TY - GEN
T1 - Conic Optimization Theory
T2 - 2018 Annual American Control Conference, ACC 2018
AU - Zhang, Richard Y.
AU - Josz, Cédric
AU - Sojoudi, Somayeh
N1 - Funding Information:
Richard Y. Zhang is with the Department of Industrial Engineering and Operations Research, University of California, Berkeley. Cédric Josz is with the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. Somayeh Sojoudi is with the Departments of Electrical Engineering and Computer Sciences and Mechanical Engineering, University of California, Berkeley. This work was supported by the ONR grant N00014-17-1-2933, DARPA grant D16AP00002, and AFOSR grant FA9550-17-1-0163.
Publisher Copyright:
© 2018 AACC.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - Optimization is at the core of control theory and appears in several areas of this field, such as optimal control, distributed control, system identification, robust control, state estimation, model predictive control and dynamic programming. The recent advances in various topics of modern optimization have also been revamping the area of machine learning. Motivated by the crucial role of optimization theory in the design, analysis, control and operation of real-world systems, this tutorial paper offers a detailed overview of some major advances in this area, namely conic optimization and its emerging applications. First, we discuss the importance of conic optimization in different areas. Then, we explain seminal results on the design of hierarchies of convex relaxations for a wide range of nonconvex problems. Finally, we study different numerical algorithms for large-scale conic optimization problems.
AB - Optimization is at the core of control theory and appears in several areas of this field, such as optimal control, distributed control, system identification, robust control, state estimation, model predictive control and dynamic programming. The recent advances in various topics of modern optimization have also been revamping the area of machine learning. Motivated by the crucial role of optimization theory in the design, analysis, control and operation of real-world systems, this tutorial paper offers a detailed overview of some major advances in this area, namely conic optimization and its emerging applications. First, we discuss the importance of conic optimization in different areas. Then, we explain seminal results on the design of hierarchies of convex relaxations for a wide range of nonconvex problems. Finally, we study different numerical algorithms for large-scale conic optimization problems.
UR - http://www.scopus.com/inward/record.url?scp=85052572864&partnerID=8YFLogxK
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U2 - 10.23919/ACC.2018.8430887
DO - 10.23919/ACC.2018.8430887
M3 - Conference contribution
AN - SCOPUS:85052572864
SN - 9781538654286
T3 - Proceedings of the American Control Conference
SP - 798
EP - 815
BT - 2018 Annual American Control Conference, ACC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 June 2018 through 29 June 2018
ER -