Quantum-behaved particle swarm optimization for far-distance rapid cooperative rendezvous between two spacecraft

• Published in: Advances in space research Vol. 62; no. 11; pp. 2998 - 3011
• Main Authors: Yang, Kun, Feng, Weiming, Liu, Gang, Zhao, Junfeng, Su, Piaoyi
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2018
• Subjects: Cooperative rendezvous; Optimal control; Particle Swarm Optimization (PSO); Quantum-behaved Particle Swarm Optimization (QPSO); Sequential Quadratic Programming (SQP); Cooperative rendezvous; Optimal control; Quantum-behaved Particle Swarm Optimization (QPSO); Sequential Quadratic Programming (SQP); Particle Swarm Optimization (PSO)
• ISSN: 0273-1177; 1879-1948
• DOI: 10.1016/j.asr.2018.08.006

•Obtain the optimal solution of far rapid cooperative rendezvous in general case.•Design QPSO-SQP and proving the advance of QPSO-SQP.•Solve the complex optimal control problem with 29 variables. Focused on far-distance rapid cooperative rendezvous between two spacecraft under continuous large thrust, this paper presents a series of artificial intelligence algorithms for fuel and time optimization. The process of far-distance rapid cooperative rendezvous was optimized by a type of hybrid algorithm-integrated Quantum-behaved Particle Swarm Optimization (QPSO) and Sequential Quadratic Programming (SQP). The convergent co-state vectors were obtained by QPSO and subsequently set as the initial values of SQP to search for the exact solutions in a smaller area. Applications of non-coplanar cooperative rendezvous are provided to demonstrate that the QPSO-SQP algorithm has better performance than other popular algorithms in less time consumption, faster convergence rate and highly stable solutions.