• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.330-340
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• 2002

In this Paper. a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.117-121
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• 2005

This paper deals with the state estimation of linear time-invariant discrete systems with unknown inputs. The forward sequences of the output are treated as additional outputs. In this case, the rank condition for designing the unknown input estimator is relaxed. The gain for minimal estimation error variance is presented, and a numerical example is given to verify the proposed unknown input estimator.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.15-21
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• 2017

In this paper, the decentralized fuzzy observer design technique is presented for discrete-time nonlinear interconnected systems, which are assumed to be with unknown interconnections. To design the decentralized fuzzy observer, the design problem is considered and the performance function is defined to solve the design problem. Based on the performance function, the sufficient condition is derived for the observer design, and its condition is formulated into linear matrix inequalities. Finally, by the simulation result, the validity of the proposed observer design technique is shown.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.496-498
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.95-98
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete -time system have proper reason. Sufficiently conditions for the global state -matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMls). Finally, we prove the effectiveness and stabilization of the proposed intelligent digital redesign method by applying the chaotic Lorentz system.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.884-889
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• 1989

In this paper, a new procedure for selecting weighting matrices in linear discrete time quadratic optimal control problem (LQ-problem) is proposed. In LQ-problems, the quadratic weighting matrices are usually decided on trial and error in order to get a good response. But using the proposed method, the quadratic weights are decided in such a way that all poles of the closed loop system are located in a desired region for good responses as well as for stability and values of the quadratic cost function are kept less then a specified value.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.6
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• pp.38-43
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• 1980

For linear discrete-time time-invariant multi-input mufti-output systems, a necessary condition which an optimal output Proportional feedback gains must satisfr is deiived. Quadratic performance index is used. The result is extended to the desi01 problem for determining optimal output proportional plus integral feedback gains. For illustration, an example problem is solved and discussed.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.170-183
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• 2007

This paper presents a delay-dependent approach to robust filtering for linear parameter-varying (LPV) systems with discrete and distributed time-invariant delays in the states and outputs. It is assumed that the state-space matrices affinely depend on parameters that are measurable in real-time. Some new parameter-dependent delay-dependent stability conditions are established in terms of linear matrix inequalities (LMIs) such that the filtering process remains asymptotically stable and satisfies a prescribed $H_{\infty}$ performance level. Using polynomially parameter-dependent quadratic (PPDQ) functions and some Lagrange multiplier matrices, we establish the parameter-independent delay-dependent conditions with high precision under which the desired robust $H_{\infty}$ filters exist and derive the explicit expression of these filters. A numerical example is provided to demonstrate the validity of the proposed design approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.780-785
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• 2007

This paper proposes the decentralized dynamic output feedback controller for discrete-time nonlinear interconnected systems using Takagi-Sugeno (T-S) fuzzy model. Through T-S fuzzy model of each subsystem, the decentralized dynamic output feedback controller is designed. By the closed-loop subsystems with controller, it represents the linear matrix inequality (LMI) for stability of whole interconnected system. The value of control gain are obtained by LMI. An example is given to show the experimentally verification discussed throughout the paper.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.10a
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• pp.7-7
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• 1992

Extending discrete event modelling formalisms to facilitate greater symbol manipulation capabilities is important to further their use in intelligent control and design of high autonomy systems. This paper defines an extension to the DEVS formalism that facilitates symbolic expression of discrete event times by extending the time base from the real numbers to the field of linear polynomials over the reals. A simulation algorithm is developed to generate the branching trajectories resulting from the underlying non-determinism. To efficiently manage linear polynomial constraints based on feasibility checking algorithm borrowed from linear programming. The extended formalism offers a convenient means to conduct multiple, simultaneous explorations of model behaviors. Examples of application are given with consideration on fault model analysis.