Article
Engineering, Aerospace
Xin Sun, Baihai Zhang, Runqi Chai, Antonios Tsourdos, Senchun Chai
Summary: This article presents a novel approach for solving chance-constrained trajectory optimization problems in nonlinear dynamic systems. By transforming the chance constraints into deterministic ones and utilizing iterative convex optimization and successive linearization algorithms, feasible trajectory solutions are obtained.
AEROSPACE SCIENCE AND TECHNOLOGY
(2022)
Article
Automation & Control Systems
Juho Bae, Sang-Don Lee, Young-Won Kim, Chang-Hun Lee, Sung-Yug Kim
Summary: This paper proposes a convex-optimization-based entry guidance method for a spaceplane, which can be implemented online and is less sensitive to initial guess accuracy while mitigating a high-frequency jittering issue. The highly nonlinear, constrained, and nonconvex entry guidance problem is transformed into sequential convex sub-problems using a combination of successive linearization and convexification techniques.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2022)
Article
Computer Science, Information Systems
Baha Alzalg, Hadjer Alioui
Summary: This paper discusses five applications that lead to stochastic mixed-integer second-order cone programming problems, presents solution algorithms for solving these problems, and explores how bringing applications to the surface can detect tractable special cases.
Article
Engineering, Electrical & Electronic
Tohid Akbari, Saeed Zolfaghari Moghaddam
Summary: This paper proposes a new mathematical framework for distribution expansion planning (DEP), which models the uncertainties associated with electric demand and wind production using plausible ellipsoidal uncertainty sets. A hybrid model combining stochastic programming and robust optimization is constructed to tackle the problem. Numerical simulations demonstrate the superiority of the hybrid model compared to existing ones.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Wenhao Jia, Tao Ding, Mohammad Shahidehpour
Summary: The paper proposes a data-driven approach to fit the fluid and gas energy flow equations by polynomial functions through experimental data, and establishes a convex optimization model to find the solution. It also suggests a tight reformulation to exactly reformulate the model as a second-order cone programming (SOCP) for tractable solution.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Computer Science, Software Engineering
Roberto Andreani, Gabriel Haeser, Leonardo M. Mito, Hector Ramirez, Thiago P. Silveira
Summary: In this paper, a general and geometric approach is proposed for defining a new extension of the constant rank condition to the conic context. The main advantage is that the strong second-order properties of the constant rank condition can be recast in a conic context. Specifically, a second-order necessary optimality condition is obtained that is stronger than the classical one obtained under Robinson's constraint qualification.
MATHEMATICAL PROGRAMMING
(2023)
Article
Computer Science, Artificial Intelligence
Zemin Zong, Xuewen Mu
Summary: A new second-order cone programming (SOCP) formulation is proposed in this study, inspired by the soft-margin linear programming support vector machine (LP-SVM) formulation and cost-sensitive framework. The proposed method maximizes slack variables for each class, relaxes the bounds on the VC dimension using the l(infinity)-norm, and penalizes them using corresponding regularization parametrization. It offers a flexible classifier extending the advantages of soft-margin LP-SVM to the second-order cone, and solves only two SOCP problems with second-order cone constraints, resulting in similar results to SOCP-SVM problem with less computational effort. Numerical experiments demonstrate that the proposed method outperforms conventional SOCP-SVM formulations and standard linear SVM formulations in terms of classification performance.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Josh A. Taylor, Alain Rapaport
Summary: The study focuses on maximizing biogas production in a gradostat, with a main technical emphasis on the nonconvex constraint describing microbial growth. By formulating a relaxation and using numerical approximations, steady state models are extended to multiple time periods, resulting in second-order cone programs solvable with standard industrial software.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Khalil Gholami, Ali Azizivahed, Li Li, Jiangfeng Zhang
Summary: Optimal power flow is an important tool for power system operations, but its non-linear AC power flow equations present challenges for finding a global optimum. This paper proposes a new method using semi-Lorentz transformation to approach the global optimum of AC OPF relaxed by SOCP. Comparative analysis in case studies demonstrates the robust precision and higher efficiency of the proposed method.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Jianzhe Zhen, Frans J. C. T. de Ruiter, Ernst Roos, Dick den Hertog
Summary: This paper proposes a computationally tractable approximation for solving nonlinear optimization problems with uncertain second-order cone and semidefinite programming constraints. Extensive computational experiments demonstrate the effectiveness and efficiency of the proposed approach in solving various problems such as computing the minimum volume circumscribing ellipsoid, robust regressions, and robust sensor networks.
INFORMS JOURNAL ON COMPUTING
(2022)
Article
Operations Research & Management Science
Nguyen T. V. Hang, Boris S. Mordukhovich, M. Ebrahim Sarabi
Summary: This paper focuses on the augmented Lagrangian method for second-order cone programming, establishing a uniform second-order growth condition using generalized differential tools of second-order variational analysis and proving the solvability of subproblems and linear primal-dual convergence of this method.
JOURNAL OF GLOBAL OPTIMIZATION
(2022)
Article
Robotics
John N. Nganga, Patrick M. Wensing
Summary: This study introduces a method to reduce the computational demands when incorporating second-order dynamics sensitivity information into the DDP algorithm. By leveraging reverse-mode accumulation of derivative information to compute a key vector-tensor product directly, the need for computing the derivative tensor can be avoided, leading to faster computation. The benchmarks show that benefits of DDP can be achieved without sacrificing evaluation time, and in fewer iterations compared to iLQR.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Operations Research & Management Science
Arezu Zare
Summary: This study presents an equivalent quadratic reformulation of the non-convex quadratic fractional optimization problem using the Dinkelbach method. The global optimum is obtained by applying the semidefinite relaxation approach and rank-one decomposition algorithm at each iteration. Experimental results demonstrate the effectiveness of the proposed methods.
OPTIMIZATION LETTERS
(2023)
Article
Automation & Control Systems
Shuyao Tan, Emna Krichen, Alain Rapaport, Elodie Passeport, Josh A. Taylor
Summary: This paper investigates the fitting of data using second-order cone programming, particularly in the context of biochemical process optimization. We solve the nonconvex fitting problem using the concave-convex procedure, and validate the effectiveness of our approach through experiments.
JOURNAL OF PROCESS CONTROL
(2022)
Article
Mathematics, Applied
Cheolmin Kim, Sanjay Mehrotra
Summary: The study focuses on linear fractional programming problems and proposes a novel reformulation method, developing a solution algorithm based on second order cone programs. It iteratively refines piecewise linear approximations by dividing hyper-rectangles, achieving good results in solving the problem efficiently.
SIAM JOURNAL ON OPTIMIZATION
(2021)
Article
Engineering, Aerospace
Xinfu Liu, Zuojun Shen, Ping Lu
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2016)
Article
Engineering, Aerospace
Binfeng Pan, Ping Lu, Xun Pan, Yangyang Ma
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2016)
Editorial Material
Engineering, Aerospace
Ping Lu
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2017)
Article
Engineering, Aerospace
Ping Lu, Christopher W. Brunner, Susan J. Stachowiak, Gavin F. Mendeck, Michael A. Tigges, Christopher J. Cerimele
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2017)
Article
Engineering, Aerospace
Xinfu Liu, Zuojun Shen, Ping Lu
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2017)
Article
Engineering, Aerospace
Ping Lu
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2018)
Article
Engineering, Aerospace
Robin M. Pinson, Ping Lu
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2018)
Article
Engineering, Aerospace
Ping Lu
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2019)
Article
Engineering, Aerospace
Changhuang Wan, Ran Dai, Ping Lu
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2019)
Article
Engineering, Aerospace
Ping Lu, Ryan Callan
Summary: This paper presents new and significant advances in propellant-optimal powered descent guidance based on the indirect method. By taking a fully numerical approach, the paper improves the recent indirect method and develops a fully automated algorithm capable of generating the complete optimal powered descent trajectory subject to imposed constraints. It also proposes a guidance approach to mitigate the risk of solution degradation in a closed-loop solution.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2023)
Article
Engineering, Aerospace
Binfeng Pan, Yang Ni, Yangyang Ma, Ping Lu
Summary: This paper proposes a novel smoothing homotopy paradigm inspired by widely used smoothing techniques in image processing and statistical analysis, for solving general optimal control problems with the indirect method. Unlike existing approaches, the sensitivity associated with the two-point-boundary-value problem (TPBVP) in optimal control is reduced by convolving an appropriate part of the TPBVP with a smoothing kernel. The homotopic process is applied to the bandwidth of the smoothing, and two different smoothing homotopy methods are developed based on the choice of a Gaussian or non-Gaussian kernel, each with distinctive features.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2023)
Article
Engineering, Aerospace
Ping Lu, Alexander Lewis, Richard J. Adams, Michael D. DeVore, Christopher D. Petersen
Summary: A methodology using convex optimization is developed to find the propellant-optimal finite-thrust trajectory of a spacecraft to inject into a specified NMC orbit, by introducing a new philosophical perspective and showing the NMC problem equivalent to a two-dimensional constrained optimization problem. Two numerical approaches, based on convex relaxation and linearization-projection, are investigated and complement each other to cover all possible cases. A hybrid algorithm is designed to solve the NMC problem reliably and rapidly without user-supplied parameters or initial guesses.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2021)
Article
Engineering, Aerospace
Xinfu Liu, Ping Lu, Binfeng Pan
Proceedings Paper
Engineering, Aerospace
Robin Pinson, Ping Lu
ASTRODYNAMICS 2015
(2016)
