• Title/Summary/Keyword: Linear Discrete-Time Systems

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DISCRETE-TIME MIXED $H_2/H_{\infty}$ FILTER DESIGN USING THE LMI APPROACH

  • Ryu, Hee-Seob;Yoo, Kyung-Sang;Kwon, Oh-Kyu
    • 제어로봇시스템학회:학술대회논문집
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    • 1999.10a
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    • pp.129-132
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    • 1999
  • This paper deals with the optimal filtering problem constrained to input noise signal corrupting the measurement output for linear discrete-time systems. The transfer matrix H$_2$and/or H$_{\infty}$ norms are used as criteria in an estimation error sense. In this paper, the mixed $H_2/H_{\infty}$ filtering Problem in lineal discrete-time systems is solved using the LMI approach, yielding a compromise between the H$_2$and H$_{\infty}$ filter designs. This filter design problems we formulated in a convex optimization framework using linear matrix inequalities. A numerical example is presented.

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Discrete-time Sliding Mode Control with Input Shaping for flexible systems

  • Woo, Lim-Hyun;Choo, Chung-Chung
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.130.5-130
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    • 2001
  • This paper presents a discrete-time sliding mode control method for linear time-invariant systems with matched uncertainties. In this paper, we suggest a method of adding a command generator using input shaping filter to a discrete-time sliding mode controller. We design the number of steps required to reach the sliding layer and the magnitude of a control input, respectively using the shaping filter. Therefore we can minimize the excitation of the resonance mode and increase the tracking performance of a system. Simulation results are included to show its effectiveness.

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Model-free $H_{\infty}$ Control of Linear Discrete-time Systems using Q-learning and LMI Based on I/O Data (입출력 데이터 기반 Q-학습과 LMI를 이용한 선형 이산 시간 시스템의 모델-프리 $H_{\infty}$ 제어기 설계)

  • Kim, Jin-Hoon;Lewis, F.L.
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.7
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    • pp.1411-1417
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    • 2009
  • In this paper, we consider the design of $H_{\infty}$ control of linear discrete-time systems having no mathematical model. The basic approach is to use Q-learning which is a reinforcement learning method based on actor-critic structure. The model-free control design is to use not the mathematical model of the system but the informations on states and inputs. As a result, the derived iterative algorithm is expressed as linear matrix inequalities(LMI) of measured data from system states and inputs. It is shown that, for a sufficiently rich enough disturbance, this algorithm converges to the standard $H_{\infty}$ control solution obtained using the exact system model. A simple numerical example is given to show the usefulness of our result on practical application.

Stability Regions of Linear Slowly Time-Varying Systemsa (천천히 변하는 선형 시변 시스템의 안정도 영역)

  • 최종호;장태정
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.210-213
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    • 1988
  • By using Lyapunov method, sufficient conditions for linear time-varying continuous-time and discrete-time systems to be stable are presented under the assumption that the systems are slowly time-varying. Though it is not simple to find the stability regions immediately, one could find practical and large stability regions by constructing an appropriate algorithm.

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Data-based Stability Analysis for MIMO Linear Time-invariant Discrete-time Systems

  • Park, Un-Sik;Ikeda, Masao
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.680-684
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    • 2005
  • This paper presents a data-based stability analysis of a MIMO linear time-invariant discrete-time system, as an extension of the previous results for a SISO system. In the MIMO case, a similar discussion as in the case of a SISO system is also applied, except that an augmented input and output space is considered whose dimension is determined in relation to both the orders of the input and output vectors and the numbers of inputs and outputs. As certain subspaces of the input and output space, both output data space and closed-loop data space are defined, which contain all the behaviors of a system, respectively, with zero input in open-loop and with a control input in closed-loop. Then, we can derive the data-based stability conditions, in which the open-loop stability can be checked by using a data matrix whose column vectors span the output data space and the closed-loop stability can also be checked by using a data matrix whose column vectors span the closed-loop data space.

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Robust Finite-time Dissipative State Feedback Controller Design for Discrete-time Uncertain Singular Systems (이산시간 불확실 특이시스템의 유한시간 강인 산일성 상태궤환 제어기 설계)

  • Kim, Jong Hae;Oh, Do Chang
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.11
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    • pp.1598-1604
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    • 2015
  • In this paper, we treat the problem of a robust finite-time dissipative state feedback controller design method for discrete-time singular systems with polytopic uncertainties. A BRL(bounded real lemma) for finite-time stability of discrete-time singular systems is derived. A finite-time dissipative state feedback controller design method satisfying finite-time stability and dissipativity is proposed by LMI(linear matrix inequality) technique on the basis of the obtained BRL. Moreover it is shown that the obtained condition can be extended into polytopic uncertain systems by proper manipulations. Finally, illustrative examples are given to show the applicability of the proposed method.

Stability of intervalwise receding horizon control for linear tie-varying systems

  • Ki, Ki-Baek;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.430-433
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    • 1997
  • In this paper, an intervalwise receding horizon control (IRHC) is proposed which stabilizes linear continuous and discrete time-varying systems each other by means of a feedback control stemming from a receding horizon concept and a minimum quadratic cost. The results parallel those obtained for continuous [4],[9] and discrete time varying system [5],[15] each other.

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A regularity condition for asymptotic tracking in discrete-time nonlinear systems

  • Song, Yongkyu
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.138-143
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    • 1993
  • A well-defined relative degree, which is one of the basic assumptions in adaptive control or nonlinear synthesis problems, is addressed. It is shown that this is essentially a necessary condition for asymptotic tracking in discrete-time nonlinear systems. To show this, tracking problems are defined, and a local linear input-output behavior of a discrete-time system is introduced in relation to a well-defined relative degree. It is then shown that if a plant is invertible and accessible from the origin and a compensator solves the local asymptotic tracking problem, then the plant necessarily has a well-defined relative degree at the origin.

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Gain Scheduled Discrete Time Control for Disturbance Attenuation of Systems with Bounded Control Input (제어입력 크기제한을 갖는 시스템에서 외란 응답 감소를 위한 이산시간 이득 스케줄 제어)

  • Kang, Min-Sig;Yoon, Woo-Hyun
    • Journal of the Korean Society for Precision Engineering
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    • v.26 no.3
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    • pp.32-39
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    • 2009
  • A new discrete time gain-scheduled control design is proposed to improve disturbance attenuation for systems with bounded control input under known disturbance maximum norm. The state feedback gains are scheduled according to the proximity of the state of the plant to the origin. The controllers are derived in the framework of linear matrix inequality(LMI) optimization. This procedure yields a linear time varying control structure that allows higher gain and hence higher performance controllers as the state moves closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition under the given disturbance maximum norm.

Robust FIR filter for Linear Discrete-time System

  • Quan, Zhong-Hua;Han, Soo-Hee;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2548-2551
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    • 2005
  • In this paper, a robust receding horizon finite impulse response(FIR) filter is proposed for a class of linear discrete time systems with uncertainty satisfying an integral quadratic constraint. The robust state estimation problem involves constructing the set of all possible states at the current time consistent with given system input, output measurements and the integral quadratic constraint.

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