• International Journal of Control, Automation, and Systems
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• 제1권1호
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• pp.142-148
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• 2003

Reinforcement learning is considered as an important tool for robotic learning in unknown/uncertain environments. In this paper, we propose an evaluation function expressed in a vector form to realize multi-dimensional reinforcement learning. The novel feature of the proposed method is that learning one behavior induces parallel learning of other behaviors though the objectives of each behavior are different. In brief, all behaviors watch other behaviors from a critical point of view. Therefore, in the proposed method, there is cross-criticism and parallel learning that make the multi-dimensional learning process more efficient. By ap-plying the proposed learning method, we carried out multi-dimensional evaluation (reward) and multi-dimensional learning simultaneously in one trial. A special neural network (Q-net), in which the weights and the output are represented by vectors, is proposed to realize a critic net-work for Q-learning. The proposed learning method is applied for behavior planning of mobile robots.

• 한국통신학회논문지
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• 제38A권6호
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• pp.535-544
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• 2013

본 논문은 단일 송신안테나를 갖는 다수의 모바일 터미널이 가상 MIMO 링크를 구성하는 MIMO 시스템에서의 역방향 전력 제어 방법을 제안한다. 기존의 성능을 향상 시키기 위하여 전력 벌칙 항을 추가하는 게임이론 기반의 전력 제어 방식과 달리, 전체 유효 간섭 전력에 대한 제한 조건 하에서 선형 수신 빔형성을 이용한 전송율의 유틸리티 함수를 최대화 하는 방법을 고려하였다. 또한, 전력제어 과정에 이너시아를 도입하여 제안 전력 제어가 수렴함을 보였다. 모의 실험을 통하여 간섭이 지배적인 다중셀 시스템에서 제안 전력 제어 방법이 시스템의 성능을 크게 향상 시킴을 입증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.493-493
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• 2000

Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of database. The two values (on-off) decision making method without transition had been proposed by one of the author in a previous work for a purpose of realizing human on-off decision making. The current method is an extension of the previous on-off decision making. By combining the conditional probability and the transitional probability, the closed form of the algorithm for the multi-valued transitional decision making was derived. The proposed multi-valued decision making was successfully applied to the determination of the five levels of the vigilance of a subject during the EEG recording; awake stage, drowsy stage and sleeping stages (stage 1, stage 2/3, REM (rapid eye movement)). The method for determining the vigilance level can be directly usable for the two purposes; selection of awake EEG segments for automatic EEG interpretation, and determination of sleep stages through sleep EEG. The proposed multi-valued decision making with a mathematical background of the probability can be applicable widely, in industries and in medical fields for purposes of the multi-valued decision making.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.753-757
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• 2004

This paper describes a PC-based distributed multi-rate realtime control system using USB protocol, which is developed as a general motion controller. The control system consists of two control programs: one running at 1 kHz sampling rate on a PC with Linux and another running at 10 kHz sampling rate on a remotely located motion control card called RASID (remote axis serial interface device). Two programs communicates through USB at every 1 msec. A USB communication driver is developed to ensured the 1 msec desired communication time. The main program running on the PC generates reference trajectory at 1 kHz and send it to the RASID through USB and RASIDs located near the motors gather the sensor information and execute the low-level control at 10 kHz. The USB-based connectivity reduces the wiring harness and eventually the manufacturing cost of the machine. The multi-rate nature of the developed system improves the control capability. The effect of sampling rate is analyzed and simulated.

• Journal of Mechanical Science and Technology
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• 제15권5호
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• pp.544-554
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• 2001

A shop floor can be considered as an important level to develop Computer Integrated Manufacturing system (CIMs). However, a shop floor is a dynamic environment where unexpected events continuously occur, and impose changes to the planned activities. To deal with this problem, a shop floor should adopt an appropriate control system that is responsible for the coordination and control of the manufacturing physical flow and information flow. In this paper, a hybrid control system is described with a shop floor activity methodology called Multi-Layered Task Initiation Diagram (MTD). The architecture of the control model contains three levels: i.e., he shop floor controller (SFC), the intelligent agent controller (IAC) and the equipment controller (EC). The methodology behind the development of the control system is an intelligent multi-agent paradigm that enables the shop floor control system to be an independent, an autonomous, and distributed system, and to achieve an adaptability to change of the manufacturing environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1296-1299
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• 1996

This paper proposes a design automation method for the flight control system of an aircraft based on optimization. The control system design problem which has many specifications is formulated as multi-objective optimization problem. The solution of this optimization problem should be considered in terms of Pareto-optimality. In this paper, we use an evolutionary algorithm providing numerous Pareto-optimal solutions. These solutions are given to a control system designer and the most suitable solution is selected. This method decreases tasks required to determine the control parameters satisfying all specifications. The design automation of a flight control system is illustrated through an example.

• 대한임베디드공학회논문지
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• 제14권6호
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• pp.339-346
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• 2019

Multi-axis servo systems are widely used in various fields such as industiral systems for improving production efficiency, robotics and complex systems where many mechanical devices and sensor systems are connected. Such a servo system requires that the servo control technique to realize the synchronization of the drive shaft in the steady state and transient conditions and to control so as to follow the target track in order to improve product precision and production efficiency. In addition, embedded type hardware is required for smooth control of the entire multi-axis system. Therefore, this paper uses hardware based on FPGA which is widely used in digital signal processing field and various control system because hardware design change is easy and parallel processing is possible. In addition, Labview based servo motor control program was studied that can control the servo motor by ensuring the performance and flexibility of the FPGA and follow the target trajectory according to various speed processing and accurate timing synchronization.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.286-290
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• 2000

Optimal neuro-control algorithm is extended to the control of a multi-degree-of-freedom structure. An active mass driver(AMD) system on the top roof is used as an exciter. The control signals are made by a multi-layer perceptron(MLP) which is trained by minimizing a sub-optimal performance index. The performance index is a function of both the output responses and the control signals. Structure having nonlinear hysteretic behavior is also trained and controlled by using proposed control algorithm. In training neuro-controller, emulator neural network is not used. Instead, sensitivity-test data are used. Therefore, only one neural network is used for the control system. Both the time delay effect and the dynamics of hydraulic actuator are included in the simulation. Example shows that optimal neuro-control algorithm can be applicable to the multi-degree of freedom structures.

• Journal of Power Electronics
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• 제13권6호
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• pp.928-938
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• 2013

This paper proposes a novel control method for a multi-output switched-resonant converter. Output voltage can be regulated against variations in the supply voltage and load by controlling the voltage of the resonant capacitor (pulse amplitude control). Precise control is possible when pulse amplitude control is combined with pulse number control. The converter is analyzed, and design considerations are explained by using examples. Control implementation is described and load regulation and ripples are analyzed by simulation and hardware results. The topology is modified to obtain an additional negative output without any additional hardware other than a diode. The analysis of such a triple output converter with two positive outputs and one negative output is conducted and confirmed. The topology and control scheme are scalable to any number of outputs.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.450-453
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• 1997

An active control for the swing of crane systems is very important for increasing the productivity. This article introduces the control for the position and the swing of a crane using the fuzzy learning method. Because the crane is a multi-variable system, learning is done to control both position and swing of the crane. Also the fuzzy control rules are separately acquired with the loading and unloading situation of the crane for more accurate control. The result of simulations shows that the crane is just controlled for a very large swing angle of 1 radian within nearly one cycle.