• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.625-631
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• 2011

This paper presents a discrete-time output feedback consensus algorithm for Multi-Agent Systems (MAS). Under the assumption that an agent is aware of the relative state information about its neighbors, a state feedback consensus algorithm is designed based on Linear Matrix Inequality (LMI) method. In general, however, it is possible to obtain its relative output information rather than the relative state information. To reconcile this problem, an Unknown Input Observer (UIO) is employed in this paper. To this end, first it is shown that the relative state information can be estimated using the UIO and the measured relative output information. Then a certainty-equivalence type output feedback consensus algorithm is proposed by combining the LMI-based state feedback consensus algorithm with the UIO. Finally, simulation results are given to illustrate that the proposed method successfully achieves the state consensus.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.167-173
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• 2019

This study investigates the problem of leader-following consensus for multi-agent systems with output saturations. This study assumes that the agents are described as a neutrally stable system, and the leader agent generates the bounded trajectory within the saturation level. Then, the objective of the leader-following consensus is to track the trajectory of the leader by exchanging information with neighbors. To solve this problem, we propose an observer-based distributed consensus algorithm. Then, we provide a consensus analysis by applying the Lyapunov stability theorem and LaSalle's invariance principle. The result shows that the agents achieve the leader-following consensus in a global sense. Moreover, we can achieve the consensus by choosing any positive control gain. Finally, we perform a numerical simulation to demonstrate the validity of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.857-862
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• 2011

This paper studies the output consensus problem for a class of heterogeneous linear multi-agent systems under a fixed directed communication network. The dynamics, as well as its dimension, of each agent can widely differ from the others, but all the agents are assumed to have the same transfer matrix. In addition, only the system outputs are constrained to be delivered through the network. Under these conditions, we show that the output consensus is reached by a group of identical controllers, which is designed to achieve the state consensus for the homogeneous multi-agent system obtained from the minimal realization of the transfer matrix. Finally, an example is given to demonstrate the proposed result.

• Journal of IKEEE
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• v.20 no.4
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• pp.378-384
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• 2016

This paper addresses the output feedback consensus problem for high-order integrators under a directed network with a communication delay. In order to solve this problem, the dynamic output feedback controller is proposed. Also, by using Lyapunov-Krasovskii functional, it is shown that the existence of the proposed consensus controller can always be guaranteed even in the presence of an arbitrarily large communication delay.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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• pp.243-248
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• 2013

In wireless sensor networks, consensus algorithms for dynamic systems may flexibly usable for their data fusion of a sensor network. In this paper, a distributed data fusion filter is implemented using an average consensus based on distributed sensor data, which is composed of some sensor nodes and a sink node to track the mean values of n sensors' data. The consensus filter resolve the problem of data fusion by a distribution Kalman filtering scheme. We showed that the consensus filter has an optimal convergence to decrease of noise propagation and fast tracking ability for input signals. In order to verify for the results of consensus filtering, we showed the output signals of sensor nodes and their filtering results, and then showed the result of the combined signal and the consensus filtering using zeegbee communication.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.222-226
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• 2010

In this paper we study the consensus problem of SISO (Single-Input Single-Output) linear multi-agent systems under a fixed weighted undirected network communication. The dynamics of each agent can be of any order, while it is constrained to be neutrally stable. Based on a simple root locus argument, we show that the problem at hand is always solvable if the gain and zeros of the dynamic compensator, of which dimension is the same as the number of plant poles on the imaginary axis, are chosen suitably, finally the result is successfully verified by an example.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1304-1305
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• 2015

본 논문은 타카기--수게노 퍼지 다개체 시스템의 상태 일치를 위해, 관측기 기반 출력 궤환 퍼지 제어기의 설계 기법을 제안한다. 각 개체간의 통신 네트워크는 그래프 이론을 통해 나타내며, 제어기의 설계 조건은 선형 행렬 부등식으로 표현한다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.169-175
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• 1996

In this paper, a new parallel neural network system that performs dynamic competitive learning is proposed. Conventional learning mehtods utilize the full dimension of the original input patterns. However, a particular attribute or dimension of the input patterns does not necessarily contribute to classification. The proposed system consists of parallel neural networks with the reduced input dimension in order to take advantage of the information in each dimension of the input patterns. Consensus schemes were developed to decide the netowrks performs a competitive learning that dynamically generates output neurons as learning proceeds. Each output neuron has it sown class threshold in the proposed dynamic competitive learning. Because the class threshold in the proposed dynamic learning phase, the proposed neural netowrk adapts properly to the input patterns distribution. Experimental results with remote sensing and speech data indicate the improved performance of the proposed method compared to the conventional learning methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1001-1004
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• 1993

The Multisensor Fusion Problem (MFP) deals with the methodologies involved in effectively combining together homogeneous or non-homegeneous information obtained from multiple redundant or disparate sensors in order to perform a task more accurately, efficiently, and reliably. The inherent uncertainties in the sensory information are represented using Fuzzy Numbers, -numbers, and the Uncertainty-Reductive Fusion Technique (URFT) is introduced to combine the multiple sensory information into one consensus -number. The MFP is formulated from the Information Theory perspective where sensors are viewed as information sources with a fixed output alphabet and systems are modeled as a network of information processing and processing and propagating channels. The performance of the URFT is compared with other fusion techniques in solving the 3-Sensor Problem.

• Asia pacific journal of information systems
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• v.9 no.1
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• pp.143-163
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• 1999

This study investigates the effect of group size on group performance, here the quality of group decision, Four effects are proposed and tested in a field experimental setting : (1) the relationship between the group size and the distribution of individual's problem-solving ability ; (2) the change of the group decision quality as group size increases ; (3) the relationship between the group decision quality and the quality of the best/worst member as group size increases ; (4) the relationship between the group decision quality and the average quality of individuals in the group as group size increases. Data showed that contrary to the exiting results, group decision quality was not improved with the group size. Rather, it showed a little tendency that group decision quality was worsened with the group size. Data also showed that consensus-oriented group decision making process produced the compromised output. Thus, group decision quality was not better than the average group members'. The opinion of the best member was not accepted. The implications of the findings are discussed for the development of a Korean GSS.