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Any space trajectories are subject to state uncertainty due to imperfect state knowledge, random disturbances, and partially known dynamical environments. Ideally, such uncertainty and associated r...

Dynamical environments around small celestial bodies are complex and uncertain, leading to highly perturbed, uncertain orbital motions in their proximity. Under such complexity and uncertainty, mis...

With appropriate control algorithms, solar radiation pressure (SRP) can be effectively used for orbit control around small celestial bodies. In contrast to the historical treatment of SRP as a dist...

This paper presents the trajectory design for EQUilibriUm Lunar-Earth point 6U Spacecraft (EQUULEUS), which aims to demonstrate orbit control capability of CubeSats in the cislunar space. The mission plans to observe the far side of the Moon from an Earth-Moon L2 (EML2) libration point orbit. The EQUULEUS trajectory design needs to react to uncertainties of mission design parameters such as the launch conditions, errors, and thrust levels. The main challenge is to quickly design science orbits at EML2 and low-energy transfers from the post-deployment trajectory to the science orbits within the CubeSat’s limited propulsion capabilities. To overcome this challenge, we develop a systematic trajectory design approach that 1) designs over 13,000 EML2 quasi-halo orbits in a full-ephemeris model with a statistical stationkeeping cost evaluation, and 2) identifies families of low-energy transfers to the science orbits using lunar flybys and solar perturbations. The approach is successfully applied for the trajectory design of EQUULEUS.

In-situ robotic asteroid exploration is integral to current and future space programs for sustainable human exploration and resupply in deep space, deflection of potentially hazardous objects, and study of the early solar system formulation. Meanwhile, dynamical environments around asteroids are highly perturbed and uncertain, and pose challenges for spacecraft to safely navigate around them. The dynamics are influenced by a variety of sources of uncertainty, such as asteroid properties, exogenous disturbances, and errors associated with operations. These uncertainties need to be properly quantified and taken into account of the mission design processes. On the other hand, characteristics of such uncertainties are not usually given or fixed but rather dependent on the mission architecture and operational scenarios. To aid in the decision-making processes with trade-offs between the mission feasibility and uncertainties, mission designers need to quantify the feasibilities of a number of architectures for a range of possible combinations of uncertainty characteristics. To explore the solution space efficiently and reliably, this paper presents a systematic approach that leverages techniques from the fields of stochastic optimal control and convex optimization. Formulated as a convex optimization problem, the solution method enables us to solve many number (as many as ~ 105) of stochastic optimal control problems without initial guesses. The proposed approach is applied to the design of asteroid global-mapping campaigns, which demonstrates the effectiveness and validity of our approach. The result reveals important trade-off relationships between the mission feasibility and assumed uncertainty characteristics in the context of asteroid global mapping. While the convex formulation involves a dynamical approximation, the validity of the convex-programming-based solutions is confirmed through nonlinear Monte-Carlo simulations under the original dynamics.

The beta angle, an angle formed by the sunlight and a spacecraft orbital plane, is an important parameter for science orbit design of orbiter missions. This angle defines lighting conditions and eclipse occurrences, and is used for science observation planning. Not only is this parameter perturbed by the irregular gravity field of the primary body, it varies with the body’s motion around the Sun. Investigating the evolution of the beta angle is therefore critical for science orbit design. This paper analyzes the J2-perturbed beta angle evolution via orbit averaging and year averaging, and derives conditions to constrain the short- and long-term evolutions of the beta angle. The orbit averaging analysis is further extended to provide a relaxed orbit condition that allows flexible science orbit design while naturally maintaining the beta angle evolution within science requirements. These analyses are carried out for an arbitrary rotation pole direction as it defines the orientation of the irregular gravity field seen in an inertial frame. The analytical work is numerically demonstrated with science orbit design for the Psyche mission, a recently selected mission of the NASA’s Discovery Program.

The present paper extends the classically studied chance-constrained optimal control to incorporate continuous-time chance constraints. While the classical approaches provide risk guarantees only at discretized epochs, it is essential for most physical systems to have continuous-time risk guarantees; it is especially important for unstable systems. This paper develops a new approach to enforce continuous-time risk guarantees by leveraging a notion of Cumulative Lyapunov Exponent, which measures the cumulative stabilities of Linear Time-Varying (LTV) systems. The solution method finds a sequence of feedback control policies for LTV systems that minimizes the expected control cost subject to continuous-time chance constraints. We demonstrate the approach with a spacecraft orbit control scenario on an unstable orbit. Monte Carlo simulations with the optimized feedback policies show that our approach respects the continuous-time chance constraints whereas a classical approach results in the constraint violation between the discretized epochs.

This paper will provide an introduction and overview of Area-of-Effect Softbots (AoES), which are currently in development under a Phase 2 NASA Innovative Advanced Concepts (NIAC) project. AoES are designed to operate in proximity to, and on the surface of, small asteroids to support mining and planetary defense missions. Their unique design and capabilities are dependent on the incorporation of soft, compliant, and lightweight materials. AoES have a large area-to-mass ratio which allows them to take advantage of the peculiarities of the dynamical environment around small asteroids. Specifically, AoES will use solar radiation pressure to sail to the surface of the target asteroid after being deployed at a safe altitude from a mothership around the asteroid. This capability and the associated control laws will be demonstrated, removing the need for propulsion systems. Furthermore, the large, flexible surface area allows for robustness with respect to uncertainty about the asteroid surface structure - it can provide flotation to prevent sinking into a very loose, dusty regolith, and also provide anchoring to the surface through natural and electroadhesion forces. The enabling technology that will allow the AoES design loop to close is a new class of soft actuators known as HASEL actuators. These actuators harness an electrohydraulic mechanism, whereby electrostatic forces generate hydraulic pressure to drive shape change in a soft fluid-filled structure. HASELs provide an extremely power- and mass-efficient mechanism for actuating the large flexible surface areas that are the essential components defining AoES. Current system design, requirements, and key tradeoffs will be discussed - with a particular focus on the actuation, mobility, anchoring, materials, and power sys-tems/components. The nominal mission profile and concept of operations for using AoES in an asteroid mining mission will be outlined.

Accepted: 2016-12-30, 資料番号: SA1160369000