• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.528-530
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• 1999

This paper addresses the analysis and design of fuzzy control systems for a class of complex single input single output nonlinear systems. Firstly, the nonlinear system is represented by well-known Takagai-Sugeno (TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller usually is composed of two processes. One is to determine static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative of the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. One simulation example is given to show the effectiveness and feasibility of the proposed fuzzy controller design method.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.62-67
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• 1999

The neural network is a static network that consists of a number of layer: input layer, output layer and one or more hidden layer connected in a feed forward way. The popularity of neural network appear to be its ability of learning and approximation capability. The Elman Neural Network proposed the J. Elman, is a type of recurrent network. Is has the feedback links from hidden layer to context layer. So Elman Neural Network is the better performance than the neural network. In this paper. we propose the Modified Elman Neural Network. The structure of a MENN is based on the basic ENN. The recurrency of the network is due to the feedback links from the output layer and the hidden layer to the context layer. In order to certify the usefulness of the proposed method, the MENN apply to the X-Y cartesian tracking system. Simulation shows that the proposed MENN method is better performance than the multi layer neural network and ENN.

• Journal of the Korea Society of Computer and Information
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• v.4 no.3
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• pp.67-72
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• 1999

The neural network is a static network that consists of a number of layer: input layer, output layer and one or more hidden layer connected in a feed forward way. The popularity of neural network appear to be its ability of learning and approximation capability. The Elman Neural Network proposed the J. Elman. is a type of recurrent network. Is has the feedback links from hidden layer to context layer. So Elman Neural Network is the better performance than the neural network. In this paper. we propose the Modified Elman Neural Network. The structure of a MENN is based on the basic ENN. The recurrency of the network is due to the feedback links from the output layer and the hidden layer to the context layer. In order to certify the usefulness or the proposed method. the MENN apply to the multi target system. Simulation shows that the proposed MENN method is better performance than the multi layer neural network and ENN.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.750-754
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• 2005

This paper deals with the design problem of multivariable PID controllers guaranteeing the closed-loop system stability and a prescribed $H_\infty$ norm bound constraint. We reduce the problem to the static output feedback stabilization problem. We derive a necessary and sufficient condition f3r the existence of PID controllers and we give an explicit formula of PID controllers. We also give an existence condition of PID controllers guaranteeing a prescribed decay rate. Finally, we give an LMI-based design algorithm, together with a numerical design example.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2723-2725
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• 2005

In this paper, a robust $H{\infty}$ stabilization problem to a uncertain discrete-time nonlinear systems with time-delay via fuzzy static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-delayed state. Then parallel distributed compensation technique is used for designing of the robust fuzzy controller. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust $H{\infty}$ controllers are given in terms of linear matrix inequalities via similarity transform and congruence transform technique.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.701-705
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• 2014

This article presents a comparison among several yaw and roll motion controllers for vehicle rollover prevention. In the previous research, yaw and roll motion controllers can be independently designed for rollover prevention. Following this idea, several yaw and roll motion controllers are designed and compared in terms of rollover prevention. For the yaw motion control, PID, LQR, SMC (Sliding Mode Control) and TDC (Time-Delay Control) are adopted. For the roll motion control, LQR, LQ SOF (Static Output Feedback) control, PID, and SMC are adopted. To compare the performance of each controller, simulation is performed on a vehicle simulation package, CarSim$^{(R)}$. From simulation, TDC and LQ SOF are the best for yaw and roll motion control, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.160-167
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• 2001

This paper presents control and evaluation of a new haptic device with a 6-DOF parallel mechanism for interfacing with virtual reality. This haptic device has low inertial, high bandwidth compactness, and high output force capability mainly due to of base-fixed motors. It has also wider orientation workspace mainly due to a RRR type spherical joint. A control method is presented with gravity compensation and with force feedback by an F/T sensor to compensate for the effects of unmodeled dynamics such as friction and inertia. Also, dynamic performance has been evaluated by experiments. for force characteristics such as maximum applicable force, static-friction force, minimum controllable force, and force bandwidth Virtual wall simulation with the developed haptic device has been demonstrated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.122-125
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• 2002

This paper proposes a stability condition in switched system and then, introduce design method of fuzzy-model-based controller which guarantees the stability. Takagi-Sugeno(75) fuzzy model is employed to design a switching-type fuzzy-model-based ,controller. Furthermore, it is proposed that the design method stabilizing continuous and discrete-time 75 fuzzy model respectively. Each controller in each subspace stabilize the subsystem respectively. In order to guarantee the stability of the global system, it is required to guarantee the stability condition in boundaries with subsystems. The condition which guarantees the stability in boundaries is presented in this paper. Inverted Pendulum system is employed to execute computer simulations. In this computer simulation, the performance of the proposed controller is verified by the control result.

• 전기의세계
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• v.13 no.2
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• pp.5-10
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• 1964

Some nonlinearities in feedback control systems, such as relay servo, Coulomb friction, saturating amplifier of backlash in gears cause some undesirable effects. These may be static errors, limit cycles or jump phenomena. So, linearizing method of these nonlinearities using dither signals was first suggested by Loeb. He pointed out that the addition of high frequency signal to either the input or the output of a nonlinear system would make the nonlinear performance approximate the performance of linear systems. He used high-frequency sinusoidal wave as dither signal. But, in this thesis, general method of analysis is suggested for nonlinear control systmes using various dither signals, such as noise signal of Gaussian amplitude distribution, sinusoidal dither signal and sawtooth dither signal. Also, the advantage and disadvantage of these dither signals are compared. Throughout the analysis statistical method is adopted and lastly analog computer is used for the experiment of various nonlinear systems using dither signals.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2120-2122
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• 2001

This paper describes a PID controller for an attraction type magnetic levitation system considering $H^{\infty}$ performance. PID controllers are a kind of fixed structure reduced order controllers. Using change of variables a reduced order control problem can be recast into a static output feedback control problem and can be solved efficiently by LMI(Linear Matrix Inequality) method. In this paper, cone complementarity method is adopted and the simulation shows good results.