• Title/Summary/Keyword: quadratic cost function

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Delay-dependent Guaranteed Cost Control for Uncertain Time Delay System

  • Lee, In-Beum;Choi, Jin-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.62.4-62
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    • 2001
  • In this paper, we propose a delay-dependent guaranteed cost controller design method for uncertain linear systems with time delay. The uncertainty is norm bounded and time-varying. A quadratic cost function is considered as the performance measure for the given system. Based on the Lyapunov method, sufficient condition, which guarantees that the closed-loop system is asymptotically stable and the upper bound value of the closed-loop cost function is not more than a specied one, is derived in terms of Linear Matrix Inequalities(LMIs) that can be solved sufficiently. A convex optimization problem can be formulated to design a guaranteed cost controller, which minimizes the upper bound value of the cost function. Numerical examples show the activeness of the proposed method.

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Design of Model Predictive Controllers with Velocity and Acceleration Constraints (속도 및 가속도 제한조건을 갖는 모델예측제어기 설계)

  • Park, Jin-Hyun;Choi, Young-Kiu
    • Journal of the Korean Society of Mechanical Technology
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    • v.20 no.6
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    • pp.809-817
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    • 2018
  • The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix $A_r$ by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

Optimization of Economic Load Dispatch Problem Using Linearly Approximated Smooth Fuel Cost Function (선형 근사 평활 발전 비용함수를 이용한 경제급전 문제의 최적화)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.191-198
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    • 2014
  • This paper proposes a simple linear function approximation method to solve an economic load dispatch problem with complex non-smooth generating cost function. This algorithm approximates a non-smooth power cost function to a linear approximate function and subsequently shuts down a generator with the highest operating cost and reduces the power of generator with more generating cost in order to balance the generating power and demands. When applied to the most prevalent benchmark economic load dispatch cases, the proposed algorithm is found to dramatically reduce the power cost than does heuristic algorithm. Moreover, it has successfully obtained results similar to those obtained through a quadratic approximate function method.

Guaranteed Cost Control for Uncertain Time-Delay Systems with nonlinear Perturbations via Delayed Feedback (지연귀환을 통한 비선형 섭동이 존재하는 불확실 시간지연 시스템의 성능보장 제어)

  • Park, Ju-Hyun;Kwon, Oh-Min
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.6
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    • pp.581-588
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    • 2007
  • In this paper, we propose a delayed feedback guaranteed cost controller design method for linear time-delay systems with norm-bounded parameter uncertainties and nonlinear perturbations. A quadratic cost function is considered as the performance measure for the given system. Based on the Lyapunov method, an LMI optimization problem is formulated to design a controller such that the closed-loop cost function value is not more than a specified upper bound for all admissible system uncertainties and nonlinear perturbations. Numerical example show the effectiveness of the proposed method.

Tolerance Analysis and Optimization for a Lens System of a Mobile Phone Camera (휴대폰용 카메라 렌즈 시스템의 공차최적설계)

  • Jung, Sang-Jin;Choi, Dong-Hoon;Choi, Byung-Lyul;Kim, Ju-Ho
    • Korean Journal of Computational Design and Engineering
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    • v.16 no.6
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    • pp.397-406
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    • 2011
  • Since tolerance allocation in a mobile phone camera manufacturing process greatly affects production cost and reliability of optical performance, a systematic design methodology for allocating optimal tolerances is required. In this study, we proposed the tolerance optimization procedure for determining tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices. We employed Latin hypercube sampling for evaluating the reliabilities of optical performance and a function-based sequential approximate optimization technique that can reduce computational burden and well handle numerical noise in the tolerance optimization process. Using the suggested tolerance optimization approach, the optimal production cost was decreased by 30.3 % compared to the initial cost while satisfying the two constraints on the reliabilities of optical performance.

OPTIMIZATION AND IDENTIFICATION FOR THE NONLINEAR HYPERBOLIC SYSTEMS

  • Kang, Yong-Han
    • East Asian mathematical journal
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    • v.16 no.2
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    • pp.317-330
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    • 2000
  • In this paper we consider the optimal control problem of both operators and parameters for nonlinear hyperbolic systems. For the identification problem, we show that for every value of the parameter and operators, the optimal control problem has a solution. Moreover we obtain the necessary conditions of optimality for the optimal control problem on the system.

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Iterative learning control of nonlinear systems with consideration on input magnitude (입력의 크기를 고려한 비선형 시스템의 반복학습 제어)

  • Choi, Chong-Ho;Jang, Tae-Jeong
    • Journal of Institute of Control, Robotics and Systems
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    • v.2 no.3
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    • pp.165-173
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    • 1996
  • It is not desirable to have too large control input in control systems, because there are usually a limitation for the input magnitude and cost for the input energy. Previous papers in the iterative learning control did not considered on these points. In this paper, an iterative learning control method is proposed for a class of nonlinear systems with consideration on input magnitude by adopting a concept of cost function consisting of the output error and the input magnitude in quadratic form. We proposed a new input update law with an input penalty function. If we choose a reasonable input penalty function, the two control objectives, good command following and small input energy, can be achieved. The characteristics of the proposed method are shown in the simulation examples.

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Linear Quadratic Regulation and Tracking using Output Feedback with Direct Feedthrough

  • Kang, Seungeun;Cha, Jihyoung;Ko, Sangho
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.4
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    • pp.593-603
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    • 2016
  • This paper presents the development of linear quadratic regulation and output tracking algorithms using output feedback when both the measurement and performance output equations contain direct feedthrough terms. Although all physical systems can be modeled without direct feedthrough, there are still many situations where system models with direct feedthrough are important. For this situation, we modify previous work on the same topic for systems without direct feedthrough. It is shown that for the regulation problem, the optimal output feedback gain for a direct feedthrough case can be directly obtained, via a transformation, from the approach used for systems without direct feedthrough. However, for the tracking problem, a new set of coupled matrix equations for determining the optimal output feedback gain is derived from the necessary conditions for minimizing the cost function. The effectiveness of the developed algorithms is demonstrated using numerical examples.

Collision Avoidance Using Linear Quadratic Control in Satellite Formation Flying

  • Mok, Sung-Hoon;Choi, Yoon-Hyuk;Bang, Hyo-Choong
    • International Journal of Aeronautical and Space Sciences
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    • v.11 no.4
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    • pp.351-359
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    • 2010
  • This paper proposes a linear system control algorithm with collision avoidance in multiple satellites. Consideration of collision avoidance is augmented by adding a weighting term in the cost function of the original tracking problem in linear quadratic control (LQC). Because the proposed algorithm relies on a similar solution procedure to the original LQC, its inherent advantages, including gain-robustness and optimality, are preserved. To confirm and visualize the derived algorithm, a simple example of two-vehicle motion in the two-dimensional plane is illustrated. In addition, the proposed collision avoidance control is applied to satellite formation flying, and verified by numerical simulations.

A Fixed Amount Compensation Plan for a Tool Wear Process (마모공정에 대한 정량 보정계획)

  • 최인수;이민구
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.19 no.40
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    • pp.233-240
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    • 1996
  • A fixed amount compensator is proposed for a process with a linear tool wear function. A Cost model is constructed which involve process adjustment cost and quality loss. Symmetric and asymmetric quadratic functions of the deviation of a quality measurement from the nominal target value are considered as the quality loss functions. Methods of finding optimal values of initial setting and compensation limit are presented and a numerical example is given.

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