• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.187-190
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• 2003

In this paper, we address the robust adaptive backstepping controller using fuzzy neural network (FHIN) for a class of uncertain output feedback nonlinear systems with disturbance. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The state estimation is solved using K-fillers. All unknown nonlinear functions are approximated by FNN. The FNN weight adaptation rule is derived from Lyapunov stability analysis and guarantees that the adapted weight error and tracking error are bounded. The compensated controller is designed to compensate the FNN approximation error and external disturbance. Finally, simulation results show that the proposed controller can achieve favorable tracking performance and robustness with regard to unknown function and external disturbance.

• 시큐리티연구
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• 제8호
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• pp.309-336
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• 2004

Approximately equivalent to character disorder or character neuroses or behavioral reaction. For a discussion of the term as used currently, in the 1968 revision of psychiatric nomenclature(DSM-II). In DSM-I(1952 nomenclature), this term referred to those cases in which the personality, in its struggle for adjustment to internal and external stresses, utilized primarily a pattern of action or behavior rather than symptoms in the mental, somatic or emotional spheres. There is minimal subjective anxiety and little or no sense of distress. As thus defined, there are three main groups of personality disorder, personality pattern disturbance, personality trait disturbance and sociopathic, personality disturbance. Morton Prince asks whether a subconscious process can perform the same function as are ordinarily performed by conscious intelligence that is to say memory, perception, reasoning, imagination, volition, affectivity, etc? He cites clinical material at great length, concluding that the quality of the functions performed they frequently exhibit, that which is characteristic of intelligence.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.156-160
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• 1993

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an inproved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing force coming from the difference between th actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

• Transactions on Control, Automation and Systems Engineering
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• 제2권3호
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• pp.189-195
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• 2000

The mathematical solutions of the stability convergence are important problems in system control. In this paper such problems are analyzed and resolved for system control using multilayer neural networks. We describe an algorithm to control an unknown nonlinear system with a disturbance, using a multilayer neural network. We include a disturbance among the modeling error, and the weight update rules of multilayer neural network are derived to satisfy Lyapunov stability. The overall control system is based upon the feedback linearization method. The weights of the neural network used to approximate a nonlinear function are updated by rules derived in this paper . The proposed control algorithm is verified through computer simulation. That is as the weights of neural network are updated at every sampling time, we show that the output error become finite within a relatively short time.

• 전기학회논문지
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• 제58권8호
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• pp.1595-1604
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• 2009

An Optical disk driver is used in many electronic products besides the computers. In particular, the demands are recently increased as an optical disk player/recorder in the mobile products such as camcorder, portable player or in the home theater appliances, etc. However, the more the mobility is emphasized, the more the optical disk player is exposed to the disturbance inputs. For reducing the possibility of malfunction of the optical disk, we propose a nonlinear controller using the disturbance detecting algorithm based on the Kalman filter. Actual experiments were executed to verify the performance of the proposed method. The proposed method controls the tracking error signal within ${\pm}0.1{\mu}m$.

• 전기학회논문지
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• 제57권9호
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• pp.1612-1617
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• 2008

Since most disturbance observer (DOB) approaches have been limited to minimum-phase systems (or systems having no zero dynamics), we propose a new DOB structure that can be applied to non-minimum phase systems. The new structure features an additional system, which is called as V-filter, whose role is to yield a minimum phase system when connected with the plant in parallel. In order to design the V-filter systematically we first consider a class of linear systems that can be stabilized via PID controller. By inverting the controller's transfer function, we can simply construct the filter. A convenient way of designing V-filter is presented by using an iterative linear matrix inequality (LMI) algorithm. With an illustrative example the simulation result shows that substantial improvement in the performance has been achieved compared with the control system without the DOB.

• 제어로봇시스템학회논문지
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• 제22권8호
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• pp.650-655
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• 2016

In this paper, a novel RLS-based DOB (Recursive Least Squares Disturbance Observer) scheme is proposed to improve the performance of DOB for nominal model identification. A nominal model can be generally assumed to be a second order system in the form of a proper transfer function of an ARMA (Autoregressive Moving Average) model. The RLS algorithm for the model identification is proposed in association with DOB. Experimental studies of the balancing control of a one-wheel robot are conducted to demonstrate the feasibility of the proposed method. The performances between the conventional DOB scheme and the proposed scheme are compared.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.956-958
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• 1996

The moving vehicle with disturbances has the 6 dof motion in the pitching, yawing and rolling directions of two independent axes. The control system in such a moving vehicle has to perform disturbance rejection well. The paper presents PID controller with disturbance rejection function, low sensitivity filter and notch filter for the bending frequency rejection. The performance of a designed system has been certified by the simulation and experiment results.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2003년도 춘계 학술발표회논문집
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• pp.140-147
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• 2003

There are many problems in the prediction of soil dynamic behaviors because undrained excess pore water pressure builds up and then the strain softening behavior is occurred simultaneously. A few analytical methods based on the dynamic constitutive model have been proposed but the model hardly predict the excess pore water pressure directly. In this study, the verification on the disturbed state concept (DSC) model, proposed by Dr, Desai was performed. Some laboratory tests such as conventional triaxial tests and cyclic triaxial tests were carried out to determine DSC Parameters and then disturbance values are determined by the proposed equation. Through this verification, it is proved that the disturbed state concept can express reliably the soil dynamic characteristics such as excess pore water pressure and strain softening behavior. It is also found that the critical disturbance which is determined at the minimum curvature of disturbance function can be a the specific index.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2023년도 춘계학술대회
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• pp.254-255
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• 2023

This paper discovers a robust managerial strategy for a stochastic inventory of perishable products, where the model experiences changing factors including inner parameters and an external disturbance with unknown form. An analytical solution for the optimization problem can be obtained by applying the Hamilton-Bellman-Jacobi equation, however the policy result cannot completely suppress the oscillation from the external disturbance. Therefore, an intelligent approach named Radial Basis Function Neural Networks is applied to estimate the unknown disturbance and provide a robust controller to manipulate the inventory level more effective. The final results show the outstanding performance of RBFNN controller, where both the estimation error and control error are guaranteed in the predefined limit.