Work

Optimal Trajectory Tracking Using Newton and Levenberg‐Marquardt‐Like Algorithms for Constrained Time‐Varying Optimization

Year: 2025

Type: article

Abstract: ABSTRACT In this paper, we propose continuous‐time algorithms for tracking the optimal trajectory of time‐varying optimization problems with time‐varying constraints in a predefined time, where the time of convergence is selected a priori. A robust Newton‐like approach is developed for the cases, where the exact knowledge of the rate of change of the gradient of objective function is unknown. Levenberg‐Marquardt‐like algorithm is proposed for the cases when the Hessian of the objective function is singular or near singular. Lyapunov‐based convergence analysis is discussed for the proposed algorithms. Simulation results for time‐varying optimization problems show the efficacy of the proposed approach. We demonstrate the applicability of the proposed method through its use in a collision‐free robot navigation problem.

Source: Optimal Control Applications and Methods

DOI: 10.1002/oca.3292

Authors: Sunidhi Pandey, Parijat Prasun, Shyam Kamal, Devender Singh, Debdas Ghosh, Sorin Olaru

Institutions: Indian Institute of Technology BHU, Centre National de la Recherche Scientifique, Université Paris-Saclay, Laboratoire des signaux et systèmes, CentraleSupélec

Language: English

Topic: Advanced Control Systems Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4409857039

FWCI: 1.901

Cites: 24

Cited by: 5

Related to: 10