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We propose a sampling-based trajectory optimization methodology for constrained problems. We extend recent works on stochastic search to deal with box control constraints,as well as nonlinear state constraints for discrete dynamical…

Optimization and Control · Mathematics 2019-11-13 George I. Boutselis , Ziyi Wang , Evangelos A. Theodorou

Dynamic Optimization Problems (DOPs) are challenging to address due to their complex nature, i.e., dynamic environment variation. Evolutionary Computation methods are generally advantaged in solving DOPs since they resemble dynamic…

Neural and Evolutionary Computing · Computer Science 2026-02-02 Zijian Gao , Yuanting Zhong , Zeyuan Ma , Yue-Jiao Gong , Hongshu Guo

This paper focuses on robustness to disturbance forces and uncertain payloads. We present a novel formulation to optimize the robustness of dynamic trajectories. A straightforward transcription of this formulation into a nonlinear…

Robotics · Computer Science 2020-08-04 Henrique Ferrolho , Wolfgang Merkt , Vladimir Ivan , Wouter Wolfslag , Sethu Vijayakumar

This note uses the Total Least-Squares (TLS) line-fitting problem as a canvas to explore some modern optimization tools. The contribution is meant to be tutorial in nature. The TLS problem has a lot of mathematical similarities to important…

Robotics · Computer Science 2022-06-13 Timothy D Barfoot , Connor Holmes , Frederike Dumbgen

This paper presents a method to verify closed-loop properties of optimization-based controllers for deterministic and stochastic constrained polynomial discrete-time dynamical systems. The closed-loop properties amenable to the proposed…

Optimization and Control · Mathematics 2016-11-16 Milan Korda , Colin N. Jones

In this article, we address a class of non convex, integer, non linear mathematical programs using dynamic programming. The mathematical program considered, whose properties are studied in this article, may be used to model the optimal…

Discrete Mathematics · Computer Science 2021-12-28 David Nizard , Nicolas Dupin , Dominique Quadri

Investigation of detailed and complex optimisation problem formulations that reflect realistic scenarios is a burgeoning field of research. A growing body of work exists for the Travelling Thief Problem, including multi-objective…

Neural and Evolutionary Computing · Computer Science 2020-02-10 Daniel Herring , Michael Kirley , Xin Yao

In this paper, we address the problem of closed-loop control of nonlinear dynamical systems subjected to probabilistic uncertainties. More precisely, we design time-varying polynomial feedback controllers to follow the given nominal…

Optimization and Control · Mathematics 2019-12-10 Ashkan Jasour , Brian Williams

The standard quadratic optimization problem (StQP) consists of minimizing a quadratic form over the standard simplex. Without convexity or concavity of the quadratic form, the StQP is NP-hard. This problem has many relevant real-life…

Optimization and Control · Mathematics 2025-04-10 Immanuel M. Bomze , Daniel de Vicente

Systematic design and verification of advanced control strategies for complex systems under uncertainty largely remains an open problem. Despite the promise of blackbox optimization methods for automated controller tuning, they generally…

Systems and Control · Electrical Eng. & Systems 2020-11-17 Joel A. Paulson , Ali Mesbah

We develop an optimization-based framework for joint real-time trajectory planning and feedback control of feedback-linearizable systems. To achieve this goal, we define a target trajectory as the optimal solution of a time-varying…

Systems and Control · Electrical Eng. & Systems 2020-03-17 Tianqi Zheng , John Simpson-Porco , Enrique Mallada

This paper presents a Segmented Trajectory Optimization (STO) method for autonomous parking, which refines an initial trajectory into a dynamically feasible and collision-free one using an iterative SQP-based approach. STO maintains the…

Robotics · Computer Science 2025-09-05 Hang Yu , Renjie Li

Equipping approximate dynamic programming (ADP) with inputconstraints has a tremendous significance. This enables ADP to be applied tothe systems with actuator limitations, which is quite common for dynamicalsystems. In a conventional…

Optimization and Control · Mathematics 2018-05-24 Xuefeng Bao , Zhi-Hong Mao , Nitin Sharma

A promising approach to optimal control of nonlinear systems involves iteratively linearizing the system and solving an optimization problem at each time instant to determine the optimal control input. Since this approach relies on online…

Optimization and Control · Mathematics 2025-01-30 Anran Li , John P. Swensen , Mehdi Hosseinzadeh

Existing works on "black-box" model interpretation use local-linear approximations to explain the predictions made for each data instance in terms of the importance assigned to the different features for arriving at the prediction. These…

Machine Learning · Computer Science 2019-08-28 Kartik Ahuja , William Zame , Mihaela van der Schaar

Classical adaptive control proves total-system stability for control of linear plants, but only for plants meeting very restrictive assumptions. Approximate Dynamic Programming (ADP) has the potential, in principle, to ensure stability…

adap-org · Physics 2015-06-24 Paul J. Werbos

We study the problem of predictive runtime monitoring of black-box dynamical systems with quantitative safety properties. The black-box setting stipulates that the exact semantics of the dynamical system and the controller are unknown, and…

Systems and Control · Electrical Eng. & Systems 2024-12-24 Thomas A. Henzinger , Fabian Kresse , Kaushik Mallik , Emily Yu , Đorđe Žikelić

The Standard Quadratic optimization Problem (StQP), arguably the simplest among all classes of NP-hard optimization problems, consists of extremizing a quadratic form (the simplest nonlinear polynomial) over the standard simplex (the…

Optimization and Control · Mathematics 2024-06-04 Immanuel Bomze , Bo Peng , Yuzhou Qiu , E. Alper Yildirim

In the article Positive Dynamic Programming, David Blackwell tries to answer the question concerning the existence of optimal stationary strategies for a positive dynamic programming problem. The principal results obtained in the paper are…

Optimization and Control · Mathematics 2024-08-07 Aaqib Peerzada

We present DDTO--deferred-decision trajectory optimization--a framework for trajectory generation with resilience to unmodeled uncertainties and contingencies. The key idea is to ensure that a collection of candidate targets is reachable…

Optimization and Control · Mathematics 2025-02-11 Purnanand Elango , Selahattin Burak Sarsilmaz , Behcet Acikmese