Generation of optimal trajectories for soft landing on the lunar surface, with optimal control approach using Particle Swarm Programming
Document Type : selected article
Authors
1
Faculty of Mechanical Engineering, University of Guilan, Iran
2
Faculty of mechanical engineering, University of Guilan, Rasht, Iran
3
University of RMIT, Melbourne, Australia
Abstract
In this article, the optimal path for the soft landing on the lunar surface is generated. Path planning is defined as an optimization problem that aims to achieve the optimal control function for the spacecraft. The thrust value of the device is fixed and the thrust angle is considered as a control variable. The objective function is to minimize the landing time and actually maximize the mass of the device at the moment of landing. The speed constraints related to the soft landing of the vehicle are also included in the objective function in the form of a cost function. Due to the unstructured and infinite search space, a new meta-heuristic algorithm called Particle Swarm Programming is used to find the optimal controller function. This algorithm is based on the Particle Swarm Optimization algorithm and has a favorable performance in the simultaneous optimization of the structure and parameters. The design of the controller was done in two types: open-loop, time-dependent, and closed-loop, time-independent, and in both types, it was able to find the optimal solution for the controller function. The resulting numerical results show a very high agreement of the controller function with the response of other optimization methods. Finally, to make the simulation more realistic, the turbulence conditions are applied to the spacecraft thrust force and the results prove the superiority of the closed-loop, time-independent controller.
Keywords
Subjects
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[5] X. Wu, K. Zhang, X. Xin and C. Ming, "Fuel-optimal control for soft lunar landing based on a quadratic regularization approach", European Journal of Control, vol. 49, pp. 84-93, 2019.
[6] Q.B. PENG, H.Y. LI, H.X. SHEN and G.J. TANG, "Hybrid optimization of powered descent trajectory for manned lunar mission", TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, vol. 56, no. 3, pp. 113-120, 2013.
[7] A. Banerjee and R. Padhi, "Multi-phase MPSP Guidance for Lunar Soft Landing," Transactions of the Indian National Academy of Engineering, vol. 5, pp. 61-74, 2020.
[8] N. Remesh, R. Ramanan and V. Lalithambika, "Fuel-optimal and Energy-optimal guidance schemes for lunar soft landing at a desired location", Advances in Space Research, vol. 67, no. 6, 2021.
[9] A. D’Ambrosio, A. Carbone, D. Spiller and F. Curti, "PSO-Based Soft Lunar Landing with Hazard Avoidance: Analysis and Experimentation", Aerospace, vol. 8, 2021.
[10] R. Jamilnia, "Designing and comparing of strategies for soft landing on the Moon using direct collocation (in Persian)" ,in The 20th Conference of Iranian AerospaceSociety,Malek-Ashtar University of Technology, Tehran, 2022.
[11] K. Wang, Z. Chen and J. Li, "Fuel-Optimal Trajectory Planning for Lunar Vertical Landing", Guidance, Navigation and Control, vol. 4, 2024.
[12] J. Kennedy and R. Eberhart, "Particle Swarm Optimization",inProceedings of IEEE International Conference on Neural Networks. IV., 1995.
[13] Z. Liu, P. Zhu, W. Chen and R.J. Yang, "Improved particle swarm optimization algorithm using design of experiment and data mining techniques", Structural and Multidisciplinary Optimization, 2015.
[14] K. Hasan and C. Rahime, "A PSO based approach: Scout particle swarm algorithm for continuous global optimization problems", Computational Design and Engineering, vol. 6, no. 2, p. 129–142, 2019.
[15] W. Zongshan, D. Hongwei, W. Jie, H. Peng, L. Aishan, Y. Zhijun and H. Xiang, "Adaptive guided salp swarm algorithm with velocity clamping mechanism for solving optimization problems", Computational Design and Engineering, vol. 9, no. 6, p. 2196–2234, 2022.
[16] H. R. Rafat Zaman and F. Soleimanian Gharehchopogh, "An improved particle swarm optimization with backtracking search optimization algorithm for solving continuous optimization problems", Engineering with Computers , vol. 38, p. 2797–2831, 2022.
[17] F. Rossi, P. v. Beek and T. Walsh, "Soft Constraints", in Handbook of Constraint Programming, Elsevier, 2006, pp. 281-328.
[18] M. Clerc and J. Kennedy, "The particle swarm - explosion, stability, and convergence in a multidimensional complex space", IEEE Transactions on Evolutionary Computation, vol. 6, no. 1, 2002.
[19] P. Mercorelli, T. V. Niekerk and O. Sergiyenko, "A PD Regulator to Minimize Noise Effect Using a Minimal Variance Method for Soft Landing Control of an Electromagnetic Valve Actuator", in IEEE AFRICON, Cape Town, 2017.
Volume 4, Issue 2
March 2025Pages 134-152
- Receive Date 02 October 2024
- Revise Date 10 November 2024
- Accept Date 08 January 2025