Robust space trajectory design using belief stochastic optimal control

This paper presents a belief-based formulation and a novel approach for the robust solution of optimal control problems under uncertainty. The introduced formulation, based on the Belief Markov Decision Process model, reformulates the control problem directly in terms of uncertainty distributions, called beliefs, rather than on realisations of the system state. Successively, an approach inspired by navigation analysis is developed to transcribe and solve such problem in the presence of observation windows, employing a polynomial expansion for the dynamical propagation. Finally, the developed method is applied to the robust optimisation of a flyby trajectory of Europa Clipper mission in a scenario characterised by knowledge, execution and observation errors

Ultra-soft 100 nm Thick Zero Poisson’s Ratio Film with 60% Reversible Compressibility

About a 100 nm thick multilayer film of nanoparticle monolayers and polymer layers is shown to behave like cellular-foam with a modulus below 100 KPa. The 1.25 cm radius film adhered to a rigid surface can be compressed reversibly to 60% strain. The more than four orders of magnitude lower modulus compared to its constituents is explained by considering local bending in the (nano)cellular structure, similar to cork and wings of beetles. As the rigidity of the polymer backbone is increased in just four monolayers the modulus of the composite increases by over 70%. Electro-optical map of the strain distribution over the area of compression and increase in modulus with thickness indicates the films have zero Poisson’s ratio

Morphing hybrid honeycomb (MOHYCOMB) with in situ

Electrostatic adhesion can be used as a means of reversible attachment. Through application of high voltage (~2kV) across closely spaced parallel plate electrodes, significant shear stresses (11 kPa) can be generated. The highest levels of electrostatic holding force can be achieved through close contact of connection surfaces; this is facilitated by flexible electrodes which can conform to reduce air gaps. Cellular structures are comprised of thin walled elements, making them ideal host structures for electrostatic adhesive elements. The reversible adhesion provides control of the internal connectivity of the cellular structure, and determines the effective cell geometry. This would offer variable stiffness and control of the effective Poisson’s ratio of the global cellular array. Using copper-polyimide thin film laminates and PVDF thin film dielectrics, double lap shear electrostatic adhesive elements have been introduced to a cellular geometry. By activating different groups of reversible adhesive interfaces, the cellular array can assume four different cell configurations. A maximum stiffness modulation of 450 % between the “All off” and “All on” cell morphologies has been demonstrated. This structure is also capable of in-situ effective Poisson’s ratio variations, with the ability to switch between values of -0.45 and 0.54. Such a structure offers the potential for tuneable vibration absorption (due to its variable stiffness properties), or as a smart honeycomb with controllable curvature and is termed MOHYCOMB (MOrphing HYbrid honeyCOMB)

Autonomous interplanetary trajectory planning using structured-chromosome evolutionary algorithms

A main challenge in designing interplanetary trajectories is the fact that the number of design variables varies among different solutions. Global optimization methods that optimize this type of multi-modal objective functions can only handle problems with a fixed number of design variables. This paper presents the Structured-Chromosome Evolutionary Algorithm (SCEA) framework which was developed to handle variable size design space optimization problems. In this framework, a solution (chromosome) is represented by a hierarchical data structure where the genes in the chromosome are classified as dependent and non-dependent genes. This structure provides the capability to apply genetic operations between solutions of different lengths and thus to automatically determine the number of swing-bys, the planets to swing-by, launch and arrival dates, and the number of deep space maneuvers as well as their locations, magnitudes, and directions, in an optimal sense. This new method is applied to several interplanetary trajectory design problems. The results presented in this paper show that solutions obtained using this tool match known solutions for complex case studies. In addition, a comparative study of genetic algorithms and differential evolution for the same set of problems is contributed. © 2012 by the American Institute of Aeronautics and Astronautics, Inc