Trajectory optimization of space vehicle in rendezvous proximity operation with evolutionary feasibility conserving techniques. (January 2023)

• Record Type: Journal Article
• Authors: Shirazi, Abolfazl; Ceberio, Josu; Lozano, Jose A.
• Is Part Of: Engineering applications of artificial intelligence. Volume 117:Part A(2023)
• Publication Date: 2023-01
• Subjects: Trajectory optimization -- Space transportation -- Estimation of distribution algorithms -- Satellite rendezvous -- Proximity operation; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105523
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: In this paper, a direct approach is developed for discovering optimal transfer trajectories of close-range rendezvous of satellites considering disturbances in elliptical orbits. The control vector representing the inputs is parameterized via different interpolation methods, and an Estimation of Distribution Algorithm (EDA) that implements mixtures of probability models is presented. To satisfy the terminal conditions, which are represented as non-linear inequality constraints, several feasibility conserving mechanisms associated with learning and sampling methods of the EDAs are proposed, which guarantee the feasibility of the explored solutions. They include a particular implementation of a clustering algorithm, outlier detection, and several heuristic mapping methods. The combination of the proposed operators guides the optimization process in achieving the optimal solution by surfing the regions of the search domain associated with feasible solutions. Numerical simulations confirm that space transfer trajectories with minimum-fuel consumption for the chaser spacecraft can be obtained with terminal condition satisfaction in rendezvous proximity operation. Highlights: Trajectory optimization in close-range space rendezvous mission is considered. An evolutionary algorithm based on Estimation of Distribution Algorithms is proposed. Novel feasibility conserving mechanisms are employed in the algorithm. Results indicate the effectiveness and the efficiency of the proposed approach.