• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5379-5388
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• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.1
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• pp.110-119
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• 1997

Four wheel steering(4WS) systems which can control the lateral and yaw motions of vehicles by steering front and rear wheels simultaneously, have been regarded as effective for improving the stability and handing performance of vehicles. However, since the 4WS systems depend only on the lateral force of tire, they have some limitation due to the nonlinear characteristics of tire related with the saturation phenomenon of lateral force to the slip angle of tire in a near-limit-performance maneuvering range. In this study, in other to evaluate the effect of nonlinear characteristics of tire on the dynamic performance of vehicles, a new concept for driving the cornering stiffness of nonlinear tire by using the "Magic Formula" tire model is proposed. In addition, the nonlinear 4WS vehicle model is constructed based on the proposed cornering stiffness of nonlinear tire. It is noted from simulation that the nonlinear characteristics of tire affect greatly on the 4WS vehicle performance.rformance.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.104-109
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• 2000

In this paper, the output feedback stabilizing problem is solved using any given state feedback control law. Compared to the linear systems is not so straightforward for nonlinear systems. We briefly explain the intrinsic obstructions for this problem and provide new output feedback scheme which achieves the semi-global stabilization with the high-gain state observer. THe overall uniform observability of the plant. Therefore, the result can be regarded as an extension of the separation principle for linear systems in some aspect.

• Journal of the Korean Mathematical Society
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• v.53 no.5
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• pp.1115-1131
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• 2016

In this paper we develop useful relations which estimate the difference between the solutions of nonlinear impulsive differential systems with different initial values. Then we obtain the converse h-stability theorem of Massera's type for the nonlinear impulsive systems by employing the $t_{\infty}$-similarity of the associated impulsive variational systems and relations.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.339-345
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• 2006

An analysis methodology of Decentralized Dynamic Surface Control (DDSC) for the large-scale interconnected nonlinear systems is presented in this paper. While the centralized DSC approach proposed in [14] has a difficulty to check the quadratic stability for the large-scale systems numerically due to dramatic increases of the order of overall augmented error dynamics, DDSC is relatively easy to check the quadratic stability since lower order error dynamics of individual subsystems are used. Then, a systematic procedure for designing DDSC will be developed. Furthermore, after a quadratic function containing a reachable set is defined, it will be calculated numerically to indicate the performance of DDSC in the framework of convex optimization. Finally an illustrative example will be given for showing the advantages of DDSC compared with other decentralized nonlinear control techniques.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.146-154
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• 2006

In this paper, we propose direct and indirect adaptive fuzzy sliding mode control approaches for a class of nonaffine nonlinear systems. In the direct case, we use the implicit function theory to prove the existence of an ideal implicit feedback linearization controller, and hence approximate it to attain the desired performances. In the indirect case, we exploit the linear structure of a Takagi-Sugeno fuzzy system with constant conclusion to establish an affine-in-control model, and therefore design an indirect adaptive fuzzy controller. In both cases, the adaptation laws of the adjustable parameters are deduced from the stability analysis, in the sense of Lyapunov, to get a more accurate approximation level. In addition to their robustness, the design of the proposed approaches does not require the upper bounds of both external disturbances and approximation errors. To show the efficiency of the proposed controllers, a simulation example is presented.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.47-50
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• 2003

For large-scale systems which are composed of interconnections of many lower-dimensional subsystems, decentralized control is preferable since it can alleviate the computational burden, avoid communication between different subsystems, and make the control more feasible and simpler. A power system is such a large-scale system where generators are interconnected through transmission lines. Decentralized control is therefore considered for power systems. In this paper, a robust decentralized excitation control scheme for interactions is proposed to enhance the transient stability of multimachine power systems. First we employ a DFL(Direct Feedback Linearization) compensator to rancel most of the nonlinearities; however, the resulting model still contains nonlinear interconnections. Therefore, we design a robust controller in order to deal with Interconnection terms. In this procedure, an upper bound of interconnection terms is estimated by an estimator. The resulting adaptive scheme guarantees the uniform ultimate boundedness of the closed-loop dynamic systems in the presence of the uncertainties.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.187-191
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• 2007

We analyze the stability property of a class of nonlinear time-delay systems. We show that the state variable is bounded both below and above, and the lower and upper bounds of the state are obtained in terms of a system parameter by using the comparison lemma. We establish a time-delay independent sufficient condition for the global asymptotic stability by employing a Lyapunov-Krasovskii functional obtained from a change of the state variable. The simulation results illustrate the validity of the sufficient condition for the global asymptotic stability.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.50-55
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• 1998

The GMDH(Group Method of Data Handling) is a useful data analysis technique for identification of nonlinear complex systems. Therefore, in this paper the application method of GMDH algorithm for modeling nonlinear dynamic systems is proposed. The identification of dynamic systems by using GMDH consists of applying a set of input/output data and computing the necessary coefficient set dynamically. Also, in this paper, by reducing sequentially the criterion which can adopt or reject the data, a method to prevent excessive computation that is a disadvantage of GMDH is proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.631-634
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• 2014

We propose a measurement state feedback controller for a class of nonlinear systems that have uncertain nonlinearity and sensor noise. The new design method based on the matrix inequality approach solves the measurement feedback control problem of a class of nonlinear systems. As a result, the proposed methods using a matrix inequality approach has the flexibility to apply the controller. In addition, the sensor noise can be attenuated for more generalized systems containing uncertain nonlinearities.