• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.873-876
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• 1993

A fuzzy controller designed by mini-max-gravity(MMG) method is essentially nonlinear with respect to the controller's input and output relationship, and stability analysis is thus needed to construct a stable control system. This paper deals with a design method of a position-type MMG fuzzy controller stable in a sense of Lyapunov when considered is a single-input-single-output linear, stable plant. We first introduce a method to construct a Laypunov function by using an eigen-value of A matrix of the linear, stable plant dynamics and then we derive an asymtotic stability condition in terms of scale factors for fuzzy state variables and controller gain. The stability condition is found reasonably practical through comparing the theoretical stability region with that obtained from simulations.

• 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.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.877-885
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• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.1
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• pp.39-63
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• 2019

In this paper, we study the effect of Cytotoxic T Lymphocyte (CTL) and antibody immune responses on the virus dynamics with both virus-to-cell and cell-to-cell transmissions. The infection rate is given by Holling type-II. We first show that the model is biologically acceptable by showing that the solutions of the model are nonnegative and bounded. We find the equilibria of the model and investigate their global stability analysis. We derive five threshold parameters which fully determine the existence and stability of the five equilibria of the model. The global stability of all equilibria of the model is proven using Lyapunov method and applying LaSalle's invariance principle. To support our theoretical results we have performed some numerical simulations for the model. The results show the CTL and antibody immune response can control the disease progression.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.502-504
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• 2010

We propose novel transition rule of cellular automata for image enhancement and sharpening algorithm using it. Transition rule present sequential and parallel behavior. it also satisfy Lyapunov function. This image sharpening was developed and experimented by using a dynamic feature of convergence to fixed points. We can obtain efficiently sharpened image by performing arithmetic operation at the gradual parts of difference of brightness without image information.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.73-81
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• 1997

An new class of robust position/force hybrid control law is proposed for uncertain robot manipulators. The uncertainty is nonlinear and (plssibly fast) time-varying. Therefore, the uncertain factors such as imper- fect modeling, friction, payload change, and external disturbance are all addressed. Based on the possible bound of the uncertainty, the controller is constructed and the stability study based on Lyapunov function is presented. To show that the proposed control laws are indeed applicable, the theoretical result is applied to a SCARA-type robot manipulator and simulation result is presented.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1732-1733
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• 2011

This paper presents observer-based controller design for interval type-2 fuzzy system with staircase membership approximation. In type-2 fuzzy case, membership function is itself fuzzy set itself. Thus, type-2 fuzzy system can deal with parametric uncertainties of nonlinear system by capturing the uncertainties in membership function. Likewise, stabilization condition of type-2 fuzzy system is derived from quadratic Lyapunov function, and it goes to linear matrix inequality. Furthermore, in this paper, to relax the conservativeness of stabilization condition, staircase membership function approximating method is applied. Observer-based control method is adopted to control system which has some unmeasurable states. To prove suitability of our proposed method, numerical example is presented.

• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1916-1922
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• 2004

A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.