• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.78-82
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• 1995

In this paper, we consider the robustness analysis problem in state space models with linear time invariant perturbations. Based upon the discrete-time Lyapunov approach, sufficient conditions are derived for the eigenvalues of perturbed matrix to be located in a circle, and robustness bounds on perturbations are obtained. Spaecially, for the case of a diagonalizable hermitian matrix the bound is given in terms of the nominal matrix without the solution of Lyapunov equation. This robustness analysis takes account not only of stability robustness but also of certain types of performance robustness. For two perturbation classes resulting bounds are shown to be improved over the existing ones. Examples given include comparison of the proposed analysis method with existing one.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.71-78
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• 2008

New formation flight controller for unmanned aerial vehicles is proposed. A behavioral decentralized control approach called formation geometry center control is adopted. Trajectory tracking as well as formation geometry keeping are the purpose of the formation flight, and therefore two controllers are designed: a trajectory tracking controller for reference trajectory tracking, and a position controller for formation geometry keeping. Each controller is designed using Lyapunov stability theorem to guarantee the asymptotic stability. Formation flight controller is finally obtained by combining the trajectory tracking controller and the formation geometry keeping controller using a weighting parameter that depends on the relative distance error between unmanned aerial vehicles. Numerical simulations are performed to validate the performance of the proposed controller.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.495-505
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• 2006

A class of robust control for flexible joint manipulators with nonlinearity mismatched uncertainty is designed based on Lyapunov approach. The uncertainties are unknown but their values are within certain prescribed sets. No statistic information of the uncertainties is imposed. The control which utilizes state transformation via virtual control is proposed. The resulting robust control guarantees practical stability for the transformed system and later the stability for the original system is proved. The designed robust control is implemented by experiments in a 2-link flexible joint manipulator.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.189-195
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• 2000

The mathematical solutions of the stability convergence are important problems in system control. In this paper such problems are analyzed and resolved for system control using multilayer neural networks. We describe an algorithm to control an unknown nonlinear system with a disturbance, using a multilayer neural network. We include a disturbance among the modeling error, and the weight update rules of multilayer neural network are derived to satisfy Lyapunov stability. The overall control system is based upon the feedback linearization method. The weights of the neural network used to approximate a nonlinear function are updated by rules derived in this paper . The proposed control algorithm is verified through computer simulation. That is as the weights of neural network are updated at every sampling time, we show that the output error become finite within a relatively short time.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.552-563
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• 2005

In this paper, we propose a wavelet based fuzzy neural network (WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges the advantages of the neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of the wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of a mobile robot via the gradient descent (GD) method. In addition, an approach that uses adaptive learning rates for training of the WFNN controller is driven via a Lyapunov stability analysis to guarantee fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control results of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.2
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• pp.8-15
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• 2010

This paper proposes a robust high-gain observer design scheme for nonlinear systems and its stability is analyzed based on Lyapunov theory. It is assumed that their states are unmeasurable. The proposed high-gain observer has the integrator of the estimation error in dynamics. It improves the performance of high-gain observers and makes the proposed observer robust to noisy measurements, uncertainties and peaking phenomenon as well. Its stability is analyzed by the Lyapunov approach. In order to verify the effectiveness of the proposed scheme, it is applied to output feedback controllers and some comparative simulation result with the existed observer based output feedback controllers and state feedback controllers is given.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.443-445
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• 1998

In this paper, an alternate method for state-covariance assignment for SISO(single input single output) linear systems is proposed. This method is based on the inverse solution of the Lyapunov matrix equation and the resulting formulas are similar in structure to the formulas for pole placement. Further, the set of all assignable covariance matrices to a SISO linear system is also characterized.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.518-521
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• 1994

Most of the theorems of nonlinear stability is based on the Lyapunov stability theory. The Lyapunov function method is most well-known and provides precise and rigorous theoretical backgrounds. However, the conventional approach to direct stability analysis has been performed without taking account of damping effects. For accurate stability analysis of nonlinear systems, the damping effects should be considered. This paper presents a new method to derive a group of Lyapunov functions to reflect the damping effects by considering the integral relationships of the system governing equations.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.342-347
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• 2003

In this paper, an active vibration control of a translating tensioned string with the use of an electro-hydraulic servo mechanism at the right boundary is investigated. The dynamics of the moving strip is modeled as a string with tension by using Hamilton’s principle for the systems with changing mass. The control objective is to suppress the transverse vibrations of the strip via boundary control. A right boundary control law in the form of current input to the servo valve based upon the Lyapunov’s second method is derived. It is revealed that a time-varying boundary force and a suitable passive damping at the right boundary can successfully suppress the transverse vibrations. The exponential stability of the closed loop system is proved. The effectiveness of the control laws proposed is demonstrated via simulations.

• Kyungpook Mathematical Journal
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• v.54 no.2
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• pp.293-320
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• 2014

In this paper, global chaos synchronization is investigated for WINDMI (J. C. Sprott, 2003) and Coullet (P. Coullet et al, 1979) chaotic systems using adaptive backstepping control design based on recursive feedback control. Our theorems on synchronization for WINDMI and Coullet chaotic systems are established using Lyapunov stability theory. The adaptive backstepping control links the choice of Lyapunov function with the design of a controller and guarantees global stability performance of strict-feedback chaotic systems. The adaptive backstepping control maintains the parameter vector at a predetermined desired value. The adaptive backstepping control method is effective and convenient to synchronize and estimate the parameters of the chaotic systems. Mainly, this technique gives the flexibility to construct a control law and estimate the parameter values. Numerical simulations are also given to illustrate and validate the synchronization results derived in this paper.