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Multiple-Horizon Model Predictive Control of Spacecraft for Landing on Asteroids

Alandi Hallaj, Mohammad Amin | 2018

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 51542 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Asadian, Nima
  7. Abstract:
  8. This dissertation investigates the Multiple-Horizon Multiple-Model Predictive Control method and its application in soft landing problem on an irregular-shaped asteroid. In this way, a predictive framework including a heuristic guidance law named Predictive Path Planning and Multiple-Horizon Multiple-Model Predictive Control (MHMM-PC) as the control scheme is introduced for soft landing on an asteroid. Obviously, reducing the fuel consumption is a priority in space missions. Thus, the employed control framework should minimize the required control effort. Furthermore, the control method should be robust enough to deal with the effects of model uncertainties and disturbances. The unique feature of MPC has the prediction-based decision making process, which might be useful in space missions. One of the major problems with nonlinear Model Predictive Control (MPC) is its computational complexity, which in turn does not let the control method be used in real-time. This fact is validated that not all of the information over a finite horizon is needed for a decision-making process. In addition, it is not necessary to use an exact dynamics model to predict the system’s behavior during a long period. Furthermore, it is proposed that all of the environment information should be used for close future while only the key information of the far future can be employed. Multiple-Horizon Multiple-Model Predictive Control is employed to make the spacecraft track the designed reference trajectory. The MHMM-PC, which is an MPC scheme, utilizes several prediction models instead of one. Not only does the presented guidance law satisfy the collision avoidance constraint, but also guarantees the landing accuracy and vertical landing condition. In this manner, the introduced control approach heritages the advantages of optimality and tackling external disturbances and model uncertainties from classical MPC and at the same time has the advantage of lower computational burden than MPC
  9. Keywords:
  10. Model Predictive Control ; Multiple Horizon Model Predictive Control ; Probabilistic Multiple-horizon Model Predictive Control ; Asteroid Landing ; Stochastic Control

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