• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.30-35
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• 2003

In the control system analysis and synthesis, the nonminimum phase system has some difficulties due to the undershoot behaviour and the constrained sensitivity function. SISO problems has been widely investigated in the literatures, and it is well known that the undershoot cannot be eliminated by any linear feedback control. However, the undershoot compensation in MIMO system is less studied, and this paper is to deal with the zero property and the nonminimum phase behaviour of the MIMO system. Firstly, some definitions of the zeros will be introduced. Second, some systems including nonminimum phase transmission zeros are exemplified to show that the undershoot behaviour could be eliminated by a linear feedback in MIMO systems.

• Transactions on Control, Automation and Systems Engineering
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• 제3권3호
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• pp.152-158
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• 2001

This paper proposes a simple feedforward compensator in order to decrease the amount of undershoots and overshoots on the step response in nonminimum phase systems. The compensator makes the step type input be a ramp input with saturation for 0$\leq$t<${\alpha}$. It is shown in this paper that the compensated system has small amount of undershoot and overshoot at the price of rise time compared to the system without compensator. Also, provided the system is properly stable, the influence of the design parameter ${\alpha}$ on the step response of the nonminimum phase system is investigated in the case of Type A, and Type B undershoot, which gives a guideline for the compensator design.

• 전기학회논문지
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• 제57권1호
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• pp.117-120
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• 2008

This paper investigates the convergence condition of ADILC(iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.225-227
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• 2006

This note investigates the convergence condition of ADILC (iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

• 제어로봇시스템학회논문지
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• 제7권11호
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• pp.891-895
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• 2001

An alternative inverse feedback structure for adaptive active control of periodic noise is introduced for systems with nonminimum phase cancellation path. To obtain the inverse model of the nonminimum phase cancellation path, the cancellation path model can be factorized into a minimum phase term and a maximum phase term. The maximum phase term containing unstable zeros makes the inverse model unstable. To avoid the instability, we alter the inverse model of the maximum phase system into an anti-causal FIR one. An LMS predictor estimates the future samples of the noise, which are necessary for causality of both anti-causal FIR approximation for the stable inverse of the maximum phase system and time-delay existing in the cancellation path. The proposed method has a faster convergence behavior and a better transient response than the conventional filtered-x LMS algorithms with the same internal model control structure since a filtered reference signal is not required. We compare the proposed methods with the conventional methods through simulation studies.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.437-442
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• 2000

An alternative inverse feedback structure for adaptive active control of periodic noise is introduced for systems with nonminimum phase cancellation path. To obtain the inverse model of the nonminimum phase cancellation path, the cancellation path model can be factorized into a minimum phase term and a maximum phase term. The maximum phase term containing unstable zeros makes the inverse model unstable. To avoid the instability, we alter the inverse model of the maximum phase system into an anti-causal FIR one. An LMS predictor estimates the future samples of the noise, which are necessary for causality of both anti-causal FIR approximation for the stable inverse of the maximum phase system and time-delay existing in the cancellation path. The proposed method has a faster convergence behavior and a better transient response than the conventional FX-LMS algorithms with the same internal model control structure since a filtered reference signal is not required. We compare the proposed methods with the conventional methods through simulation studies.

• 대한전기학회논문지
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• 제35권11호
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• pp.529-534
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• 1986

In recent year, there have been much techniques for designing globally stable adaptive control systems when the unknown plant is minimum phase. This paper presents a new seheme for indirect adaptive control structure for nonminimum phase plant of which parameters are estimated from the least-square algorithm. Its effectiveness has been demonstrated by computer simulation carried out for a second-order plant.

• 한국군사과학기술학회지
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• 제21권2호
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• pp.204-210
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• 2018

As the 4th industrial revolution and artificial intelligence technology develop, it is expected that there will be a revolutionary changes in the security robot. However, artificial intelligence system requires enormous hardwares for tremendous computing loads, and there are many challenges that need to be addressed more technologically. This paper introduces precise tracking control technique of autonomous system that need to move repetitive paths for security purpose. The input feedforward signal is generated by using the inverse based iterative learning control theory for the 2 input 2 output nonminimum-phase system which was difficult to overcome by the conventional feedback control system. The simulation results of the input signal generation and precision tracking of given path corresponding to the repetition rate of extreme, such as bandwidth of the system, shows the efficacy of suggested techniques and possibility to be used in military security purposes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.79-82
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• 1999

The right half plane (RHP) zeros may cause severe problems, such as undershoots, oscillations and time delay in the transient response of the systems. In this paper, we formulate a linear quadratic type problem to deal with the effects of the RHP zeros in the nonminimum phase systems. Based on the LQ formulation, this paper shows the trade-off relation between undershoot and rising time performances in nonminimum phase systems by using a new performance index which consists of new state and tracking error. And performances of the proposed method are shown via computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.422-425
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• 1997

We consider the robust control problem for nonminimum phase(NMP) systems with parametric uncertainty which appear often in aircraft and missile control. First, a new method that makes such an uncertain NMP system to be factored as a interval minimum phase(MP) transfer function and a time delay term in the Pade approximation form has been presented. The controller to be proposed consists of a compensator $C_{Q}$(s) with Smith predictor in the internal model control(IMC) structure, so that it can have good robustness and performance against the structured uncertainty and the time delay behaviour due to NMP plant the $C_{Q}$(s) is designed on the MP model by using QFT. The stability and performance of overall system has been evaluated by the generalized Kharitonov theorem.rem.