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This work considers the design of separating input signals in order to discriminate among a finite number of uncertain nonlinear models. Each nonlinear model corresponds to a system operating mode, unobserved intents of other drivers or robots, or to fault types or attack strategies, etc., and the separating inputs are designed such that the output trajectories of all the nonlinear models are guaranteed to be distinguishable from each other under any realization of uncertainties in the initial condition, model discrepancies or noise. I propose a two-step approach. First, using an optimization-based approach, we over-approximate nonlinear dynamics by uncertain affine models, as abstractions that preserve all its system behaviors such that any discrimination guarantees for the affine abstraction also hold for the original nonlinear system. Then, I propose a novel solution in the form of a mixed-integer linear program (MILP) to the active model discrimination problem for uncertain affine models, which includes the affine abstraction and thus, the nonlinear models. Finally, I demonstrate the effectiveness of our approach for identifying the intention of other vehicles in a highway lane changing scenario. For the abstraction, I explore two approaches. In the first approach, I construct the bounding planes using a Mixed-Integer Nonlinear Problem (MINLP) formulation of the given system with appropriately designed constraints. For the second approach, I solve a linear programming (LP) problem that over-approximates the nonlinear function at only the grid points of a mesh with a given resolution and then accounting for the entire domain via an appropriate correction term. To achieve a desired approximation accuracy, we also iteratively subdivide the domain into subregions. This method applies to nonlinear functions with different degrees of smoothness, including Lipschitz continuous functions, and improves on existing approaches by enabling the use of tighter bounds. Finally, we compare the effectiveness of this approach with the existing optimization-based methods in simulation and illustrate its applicability for estimator design.
ContributorsSingh, Kanishka Raj (Author) / Yong, Sze Zheng (Thesis advisor) / Artemiadis, Panagiotis (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2018
Description
Energy projects have the potential to provide critical services for human well-being and help eradicate poverty. However, too many projects fail because their approach oversimplifies the problem to energy poverty: viewing it as a narrow problem of access to energy services and technologies. This thesis presents an alternative paradigm for energy project development, grounded in theories of socio-energy systems, recognizing that energy and poverty coexist as a social, economic, and technological problem.
First, it shows that social, economic, and energy insecurity creates a complex energy-poverty nexus, undermining equitable, fair, and sustainable energy futures in marginalized communities. Indirect and access-based measures of energy poverty are a mismatch for the complexity of the energy-poverty nexus. The thesis, using the concept of social value of energy, develops a methodology for systematically mapping benefits, burdens and externalities of the energy system, illustrated using empirical investigations in communities in Nepal, India, Brazil, and Philippines. The thesis argues that key determinants of the energy-poverty nexus are the functional and economic capabilities of users, stressors and resulting thresholds of capabilities characterizing the energy and poverty relationship. It proposes ‘energy thriving’ as an alternative standard for evaluating project outcomes, requiring energy systems to not only remedy human well-being deficits but create enabling conditions for discovering higher forms of well-being.
Second, a novel, experimental approach to sustainability interventions is developed, to improve the outcomes of energy projects. The thesis presents results from a test bed for community sustainability interventions established in the village of Rio Claro in Brazil, to test innovative project design strategies and develop a primer for co-producing sustainable solutions. The Sustainable Rio Claro 2020 initiative served as a longitudinal experiment in participatory collective action for sustainable futures.
Finally, results are discussed from a collaborative project with grassroots practitioners to understand the energy-poverty nexus, map the social value of energy and develop energy thriving solutions. Partnering with local private and non-profit organizations in Uganda, Bolivia, Nepal and Philippines, the project evaluated and refined methods for designing and implementing innovative energy projects using the theoretical ideas developed in the thesis, subsequently developing a practitioner toolkit for the purpose.
First, it shows that social, economic, and energy insecurity creates a complex energy-poverty nexus, undermining equitable, fair, and sustainable energy futures in marginalized communities. Indirect and access-based measures of energy poverty are a mismatch for the complexity of the energy-poverty nexus. The thesis, using the concept of social value of energy, develops a methodology for systematically mapping benefits, burdens and externalities of the energy system, illustrated using empirical investigations in communities in Nepal, India, Brazil, and Philippines. The thesis argues that key determinants of the energy-poverty nexus are the functional and economic capabilities of users, stressors and resulting thresholds of capabilities characterizing the energy and poverty relationship. It proposes ‘energy thriving’ as an alternative standard for evaluating project outcomes, requiring energy systems to not only remedy human well-being deficits but create enabling conditions for discovering higher forms of well-being.
Second, a novel, experimental approach to sustainability interventions is developed, to improve the outcomes of energy projects. The thesis presents results from a test bed for community sustainability interventions established in the village of Rio Claro in Brazil, to test innovative project design strategies and develop a primer for co-producing sustainable solutions. The Sustainable Rio Claro 2020 initiative served as a longitudinal experiment in participatory collective action for sustainable futures.
Finally, results are discussed from a collaborative project with grassroots practitioners to understand the energy-poverty nexus, map the social value of energy and develop energy thriving solutions. Partnering with local private and non-profit organizations in Uganda, Bolivia, Nepal and Philippines, the project evaluated and refined methods for designing and implementing innovative energy projects using the theoretical ideas developed in the thesis, subsequently developing a practitioner toolkit for the purpose.
ContributorsBiswas, Saurabh (Author) / Miller, Clark A. (Thesis advisor) / Wiek, Arnim (Committee member) / Janssen, Marcus A (Committee member) / Arizona State University (Publisher)
Created2020