• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.103.1-103
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• 2002

In variable structure control algorithms, The control law used to realized the desired sliding mode dynamics is discontinuous on the switching manifold. However, due to imperfections in switching, such as time delays, the system trajectory chatters instead of sliding along the switching manifold. This chattering is undesirable because it may excite unmodeled high frequency dynamics in the physical system. In this paper, to overcome this drawback a self-organizing fuzzy sliding mode control algorithm using gradient descent method is proposed. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties ill the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• Advances in Computational Design
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• 제5권3호
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• pp.233-260
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• 2020

The main purpose to introduce model based controller in proposed control technique is to provide better and fast learning of the floating dynamics by means of fuzzy logic controller and also cancelling effect of nonlinear terms of the system. An iterative adaptive dynamic programming algorithm is proposed to deal with the optimal trajectory-tracking control problems for autonomous underwater vehicle (AUV). The optimal tracking control problem is converted into an optimal regulation problem by system transformation. Then the optimal regulation problem is solved by the policy iteration adaptive dynamic programming algorithm. Finally, simulation example is given to show the performance of the iterative adaptive dynamic programming algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.1-6
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• 1992

A principle of "orthogonalization" is proposed as an extended notion of hybrid (force and position) control for robot manipulators under geometric endpoint constraints. The principle realizes the hybrid control in a strict sense by letting position and velocity feedback signals be orthogonal in joint space to the contact force vector whose components are exerted at corresponding joints. This orthogonalization is executed via a projection matrix computed in real-time from a gradient of the equation of the surface in joint coordinates and hence both projected position and velocity feedback signals become perpendicular to the force vector that is normal to the surface at the contact point in joint space. To show the important role of the principle in control of robot manipulators, three basic problems are analyzed, the first is a hybrid trajectory tracking problem by means of a "modified hybrid computed torque method", the second is a model-based adaptive control problem for robot manipulators under geometric endpoint constraints, and the third is an iterative learning control problem. It is shown that the passivity of residual error dynamics of robots follows from the orthogonalization principle and it plays a crucial role in convergence properties of both positional and force error signals.force error signals.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.193-196
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• 2002

This paper proposes the control problem of an inverted pendulum system based on Sugeno-Type of fuzzy logic. The universal approximating capability, learning ability, adaptation capability and disturbance rejection are collected in one control strategy. The proposed scheme does not require an accurate dynamic model and the joint acceleration measurement, yet it guarantees asymptotic trajectory tracking. Experimental results perform with an inverted pendulum to show the effectiveness of the approach.

• 한국항공운항학회지
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• 제23권4호
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• pp.42-48
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• 2015

This paper has its purpose on constructing a prediction model of the arrival sequencing strategy which reflects the actual sequencing patterns of air traffic controllers. As the first step, we analyzed a pair-wise sequencing of two aircraft entering TMA from different entering points. Based on the historical trajectory data, several traffic factors such as time, speed and traffic density were examined for the model. With statistically significant factors, we constructed a prediction model of arrival sequencing through a binary logistic regression analysis. With the estimated coefficients, the performance of the model was conducted through a cross validation.

• International Journal of Aeronautical and Space Sciences
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• 제7권1호
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• pp.129-136
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• 2006

A new guidance synthesis for anti-ship missiles to control impact angle and impact time is proposed in this paper. The flight vehicle is assumed as a 1st order lag system to consider more practical system. The proposed guidance synthesis enhances the survivability of anti-ship missiles because multiple anti-ship missiles with the proposed synthesis can hit the target simultaneously. The control input to satisfy constraints of zero miss distance and impact angle, and the feedforward bias control input to control impact time constitute the guidance law. The former is from trajectory shaping guidance, the latter is from neural network. And particle swarm optimization method is introduced to furnish reference input and output for learning in neural network. The performance of the proposed synthesis in the accuracy of impact time and angle is validated by numerical examples.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.567-574
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• 2006

This paper presents the hardware implementation of a neural network controller for a nonlinear system with a micro-controller unit (MCU) and a field programmable gate array (FPGA) chip. As an on-line learning algorithm of a neural network, the reference compensation technique has been implemented on an MCU, while PID controllers with other functions such as counters and PWM generators are implemented on an FPGA chip. Interface between an MCU and a field programmable gate array (FPGA) chip has been developed to complete hardware implementation of a neural controller. The developed neural control hardware has been tested for balancing the inverted pendulum while controlling a desired trajectory of a cart as a nonlinear system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.131-135
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• 2001

본 논문에서는 작업 변수 또는 동작의 의도에 따라 다양한 형태의 궤적을 생성할 수 있는 동적 궤적 메모리(MTM)와 로봇 관절의 속도 및 가속도 제약조건을 만족하는 동작 시간을 계산하는 방법인 제약 조건을 고려한 표본화 간격 계산법(STICCON)이라는 두 가지 방법을 제시한다. 그리고 그 방법은 인간형 로봇의 동작 궤적 생성을 위한 구조적인 틀을 제안한다. 제안된 방법은 인간형 로봇의 궤적 생성 방법이 가져야 하는 두 가지 특성, 즉 복잡하고 다양한 동작의 궤적 표현 능력과 제약 조건에 따른 동적 궤적의 변형 과정을 모두 가지고 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.359-361
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• 1994

This paper propose a Neural - GA-ES DC motor speed controller. The purpose is to achieve accurate trajectory control of the motor speed. A feedforward neural network structure is used for the controller. Genetic algorithm and evolution strategy is used for learning controller. Simulations are performed to demonstrate the effectiveness of proposed genetic algorithm and evolution strategy with neural structure.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권4호
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• pp.268-276
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• 2015

A ship's sailing route or plan is determined by the master as the decision maker of the vessel, and depends on the characteristics of the navigational environment and the conditions of the ship. The trajectory, which appears as a result of the ship's navigation, is monitored and stored by a Vessel Traffic Service center, and is used for an analysis of the ship's navigational pattern and risk assessment within a particular area. However, such an analysis is performed in the same manner, despite the different navigational environments between coastal areas and the harbor limits. The navigational environment within the harbor limits changes rapidly owing to construction of the port facilities, dredging operations, and so on. In this study, a support vector machine was used for processing and modeling the trajectory data. A K-fold cross-validation and a grid search were used for selecting the optimal parameters. A complicated traffic route similar to the circumstances of the harbor limits was constructed for a validation of the model. A group of vessels was composed, each vessel of which was given various speed and course changes along a specified route. As a result of the machine learning, the optimal route and voyage data model were obtained. Finally, the model was presented to Vessel Traffic Service operators to detect any anomalous vessel behaviors. Using the proposed data modeling method, we intend to support the decision-making of Vessel Traffic Service operators in terms of navigational patterns and their characteristics.