비선형 시스템규명

정길도(Kil-To Chong) Korean Society for Precision Engineering 1995 한국정밀공학회지 Vol.12 No.5

비선형 시스템의 신경회로망을 이용한 모델링 기법

정길도(Kil To Chong),노태수(Tae-Soo No),홍동표(Dong-Pyo Hong) Korean Society for Precision Engineering 1996 한국정밀공학회지 Vol.13 No.12

Tracking control of wheeled mobile robot using a receding horizon controller with time-delay

Yu Gao,Kil To Chong(정길도) 제어로봇시스템학회 2008 제어로봇시스템학회 국내학술대회 논문집 Vol.2008 No.10

In this study, a receding horizon (RH) controller is developed for the tracking control of wheeled mobile robots (WMRs) subject to nonholonomic constraints in environments without obstacles. The tracking-error kinematic model is first linearized at the equilibrium point. Then, it is transformed into an exact discrete form considering the time-delay. The control policy is derived from the optimization of a quadratic cost function, which penalizes the tracking error and control variables in each sampling time. The minimization problem is solved by using the OP (Quadratic Programming) method taking the current error state as the initial value and including the input constraints, which include the velocity and acceleration constraints to prevent the mobile robot from slipping. The performance of the control algorithm is verified via computer simulations with predefined trajectory showing that the strategy is feasible.

Fuzzy logic based Obstacle Avoidance system for Mobile Robot

Subbash Panati,Kil to Chong(정길도) 제어로봇시스템학회 2014 제어로봇시스템학회 각 지부별 자료집 Vol.2014 No.12

Mobile robot navigation in real world environment is a key research area related to autonomous robots. Path planning and obstacle avoidance play a key role in mobile robot navigation. This paper proposes a sensor based path planning method which utilizes fuzzy logic for mobile robot obstacle avoidance. The ultrasonic sensors are used to acquire the information about the environment around the mobile robot, based on the sensor readings the fuzzy rules are fired to make a decision on the angular velocity of the left and right wheels of mobile robot. The fuzzy rules and membership functions are constructed based on human reasoning and are tuned by iterative simulations. The simulation results show the effectiveness of the proposed method.

Multi-Robots and Robot Sensor Network Applications

Bayanjargal Baasandorj,Kil To Chong(정길도) 제어로봇시스템학회 2014 제어로봇시스템학회 각 지부별 자료집 Vol.2014 No.12

The interaction of distributed robotics and wireless sensor networks has led to the creation of mobile sensor networks. Mobile sensor networks are a class of networks where small sensing devices move in a space over time to collaboratively monitor physical and environmental condition. They are the growing popular class of WSN in which mobility plays a key role in the execution of the application. By introducing mobility to nodes in WSN, we can enhance its capability and flexibility to support multiple mansions and to handle the aforementioned problems. The decreasing costs and the increasing capabilities make mobile sensor networks possible and practical. More and more researches focus on the development of mobile wireless sensor networks (MWSNs) due to its favorable advantages and applications. The research on mobile sensor networks has been plenty worldwide. Robotics can be used in wireless sensor networks to solve many problems such as node repositioning, node localization, acting as data mules, detecting and reacting to sensor failure, aggregate sensor data and even provide mobile battery chargers for the nodes. And also wireless sensor networks can help solve many problems in robotics, such as path planning, robot localization sensing, mapping. Most of the problems in traditional sensor networks may be addressed by incorporating intelligent, mobile robots directly into it. Mobile robots provide the means to explore and interact with the environment in a dynamic and decentralized way. In addition to enabling mission capabilities well beyond those provided by sensor networks, these new systems of networked sensors and robots allow for the development of new solutions to classical problems such as localization and navigation. In this paper we present a overview of multi-robots systems its uses and in the second part reviewed Robotic Sensor network applications.

신경 회로망 예측 모델을 이용한 실시간 멀티미디어 데이터 전송률 제어

김용석,권방현,정길도,Kim, Yong-Seok,Kwon, Bang-Hyun,Chong, Kil-To 한국통신학회 2005 韓國通信學會論文誌 Vol.30 No.2B

본 논문에서는 멀티미디어 전송 시 QoS(Quality of Service)를 개선하기 위한 유효패킷 전송률을 향상 시키는 방법으로 신경회로망을 이용한 예측 알고리즘을 제안하였다. 신경회로망 모델을 이용하여 왕복지연시간과 패킷손실률을 예측하고 예측된 인자를 이용하여 데이터 전송률을 결정하는 방법이다. 제안한 방법은 과거의 데이터를 기준으로 전송률을 결정하여 전송하는 데이터의 양을 제어하는 기존의 방법보다 향상된 성능을 확보할 수 있게 된다. 제안한 방법의 성능을 확인하기 위하여 실 시스템에 적용하는 실험을 실시하였다. 리눅스 운영 PC를 사용하였으며, UDP 프로토콜을 이용하여 실시간 데이터를 전송하는 실험 장치를 구현하였다. 제안한 방법의 유효패킷 전송률이 기존의 TCP-Friendly 혼잡제어 방법에 비하여 5% 정도 향상된 성능을 보였다. This paper proposes a neural network prediction model to improve the valid packet transmission rate for the QoS(Quality of Service) of multimedia transmission. The Round Trip Time(RTT) and Packet Loss Rate(PLR) are predicted using a neural network and then the transmission rate is decided based on the predicted RTT and the PLR. The suggested method will improve the transmission rate since it uses the rate control factors corresponding to time of data is being transmitted, while the conventional one uses the transmission rate determined based on the past informations. An experimental set-up has been established using a Linux PC system, and the multimedia data are transmitted using UDP protocol in real time. The valid transmitted packets are about 5% higher than the one in the conventional TCP-Friendly congestion control method when the suggested algorithm was applied.

젖소의 사양관리 시스템 개발

김동원,한병성,정길도,김용준,김명순,임태영,채석,Kim, Dong-Won,Han, Byung-Sung,Chong, Kil-To,Kim, Yong-Jun,Kim, Myoung-Soon,Lim, Tae-Yeong,Chae, Seok 대한산업공학회 1998 산업공학 Vol.11 No.3

The agriculture and fishery share in the Korean GDP is continuously decreasing after 1960s. Furthermore the proportion of these industries in the GDP has diminished as low as 10 percent in recent years. However, the stockbreeding sector in these industries are considerably expanded. More than 50 percent of the whole farmhouses are involved in the livestock farming, and the stock farming portion is steadily increased in its size and scope. Thus, the mechanization and the automization of stockbreeding equipments are greatly required to reduce down production cost, as well as to win the competitiveness in the global market. From this aspect, developed in this paper is a stockbreeding management system (SMS) for dairy cattle, which can be used in small and medium sized dairy farms. First, the basic schema of the stockbreeding management system are addressed in view of stockbreeding management for individual dairy cattle. Electronic identification (EI) systems and sensory devices have changed stockbreeding management strategy from group stock control into individual stock control manner. The SMS receives stock body measurement data through the sensory devices such as weight, temperature, and milk conductivity meters. A common database then integrates those measuring data together so that the SMS can determine the appropriate solution on each stock's breeding such as feeding and milking. Thus, each stock can be supervised by a sophisticated SMS that provides the best solution to the stockbreeding throughout the stock's whole life-cycle. Secondly. six major submodules of the SMS, based on the EI and sensory devices, are proposed. They are individual stock management, disease management, health management, feeding management, milking management, and a propagation management submodule. Finally, a prototype system for the SMS is demonstrated. The system is developed using Delphi 2 client-server system run under the Windows 95 environment.

Mobile sensor Networks and Robotics

Aamir Reyaz,Kil To Chong(정길도) 제어로봇시스템학회 2014 제어로봇시스템학회 각 지부별 자료집 Vol.2014 No.12

Q-learning for intersection traffic flow Control based on agents

주선(ZhouXuan),정길도(Kil To Chong) 대한전기학회 2009 정보 및 제어 심포지엄 논문집 Vol.2009 No.5

In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

Fast Global Kernel Fuzzy C-Means Clustering Algorithm for Consonant/Vowel Segmentation of Speech Signal

Xian Zang,Kil To Chong(정길도) 제어로봇시스템학회 2012 제어로봇시스템학회 각 지부별 자료집 Vol.2012 No.12

A clustering method using fast global kernel fuzzy c-means is developed to segment the speech signal into small non-overlapping blocks for consonant/vowel segmentation. This method proceeds in an incremental way attempting to optimally add new cluster center at each stage through kernel fuzzy c-means. It overcomes the well-known shortcomings of the most popular clustering method, fuzzy c-means, and improves the clustering accuracy. Due to the speeding up scheme, the complexity is lowered and the convergence speed is improved. Simulation results demonstrate the effectiveness of the proposed method in consonant/vowel segmentation.