• 전기학회논문지
• /
• 제67권2호
• /
• pp.308-313
• /
• 2018

In this paper, we propose a sampled-data model predictive tracking control deign for leader-following control of multi-mobile robot system. The error dynamics of leader-following robots is modeled as a Linear Parameter Varying (LPV) model. Also, the Lyapunov function is presented to guarantee stability of the networked control system. Based on the stabilization condition using a quadratic Lyapunov function approach, model predictive sampled-data controller is designed. Finally, the leader-following control of multi mobile robots is simulated to show effectiveness of the proposed method.

• 전력전자학회:학술대회논문집
• /
• 전력전자학회 2007년도 추계학술대회 논문집
• /
• pp.53-55
• /
• 2007

This paper describes an implementation of a wide-range dimming controller of a LED backlight for Avionics applications such as the control data unit(CDU) and multi-function display(MFD). A feedback controller using a light sensor is proposed to control the brightness in the low dimming range. The proposed controller provides an improved control performance in the wide dimming range of 1:3000 even under the temperature variations. The experimental results are provided to show the effectiveness of the proposed control system.

• 한국자동차공학회논문집
• /
• 제14권6호
• /
• pp.160-170
• /
• 2006

If hydraulic pump controlled by mechanical type regulator has more than one control function, the construction of regulator will be very complicated and control performance falls drastically. It is difficult to have more than one control function for hydraulic pump controlled by electronic type hydraulic valve due to the inconsistency of controllers. This paper proposes a multi-function control technique which controls continuously flow, pressure and power by using EPPR(Electronic Proportional Pressure Reducing) valve in swash plate type axial piston pump. Nonlinear mathematical model is developed from the continuity equation for the pressurized control volume and the torque balance for the swash plate motion. To simplify the model we make the linear state equation by differentiating the nonlinear model. A reaction spring is installed in servo cylinder to secure the stability of the control system. We analyze the stability and disturbance by using the state variable model. Finally, we review the control performances of flow, pressure and power by tests using PID controller.

• 전자공학회논문지
• /
• 제51권4호
• /
• pp.33-41
• /
• 2014

본 논문에서는 모바일 시스템 환경에서 멀티포트 메모리 컨트롤러의 특성을 고려한 직접 메모리 접근 컨트롤러를 사용하여 고속 데이터 전송을 효과적으로 수행하는 메모리 액세스 방법을 보인다. 제안된 직접 메모리 접근 컨트롤러는 여러 개의 직접 메모리 접근 채널을 제어 할 수 있는 통합 채널 관리 기능을 제공하며, 그 채널들은 물리적으로 분리되어 서로 독립적으로 동작한다. 제안된 직접 메모리 접근 방법을 통한 데이터 전송을 이용함으로써 읽기 동작에 대하여 72%, 쓰기 동작에 대하여 69%의 데이터 전송 성능 향상을 얻었다. 특히, 4 채널 접근 모드에 대해서 제안된 방법이 기존 직접 메모리 접근 방법에 비하여 63% 적은 전체 전송 사이클을 가짐으로써 전송 성능 향상에 기여할 수 있음을 보인다.

• 한국전자파학회논문지
• /
• 제30권1호
• /
• pp.70-78
• /
• 2019

본 논문에서 통합 전장 시뮬레이터 환경인 AddSIM에서 레이다 동작을 모의하기 위한 고해상도 다기능 레이다의 모델링을 제안한다. 다기능 레이다 모델을 AddSIM에 연동하기 위해, 모델링은 물리부, 논리부, 정보부로 구성된 컴포넌트 기반의 구조를 가져야 한다. 이를 위해, 레이다의 RF 하드웨어부를 물리부로, 제어부를 논리부로, 레이다의 RF 제원을 정보부로 각각 분리한다. 레이다의 물리부/논리부에 대한 세부 모델링 방법을 기술하며, 공학급 레벨의 시뮬레이션을 위한 데이터 구조 또한 제시한다. 다중 표적이 교전하는 시나리오에서 다기능 레이다의 성능이 수치적으로 분석하며 제안된 모델에 대한 타당성을 검증한다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
• /
• pp.341-345
• /
• 1997

A novel fuzzy basis function vector-based adaptive control approach for Multi-input and Multi-output(MIMO) system is presented in this paper, in which the nonlinear plants is first linearised, the fuzzy basis function vector is then introduced to adaptively learn the upper bound of the system uncertainty vector, and its output is used as the parameters of the compensator in the sense that both the asymptotic error convergence can be obtained for the colsed loop nonlinear control system.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제15권1호
• /
• pp.12-19
• /
• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

• 전자공학회논문지C
• /
• 제35C권8호
• /
• pp.68-74
• /
• 1998

The neural network predictiv econtroller (NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output (NNP:neural network predictor) and the other one is for control the plant(NNC: neural network controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and predictin error. The NNP forecasts the future output based upon the current control input and the estimated control output. The input and the output data of a system and a new method using evolution strategy are used to train the NNP. A two-step NNPC is applied to control the temeprature in boiler systems. It was compared with PI controller and auto-tuning PID controller. The computer simulaton and experimental results show that the proposed method has better performances than the other method.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1993년도 하계학술대회 논문집 A
• /
• pp.231-234
• /
• 1993

This paper deals with the design of an adaptive controller using neural network. We present RBFMLP Neural Network which consists of serial-connected two networks - Radial Basis Function Network and Multi Layer Perceptron, and then design a controller based on proposed networks with the adaptive control system structure, The plant and parameters of the controller are identified by the neural networks. We use the dynamic backpropagation algorithm for the learning of networks. Simulations represent the superiorities of the proposed network and the controller.

• 조명전기설비학회논문지
• /
• 제26권10호
• /
• pp.89-94
• /
• 2012

This research is to apply the control of neuron networks for the real-time walking control of Multi-articulated robot. Multi-articulated robot is expressed with a complicated mathematical model on account of the mechanic, electric non-linearity which each articulation of mechanism has, and includes an unstable factor in time of walking control. If such a complex expression is included in control operation, it leads to the disadvantage that operation time is lengthened. Thus, if the rapid change of the load or the disturbance is given, it is difficult to fulfill the control of desired performance. This paper proposes a new mode to implement a neural network controller by installing a real object for controlling and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The proposed control algorithm generated control signs corresponding to the non-linearity of Multi-articulated robot, which could generate desired motion in real time.