Browsing by Author "Zaragoza Prous, Guillermo"

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    A decreasing horizon model predictive control for landing reusable launch vehicles
    (MDPI, 2025-02-01) Zaragoza Prous, Guillermo; Grustan-Gutierrez, Enric; Felicetti, Leonard
    A novel approach to model predictive control (MPC) with a decreasing horizon is analysed for guiding and controlling reusable launch vehicles (RLVs) during powered descent phases. Conventional MPC methods typically use receding horizons, where optimal control inputs are computed over fixed time intervals. However, when applied directly, these methods can cause a hovering-like behaviour, preventing the vehicle from reaching the landing platform, as the landing time is continually deferred at each iteration. The proposed solution addresses this problem by adjusting the prediction horizon dynamically, reducing its length over time. This dynamic adjustment is driven by a time-scaling factor and the time elapsed since the previous MPC iteration. Optimal control solutions are derived through convex optimization techniques. To evaluate the algorithm’s robustness against initial conditions, a Monte Carlo analysis is performed by varying initial position, velocity and mass. This method can also be used as a viable methodology for selecting tuning parameters for the MPC to ensure a successful and safe landing for a wide range of initial conditions.
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    Application of nanosatellites for lunar missions
    (IEEE, 2021-06-07) Bellome, Andrea; Nakhaee-Zadeh, Aydin; Zaragoza Prous, Guillermo; Leng, Louis; Coyle, Matthew; D'Souza, Sharon; Mummigatti, Suchetan; Serfontein, Zaria
    Two major themes for the space sector in recent years have been the resurgence of missions to the Moon, facilitating the expansion of human presence into the Solar System, and the rapid growth in CubeSat launches. Lunar missions will play an important role in sustainable space exploration, as discussed in the Global Exploration Roadmap. The Roadmap outlines the next steps for the current and next generation of explorers and reaffirms the interest of 14 space agencies to return to the Moon. Over the past decade, a more daring approach to space innovation and the proliferation of low-cost small satellites have invited commercialization and, subsequently, have accelerated the development of miniaturized technologies and substantially reduced the costs associated with CubeSats. In this context, CubeSats are increasingly being considered as platforms for pioneering missions beyond low-Earth orbit. This paper describes a 3U nanosatellite mission to the Moon, designed as part of the UKSEDS Satellite Design Competition, capable of capturing and analysing details of the lunar environment. To achieve the primary mission objectives, a camera and an infrared spectrometer have been included to relay information about historic lunar landmarks to Earth. The design was developed to be integrated with Open Cosmos' OpenKit and reviewed by experts in the field from SSPI. The paper includes a detailed assessment of the current state of miniaturized instruments and the quality of scientific return which can be achieved by a lunar CubeSat mission. This concludes in an overall feasibility study of lunar CubeSats, a discussion of the current limitations and challenges associated with CubeSat technologies and a framework for future missions.
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    Model predictive control strategy with a decreasing horizon interval for a reusable launcher in a landing scenario
    (International Astronautical Federation (IAF), 2024-10-18) Zaragoza Prous, Guillermo; Felicetti, Leonard; Grustan Gutierrez, Enric
    The descending and landing problem of an Reusable Launch Vehicle (RLV) concerns a wide variety of factors to overcome, such as the instability generated due to the aerodynamic forces during the descent phases and the strict requirements for accurate pinpoint landing to be met with limited control authority. In addition, the Guidance algorithm needs to be continuously and rapidly updated, in order to cope with the dynamically changing conditions that the RLV can experience during the re-entry and landing phase. One of the key technologies being studied to solve this problem is Model Predictive Control (MPC). MPC uses a linearized model of the problem to obtain a solution of the scenario, given a specific landing time in the future, called the prediction horizon (PH). In this paper, a new strategy to manage the PH of an MPC scheme is proposed for the landing scenario of an RLV. This strategy considers an offline predefined interval of PHs to obtain a valid solution instead of a single predefined PH. This strategy guarantees a wider set of feasible solutions to be searched with a Convex Optimization method, increasing the robustness of the algorithm at the guidance stage. A simulation setup is introduced for the landing scenario of an RLV, including full simulation of translational and rotational dynamics, along with the control laws to actuate each of the actuators of the vehicle. The results of the presented algorithm are then shown for the landing scenario of the first stage of a rocket.
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    A shrinking horizon model predictive control for landing of reusable launch vehicles
    (International Astronautical Federation (IAF), 2022-09-22) Zaragoza Prous, Guillermo; Felicetti, Leonard
    The recent advancements of the onboard computational capabilities enable the deployment of GNC algorithms to perform autonomous decisions and complex operations in the final stages of a landing manoeuvre of Reusable Launch Vehicles (RLV). In most cases, such algorithms embed model predictive schemes to optimize during flight by offering a wider versatility compared to classical schemes and the capabilities of identifying potential future behaviours and risks for the mission. Applications such as the vertical landing of reusable launchers (i.e. SpaceX Falcon 9, and Blue Origin New Shepard) and planetary landers (NASA Perseverance) are currently operating or under development by considering the potential benefits of such a technology. A shrinking horizon Model Predictive Control (MPC) is proposed for the guidance and control of RLV during powered descent phases. Standard MPC schemes use receding horizons where the optimal controls are calculated during constant time-length intervals. The direct implementation of such schemes leads to a hovering-like behaviour of the vehicle, which will never reach the landing platform as the final time of landing is always postponed at each iteration step. The solution proposed in this paper consists on implementing an MPC algorithm that calculates and updates the optimal thrust profile along time-dependent decreasing horizons. The algorithm updates and adapts the time-length of the receding horizon as a function of a time-scaling factor and the time that has passed since the last MPC iteration. It introduces a new concept called terminal horizon, which determines the maximum time in which the RLV must be landed. The optimal solutions are found through convex optimisation algorithms. Numerical simulations and results show an enhanced performance of the guidance scheme and validate the idea that a decreasing horizon is more suitable than a receding one in a powered descent scenario. Monte Carlo and Parametric analyses are performed to assess the performance of the proposed algorithm in a landing test case scenario. This simulated case considers the disturbances caused by Earth’s atmosphere drag force in interaction with a descending first stage of SpaceX Falcon 9 rocket. This study demonstrates the applicability of the proposed MPC technique identifying feasibility boundaries for tuning the MPC parameters and determining the range of initial conditions that allow for a successful landing.