• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1821-1826
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• 2009

An adaptive neural controller for perturbed strict-feedback nonlinear system is proposed. All the previous adaptive neural (or fuzzy) controllers are based on the backstepping scheme where the universal approximators are employed in every design steps. These schemes involve virtual controls and their time derivatives that make the stability analysis and implementation of the controller very complex. This fact is called 'explosion of complexty ' since the complexity grows exponentially as the system dynamic order increases. The proposed adaptive neural control scheme adopt the backstepping design procedure only for determining ideal control law and employ only one neural network to approximate the finally selected ideal controller, which makes the controller design procedure and stability analysis considerably simple compared to the previously proposed controllers. It is shown that all the time-varing signals containing tracking error are stable in the Lyapunov viewpoint.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.151-156
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• 2008

This paper presents the stability analysis and design for a sampled-data fuzzy control system with neutral type of time delay, which is formed by a nonlinear plant and a sampled-data fuzzy controller connected in a closed loop. The sampling activity and neutral type of time delay will complicate the system dynamics and make the stability analysis much more difficult than that for a pure continuous-time fuzzy control system. Based on the fuzzy-model-based control approach, LMI(linear matrix inequality)-based stability conditions are derived to guarantee the nonlinear networked system stability. An application example will be given to show the merits and design a procedure of the proposed approach.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.21-31
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• 2000

In this paper, an analysis of the stability for a class of discrete-time neural network control systems is presentd. Based on Lyapunov's direct method, a sufficient stability condition for the neural network control systems is systematically derived and the modified back propagation algorithm which reflects the derived stability condition is suggested. The modified BP originates from the derived sufficient condition and guarantees the exponential stability of the resulting trained closed system. Finally, computer simulation is included to show an example where the derived stability condition and the BP modified bythe condition is used to train the control plant.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.159-164
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• 2010

This paper focuses on the stability analysis and stabilization for networked control system with neutral type of time-delay. By utilizing the delay partitioning idea, new stability criteria are proposed in terms of linear matrix inequalities(LMIs). These conditions are developed based on the Lyapunov-Krasovskii functionals. Based on the derived criteria, a sufficient condition for te solvability of this problem is obtained in terms of linear matrix inequality without decomposing the original system matrices. Also, it is shown that the proposed controller design method is general for networked control systems. Finally, illustrative examples are presented to show the applicability of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.183-189
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• 2013

This paper presents a stabilization method for NCS (Networked Control Systems) with two additive time-varying delays. Each time delay component between the plant and the controller has different characteristics depending on communication network, and has the upper and lower bounds. The time delay occurring from the controller to the plant has an effect on the time delay occurring from the plant to the controller, and the relationship between two delays is taken into account on the stability analysis. Based on the two additive delay components and the bound conditions, the appropriate Lyapunov-Krasovskii functional and the LMI (Linear Matrix Inequality) method derive the stability condition and the $H_{\infty}$ norm constraint for time-varying delayed NCS. Simulation results are finally given to demonstrate the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.526-532
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• 2014

In this paper, we present and analyze a LQ (Linear Quadratic) inverse optimal state-consensus protocol for continuous-time multi-agent systems with undirected graph topology. By Lyapunov analysis of the state-consensus error dynamics, we show the sufficient conditions on the algebraic connectivity of the graph to guarantee LQ inverse optimality and closed-loop stability. A more relaxed stability condition is also provided in terms of the algebraic connectivity. Finally, a formation control protocol for multiple mobile robots is proposed based on the target LQ inverse optimal consensus protocol, and the simulation results are provided to verify the performance of the proposed LQ inverse formation control method.

• Bulletin of the Korean Mathematical Society
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• v.54 no.6
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• pp.1893-1912
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• 2017

In this paper, we aim to construct a nonstandard finite difference (NSFD) scheme to solve numerically a mathematical model for cholera epidemic dynamics. We first show that if the basic reproduction number is less than unity, the disease-free equilibrium (DFE) is locally asymptotically stable. Moreover, we mainly establish the global stability analysis of the DFE and endemic equilibrium by using suitable Lyapunov functionals regardless of the time step size. Finally, numerical simulations with different time step sizes and initial conditions are carried out and comparisons are made with other well-known methods to illustrate the main theoretical results.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1640_1641
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• 2009

Dynamic friction and force ripple are the most predominant factors that affect the positioning accuracy of permanent magnet synchronous motor(PMSM) servo drives system, and it is desirable to compensate them in finite time with a continuous control law. In this paper, based on LuGre dynamic friction model, a robust adaptive skidding mode controller is proposed to compensate the nonlinear effect of friction and force ripple. The controller scheme consists of a PD component and a robust adaptive sliding mode controller for estimating the unknown system parameter. Using Lyapunov stability theorem, asymptotic stability analysis and position tracking performance are guaranteed. Simulation results well verify the feasibility and the effectiveness of the proposed scheme for high0precision motion trajectory tracking.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.4
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• pp.312-316
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• 2004

In this paper, it is presented an adaptive robust control system to implement real-time control of a robot manipulator. There are Quantitative or qualitative differences between a real robot manipulator and a robot modeling. In order to compensate these differences, uncertain factors are added to a robot modeling. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, etc. Also, uncertainty is often nonlinear and time-varying. In the proceeding work, we proposed a class of robust control of a robot manipulator and provided the stability analysis. In the work, we propose a class of adaptive robust control of robot manipulator with bound estimation. Through experiments, the proposed adaptive robust control scheme is proved to be an efficient control technique for real-time control of a robot system using DSP.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.233-239
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• 2005

This paper presents the design and evaluation of a tiltrotor attitude controller. The implemented response type of the command augumentation system is Attitude Command Attitude Hold. The controller architecture can alleviate the need for extensive gain scheduling and thus has the potential to reduce development time. The control algorithm is constructed using the feedback linearization technique. And an on-line adaptive architecture that employs a neural network compensating the model inversion error caused by the deficiency of full knowledge tiltrotor aircraft dynamics is applied to augment the attitude control system. The use of Lyapunov stability analysis guarantees boundedness of the tracking error and network parameters. The performance of the controller is evaluated against ADS-33E criteria, using the nonlinear tiltrotor simulation code for Bell TR301 developed by KARI. (Korea Aerospace Research Institute)