• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.356-361
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• 2006

This paper deals with a fault detection system design for nonlinear systems with uncertain time varying parameters modelled as a T-S fuzzy system. A coprime factorization for T-S fuzzy systems is defined and a residual generator is designed using a left coprime factor. A fault detection criteria derived from the residual generator is also suggested. In order to demonstrate the efficacy of the suggested method, the fault detection method is applied to an inverted pendulum system and computer simulations are performed.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.34.4-34
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• 2001

It is well known that one can easily design a high-gain adaptive output feedback control for a class of nonlinear systems which satisfy a certain condition so called output feedback exponential passivity (OFEP). The designed high gain adaptive controller has simple structure and high robustness with regard to bounded disterbances and unknown order of the controlled system. However, from the viewpoint of practical application, it is important to consider a robust control scheme for controlled systems for which some of the assumptions of output feedback stabilization are not valid. In this paper, we deal with a design problem of the robust high-gain adaptive output feedback control for the OFEP nonlinear systems with uncertain nonlinearities and/or disturbances.

• Architectural research
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• v.24 no.3
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• pp.75-84
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• 2022

Scads of earthquake-resistant systems are being invented around the globe to ensure structural resistance against the lateral forces induced by earthquake loadings considering structural safety, efficiency, and economic aspects. Shear wall and Bracing systems are proved to be two of the most viable solutions for seismic strengthening of structures. In the present study, three numerical models of a G+10 storied building are developed in commercial building analysis software considering shear wall and bracing systems for earthquake resistance. Material nonlinearity is introduced by using plastic hinges. Analyses are performed utilizing two dynamic methods: Response Spectrum analysis and nonlinear Time-history analysis using Kobe and Loma Prieta earthquake data and results are compared to observe the nonlinear behavior of structures. The outcomes exposed that a significant increase in the seismic responses occurs due to the nonlinearity in the building systems. It was also found that building with shear wall exhibits maximum resistance and minimum nonlinearity when subjected to dynamic loadings.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.172-177
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• 2006

In the networked control system (NCS), the uncertain network-induced delay and nonlinear controlled object are the main problems, because they can degrade the performance of the control system and even destabilize it. In this paper, a class of uncertain and nonlinear networked control systems is discussed and its sufficient condition for the robust asymptotic stability is presented. Further, the maximum network-induced delay that insures the system stability is obtained. The Lyapunov and LMI theorems are employed to investigate the problem. The result of an illustrative example shows that the robust stability analysis is sufficient.

• Journal of IKEEE
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• v.22 no.1
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• pp.121-126
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• 2018

This paper addresses the consensus problem for nonlinear multi-agent systems using observer based controller. In order to solve this problem, the high gain approach is combined with the previous low gain controller. Also, it is shown that the proposed observer based controller can always guarantee the consensus of nonlinear systems with lower triangular nonlinearity.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.4
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• pp.198-204
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• 2003

In this paper, we presented a new algebraic iterative algorithm for the optimal control of the nonlinear systems. The algorithm is based on two steps. The first step transforms nonlinear optimal control problem into a sequence of linear optimal control problem using the quasilinearization method. In the second step, TPBCP(two point boundary condition problem) is solved by algebraic equations instead of differential equations using the new integral operational matrix of BPF(block pulse functions). The proposed algorithm is simple and efficient in computation for the optimal control of nonlinear systems and is less error value than that by the conventional matrix. In computer simulation, the algorithm was verified through the optimal control design of synchronous machine connected to an infinite bus.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.714-719
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• 1994

This paper proposes a method of suboptimal control for DC servomotor using a neural network. First we consider a nonlinear observer which is constructed by using an approximated linear dynamics of the nonlinear system and a, neural network. The reccurent neural network is used for the learning of the dynamical system. Next we consider the nonlinear observer. Then, we apply the observer output to nonlinear optimal regulator and confirm the effectiveness by applying the method to the inverse pendulum system.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.262-269
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• 2005

In this paper, a nonlinear robust control approach is applied to design a controller for the Static Synchronous Compensator (STATCOM). A robust control dynamic model of STATCOM in a one-machine, infinite-bus system is established with consideration of the torque disturbance acting on the rotating shaft of the generator set and the disturbance to the output voltage of STATCOM. A novel recursive approach is utilized to construct the energy storage function of the system such that the solution to the disturbance attenuation control problem is acquired, which avoids the difficulty involved in solving the Hamilton-Jacobi-Issacs (HJI) inequality. Sequentially, the nonlinear disturbance attenuation control strategy of STATCOM is obtained. Simulation results demonstrate that STATCOM with the proposed controller can more effectively improve the voltage stability, damp the oscillation, and enhance the transient stability of power systems compared to the conventional PI+PSS controller.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.920-929
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• 2005

This paper presents controller design method for nonlinear radar gimbal system with parameter uncertainty and time delay. In order to consider nonlinearity of gimbal bearing frictional torque, we firstly represent fuzzy model for the nonlinear gimbal system, which is achieved by fuzzy combination of linear models through nonlinear fuzzy membership functions. And secondly we propose a delay dependent fuzzy $H_\infty$ controller design method for the delayed fuzzy model with parameter uncertainty and design radar gimbal controller. The designed controller stabilize gimbal system and guarantee $H_\infty$ performance. A computer simulation is given to illustrate stabilized control performances of the designed controller.