• Title/Summary/Keyword: Linear Quadratic Controller

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Nonfragile Guaranteed Cost Controller Design for Uncertain Large-Scale Systems (섭동을 갖는 대규모 시스템의 비약성 성능보장 제어기 설계)

  • Park, Ju-Hyeon
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.11
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    • pp.503-509
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    • 2002
  • In this paper, the robust non-fragile guaranteed cost control problem is studied for a class of linear large-scale systems with uncertainties and a given quadratic cost functions. The uncertainty in the system is assumed to be norm-bounded and time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design a state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound for all admissible uncertainties and controller gain variations. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost controllers is given in terms of the feasible solutions to a certain LMI. A numerical example is given to illustrate the proposed method.

Design of Optimized Fuzzy Controller by Means of HFC-based Genetic Algorithms for Rotary Inverted Pendulum System (회전형 역 진자 시스템에 대한 계층적 공정 경쟁 기반 유전자 알고리즘을 이용한 최적 Fuzzy 제어기 설계)

  • Jung, Seung-Hyun;Choi, Jeoung-Nae;Oh, Sung-Kwun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.2
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    • pp.236-242
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    • 2008
  • In this paper, we propose an optimized fuzzy controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for rotary inverted pendulum system. We adopt fuzzy controller to control the rotary inverted pendulum and the fuzzy rules of the fuzzy controller are designed based on the design methodology of Linear Quadratic Regulator (LQR) controller. Simple Genetic Algorithms (SGAs) is well known as optimization algorithms supporting search of a global character. There is a long list of successful usages of GAs reported in different application domains. It should be stressed, however, that GAs could still get trapped in a sub-optimal regions of the search space due to premature convergence. Accordingly the parallel genetic algorithm was developed to eliminate an effect of premature convergence. In particular, as one of diverse types of the PGA, HFCGA has emerged as an effective optimization mechanism for dealing with very large search space. We use HFCGA to optimize the parameter of the fuzzy controller. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy controller leads to superb performance in comparison with the conventional LQR controller as well as SGAs based fuzzy controller.

INTERNAL FEEDBACK CONTROL OF THE BENJAMIN-BONA-MAHONY-BURGERS EQUATION

  • Piao, Guang-Ri;Lee, Hyung-Chen
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.18 no.3
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    • pp.269-277
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    • 2014
  • A numerical scheme is proposed to control the BBMB (Benjamin-Bona-Mahony-Burgers) equation, and the scheme consists of three steps. Firstly, BBMB equation is converted to a finite set of nonlinear ordinary differential equations by the quadratic B-spline finite element method in spatial. Secondly, the controller is designed based on the linear quadratic regulator (LQR) theory; Finally, the system of the closed loop compensator obtained on the basis of the previous two steps is solved by the backward Euler method. The controlled numerical solutions are obtained for various values of parameters and different initial conditions. Numerical simulations show that the scheme is efficient and feasible.

A control allocation sterategy based on multi-parametric quadratic programming algorithm

  • Jeong, Tae-Yeong;Ji, Sang-Won;Kim, Young-Bok
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.49 no.2
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    • pp.153-160
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    • 2013
  • Control allocation is an important part of a system. It implements the function that map the desired command forces from the controller into the commands of the different actuators. In this paper, the authors present an approach for solving constrained control allocation problem in vessel system by using multi-parametric quadratic programming (mp-QP) algorithm. The goal of mp-QP algorithm applied in this study is to compute a solution to minimize a quadratic performance index subject to linear equality and inequality constraints. The solution can be pre-computed off-line in the explicit form of a piecewise linear (PWL) function of the generalized forces and constrains. The efficiency of mp-QP approach is evaluated through a dynamic positioning simulation for a vessel by using four tugboats with constraints about limited pushing forces and found to work well.

Stability Analysis of Fuzzy-Model-Based Controller by Piecewise Quadratic

  • Wook Chang;Joo, Young-Hoon;Park, Jin-Bae
    • 제어로봇시스템학회:학술대회논문집
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    • 1999.10a
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    • pp.169-172
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    • 1999
  • In this paper, piecewise quadratic Lyapunov functions are used to analyze the stability of fuzzy-model-based controller. We represent the nonlinear system using a Takagi-Sugeno fuzzy model, which represent the given nonlinear system by fuzzy inference rules and local linear dynamic models. The proposed stability analysis technique is developed by dividing the whole fuzzy system into the smaller separate fuzry systems to reduce the conservatism. Some necessary and sufficient conditions for the proposed method are obtained. Finally, stability of the closed system with various kinds of controller for TS fuzzy model is checked through the proposed method.

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Design of First Order Controllers with Time Domain Specifications(ICCAS 2003)

  • Kim, Keun-Sik;Woo, Young-Tae;Kim, Young-Chol
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1-6
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    • 2003
  • This paper considers the problem of determining a set of stabilizing first order controller gains, for a given linear time invariant plant, that meets or exceeds closed loop step response specifications. The method utilizes two recent results: For a given system, (1) finding a set of stabilizing first order controller gains and (2) the relationship between time response (overshoot and speed) and the coefficients of the characteristic polynomial. The method allows us to extract a subset of first order controller gains that meets stability as well as time domain performance requirements. The computations involved are the intersections of two dimensional sets described by linear and quadratic inequalities in the controller design space. It is illustrated by examples.

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LQG/LTR-PID based Controller Design of UAV Slung-Load Transportation System (LQG/LTR과 PID 기반의 무인항공기 슬렁-로드 수송 시스템의 제어기 설계)

  • Lee, Hae-In;Yoo, Dong-Wan;Lee, Byung-Yoon;Moon, Gun-Hee;Lee, Dong-Yeon;Tahk, Min-Jea
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.12
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    • pp.1209-1216
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    • 2014
  • This paper copes with control design for unmanned aerial vehicle transportation system. Moving pendulum dynamics of slung-load system is derived using two methods: Udwadia-Kalaba equation and Newtonian approach. PID controller is applied to Udwadia-Kalaba equation model for structural consistency and linear quadratic Gaussian / Loop Transfer Recovery (LQG/LTR) technique is employed for Newtonian model with minimal state-space realization. Characteristics of PID and LQG/LTR controller are compared, and two controllers are combined to compensate the drawbacks of each other. Numerical simulation is set for two cases and conducted to evaluate performance of designed controllers. The result proves that combination of LQG/LTR and PID control performs stable and robust.

Feedback Linearization Control of the Looper System in Hot Strip Mills

  • Hwang, I-Cheol;Kim, Seong-Bae
    • Journal of Mechanical Science and Technology
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    • v.17 no.11
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    • pp.1608-1615
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    • 2003
  • This paper studies on the linearization of a looper system in hot strip mills, that plays an important role in regulating a strip tension or a strip width. Nonlinear dynamic equations of the looper system are analytically linearized by a static feedback linearization algorithm with a compensator. The proposed linear model of the looper is validated by a comparison with a linear model using Taylor's series. It is shown that the linear model by static feedback well describes nonlinearities of the looper system than one using Taylor's series. Furthermore, it is shown from the design of an ILQ controller that the linear model by static feedback is very useful in designing a linear controller of the looper system.

Decomposed Linear Quadratic Gaussian with Loop Transfer Recovery Controller Design for an Undersea Vehicle (수중운동체를 위한 분할 LQG/LTR 제어기 구성)

  • Han, Hyung-Seok;Lee, Jang-Gyu
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.121-124
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    • 1989
  • In this thesis, a decomposed LQG/LTR controller is designed for an undersea vehicle. The modellig error which results from decomposition of the original model is considered to the design specification for maintaining the robust stability. The LQG/LTR controller designed with new specification is simulated.

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A study on the design of robust controllers with guaranteed cost bounds (강인 성능을 보장하는 제어기 설계에 관한 연구)

  • 이준화;김상우;권욱현
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.60-65
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    • 1991
  • In this paper, robust controllers which guarantee the stability and the quadratic performance in the presence of the state and the input matrix uncertainties are presented. Modified quadratic performance indices which include the model uncertainties are proposed for continuous and discrete time linear systems. And it is shown that the solution of the proposed optimal performance problem is the robust controller.

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