Change search
Link to record
Permanent link

Direct link
BETA
Publications (4 of 4) Show all publications
Li, Y., Zhang, H., Yao, Y. & Hu, X. (2018). A Convex Optimization Approach to Inverse Optimal Control. In: Chen, X Zhao, QC (Ed.), 2018 37Th Chinese Control Conference, CCC (CCC): . Paper presented at 37th Chinese Control Conference, CCC 2018; Wuhan; China; 25 July 2018 through 27 July 2018 (pp. 257-262). IEEE, 2018
Open this publication in new window or tab >>A Convex Optimization Approach to Inverse Optimal Control
2018 (English)In: 2018 37Th Chinese Control Conference, CCC (CCC) / [ed] Chen, X Zhao, QC, IEEE, 2018, Vol. 2018, p. 257-262Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, the problem of inverse optimal control (IOC) is investigated, where the quadratic cost function of a dynamic process is required to be recovered based on the observation of optimal control sequences. In order to guarantee the feasibility of the problem, the IOC is reformulated as an infinite-dimensional convex optimization problem, which is then solved in the primal-dual framework. In addition, the feasibility of the original IOC could be determined from the optimal value of reformulated problem, which also gives out an approximate solution when the original problem is not feasible. In addition, several simplification methods are proposed to facilitate the computation, by which the problem is reduced to a boundary value problem of ordinary differential equations. Finally, numerical simulations are used to demonstrate the effectiveness and feasibility of the proposed methods.

Place, publisher, year, edition, pages
IEEE, 2018
Series
Chinese Control Conference, ISSN 2161-2927
Keywords
Inverse optimal control, Convex optimization, Primal-dual method
National Category
Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-254152 (URN)10.23919/ChiCC.2018.8482872 (DOI)000468622100046 ()2-s2.0-85056081591 (Scopus ID)978-9-8815-6395-8 (ISBN)
Conference
37th Chinese Control Conference, CCC 2018; Wuhan; China; 25 July 2018 through 27 July 2018
Note

QC 20190620

Available from: 2019-06-20 Created: 2019-06-20 Last updated: 2019-06-20Bibliographically approved
Li, Y. & Hu, X.A Differential Game Approach to Optimal Intrinsic Formation Control.
Open this publication in new window or tab >>A Differential Game Approach to Optimal Intrinsic Formation Control
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In this paper, the optimal formation control problem of a multi-agent system is investigated. The foraging behavior of N agents is modeled as a finite-horizon non-cooperative differential game under local information, and its Nash equilibrium is studied. The formations are achieved in an intrinsic way in the sense that they are only attributed to the inter-agent interaction and geometric properties of the network, where the desired formations are not designated beforehand. Through the design of individual costs and network topology, regular polygons, antipodal formations and Platonic solids can be achieved as Nash equilibria while inter-agent collisions are avoided. Finally, numerical simulations are provided in both two-dimensional and three-dimensional Euclidean space to demonstrate the effectiveness and feasibility of the proposed methods.

Keywords
Noncooperative differential game, distributed formation control, collision free.
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-252435 (URN)
Note

QC 20190529

Available from: 2019-05-29 Created: 2019-05-29 Last updated: 2019-10-18Bibliographically approved
Li, Y., Yao, Y. & Hu, X.Continuous-Time Inverse Quadratic Optimal Control Problem.
Open this publication in new window or tab >>Continuous-Time Inverse Quadratic Optimal Control Problem
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In this paper, the problem of finite horizon inverse optimal control (IOC) is investigated, where the quadratic cost function of a dynamic process is required to be recovered based on the observation of optimal control sequences.We propose the first complete result of the necessary and sufficient condition for the existence of corresponding LQ cost functions. Under feasible cases, the analytic expression of the whole solution space is derived and the equivalence of weighting matrices in LQ problems is discussed. For infeasible problems, an infinite dimensional convex problem is formulated to obtain a best-fit approximate solution with minimal control residual. And the optimality condition is solved under a static quadratic programming framework to facilitate the computation. Finally, numerical simulations are used to demonstrate the effectiveness and feasibility of the proposed methods.

Keywords
Inverse optimization, linear quadratic problem, linear matrix inequality.
National Category
Mathematics Control Engineering
Research subject
Applied and Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-252347 (URN)
Note

QC 20190529

Available from: 2019-05-28 Created: 2019-05-28 Last updated: 2019-06-03Bibliographically approved
Li, Y., Wang, X., Djehiche, B. & Hu, X.Credit Scoring by Incorporating Dynamic Network Information.
Open this publication in new window or tab >>Credit Scoring by Incorporating Dynamic Network Information
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In this paper,  the credit scoring problem is studied by incorporating network information, where the advantages of such incorporation are investigated in two scenarios. Firstly, a Bayesian optimal filter is proposed to provide a prediction for lenders assuming that published credit scores are estimated merely from structured individual data. Such prediction is used as a monitoring indicator for the risk warning  in lenders' future financial decisions. Secondly, we further propose a recursive Bayes estimator to improve the accuracy of credit scoring estimation by incorporating the dynamic interaction topology of clients as well. It is shown that under the proposed evolution framework, the designed estimator has a higher precision than any efficient estimator, and the mean square errors are strictly smaller than the Cram\'er--Rao lower bound for clients within a certain range of scores. Finally, simulation results for a specific case illustrate the effectiveness and feasibility of the proposed methods.

Keywords
Credit scoring, network information, Bayesian filtering, average risk minimization.
National Category
Mathematics Economics
Research subject
Applied and Computational Mathematics; Economics
Identifiers
urn:nbn:se:kth:diva-252433 (URN)
Note

QC 20190529

Available from: 2019-05-29 Created: 2019-05-29 Last updated: 2019-06-03Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-7287-1495,

Search in DiVA

Show all publications