• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.11
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• pp.127-139
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• 1996

In this paper we propose a new controller design method using hybrid fuzzy-neural netowrk and neural network identification in order ot control systems which are more and more getting nonlinearity. Proposed method performs, for a nonlinear plant with unknown functions, hybird identification using a fuzzy-neural network and a neural network, and then a stable nonlinear controller is designed with those identified informations. To identify a nonlinear function, which is directly related to input signals, we can use a neural network which is satisfied with the proposed stable condition. To identify a nonlinear function, which is not directly related to input signals, we can use a fuzzy-neural network which has excellent identification characteristics. In order to verify excellent control performances of the proposed method, we compare the porposed control method with a conventional neural network control method through simulations and experiments with one link manipulator.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.623-629
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• 2010

In this paper, a new robust variable structure controller based on a nonlinear integral type sliding surface is presented for the control of uncertain systems with mismatched uncertainties and disturbance. A nonlinear integral type sliding surface is suggested for removing the reaching phase. After its ideal sliding dynamics is obtained, the two design methods are presented. A corresponding control input is proposed to satisfy the closed loop stability in the sense of Lyapunov and the existence condition of the sliding mode on the nonlinear integral type sliding surface, which will be investigated in Theorem 1. Through a design example and simulation study, the usefulness of the proposed controller is verified.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.81-84
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• 1996

We propose the robust nonlinear controller design methodology, the $H_{\infty}$ constrained quasi - linear quadratic Gaussian control (QLQG/ $H_{\infty}$), for the statistically-linearized multivariable system with hard nonlinearties such as Coulomb friction, deadzone, etc. The $H_{\infty}$ performance constraint is involved in the optimization process by replacing the covariance Lyapunov equation with the Riccati equation whose solution leads to an upper bound of the QLQG performance. Because of the system's nonlinearity, however, one equation among three Riccati equations contain the nonlinear correction terms that are very difficult to solve numerically. To treat this problem, we use simple algebraic techniques. With some analytic transformation for Riccati equations, the nonlinear correction terms can be so eliminated that the set of a linear controller to the different operating points are designed. Synthesizing these via inverse random input describing function (IRIDF) technique, the final nonlinear controller can be designed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1500-1503
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• 1996

This paper combines the disturbance accommodating control(DAC) and nonlinear model inversion control for a skid-to-turn(STT) missile. The missile autopilot may be designed to be robust with respect to a variety of uncertainties. We proposes the two step control design method. Nonlinear model inversion control is used as the main design method. Due to the model uncertainties and external disturbances, the exact nonlinear model inversion can not be achieved. DAC is designed to detect, to identify, and to compensate these uncertainties. DAC's disturbance observer is linear. Thus it is easy to implement. It does not cause the convergence problem due to coexistence between the modeling uncertainties and external disturbances. 6 DOF simulation results show that the proposed method may improve the missile tracking performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.253-257
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• 2013

This paper proposes the robust observer design for nonlinear systems with delayed output and external disturbance. It is shown that by considering a nonlinear term of error dynamics as an additional state variable, the nonlinear error dynamics with time delay can be transformed into the linear one with time delay. Sufficient conditions for existence of a robust observer are characterized by linear matrix inequalities. Finally, an illustrative example is given in order to show the effectiveness of our design method.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.76.3-76
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• 2002

The purpose of this paper is to present a new nonlinear feedback control called AACC (Augmented automatic choosing control) for nonlinear systems. Generally, it is easy to design the optimal control laws for linear systems, but it is not so for nonlinear systems, though they have been studied for many years. One of most popular and practical nonlinear control laws is synthesized by applying a linearization method by Taylor expansion truncated at the first order and the linear optimal control method. This is only effective in a small region around the steady state point or in almost linear systems. Controllers based on a change of coordinates in differential geometry are effective in wider...

• Earthquakes and Structures
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• v.7 no.6
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• pp.1025-1044
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• 2014

In this paper, a systematic technique is proposed for the optimal placement and design of nonlinear dampers for building structures. The concept of Output Frequency Response Function (OFRF) is applied to analytically represent the output frequency response of a building frame where nonlinear viscous dampers are fitted for suppression of vibration during earthquakes. An effective algorithm is derived using the analytical representation to optimally determine the locations and parameters of the nonlinear dampers. Various numerical examples are provided to verify the effectiveness of the optimal designs. A comparison of the vibration suppression performance with that of the frame structure under a random or uniform damping allocation is also made to demonstrate the advantages of the new designs over traditional solutions.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.42-48
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• 2008

This paper presents an observer design method for a special class of multi input multi output(MIMO) nonlinear systems. First, we characterize the class of MIMO nonlinear systems with a block triangular structure. Also, the observability matrices for SISO nonlinear systems are extended to MIMO systems. By using the generalized observability matrices, it is shown that under the boundedness conditions of system state and input, the proposed observer guarantees the local exponential stability of error dynamics. Finally, its application to induction motor is given to verify the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.314-321
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• 2009

In this paper, the robust nonlinear observer will be developed for PEM fuel cell system. Nonlinear model of PEM fuel cell system is introduced to study the design problems of observer. Sliding mode observer is designed to estimate the cathode and anode pressures of PEMFC system. And a nonlinear state observer is also designed to estimate the other states such as supply manifold pressure, Oxygen pressure, Hydrogen pressure, return manifold pressure, etc. The validity of the proposed observer will be verified by using Lyapunov's stability analysis method.

• IE interfaces
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• v.16 no.spc
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• pp.39-44
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• 2003

As one of many design variables, the role of dimension tolerances is to restrict the amount of size variation in a manufactured feature while ensuring functionality. In this study, a nonlinear integer model has been modeled to allocate the optimal tolerance to each individual feature at a minimum manufacturing cost. While a normal distribution determines statistically worst tolerances with its symmetrical property in many previous tolerance allocation studies, a asymmetrical distribution is more realistic because its mean is not always coincident with a process center. A nonlinear integer model is modeled to allocate the optimal tolerance to a feature based on a beta distribution at a minimum total cost. The total cost as a function of tolerances is defined by machining cost and quality loss. After the convexity of manufacturing cost is checked by the Hessian matrix, the model is solved by the Complex Method. Finally, a numerical example is presented demonstrating successful model implementation for a nonlinear design case.