Towards synthetic biological approaches to resource utilization on space missions.

This paper demonstrates the significant utility of deploying non-traditional biological techniques to harness available volatiles and waste resources on manned missions to explore the Moon and Mars. Compared with anticipated non-biological approaches, it is determined that for 916 day Martian missions: 205 days of high-quality methane and oxygen Mars bioproduction with Methanobacterium thermoautotrophicum can reduce the mass of a Martian fuel-manufacture plant by 56%; 496 days of biomass generation with Arthrospira platensis and Arthrospira maxima on Mars can decrease the shipped wet-food mixed-menu mass for a Mars stay and a one-way voyage by 38%; 202 days of Mars polyhydroxybutyrate synthesis with Cupriavidus necator can lower the shipped mass to three-dimensional print a 120 m(3) six-person habitat by 85% and a few days of acetaminophen production with engineered Synechocystis sp. PCC 6803 can completely replenish expired or irradiated stocks of the pharmaceutical, thereby providing independence from unmanned resupply spacecraft that take up to 210 days to arrive. Analogous outcomes are included for lunar missions. Because of the benign assumptions involved, the results provide a glimpse of the intriguing potential of 'space synthetic biology', and help focus related efforts for immediate, near-term impact

Selective Evolutionary Generation Systems: Theory and Applications.

This dissertation is devoted to the problem of behavior design, which is a generalization of the standard global optimization problem: instead of generating the optimizer, the generalization produces, on the space of candidate optimizers, a probability density function referred to as the behavior. The generalization depends on a parameter, the level of selectivity, such that as this parameter tends to infinity, the behavior becomes a delta function at the location of the global optimizer. The motivation for this generalization is that traditional off-line global optimization is non-resilient and non-opportunistic. That is, traditional global optimization is unresponsive to perturbations of the objective function. On-line optimization methods that are more resilient and opportunistic than their off-line counterparts typically consist of the computationally expensive sequential repetition of off-line techniques. A novel approach to inexpensive resilience and opportunism is to utilize the theory of Selective Evolutionary Generation Systems (SEGS), which sequentially and probabilistically selects a candidate optimizer based on the ratio of the fitness values of two candidates and the level of selectivity. Using time-homogeneous, irreducible, ergodic Markov chains to model a sequence of local, and hence inexpensive, dynamic transitions, this dissertation proves that such transitions result in behavior that is called rational; such behavior is desirable because it can lead to both efficient search for an optimizer as well as resilient and opportunistic behavior. The dissertation also identifies system-theoretic properties of the proposed scheme, including equilibria, their stability and their optimality. Moreover, this dissertation demonstrates that the canonical genetic algorithm with fitness proportional selection and the (1+1) evolutionary strategy are particular cases of the scheme. Applications in three areas illustrate the versatility of the SEGS theory: flight mechanics, control of dynamic systems, and artificial intelligence. The dissertation results touch upon several open problems in the fields of artificial life, complex systems, artificial intelligence, and robotics.Ph.D.Aerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/77855/1/amenezes_1.pd

Rational Behavior Design Using Multi-Selective Generation

Abstract-This paper extends a technique that solves a generalization of the standard global optimization problem: instead of generating the optimizer, the technique produces, on the search space, a probability density function referred to as the behavior. The generalized solution depends on a parameter, the level of selectivity, such that as this parameter tends to infinity, the behavior becomes a delta function at the location of the optimizer. The motivation for this generalization is that traditional off-line global optimization is unresponsive to perturbations of the objective function. Although the original technique achieves responsive optimization, a large number of iterations may be required. In most instances, the extended technique of this paper, which is known as multi-selective generation, averages fewer iterations to achieve responsive optimization. Multi-selective generation is formulated here to generalize the canonical genetic algorithm with fitness proportional selection. Necessary and sufficient conditions that are required by multiselective generation to achieve so-called rational behavior are specified. Rational behavior is desirable because it can lead to both efficient search and responsive optimization. However, the conditions for the extended technique to behave rationally are highly restrictive. The implication is that the original technique, which behaves rationally, is preferable for efficient search and responsive optimization

Cyclic Control: Problem Formulation and Stability Analysis

This paper considers the problem of controlling rotating machinery with actuators and sensors fixed in inertial space. Such a problem arises in control of charging and fusing stages in the xerographic process, drilling and milling machines, and turbo machinery. If a rotating device is represented as a set of discrete wedges, the resulting system can be conceptualized as a set of plants (wedges) with a single actuator and sensor. In such architecture, each plant can be controlled only intermittently, in a stroboscopic manner. This leads to the problem of cyclic control (CC) considered in this paper. Specifically, the problem of stabilizability in CC architecture is considered, and the resulting stabilizability conditions are compared with those in the usual, permanently acting control (PAC). In this regard, it is shown that the domain of asymptotic stability under CC is an open disc in the open left half plane (OLHP), rather than the OLHP itself, and the controller gains that place the closed loop poles at the desired locations under CC are N times larger than those under PAC, where N is the number of wedges. The results are applied to temperature stabilization of the fusing stage of a xerographic process

Towards synthetic biological approaches to resource utilization on space missions.

This paper demonstrates the significant utility of deploying non-traditional biological techniques to harness available volatiles and waste resources on manned missions to explore the Moon and Mars. Compared with anticipated non-biological approaches, it is determined that for 916 day Martian missions: 205 days of high-quality methane and oxygen Mars bioproduction with Methanobacterium thermoautotrophicum can reduce the mass of a Martian fuel-manufacture plant by 56%; 496 days of biomass generation with Arthrospira platensis and Arthrospira maxima on Mars can decrease the shipped wet-food mixed-menu mass for a Mars stay and a one-way voyage by 38%; 202 days of Mars polyhydroxybutyrate synthesis with Cupriavidus necator can lower the shipped mass to three-dimensional print a 120 m(3) six-person habitat by 85% and a few days of acetaminophen production with engineered Synechocystis sp. PCC 6803 can completely replenish expired or irradiated stocks of the pharmaceutical, thereby providing independence from unmanned resupply spacecraft that take up to 210 days to arrive. Analogous outcomes are included for lunar missions. Because of the benign assumptions involved, the results provide a glimpse of the intriguing potential of 'space synthetic biology', and help focus related efforts for immediate, near-term impact

Grand challenges in space synthetic biology.

Space synthetic biology is a branch of biotechnology dedicated to engineering biological systems for space exploration, industry and science. There is significant public and private interest in designing robust and reliable organisms that can assist on long-duration astronaut missions. Recent work has also demonstrated that such synthetic biology is a feasible payload minimization and life support approach as well. This article identifies the challenges and opportunities that lie ahead in the field of space synthetic biology, while highlighting relevant progress. It also outlines anticipated broader benefits from this field, because space engineering advances will drive technological innovation on Earth