 받는 건축구조물의 최대응답 제한을 위한 선형이차안정기의 최적설계)

  • 박지훈;황재승;민경원
    • Journal of the Earthquake Engineering Society of Korea
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    • v.5 no.6
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    • pp.37-46
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    • 2001
  • In this research, a controller design method based on optimization is proposed that can satisfy constraints on maximum responses of building structures subject to around excitation modeled by partially stochastic process. The class of controllers to be optimized is restricted to LQR. Weighting matrix on controlled outputs is used as design variable. Objective function, constraint functions and their gradients are computed by the parameterization of control gain with Riccati matrix. Full state feedback controllers designed by proposed optimization method satisfy various design objectives and their necessary maximum control forces are computed for the production of actuator. LQG controllers composed of Kalman filter and LQR designed by proposed method perform well with little deterioration. So it is possible to design output feedback controllers satisfying constraints on various maximum responses of structures.

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Control of the flexible system under irregular disturbance by using of 『random gain』

  • Cho, Yun-Hyun;Yang, Jae-Hyuk;Kim, Dae-Jung;Park, Sang-Tae;Chung, Jae-Wook;Hoon Heo
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.435-439
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    • 1998
  • A control strategy for flexible structure under irregular disturbance by using of$\boxDr$random gain$\boxUl$is developed and implemented. System equation is transformed to stochastic domain by F-P-K approach from physical domain. A controller is designed in the stochastic domain, accordingly system is controlled by$\boxDr$random gain$\boxUl$in time domain. In the paper, a new control technique is successfully employed for flexible system under white noise, and the result is verified by Monte-Carlo simulation and compared with the performance via LQR controller.

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Optimal Design of Linear Quadratic Regulator Restrict Maximum Responses of Building Structures Subject to Stochastic Excitation (확률적 가진압력을 받는 건축구조물의 최대응답 제한을 위한 선형이차안정기의 최적설계)

  • 박지훈;황재승;민경원;조소훈
    • Proceedings of the Earthquake Engineering Society of Korea Conference
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    • 2001.09a
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    • pp.373-380
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    • 2001
  • In this research, a controller design method based on optimization is proposed that can satisfy constraints on maximum responses of building structures subject to ground excitation modeled by partially stationary stochastic process. The class of controllers to be optimized is restricted to LQR. Weighting matrix on controlled outputs is used as design variable. Objective function constraint functions and their gradients are computed parameterizing control gain with Riccati matrix. Full state feedback controllers designed by Proposed optimization method satisfy various design objectives and their necessary maximum control forces are computed fur the production of actuator. Probabilities of maximum responses match statistical data from simulation results well.

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Design of LQR controller for active suspension system of Partially Filled Tank Cars

  • Feizi, Mohammad Mahdi;Rezvani, Mohammad Ali
    • Structural Engineering and Mechanics
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    • v.49 no.3
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    • pp.329-353
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    • 2014
  • Increasing usage of tank cars and their intrinsic instability due to sloshing of contents have caused growing maintenance costs as well as more frequent hazards and defects like derailment and fatigue of bogies and axels. Therefore, varieties of passive solutions have been represented to improve dynamical parameters. In this task, assuming 22 degrees of freedom, dynamic analysis of partially filled tank car traveling on a curved track is investigated. In order to consider stochastic geometry of track; irregularities have been derived randomly by Mont Carlo method. More over the fluid tank model with 1 degree of freedom is also presented by equivalent mechanical approach in terms of pendulum. An active suspension system for described car is designed by using linear quadratic optimal control theory to decrease destructive effects of fluid sloshing. Eventually, the performance of the active suspension system has been compared with that of the passive one and a study is carried out on how active suspension may affect the dynamical parameters such as displacements and Nadal's derailment index.