Currently there is a need to design, develop, and deploy autonomous and portable indoor geolocation systems to fulfil the needs of military, civilian, governmental and commercial customers where GPS and GLONASS signals are not available due to the limitations of both GPS and GLONASS signal structure designs. The goal of this dissertation is (1) to introduce geolocation systems; (2) to classify the state of the art geolocation systems; (3) to identify the issues with the state of the art indoor geolocation systems; and (4) to propose and assess four WPI indoor geolocation systems. It is assessed that the current GPS and GLONASS signal structures are inadequate to overcome two main design concerns; namely, (1) the near-far effect and (2) the multipath effect. We propose four WPI indoor geolocation systems as an alternative solution to near-far and multipath effects. The WPI indoor geolocation systems are (1) a DSSS/CDMA indoor geolocation system, (2) a DSSS/CDMA/FDMA indoor geolocation system, (3) a DSSS/OFDM/CDMA/FDMA indoor geolocation system, and (4) an OFDM/FDMA indoor geolocation system. Each system is researched, discussed, and analyzed based on its principle of operation, its transmitter, the indoor channel, and its receiver design and issues associated with obtaining an observable to achieve indoor navigation. Our assessment of these systems concludes the following. First, a DSSS/CDMA indoor geolocation system is inadequate to neither overcome the near-far effect not mitigate cross-channel interference due to the multipath. Second, a DSSS/CDMA/FDMA indoor geolocation system is a potential candidate for indoor positioning, with data rate up to 3.2 KBPS, pseudorange error, less than to 2 m and phase error less than 5 mm. Third, a DSSS/OFDM/CDMA/FDMA indoor geolocation system is a potential candidate to achieve similar or better navigation accuracy than a DSSS/CDMA indoor geolocation system and data rate up to 5 MBPS. Fourth, an OFDM/FDMA indoor geolocation system is another potential candidate with a totally different signal structure than the pervious three WPI indoor geolocation systems, but with similar pseudorange error performance.

Analytical Model of Traffic Signal Structures (TSS) is developed based on a continuous system method to observe dynamic characteristics of the structures. Conventional and basic continuous system method can show the approximate dynamic characteristics of the TSS, but the discretized continuous analytical model is proposed to get more accurate and realistic results of the TSS. In addition, the discretized continuous model can alternatively analyze the effect of the tapered cross-sectional members which are real model of TSS. For the verification of the analytical model, the dynamic characteristics of the numerical solutions by modal analysis in ABAQUS and the results of experimental measurements are provided. Compared with the numerical solutions and the experimental results, the analytical solution for each member shows its considerable accuracy. In addition, it will be also able to accurately express the effects of the linearly tapered cross-sectional member with more discretized continuous structural system. Moreover, the discretized analytical model of the TSS has the usability to observe the effects of boundary flexibility.

As we begin to analyze and construct extremely complex systems, a theory for understanding and designing the underlying architecture becomes very important. To move in the direction of a precise theory of architecture, this thesis will provide some concrete tools to analyze and design complex systems with a given network structure. The first main result of this thesis analyzes the vulnerability of a system and shows that a system's vulnerability depends on its network structure. We will consider destabilization attacks acting on a single link in a system's logical interconnection structure. The concept of a vulnerable link is characterized and necessary and sufficient conditions for identifying these links are provided. The vulnerability of various system architectures are then characterized by the vulnerability of their weakest link, and it is shown that every transfer function has a completely secure architecture with no vulnerable links. The second part of this thesis focuses on synthesizing controllers with a specified network structure. It presents a new approach to distributed controller design that exploits the dynamical structure function representation of linear time invariant systems to characterize the structure of a system. The design technique sequentially constructs each link in an arbitrary controller signal structure, and the main theorem proves that either the resulting controller is stabilizing or that no controller with the desired structure can stabilize the system.

The signal structure is a partial structure representation for dynamic systems. It characterizes the causal relationship between manifest variables and is depicted in a weighted graph, where the weights are dynamic operators. Earlier work has defined signal structure for linear time-invariant systems through dynamical structure function. This thesis focuses on the search for the signal structure of nonlinear systems and proves that the signal structure reduces to the linear definition when the systems are linear. Specifically, this work: (1) Defines the complete computational structure for nonlinear systems. (2) Provides a process to find the complete computational structure given a state space model. (3) Defines the signal structure for dynamic systems in general. (4) Provides a process to find the signal structure for a class of dynamic systems from their complete computational structure.

One of the most powerful properties of mathematical systems theory is the fact that interconnecting systems yields composites that are themselves systems. This property allows for the engineering of complex systems by aggregating simpler systems into intricate patterns. We call these interconnection patterns the "structure" of the system. Similarly, this property also enables the understanding of complex systems by decomposing them into simpler parts. We likewise call the relationship between these parts the "structure" of the system. At first glance, these may appear to represent identical views of structure of a system. However, further investigation invites the question: are these two notions of structure of a system the same? This dissertation answers this question by developing a theory of dynamical structure. The work begins be distinguishing notions of structure from their associated mathematical representations, or models, of a system. Focusing on linear time invariant (LTI) systems, the key technical contributions begin by extending the definition of the dynamical structure function to all LTI systems and proving essential invariance properties as well as extending necessary and sufficient conditions for the reconstruction of the dynamical structure function from data. Given these extensions, we then develop a framework for analyzing the structures associated with different representations of the same system and use this framework to show that interconnection (or subsystem) structures are not necessarily the same as decomposition (or signal) structures. We also show necessary and sufficient conditions for the reconstruction of the interconnection (or subsystem) structure for a class of systems. In addition to theoretical contributions, this work also makes key contributions to specific applications. In particular, network reconstruction algorithms are developed that extend the applicability of existing methods to general LTI systems while improving the computational complexity. Also, a passive reconstruction method was developed that enables reconstruction without actively probing the system. Finally, the structural theory developed here is used to analyze the vulnerability of a system to simultaneous attacks (coordinated or uncoordinated), enabling a novel approach to the security of cyber-physical-human systems.

A significant body of research has focused on tracking behaviors of predators responding to prey odor plumes, yet little is known about the specific mechanisms by which predators make decisions during tracking that lead them to a source. This dissertation advances the current knowledge of plume tracking behavior by examining blue crab tracking behavior over a large range of bed-roughnesses (thereby manipulating ambient levels of turbulence), and interpreting these results with respect to chemical signal structure derived from separate examinations of plume characteristics as determined by planar laser induced fluorescence (PLIF). Foraging success and the speed of blue crabs attempting to locate the odorant source both decline consistently with increasing bed roughness. In contrast, steering (path linearity) appears unaffected by bed roughness induced turbulence. The spatial arrangement of blue crab chemosensors combined with the three-dimensional structure of odorant plumes accounts for the differential effects of turbulence on the speed and success of crab tracking behavior. Separate examinations of tracking behavior and plume properties cannot directly examine hypotheses concerning the utility of specific chemical signal properties. In order to make a direct link between cue and behavior, three-dimensional laser induced fluorescence (3DLIF) was used to analyze three-dimensional plume structure and concentration of odor filaments that reach blue crab sensory structures. The corresponding tracking behavior was simultaneously recorded and then analyzed with a motion analysis system. These data provide the most comprehensive examination of odor signal input-behavioral output functions for animals in turbulent plumes. Crabs do not react differentially in response to the absolute concentration of antennule spikes above threshold at their antennules but do show a state-dependent acceleration response to antennule spikes. Signals arriving at the leg sensors of blue crabs help mediate upstream motion and signal change across a single set of leg sensors is sufficient to induce turning during upstream motion. Blue crabs decrease the height of their antennules in correspondence with changing plume properties as they approach the source and the timing of signals arriving at the antennules appears to affect upstream motion.