• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.582-589
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• 2003

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included Un the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.225-235
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• 2005

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included in the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.479-481
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• 1999

In this paper, We design low-order controller to achieve maximized controller stability margin and controller' Performance. FOPA(Fixed Order Pole Assignment) method is one of the approach to design controller in the parametric uncertain system. But the method to define a Target Polynomial is not explicit1y Known. In this paper, our goal is to find a controller Coefficient, such that performance and $l_2$ stability margin are maximized in the parametric uncertain system. Using Lipatove theorem and CDM(Coefficient Diagram Method), we set target polynomial constraints and design a controller which maximizes $l_2$ stability margin. we show effectiveness of the proposed controller design method by comparing $l_2$ stability many of the desired controller with that of the conventional robust controller.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1220-1223
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• 2002

In this paper, numerical robust stability analysis method and its design are presented. L$_2$robust stability of the fuzzy system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linarization control gains is proposed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.5
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• pp.26-33
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• 2002

The design method of robust $H_{\infty}$ filtering for discrete-time uncertain linear systems is investigated in this paper. The uncertain parameters are assumed to be unknown but belonging to known convex compact set of polytope type. The objective is to design a stable robust $H_{\infty}$ filter guaranteeing the asymptotic stability of filtering error dynamics and present an $L_2$ induced norm bound analytically for the modified $H_{\infty}$ performance measure. The sufficient condition for the existence of robust $H_{\infty}$ filter and the filter design method are established by LMI(linear matrix inequality) approach, which can be solved efficiently by convex optimization. The proposed algorithm is checked through an example.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.1-7
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• 2001

For a parametric uncertain system, there are many results on stability analysis, but only a few synthesis methods. In this paper, we proposed a new target polynomial decision method for the parametric uncertain system to stabilize the closed loop system with maximal parametric $l_2$ stability margin. To this, we used both Lipatov Theorem and coefficient diagram method(CDM). To show the effectiveness of the proposed method, we designed a robust controller for the inverted pendulum system with parametric uncertainties using fixed order pole assignment(FOPA) method and its performance was compared with that of the ${\mu}$ synthesis methods.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.138-146
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• 2007

The analysis and design method for achieving robust stabilization of Decentralized Dynamic Surface Control (DDSC) is presented for a class of interconnected nonlinear systems. While a centralized design approach of DSC was developed in [1], the decentralized approach to deal with large-scale interconnected systems is proposed under the assumption that interconnected functions among subsystems are unknown but bounded. To provide a closed-loop form with provable stability properties, augmented error dynamics for N nonlinear subsystems with DDSC are derived. Then, the reachable set for errors of the closed-loop systems will be approximated numerically in the form of an ellipsoid in the framework of convex optimization. Finally, a numerical algorithm to calculate the $L_2$ gain of the augmented error dynamics is presented.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.05a
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• pp.244.2-244.2
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• 2011

We introduce a novel and robust method for the preparation of nanocomposite multilayers, which allows the excellent photoluminescent (PL) properties as well as the accurate control over the composition and dimensions of multilayers. By exchanging the oleic acid stabilizers of CdSe@ZnS quantum dots (QDs) synthesized in organic solvent with 2-bromo-2-methylpropionic acid (BMPA) in the same solvent, these nanoparticles were be alternately deposited by nucleophilic substitution reaction with highly branched poly(amidoamine) dendrimer (PAMA) through layer-by-layer (LbL) assembly process. Our approach does not need to be transformed into the water-dispersible nanoparticles with electrostatic or hydrogen-bonding groups, which can deteriorate their inherent properties, for the built-up of multilayers. The nanocomposite multilayers including QDs exhibited the strong PL properties achieving densely packed surface coverage as well as long-term PL stability under atmospheric conditions in comparison with those of conventional LbL multilayers based on electrostatic interaction. Furthermore, we demonstrate that the flexible multilayer films with optical properties can be easily prepared using nucleophilic substitution reaction between bromo and amino groups in organic media. This robust and tailored method opens a new route for the design of functional film devices based on nanocomposite multilayers.

• Journal of Power Electronics
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• v.13 no.1
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• pp.139-160
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• 2013

In this paper, an intelligent robust control system (IRCS) for precision tracking control of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The IRCS comprises a recurrent wavelet-based interval type-2 fuzzy-neural-network controller (RWIT2FNNC), an RWIT2FNN estimator (RWIT2FNNE) and a compensated controller. The RWIT2FNNC combines the merits of a self-constructing interval type-2 fuzzy logic system, a recurrent neural network and a wavelet neural network. Moreover, it performs the structure and parameter-learning concurrently. The RWIT2FNNC is used as the main tracking controller to mimic the ideal control law (ICL) while the RWIT2FNNE is developed to approximate an unknown dynamic function including the lumped parameter uncertainty. Furthermore, the compensated controller is designed to achieve $L_2$ tracking performance with a desired attenuation level and to deal with uncertainties including approximation errors, optimal parameter vectors and higher order terms in the Taylor series. Moreover, the adaptive learning algorithms for the compensated controller and the RWIT2FNNE are derived by using the Lyapunov stability theorem to train the parameters of the RWIT2FNNE online. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed IRCS. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the IRCS grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.83.3-83
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• 2002

$\textbullet$ In this paper, a robust decentralized excitation control scheme is proposed $\textbullet$ We prove that the proposed control system is practically stable $\textbullet$ The origin is globally uniformly asymptotically stable in the absence of the disturbance $\textbullet$ If assumption is not satisfied, the proposed control system is still guarantees L2 stability $\textbullet$ Simulations for a three-machine power system demonstrates the effectiveness of the proposed scheme