List of English Publication

@article{nokeyp,

title = {Distributed Resilient Observer: Blended Dynamics Theory Meets ℓ1-Minimization Approach},

author = {Donggil Lee and Junsoo Kim and Hyungbo Shim},

url = {https://ieeexplore.ieee.org/document/10147254/},

doi = {10.1109/LCSYS.2023.3284592},

issn = {2475-1456},

year  = {2023},

date = {2023-06-09},

urldate = {2023-06-09},

journal = {IEEE Control Systems Letters},

volume = {7},

pages = {2083 - 2088},

abstract = {This paper presents a distributed resilient observer for continuous-time linear time-invariant plants that remains functional even under sensor attacks. The proposed method aims to determine the estimation outcome that matches the majority of sensor measurements, which is formulated as an ℓ1-minimization problem considering all the observable components of each sensor measurement. A distributed observer based on the blended dynamics theory is then proposed to solve the ℓ1-minimization problem in a distributed manner. As a result, the distributed resilient estimation is enabled for a broader class of systems compared to previous works. The design procedure is constructive with parameters obtained from a specified condition that is equivalent to the well-known null-space property.},

keywords = {Blended dynamics, Blended Dynamics Approach, Distributed state estimation, Resilient state estimation},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Blended dynamics approach to distributed optimization: Sum convexity and convergence rate},

author = {Seungjoon Lee and Hyungbo Shim},

url = {https://www.sciencedirect.com/science/article/pii/S0005109822001364},

doi = {https://doi.org/10.1016/j.automatica.2022.110290.},

issn = {0005-1098},

year  = {2022},

date = {2022-04-26},

urldate = {2022-07-01},

journal = {Automatica},

volume = {141},

pages = {110290},

abstract = {In this paper, we introduce the concept of the blended dynamics of the multi-agent system, which is constructed using dynamics of individual agents. The blended dynamics approach is applied to the distributed optimization problem where the global cost function is given by a sum of local cost functions. The benefits include (i) individual cost function need not be convex as long as the global cost function is strongly convex and (ii) the convergence rate of the distributed algorithm is arbitrarily close to the convergence rate of the centralized one. Two particular continuous-time algorithms are presented using the proportional–integral-type couplings. One has benefit of ‘initialization-free’, so that agents can join or leave the network during the operation. The other one has the minimal amount of communication information. After presenting a general theorem that can be used for designing distributed algorithms, we particularly present a distributed heavy-ball method and discuss its strength over other methods.},

keywords = {Blended Dynamics Approach, Distributed optimization},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Distributed Dynamic Quantile Solver With Plug-and-Play Operation},

author = {Jeong Mo Seong and Jeong Woo Kim and Seungjoon Lee and Hyungbo Shim},

url = {https://ieeexplore.ieee.org/document/9646895},

doi = {10.1109/ACCESS.2021.3134655},

issn = {2169-3536},

year  = {2021},

date = {2021-12-01},

urldate = {2021-12-01},

journal = {IEEE Access},

volume = {9},

pages = {165517-165525},

abstract = {In this paper, we propose a continuous-time distributed algorithm for the dynamic quantile problem. The problem is to find the quantile of time-varying signals in a network of agents, each of which having the signal of its own. For example, this problem includes finding the median, maximum, or the second largest value of the signals. The proposed algorithm guarantees convergence from arbitrary initial conditions and does not use the decaying gains. Hence our algorithm is suitable for plug-and-play operation, where agents may freely join or leave the network during the operation. An application to a simplified electricity market problem is presented to show the effectiveness of the design.},

keywords = {Blended Dynamics Approach, Distributed algorithm, Multi-agent system},

pubstate = {published},

tppubtype = {article}

}