• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.329-334
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• 2000

In this paper, we get staled harmonic maps of an almost Kaehler manifold into itself, using the stability theorem.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.316-321
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• 2003

This paper presents a design method of the wavelet neural network based controller using direct adaptive control method to deal with a stable intelligent control of chaotic systems. The various uncertainties, such as mechanical parametric variation, external disturbance, and unstructured uncertainty influence the control performance. However, the conventional control methods such as optimal control, adaptive control and robust control may not be feasible when an explicit, faithful mathematical model cannot be constructed. Therefore, an intelligent control system that is an on-line trained WNN controller based on direct adaptive control method with adaptive learning rates is proposed to control chaotic nonlinear systems whose mathematical models are not available. The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system. In the whole design process, the strict constrained conditions and prior knowledge of the controlled plant are not necessary due to the powerful learning ability of the proposed intelligent control system. The gradient-descent method is used for training a wavelet neural network controller of chaotic systems. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with application to the chaotic systems.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1438-1454
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• 2016

Because the nonlinear and time-varying characteristics of continuously variable transmission (CVT) systems driven by means of a six-phase copper rotor induction motor (CRIM) are unconscious, the control performance obtained for classical linear controllers is disappointing, when compared to more complex, nonlinear control methods. A blend modified recurrent Gegenbauer orthogonal polynomial neural network (OPNN) control system which has the online learning capability to come back to a nonlinear time-varying system, was complied to overcome difficulty in the design of a linear controller for six-phase CRIM driving CVT systems with lumped nonlinear load disturbances. The blend modified recurrent Gegenbauer OPNN control system can carry out examiner control, modified recurrent Gegenbauer OPNN control, and reimbursed control. Additionally, the adaptation law of the online parameters in the modified recurrent Gegenbauer OPNN is established on the Lyapunov stability theorem. The use of an amended artificial bee colony (ABC) optimization technique brought about two optimal learning rates for the parameters, which helped reform convergence. Finally, a comparison of the experimental results of the present study with those of previous studies demonstrates the high control performance of the proposed control scheme.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1566-1577
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• 2018

This paper presents a stability analysis of AC-DC power system feeding a speed controlled DC motor in which this load behaves as a constant power load (CPL). A CPL can significantly degrade power system stability margin. Hence, the stability analysis is very important. The DQ and generalized state-space averaging methods are used to derive the mathematical model suitable for stability issues. The paper analyzes the stability of power systems for both speed control natural frequency and DC-link parameter variations and takes into account controlled speed motor dynamics. However, accurate DC-link filter and DC motor parameters are very important for the stability study of practical systems. According to the measurement errors and a large variation in a DC-link capacitor value, the system identification is needed to provide the accurate parameters. Therefore, the paper also presents the identification of system parameters using the adaptive Tabu search technique. The stability margins can be then predicted via the eigenvalue theorem with the resulting dynamic model. The intensive time-domain simulations and experimental results are used to support the theoretical results.

• Bulletin of the Korean Mathematical Society
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• v.45 no.1
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• pp.111-118
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• 2008

Using the Hyers-Ulam-Rassias stability method, we investigate isomorphisms in quasi-Banach algebras and derivations on quasi-Banach algebras associated with the Cauchy-Jensen functional equation $$2f(\frac{x+y}{2}+z)$$=f(x)+f(y)+2f(z), which was introduced and investigated in [2, 17]. The concept of Hyers-Ulam-Rassias stability originated from the Th. M. Rassias' stability theorem that appeared in the paper: On the stability of the linear mapping in Banach spaces, Proc. Amer. Math. Soc. 72 (1978), 297-300. Furthermore, isometries and isometric isomorphisms in quasi-Banach algebras are studied.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.2
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• pp.331-338
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• 1990

In adaptive control, the lack of persistent and rich excitation causes the estimated parameters to drift, which degrade the performance of the system and may introduces instability to the system in a stochastic environment. To solve the problem of the parameter drift, the concept of single parameter adaptation is presented. For the parameter identification, a priori error is directly used for adaptation error. The structure of the controller is based upon the minimum variance control technique. The stability and robustness analysis is carried out by the sector stability theorem for the second order system. The computer simulation is performed to justify the theoretical analysis for the various cases.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.449-451
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• 1998

In this paper, we consider the problem of the robust stability of uncertain linear systems with multiple time-varying delays. The considered uncertainties are both the unstructured uncertainty which is only known its norm bound and the structured uncertainty satisfying the matching conditions, respectively. We present conditions that guarantee the robust stability of systems based on Lyapunov stability theorem and $H_{\infty}$ theory in the time domain. Finally, we show the usefulness of our results by numerical examples.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.463-465
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• 1998

In this paper, we consider the problem of robust stability of large-scale uncertain linear systems with time-varying delays. The considered uncertainties are both unstructured uncertainty which is only known its norm bound and structured uncertainty which is known its structure. Based on Lyapunov stability theorem and $H_{\infty}$ theory. we present uncertainty upper bound that guarantee the robust stability of systems. Especially, robustness bound are obtained directly without solving the Lyapunov equation. Finally, we show the usefulness of our results by numerical example.

• Journal of the Korean Mathematical Society
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• v.49 no.4
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• pp.715-731
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• 2012

This paper considers the stability of positive steady-state solutions bifurcating from the trivial solution in a delayed Lotka-Volterra two-species predator-prey diffusion system with a discrete delay and subject to the homogeneous Dirichlet boundary conditions on a general bounded open spatial domain with smooth boundary. The existence, uniqueness and asymptotic expressions of small positive steady-sate solutions bifurcating from the trivial solution are given by using the implicit function theorem. By regarding the time delay as the bifurcation parameter and analyzing in detail the eigenvalue problems of system at the positive steady-state solutions, the asymptotic stability of bifurcating steady-state solutions is studied. It is demonstrated that the bifurcating steady-state solutions are asymptotically stable when the delay is less than a certain critical value and is unstable when the delay is greater than this critical value and the system under consideration can undergo a Hopf bifurcation at the bifurcating steady-state solutions when the delay crosses through a sequence of critical values.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.93-102
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• 2005

The Nyquist robust stability margin is proposed as a measure of robust stability for systems with Affine TFM(Transfer Function Matrix) parametric uncertainty. The parametric uncertainty is modeled through a Affine TFM MIMO (Multi-Input Multi-Output) description with dead-time, and the unstructured uncertainty through a bounded perturbation of Affine polynomials. Gershgorin's theorem and concepts of diagonal dominance and GB(Gershgorin Bands) are extended to include model uncertainty. Multiloop PI/PID controllers can be tuned by using a modified version of the Ziegler-Nichols (ZN) relations. Consequently, this paper provides sufficient conditions for the robustness of Affine TFM MIMO uncertain systems with dead-time based on Rosenbrock's DNA. Simulation examples show the performance and efficiency of the proposed multiloop design method for Affine uncertain systems with dead-time.