• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1225-1230
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• 2014

This paper investigates the group average-consensus and group formation-consensus problems for first-order multi-agent systems. The control protocol for group consensus is designed by considering the positive adjacency elements. Since each intra-group Laplacian matrix cannot be satisfied with the in-degree balance because of the positive adjacency elements between groups, we decompose the Laplacian matrix into an intra-group Laplacian matrix and an inter-group Laplacian matrix. Moreover, average matrices are used in the control protocol to analyze the stability of multi-agent systems with a fixed and undirected communication topology. Using the graph theory and the Lyapunov functional, stability analysis is performed for group average-consensus and group formation-consensus, respectively. Finally, some simulation results are presented to validate the effectiveness of the proposed control protocol for group consensus.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.526-532
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• 2014

In this paper, we present and analyze a LQ (Linear Quadratic) inverse optimal state-consensus protocol for continuous-time multi-agent systems with undirected graph topology. By Lyapunov analysis of the state-consensus error dynamics, we show the sufficient conditions on the algebraic connectivity of the graph to guarantee LQ inverse optimality and closed-loop stability. A more relaxed stability condition is also provided in terms of the algebraic connectivity. Finally, a formation control protocol for multiple mobile robots is proposed based on the target LQ inverse optimal consensus protocol, and the simulation results are provided to verify the performance of the proposed LQ inverse formation control method.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.226-234
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• 2022

With advances in autonomous vehicles and networked control, there is a growing interest in the consensus control of a multi-agents system to control multi-agents with distributed control beyond the control of a single agent. Since consensus control is a distributed control, it is bound to have delay in a practical system. In addition, it is often difficult to have a very accurate mathematical model for a system. Even though a reinforcement learning (RL) method was developed to deal with these issues, it often experiences slow convergence in the presence of large uncertainties. Thus, we propose a slide RL which combines the sliding mode control with RL to be robust to the uncertainties. The structure of a sliding mode control is introduced to the action in RL while an auxiliary sliding variable is included in the state information. Numerical simulation results show that the slide RL provides comparable performance to the model-based consensus control in the presence of unknown time-varying delay and disturbance while outperforming existing state-of-the-art RL-based consensus algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.434-441
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• 2015

In this paper, we propose an inverse optimal distributed protocol for the formation and velocity consensus of nonholonomic mobile robots. The communication among mobile robots is described by a simple undirected graph, and the mobile robots' kinematics are considered. The group of mobile robots driven by the proposed protocols asymptotically achieves the desired formation and group velocity in an inverse optimal fashion. The design of the protocols is based on dynamic feedback linearization and the proposed linear quadratic (LQ) inverse optimal second-order consensus protocol. A numerical simulation is given to verify the effectiveness of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.5
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• pp.323-325
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• 2014

The consensus algorithm has a faster convergence speed as the number of cooperating neighbors increases, but the information sharing delay in the wireless network increases due to access collisions as the number of cooperating neighbors increases. Therefore, there exists a tradeoff between these two performances according to node's coverage. In this paper, we present a method of coverage control that minimizes consensus time according to network scale.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.390-397
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• 2013

This paper presents a consensus algorithm for uMAS (uncertain Multi-Agent Systems). Unlike previous results in which only nominal models for agents are considered, it is assumed that the uncertain agent model belongs to a known polytope set. In the middle of deriving the proposed algorithm, a convex set is found which includes all uncertainties in the problem using convexity of the polytope set. This set plays an important role in designing the consensus algorithm for uMAS. Based on the set, a consensus condition for uMAS is proposed and the corresponding consensus design problem is solved using LMI (Linear Matrix Inequality). Simulation result shows that the proposed consensus algorithm successfully leads to consensus of the state of uMAS.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.527-537
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• 2021

Purpose: The purpose of this study was to suggest an improved version of Proof-of-Nonce (PoN) algorithm, which is a distributed consensus algorithm used for block chain system. Methods: First, we used response surface method for design of experiment that is to generate experimental points considering non-linear relationship among variables. Then, we employed overlapped contour plots for visualizing the impact of control variables to performance target. Results: First, we modified the consensus procedure of the existing PoN algorithm by diminishing the content of the exchanged message. Then, we verified the performance improvement of the new PoN algorithm by performing a numerical experiment and paired t-test. Finally, we established new regression models for consensus time and Transactions per second (TPS) and proposed a method for optimizing control variables for obtaining performance target. Conclusion: We could improve the performance of the previous version of PoN algorithm by modifying the content of the exchanged message during 4-steps of consensus procedure, which might be a stepping stone for designing an efficient and effective consensus algorithm for blockchain system with dynamic operation environment.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.617-621
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• 2012

This paper studies asymptotic consensus problem for linear multi-agent systems. We propose a distributed state feedback control algorithm for solving the problem under fixed and undirected network communication. In contrast with the conventional algorithms that use global information (e.g., graph connectivity), the proposed algorithm only uses local information from neighbors. The principle for achieving asymptotic consensus is that, for each agent, a distributed update law gradually increases the coupling gain of LQR-type feedback and thus, the overall stability of the multi-agent system is recovered by the gain margin of LQR.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.1-9
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• 2022

The PoN (Proof of Nonce) distributed consensus algorithm basically uses a non-competitive consensus method that can guarantee an equal opportunity for all nodes to participate in the block generation process, and this method was expected to resolve the first trilemma of the blockchain, called the decentralization problem. However, the decentralization performance of the PoN distributed consensus algorithm can be greatly affected by the network transaction transmission delay characteristics of the nodes composing the block chain system. In particular, in the consensus process, differences in network node performance may significantly affect the composition of the congress and committee on a first-come, first-served basis. Therefore, in this paper, we presented a problem by analyzing the decentralization performance of the PoN distributed consensus algorithm, and suggested a fairness control algorithm using a learning-based probabilistic acceptance rule to improve it. In addition, we verified the superiority of the proposed algorithm by conducting a numerical experiment, while considering the block chain systems composed of various heterogeneous characteristic systems with different network transmission delay.

• 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.