• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.302-306
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• 2011

This paper presents Takagi-Sugeno (T-S) fuzzy-model-based controller for depth control of autonomous underwater vehicles(AUVs). Through sector nonlinearity methodology, The nonlinear AUV is represented by T-S fuzzy model. By using the Lyapunov function, the design condition of controller is derived to guarantee the performance of depth control in the format of linear matrix inequality (LMI). An example is provided to illustrate the effectiveness of the proposed methodology.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1648-1654
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• 2007

In this paper, we consider the design of $H_\infty$ high-gain state feedback control for time-delayed linear systems with limited actuator capacities. The high-gain control means that the control permits the predetermined degree of saturation. Based on new Lyapunov-Krasovskii functional, we derive a result in the form of matrix inequalities. The matrix inequalities are consisted of LMIs those confirm the positive definiteness of Lyapunov- Krasovskii functional, satisfaction of predetermined degree of saturation, reachable set and $L_2$ gain constraint. The result is dependent on the bound of time-delay and its rate, predetermined degree of saturation, actuator capacity, and the allowed size of disturbances. Finally, we give a numerical example to show the effectiveness and usefulness of our result.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.319-328
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• 2010

This paper proposes a robust adaptive fuzzy tracking control scheme for a nonholonomic mobile robot with external disturbances as well as parameter uncertainties in the robot kinematics, the robot dynamics, and the actuator dynamics. In modeling a mobile robot, the actuator dynamics is integrated with the robot kinematics and dynamics so that the actuator input voltages are the control inputs. The presented controller is designed based on a FBFN (Fuzzy Basis Function Network) to approximate an unknown nonlinear dynamic function with the uncertainties, and a robust adaptive input to overcome the uncertainties. When the controller is designed, the different parameters for two actuator models in the actuator dynamics are taken into account. The proposed control scheme does not require the kinematic and dynamic parameters of the robot and actuators accurately. It can also alleviate the input chattering and overcome the unknown friction force. The stability of the closed-loop control system including the kinematic control system is guaranteed by using the Lyapunov stability theory and the presented adaptive laws. The validity and robustness of the proposed control scheme are shown through a computer simulation.

• Journal of IKEEE
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• v.13 no.1
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• pp.11-18
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• 2009

In this paper, the stability of second order uncertain systems with regulation of PID type controllers is analyzed by using Lyapunov second method for the first time in the time domain. The property of the stability of PID regulation servo systems is revealed in sense of Lyapunov, i.e., bounded stability due to the disturbances and uncertainties. By means of the results of this stability analysis, the maximum norm bound of the error from the output without variation of the uncertainties and disturbances is determined as a function of the gains of the PID control, which make it enable to analyze the effect resulted from the variations of the disturbances and uncertainties using this norm bound for given PID gains. Using the relationship of the error from the output without variation of the uncertainties and disturbances and the PID gain with maximum bounds of the disturbances and uncertainties, the robust gain design rule is suggested so that the error from the output without the variation of the disturbances and uncertainties can be guaranteed by the prescribed specifications as the advantages of this study. The usefulness of the proposed algorithm is verified through an illustrative example.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.159-163
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• 2008

In this paper, a simplified type of adaptive controller using Nussbaum gain for the control of the spacecrapt with elastic appendages is suggested. This method doesn't need the information of the high frequency components in transfer function. While the pitch angle tracks the desired value by this method, the elastic modes are also stabilized. Only pitch angle and the pitch rate are used for the design of the output feedback controller. Especially all system parameters and the high frequency gain are assumed to be unknown. For design simplicity, a controller is designed by using only the linear part, and it's shown to satisfy the nonlinear system by the simulation with basic explanations. By using the Lyapunov function, the stability of the suggested algorithm is demonstrated, and also the effectiveness of the suggested algorithm is verified by showing the computer simulation results.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.954-959
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• 2008

This paper is concerned with the reliable $H_{\infty}$ controller design problem for uncertain linear systems against actuator failures. In the design, the $H_{\infty}$ performance of the closed-loop system is optimized during normal operation(without failures) while the system satisfies a prescribed $H_{\infty}$ performance level in the case of actuator failures. Single and parameter-dependent Lyapunov function approaches are applied in designing suboptimal reliable $H_{\infty}$ controllers. Simulation studies are presented to demonstrate the effectiveness of the proposed design procedures.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.394-396
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• 2005

In this paper, we propose an adaptive tracking control method of a mobile manipulator for contour following with a kinematic model to have several unknown dimension parameters. Moreover, we will use the decentralized control method to design two independent controllers for two subsystems. The proposed controllers in this paper are based on the Lyapunov function in order to guarantee the stability of whole system for contour following task. The updated laws are also designed to estimated the unknown dimension parameters. Finally, the simulation results are presented to show the validity of the proposed controllers in this paper.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.581-588
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• 2007

In this paper, we propose a delayed feedback guaranteed cost controller design method for linear time-delay systems with norm-bounded parameter uncertainties and nonlinear perturbations. A quadratic cost function is considered as the performance measure for the given system. Based on the Lyapunov method, an LMI optimization problem is formulated to design a controller such that the closed-loop cost function value is not more than a specified upper bound for all admissible system uncertainties and nonlinear perturbations. Numerical example show the effectiveness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.29-36
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• 1998

In this paper we propose a control law using a Lyapunov-like function that makes stable the systems which have mis-matched uncertainties. The existing control law using a Lyapunov-like function, which gives global saymptotic stability, is designed under the assumption of a targetsystem to be stable locally. But we broaden here the class of target systems by designing the control law which can give uniform ultimate boundedness to even the systems not satisfing the locally asymptotic stability. And we also show that the control law giving global asymptotic stability can be designed more systematically through using the uniform ultimate boundedness.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.449-451
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• 2003

In this paper, the stability problem for singular bilinear system is investigated. We present state feedback control laws for two classes of singular bilinear plants. Asymptotic stability of the closed-loop systems is derived by employing singular Lyapunov's direct method. The primary advantage of our approach lies in its simplicity. In order to verify effectiveness of the results, two numerical examples are given.