• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1205-1208
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• 1996

This paper proposes balanced model reduction of non-minimum phase plant. The algorithm presented in this paper is to convert high-order non-minimum phase plant into low-oder minimum phase plant using balanced model reduction. Balanced model reduction requires the error bound that Hankel singular value produces. This algorithm shows the tolerance that admits the method of this paper.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.9
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• pp.431-438
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• 2001

This paper present experimental results of source identification for non-minimum phase system. Generally, a causal linear system may be described by matrix form. The inverse problem is considered as a matrix inversion. Direct inverse method can\`t be applied for a non-minimum phase system, the reason is that the system has ill-conditioning. Therefore, in this study to execute an effective inversion, SVD inverse technique is introduced. In a Non-minimum phase system, its system matrix may be singular or near-singular and has one more very small singular values. These very small singular values have information about a phase of the system and ill-conditioning. Using this property we could solve the ill-conditioned problem of the system and then verified it for the practical system(cantilever beam). The experimental results show that SVD inverse technique works well for non-minimum phase system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.997-1002
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• 2001

This paper describes an implementation of inverse filter using SVD in order to recover the input in multi-channel system. The matrix formulation in SISO system is extended to MIMO system. In time and frequency domain we investigates the inversion of minimum phase system and non-minimum phase system. To execute an effective inversion of non-minimum phase system, SVD is introduced. First of all we computes singular values of system matrix and then investigates the phase property of system. In case of overall system is non-minimum phase, system matrix has one (or more) very small singular value(s). The very small singular value(s) carries information about phase properties of system. Using this property, approximate inverse filter of overall system is founded. The numerical simulation shows potentials in use of the inverse filter.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.8
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• pp.32-42
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• 2022

Asymptotic tracking of a non-minimum phase nonlinear system has been a popular topic in control theory and application. In this paper, we propose a new control scheme to achieve asymptotic output tracking in anon-minimum phase nonlinear system for periodic trajectories through an iterative learning control with the stable inversion. The proposed design method is robust to parameter uncertainties and periodic external disturbances since it is based on iterative learning. The performance of the proposed algorithm was demonstrated through the simulation results using a typical non-minimum nonlinear system of an inverted pendulum on a cart.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1612-1617
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• 2008

Since most disturbance observer (DOB) approaches have been limited to minimum-phase systems (or systems having no zero dynamics), we propose a new DOB structure that can be applied to non-minimum phase systems. The new structure features an additional system, which is called as V-filter, whose role is to yield a minimum phase system when connected with the plant in parallel. In order to design the V-filter systematically we first consider a class of linear systems that can be stabilized via PID controller. By inverting the controller's transfer function, we can simply construct the filter. A convenient way of designing V-filter is presented by using an iterative linear matrix inequality (LMI) algorithm. With an illustrative example the simulation result shows that substantial improvement in the performance has been achieved compared with the control system without the DOB.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.3-11
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• 2001

This paper describes an implementation of inverse filter using SVD in order to recover the input in multi-channel system. The matrix formulation in SISO system is extended to MIMO system. In time and frequency domain we investigates the inversion of minimum phase system and non-minimum phase system. To execute an effective inversion of non-minimum phase system, SVD is introduced. First of all we computes singular values of system matrix and then investigates the phase property of system. In case of overall system is non-minimum phase, system matrix has one (or more) very small singular value (s). The very small singular value (s) carries information about phase properties of system. Using this property, approximate inverse filter of overall system is founded. The numerical simulation shows potentials in use of the inverse filter.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1405-1410
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• 2009

Output voltage of a DC/DC power converter system is likely to be distorted if variable loads exist in the output terminal. This paper presents a new disturbance observer(DOB) approach to maintain a robust regulation of the output voltage of a boost type DC/DC converter. Unlike the buck-type converter case, the regulation problem of the boost converter is very complicated by the fact that, with respect to the output voltage to be regulated, the system is non-minimum phase. Owing to the non-minimum phase property the classical DOB approach has not been applied to the boost converter. Motivated by a recent result on the application of DOB to non-mimimum phase system, an output feedback control law is proposed by using a parallel feedforward compensator. Simulation results using the Simulink SimPowerSystems prove the performance of the proposed controller against load variation.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.60.1-60
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• 2002

. an output feedback stabilizing controller for non-minimum phase nonlinear systems . Assumption 1 : the Jacobi linearization of the given nonlinear linear system is controllable . Assumption 2: an appropriate transformation which transforms the zero dynamics into a special form . Assumption 3: the system satisfies the observability rank condition . Augmentation of systems by augmented by a chain of integrators

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.329-334
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• 2010

This paper presents the design of a neural network based adaptive control for missile. Acceleration of missile by tail fin control cannot be controllable by DMI (Dynamic Model Inversion) directly because it is non-minimum phase system. To avoid the non-minimum phase system, dynamic model inversion is applied with output-redefinition method. In order to evaluate performance of the suggested controllers we selected the three cases such as control surface fail, control surface loss and wing loss for model uncertainty. The corresponding aerodynamic databases to the failure cases were calculated by using the Missile DATACOM. Using a high fidelity 6DOF simulation program of the missile the performance was evaluates.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.977-983
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• 2003

An output feedback stabilizing controller far non-minimum phase nonlinear systems is presented. We first perform the standard input-output linearization of the system and then transform the zero dynamics into a special normal form in which the antistable part is not affected by the stable part and the antistable part is given in approximately linear form. Under the assumption that the nonlinear system satisfies the observability rank condition, we can design an observer f3r the extended system that is made of the augmentation of a chain of integrators. The proposed output feedback stabilizing controller can then be designed by combining the observer and the state feedback controller.