• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.206-209
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• 1988

For feedback control of a linear dynamic system the optimum linear slace regulator (OLSR) can be implemented only if all state are available for feedback. This work demonstrates that when only the output state is available for feedback, a nonlinear controllers can be improved performance over that obtained by a proportional controller. This paper found the optimal control law by well-known dynamic programming and principles of optimality. Thus, performance of both proportional and nonlinear controllers is compared with performance of optimum linear state regulator.

• Journal of the Korean Mathematical Society
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• v.48 no.4
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• pp.775-795
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• 2011

The disturbance attenuation problem for a class of discretetime switched linear systems with exponential uncertainties via switched state feedback and switched dynamic output feedback is investigated, respectively. By using Taylor series approximation and convex polytope technique, exponentially uncertain discrete-time switched linear system is transformed into an equivalent switched polytopic model with additive norm bounded uncertainty. For such equivalent switched model, one designs its switching strategy and associated state feedback controllers and dynamic output feedback controllers so that whole switched model is asymptotical stabilization with H-in nity disturbance attenuation base on switched Lyapunov function and LMI approach. Finally, two numerical examples are presented to illustrate our results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.39-42
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• 2002

For the purpose of modeling EEG signal which has nonstationary and nonlinear dynamic characteristics, this paper propose a state feedback real time recurrent neural network model. The state feedback real time recurrent neural network is structured to have memory structure in the state of hidden layers so that it has arbitrary dynamics and ability to deal with time-varying input through its own temporal operation. For the model test, Mackey-Glass time series is used as a nonlinear dynamic system and the model is applied to the prediction of three types of EEG, alpha wave, beta wave and epileptic EEG. Experimental results show that the performance of the proposed model is better than that of other neural network models which are compared in this paper in some view points of the converging speed in learning stage and normalized mean square error for the test data set.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.7
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• pp.706-717
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• 1991

In order to remove the assumption of full state availability which is one of the major difficulties with the practical realization of variable structure control systems,a new switching function with a dynamic structure is proposed. And the control performances of the output feedback variable structure control systems with the dynamic switching function are evaluated through simulation studies. The proposed dynamic switching function is driven by small number of measured output and input variables while conventional static switching function requires full state information. Therefore, the proposition of the dynamic swiching function makes practical implementation of output feedback variable structure control scheme possible for the systems with unmeasurable state variables, high order systems and large scale systems that the conventional variable structure control schemes with static switching function cannot be applied. In the variable structure control systems with the dynamic switching function, desired control performance can be guaranteed by proper choice of design parameters such as poles of switching function dynamic equation and switching control gains even though small number of measured output and input variables are provided as shown in simulation resuls.

• Journal of Mechanical Science and Technology
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• v.19 no.2
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• pp.618-624
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• 2005

We present a new state-space approach to construct a dynamic output feedback controller which stabilizes a class of linear time invariant systems. All the states of the given system are not measurable and only the output is used to design the stabilizing control law. In the design scheme, however, we first assume that the given system can be stabilized by a feedback law composed of the output and its derivatives of a certain order. Beginning with this assumption, we systematically construct a dynamic system which removes the need of the derivatives. The main advantage of the proposed controller is regarding the controller order, which may be smaller than that of conventional output feedback controller. Using a simple numerical example, it is shown that the order of the proposed controller is indeed smaller than that of reduced-order observer based output feedback controller.

• Journal of Power Electronics
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• v.13 no.3
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• pp.400-408
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• 2013

This paper presents a discrete state-space controller using state feedback control and feed-forward decoupling to provide a desirable control bandwidth and control stability for dynamic voltage restorers (DVR). The paper initially discusses three typical applications of a DVR. The load-side capacitor DVR topology is preferred because of its better filtering capability. The proposed DVR controller offers almost full controllability because of the multi-feedback of state variables, including one-beat delay feedback. Feed-forward decoupling is usually employed to prevent disturbances of the load current and source voltage. Directly obtaining the feed-forward paths of the load current and source voltage in the discrete domain is a complicated process. Fortunately, the full feed-forward decoupling strategy can be easily applied to the discrete state-space controller by means of continuous transformation. Simulation and experimental results from a digital signal processor-based system are included to support theoretical analysis.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.310-314
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• 2008

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. This novel method uses the support vector machines (SVM) with its function approximation property. It works together with RLS (Recursive least-squares) algorithm. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems.

• 전기의세계
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• v.31 no.1
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• pp.43-49
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• 1982

This paper intends to compare and illustrate the feedback effects of the state feedback scheme to a positional control system by the use of the state observer. As a case study, the dynamic properties of a proposed positional control system lie derived, first, and the design of an optimal state feedback control system by the actual states is intended as a primary case study. For the illustration of the feedback effects with the asymptotic state observer, unobservability of some state variables are assumed and an optimal state feedback design is carried by using the estimated states which is reconstructed through the observer. That is, when some of the states of the system to be controlled are not avalable, an observer is constructed to estimate the unaccessable states. Adigital computer is used for the comparative study of the feedback effects in both cases. The resultant response of the proposed system have shown quite reasonable satisfaction oncontrol quality.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.79-81
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• 2009

In this paper, we design a dynamic state feedback smooth stabilizer for a nonlinear system whose Jacobian linearization may have uncontrollable because its eigenvalues are on the right half-plane. After designing an augmented system, a dynamic exponent scaling and backstepping enable one to explicitly design a smooth stabilizer and a continuously differentiable Lyapunov function which is positive definite and proper.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.1
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• pp.85-92
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• 1989

For feedback control of a linear dynamic system the optimum linear state regulator (OLSR) can be implemented only if all states are available for feedback. This work demonstrates that when only the output state is available for feedback, a nonlinear controllers can give improved performance over that obtained by a proportional controller. This paper found the optimal control law by dynamic programming and principles of optimalityl. This, performances of both proportional and nonlinear controllers are compared with performance of optimum linear state regulator.