• Title/Summary/Keyword: SISO

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Estimation of rail irregularity using wavelet transfer function (웨이브렛 전달함수를 이용한 궤도틀림 추정)

  • Yoon, Seok-Jun;Choi, Bai-Sung;Lee, Hyeung-Jin;Kim, Man-Cheol;Choi, Sung-Hoon;Shin, Soo-Bong
    • Proceedings of the KSR Conference
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    • 2010.06a
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    • pp.330-337
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    • 2010
  • This paper shows an algorithm for identifying track irregularities using wavelet transfer function along the railway. An equivalent SISO wavelet transfer function is defined using continuous wavelet transform by the measured track geometry and acceleration at a bogie of a train. The estimated track geometry is made by inverse continuous wavelet transform from the regressed signals of measured acceleration signal and the pre-defined wavelet transfer function. The estimated rail irregularity geometry is evaluated by the coherence function and comparison of FRF(Frequency Response Function). As a result of evaluated outcome, This algorithm is regarded as appropriate for estimation of rail irregularity.

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Development of the Active Vibration Absorber Using Piezoelectric Actuators (압전세라믹을 이용한 능동진동제어장치의 개발)

  • Kwak, Myung-Hoon;Heo, Seok;Kwak, Moon-K
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.11a
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    • pp.476-481
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    • 2001
  • This research is concerned with development of the active vibration absorber using piezoelectric actuators. This active isolation system consists of a-pairs of PZT actuators bonded on a S-shaped aluminum plate and the passive damping material. The active system is connected to the passive system in series. In this paper, one of the popular control techniques which have been successfully applied to the smart structure is the Positive Position Feedback(PPF) control. The digital PPF control lows downloaded to the DSP chip and a main program, which runs SISO PPF algorithm. The structure and dynamic characteristics of the proposed active vibration isolation system and described in detail. To demonstate the effectiveness of the active vibration control, the PPF controller is first employed. Experimental results show that the active vibration isolation is possible by means of the proposed system.

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Control of a Helicopter in Hover Using the LQG and LQG/LTR Methods (LQG와 LQG/LTR방법을 이용한 헬리콥터의 비행위치 제어)

  • Kim, Jong-Shik;Ma, Sam-Sun;Song, Myong-Hun
    • Journal of the Korean Society for Precision Engineering
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    • v.7 no.1
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    • pp.74-85
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    • 1990
  • The LQG and LQG/LTR compensators have the same structrues in dynamics. The only difference is the values of the design parameters in the two compensators. The design parameters of the LQG and LQG/LTR compensators are selected in the sense of the least-squares error minimi- zation and loop shaping, respectively. In this paper, the LQG and LQG/ LTR design methods are applied to the helicopter in hover which is modeled as a SISO fourth order system. The dynamic characteristics and the perfor- mance of the two control systems are analyzed by the computer simulation. It is found that the LQG/LTR design method is systematic and has good performance in comparision with the LQG design method.

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Eigenvalue Assignment for Linear Time-Varying Systems via Ackermann-like Formula (선형 시변 시스템의 고유치 지정을 위한 Ackermann형 공식)

  • 이호철;최재원
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.3
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    • pp.186-195
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    • 2003
  • This paper deals with eigenvalue assignment techniques for linear time-varying systems as a way of achieving feedback stabilization. For this, the novel eigenvalue concepts, which are the time-varying counterparts of the conventional (time-invariant) eigenvalue notions, are introduced. Then, the Ackermann-like formulae for SISO/MIMO linear time-varying systems are proposed. It is believed that these techniques are the generalized versions of the Ackermann formulae for linear time-invariant systems. The advantages of the proposed Ackermann-like formulae are that they neither require the transformation of the original system into the phase-variable form nor compute the eigenvalues of the original system. Two examples are given to demonstrate the capabilities of the proposed techniques.

On Nonovershooting or Monotone Nondecreasing Step Response of Second-Order Systems

  • Kwon, Byung-Moon;Lee, Myung-Eui;Kwon, Oh-Kyu
    • Transactions on Control, Automation and Systems Engineering
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    • v.4 no.4
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    • pp.283-288
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    • 2002
  • This paper has shown that the impulse and the unit step responses of 2nd-order systems can be computed by an analytic method. Three different 2nd-order systems are investigated: the prototype system, the system with one LHP(left half plane) real zero and the system with one RHP(right half plane) real zero. It has also shown that the effects of the LHP or the RHP zero are very serious when the zero is getting closer to the origin on the complex plane. Based on these analytic results, this paper has presented two sufficient and necessary conditions for 2nd-order linear SISO(single-input/single-output) stable systems to have the nonovershooting and the monotone nondecreasing step response, respectively. The latter condition can be extended to the sufficient conditions for the monotone nondecreasing step response of high-order systems.

An adaptive predictive control for the bilinear process (쌍일차 공정의 적응 예측제어)

  • Lo, K.;Yoon, E. S.;Yeo, Y. K.;Song, H. K.
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.344-349
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    • 1990
  • Under the assumption that process input/output data are sufficiently rich to allow reasonable plant identification, a long-range predictive control method for SISO bilinear plant is derived. In order to ensure offset-free behaviour of the control method, a new bilinear CARIMA model with variable dead-time is introduced. Furthermore, to extend the maximum output prediction horizon, the future predicted outputs in the bilinear term are assumed to be equal to the known future set-points. With a classical recursive adaptation algorithm, the proposed control scheme is capable of stable control of bilinear plants with variable parameters, with variable dead-time, and with a model order which changes instantaneously. Several simulation results demonstrate the characteristics of the proposed bilinear model predictive control method.

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An Observer Design for MIMO Nonlinear Systems and Its Application to Induction Motor (다입력 다출력 비선형 시스템의 관측기 설계 및 인덕션 모터에 응용)

  • Lee, Sung-Ryul
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.1
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    • pp.42-48
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    • 2008
  • This paper presents an observer design method for a special class of multi input multi output(MIMO) nonlinear systems. First, we characterize the class of MIMO nonlinear systems with a block triangular structure. Also, the observability matrices for SISO nonlinear systems are extended to MIMO systems. By using the generalized observability matrices, it is shown that under the boundedness conditions of system state and input, the proposed observer guarantees the local exponential stability of error dynamics. Finally, its application to induction motor is given to verify the proposed method.

Adaptive Neural Control for Strict-feedback Nonlinear Systems without Backstepping (순궤환 비선형계통의 백스테핑 없는 적응 신경망 제어기)

  • Park, Jang-Hyun;Kim, Seong-Hwan;Park, Young-Hwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.5
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    • pp.852-857
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    • 2008
  • A new adaptive neuro-control algorithm for a SISO strict-feedback nonlinear system is proposed. All the previous adaptive neural control algorithms for strict-feedback nonlinear systems are based on the backstepping scheme, which makes the control law and stability analysis very complicated. The main contribution of the proposed method is that it demonstrates that the state-feedback control of the strict-feedback system can be viewed as the output-feedback control problem of the system in the normal form. As a result, the proposed control algorithm is considerably simpler than the previous ones based on backstepping. Depending heavily on the universal approximation property of the neural network (NN), only one NN is employed to approximate the lumped uncertain system nonlinearity. The Lyapunov stability of the NN weights and filtered tracking error is guaranteed in the semi-global sense.

Adaptive Output-feedback Neural Control for Strict-feedback Nonlinear Systems (strict-feedback 비선형 시스템의 출력궤환 적응 신경망 제어기)

  • Park Jang-Hyun;Kim Il-Whan;Kim Seong-Hwan;Moon Chae-Joo;Choi Jun-Ho
    • Proceedings of the KIPE Conference
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    • 2006.06a
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    • pp.526-528
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    • 2006
  • An adaptive output-feedback neural control problem of SISO strict-feedback nonlinear system is considered in this paper. The main contribution of the proposed method is that it is shown that the output-feedback control of the strict-feedback system can be viewed as that of the system in the normal form. As a result, proposed output-feedback control algorithm is much simpler than the previous backstepping-based controllers. Depending heavily on the universal approximation property of the neural network (NN) only one NN is employed to approximate lumped uncertain nonlinearity in the controlled system.

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A Study on Non-Fragile Controller Design for Parameter Uncertain Systems (파라미터 불확실성 시스템에 대한 비약성 제어기 설계에 관한 연구)

  • 박성욱;오준호
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.272-272
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    • 2000
  • since the controller is part or the overall closed-Loop system, it is necessary that the designed controller be able to tolerate some uncertainty in its coefficients. The adequate stability and performance margins are required for the designed nominal controllers. In the paper. we study the method to design the non-fragile fixed-structured controller for real parametric uncertain systems. When we impose the controller parameter perturbation, the structure of the controller must be given. Therefore, we assume that the controller has fixed-structure. The fixed-structure controller is practically necessary especially when the robust controller synthesis results in a high-order controller. In SISO systems, we propose the robust controller design method using the Mapping theorem. In the method, the plant uncertainty and controller Parameter are of the multilineal form in the stability and performance conditions. Then, the controller synthesis problem is easily recast to Linear Programming Problem.

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