• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.129-133
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• 2003

In this paper, we consider the robust guaranteed cost control problem for a class of uncertain neutral systems with given quadratic cost functions. The uncertainty is assumed to be norm-bounded and time-varying. The goal in this study is to design the memoryless state feedback controller such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound lot all admissible uncertainty. Some criteria for the existence of such controllers are derived based on the matrix inequality approach combined with the Lyapunov second method. A parameterized characterization of the robust guaranteed cost controllers is given in terms of the feasible solutions to the certain matrix inequalities. A numerical example is given to illustrate the proposed method.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2497-2499
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• 2002

This raper proposes a simple robust nonlinear controller design method based on Lyapunov stability for tracking reference welding trajectory and velocity of a three wheel welding mobile robot (WMR). Control law is obtained from Lyapunov control function to ensure asymptotical stability of the system. The effectiveness of the proposed controller is shown through simulation results.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.265-270
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• 2001

In this paper, a robust controller is proposed to control a robot manipulator which is governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require the dynamic model or parameter values of a robot manipulator. It, however, requires uncertainty bounds which are derived by using properties of revolute joint robot dynamics. The stability of the robot with the controller is proved by using Lyapunov's direct method. The results of computer simulations also show that the robot system is stable, and has excellent trajectory tracking performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2139-2146
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• 2011

In this paper, a robust adaptive controller is proposed for trajectory tracking of robot manipulators with the unknown friction coefficient and bounded disturbance. A new adaptive control law is developed based on sliding mode and derived from the Lyapunov stability analysis. The introduction of a boundary layer solves the problem of chattering. The proposed adaptive controller is globally asymptotically stable and guarantees zero steady state error for joint positions. The estimated friction coefficients can also approach the actual coefficients asymptotically. A simulation example is provided to demonstrate the performance of the proposed algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.668-676
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• 2008

In this paper, we considered the $H_{\infty}$ tracking control for time-delayed linear systems with saturating actuators. The considered time delay is a time varying one having bounded magnitude and rate, and the considered tracking reference is a general one only known its bounds of magnitude and rate. First, we have converted the $H_{\infty}$ tracking control problem into an equivalent $H_{\infty}$ disturbance attenuation problem using two steps of transformations. Next, based on a new Lyapunov-Krasovskii functional, we have derived the result in the form of LMI with two non-convex parameters. Finally, by numerical examples, we have shown the usefulness and effectiveness of our result.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.251-266
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• 2004

We consider a controlled nonlinear mechanical system described by the Lagrange equations. We determine the control forces $Q_1$ and the restrictions for the perturbations $Q_2$ acting on the mechanical system which allow to guarantee the asymptotic stability of the program motion of the system. We solve the problem of stabilization by the direct Lyapunov's method and the method of limiting functions and systems. In this case we can use the Lyapunov's functions having nonpositive derivatives. The following examples are considered: stabilization of program motions of mathematical pendulum with moving point of suspension and stabilization of program motions of rigid body with fixed point.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.155.5-155
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• 2001

The robust predictive control law which use the bound estimation is proposed for uncertain robot manipulators. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about model, it´s an important tend to design a robust control law that will guarantee the desired performance of the manipulator under uncertain elements. In the preceeding work, the robust predictive control law was proposed. In this work, we propose a class of robust predictive control of manipulators with the bound estimate technique and fe stability based on Lyapunov function is presented.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1014-1021
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• 2008

This paper proposes an intelligent sliding mode control method for robotic systems with the unknown bound of model uncertainties. In our control structure, the unknown bound of model uncertainties is used as the gain of the sliding controller. Then, we employ the function approximation technique to estimate the unknown nonlinear function including the width of boundary layer and the uncertainty bound of robotic systems. The adaptation laws for all parameters of the self-recurrent wavelet neural network and those for the reconstruction error compensator are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with model uncertainties and external disturbances. Accordingly, the proposed method can not only overcome the chattering phenomenon in the control effort but also have the robustness regardless of model uncertainties and external disturbances. Finally, simulation results for the five-link biped robot are included to illustrate the effectiveness of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.140-146
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• 2016

This paper proposes a control method of the Segway with unknown control coefficient and input saturation. To design a simple controller for the Segway with the model uncertainty, the prescribed performance function is used. Furthermore, an auxiliary variable is introduced to deal with unknown time-varying control coefficient and input saturation problem. Due to the auxiliary variable, function approximators are not used in this paper although all model uncertainties are unknown. Thus, the controller can be simple. From the Lyapunov stability theory, it is proved that all errors of the proposed control system remain within the prescribed performance bounds. Finally, the simulation results are presented to demonstrate the performance of the proposed scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.3
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• pp.266-272
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• 2004

In this paper, an observer-based adaptive controller is proposed to control the longitudinal motion of vehicles. The standard gradient method will be used to estimate the vehicle parameters such as mass, time constant, etc. The nonlinear model between the driving force and the vehicle acceleration will be chosen to design the state observer for the vehicle velocity and acceleration. It will be shown that the proposed observer is exponentially stable, and that the adaptive controller proposed in this paper is stable by the Lyapunov function candidate. It will be proved that the errors of the relative distance, velocity and acceleration converge to zero asymptotically fast, and that the overall system is also asymptotically stable. The simulation results are presented to investigate the effectiveness of the proposed method.