Title from PDF of title page (University of Missouri--Columbia, viewed on March 10, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Thesis advisor: Dr. Guilherme DeSouza. Vita. Includes bibliographical references.

Thesis (M.U.R.P.)--Ball State University, 2009. / Title from PDF t.p. (viewed on Mar. 01, 2010). Caption title. Creative project (M.U.R.P.), 3 hrs. Includes bibliographical references (p. 114-115).

Thesis (Ph. D.)--University of Washington, 2001. / Includes bibliographical references (leaves 133-139).

Title from PDF of title page (University of Missouri--Columbia, viewed on Feb 17, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Thesis advisor: Dr. J. Erik Loehr. Includes bibliographical references.

Thesis (M.S.)--Oregon State University, 2002. / Typescript (photocopy). Includes bibliographical references. Also available on the World Wide Web.

Thesis (Ph. D.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains vi, 92 p. : ill. Includes abstract. Includes bibliographical references (p. 85-92).

Terrestrial robots must be capable of negotiating rough terrain if they are to become autonomous outside of the lab. Although the control mechanism offered by wheels is attractive in its simplicity, any wheeled system is confined to relatively flat terrain. Wheels will also only ever be useful for rolling, while limbs observed in nature are highly multimodal. The robust locomotive utility of legs is evidenced by the many animals that walk, run, jump, swim, and climb in a world full of challenging terrain. On the other hand, legs with multiple degrees of freedom (DoF) require much more complex control and precise sensing than wheels. Legged robotic systems are easily hampered by sensor noise and bulky control loops that prohibit the high-speed adaptation to external perturbations necessary for dynamic stability in real time. Low sensor bandwidth can limit the system’s reaction time to external perturbations. It is also often necessary to filter sensor data, which introduces significant delays in the control loop. In addition, state estimation is often relied upon in order to compute active stabilizing responses. State estimation requires accurate sensor data, often involving filtering, and can involve additional nontrivial computation such as the pseudo-inversion of fullbody Jacobians. This perception portion of the control burden is all incurred before a response can be planned and executed. These delays can prevent a system from executing a corrective response before instability leads to failure. The present work presents an approach to legged system design and control that reduces both the perception and planning aspects of the online control burden. A commonly accepted design goal in robotics is to accomplish a task with the fewest possible DoF in order to tighten the control loop and avoid the curse of dimensionality. However, animals control many DoF in a manner that adapts to external perturbations faster than can be explained by efferent neural control. The passive mechanics of segmented animal limbs are capable of rejecting unexpected disturbances without the supervision of an active controller. By simulating biomimetic limbs, we can learn more about this preflexive response, how the properties of segmented biological limbs foster self-stable passive mechanics, and how the control burden can be mitigated in robotic legged systems. The contribution of this body of work is to reduce the control burden of legged locomotion for robots by drawing on self-stabilizing mechanical design and control principles observed in animal locomotion. To that end, minimal templates such as Sensory-Coupled Action Switching Modules (SCASM), Central Pattern Generators (CPGs), and the Spring-Loaded Inverted Pendulum (SLIP) model are used to learn more about the essential components of legged locomotion. The motivation behind this work lies largely in the study of how internal, predictive models and the intrinsic mechanical properties of biological limbs help animals self-stabilize in real time. Robotic systems have already begun to demonstrate the benefits of these biological design primitives in an engineering context, such as reduced cost of transportation and an immediate mechanical response that does not need to wait for sensor feedback or planning. The original research presented here explores the extent to which these principles can be utilized in order to encourage stable legged locomotion over uneven terrain with as little sensory information as possible. A method for generating feedforward, terrain-adaptive control primitives based on a compliant limb architecture is developed. Offline analysis of system dynamics is used to develop clock-driven patterns of leg stiffness and attack angle control during late swing with which passive stance phase dynamics will produce the desired apex height and stride period to within 0.1 mm and 50 μs, respectively. A feedforward method of energy modulation is incorporated that regulates velocity to within 10−5 m/s. Preservation of a constant stride period eliminates the need for detection of the apex event. Precise predictive controls based on thorough offline dynamic modeling reduce the system’s reliance on state and environmental data, even in rough terrain. These offline models of system dynamics are used to generate a controller that predicts the dynamics of running over uneven terrain using an internal clock signal. Real-time state estimation is a non-trivial bottleneck in the control of mobile systems, legged and wheeled alike. The present work significantly reduces this burden by generating predictive models that eliminate the need for state estimation within the control loop, even in the presence of damping. The resulting system achieves not only self-stable legged running, but direct control of height, speed, and stride period without inertial sensing or force feedback. Through this work, the controller dependency on accurate and rapid sensing of the body height and velocity, apex event, and ground variation was eliminated. This was done by harnessing physics-based models of leg dynamics, used to generate predictive controls that exploit the passive mechanics of the compliant limb to their full potential. While no real world system is entirely deterministic, such a predictive model may serve as the base layer for a lightweight control architecture capable of stable robotic limb control, as in animal locomotion.

This study proposed and evaluated a waste-to-resource strategy for beneficially using solid waste as ceramic raw materials. The sludge generated from waterworks and sewage treatment processes contains significant amounts of aluminum and iron, and the industrial sludge is enriched with high metal content. The hazardous metals in waste sludge may lead to metal bioaccumulation and cause adverse effects for ecosystem. This study aims to stabilize copper- and zinc-laden sludge in commonly available ceramic products, and to beneficially use waterworks and sewage sludge to incorporate waste metals. The study was first investigated by sintering simulated metal-laden sludge with Al-rich (γ-Al2O3, -Al2O3, kaolinite, mullite) and Fe-rich (Fe2O3) precursors. Secondly, the practicability of recycling Cu-bearing electroplating sludge as a part of ceramic raw materials was evaluated through thermal interaction with Al-rich precursors. Furthermore, the potential of using water and sewage treatment works sludge to stabilize metals were also examined. Sintering procedures were carried out within 650-1450 oC for 3 h, and phase transformations were studied using X-ray diffraction (XRD) with the quantification technique of Rietveld refinement analysis. The formation of CuAl2O4 spinel was initiated at 650 oC using γ-Al2O3, and the maximum copper transformation reached 80%. The copper incorporation into CuAl2O4 started at 850 oC and reached 95% in -Al2O3 system. The growth of CuAl2O4 was found at 750 oC using kaolinite, but at 900 oC in mullite system. The maximum copper transformation for both kaolinite and mullite reached ~80%. With CuAl2O4, decomposing, the formation of CuAlO2 predominated in alumina systems, but CuO and Cu2O were found in kaolinite and mullite systems. When using Fe2O3, the CuFe2O4 with tetragonal structure was observed at lower temperatures, and the cubic CuFe2O4 became predominant at 1000 oC. The formation of ZnAl2O4 spinel started at 750 oC in γ-Al2O3 system and at 950 oC in -Al2O3 system, respectively. The zinc transformation completed in both γ-Al2O3 and -Al2O3 systems at higher temperatures. The coexistence and competition between ZnAl2O4 and Zn2SiO4 were found using kaolinite and mullite. The increase of temperature to 1350 °C resulted in complete zinc transformation to ZnAl2O4 in mullite system. Through leaching tests, aluminates and ferrites were found to be superior to oxide and silicate phases in immobilizing hazardous metals. The leachates of aluminates and ferrites exhibited the behavior of incongruent dissolution, and the Zn2SiO4 leachate showed congruent dissolution. The CuAl2O4 spinel was observed when sintering Cu-laden electroplating sludge with aluminate precursors. The copper leachability decreased with CuAl2O4 developing and the lowest copper concentration in leachates was within the optimal temperature range for CuAl2O4 generation. Both copper and zinc were successfully incorporated into the spinel structure using waterworks sludge, and the cubic CuFe2O4 became the main component when using sewage sludge to stabilize copper. Overall, this study demonstrated a promising process to stabilize hazardous metals in waste materials, such as sludge, ash, and slag, through sintering with the inexpensive ceramic precursors. This may provide an avenue for economically reduce the environmental hazards of toxic metals by reliably blending them into the marketable ceramic products. / published_or_final_version / Civil Engineering / Doctoral / Doctor of Philosophy

A sensor is a battery-operated small computer with an antenna and a sensing board that can sense magnetism, sound, heat, etc. Sensors in a network communicate and cooperate with other sensors to perform given tasks. A sensor network is exposed to various dynamic factors and faults, such as topology changes, energy saving features, unreliable communication, and hardware/software failures. Thus, protocols in this sensor network should be able to adapt to dynamic factors and recover from faults. In this dissertation, we focus on designing and analyzing a class of sensor network protocols, called self-stabilizing protocols. A self-stabilizing protocol is guaranteed to return to a state where it performs its intended function correctly, when some dynamic factors or faults corrupt the state of the protocol arbitrarily. Therefore, in order to make a sensor network resilient to dynamic factors and faults, each protocol in the sensor network should be self-stabilizing. We first develop a state-based model that can be used to formally specify sensor network protocols. This model accommodates several unique characteristics of sensor networks, such as unavoidable local broadcast, probabilistic message transmission, asymmetric communication, message collision, and timeout actions and randomization steps. Second, we present analysis methods for verifying and analyzing the correctness and self-stabilization properties of sensor network protocols specified in this model. Third, using the state-based model and analysis methods, we design three self-stabilizing sensor network protocols, prove their self-stabilization properties, and estimate their performance. These three self-stabilizing protocols are a sentry-sleeper protocol that elects a sentry from a group of sensors at the beginning of each time period, a logical grid routing protocol that builds a routing tree whose root is the base station, and a family of flood sequencing protocols that distinguish between fresh and redundant flood messages using sequence numbers. / text

This thesis first addresses an important topic concerning space structure control systems, namely, attitude stabilization and control, which is followed by a study on subsystem interactions of general Multi Input Multi Output (MIMO) systems for better performance and actuator fault tolerance. A novel and simple output feedback stabilization approach is proposed for a space structure system characterized with kinematics and dynamics. The approach globally, asymptotically stabilizes the plant and the closed-loop stability is proved using Lyapunov analysis. The simplicity and robustness of the designed controller are demonstrated by investigating the closed-loop response after reducing the degree of freedom in control structure. The stability of the closed-loop system is further analyzed and the performance is compared with two other robust control approaches. The study carries on to another space plant, a Large Space Telescope (LST). Its dynamic model which is fitted with reaction wheels initially developed by NASA is analyzed and the fully coupled dynamics are derived by taking into account the nonlinear coupling phenomena and other terms neglected in their original (NASA) form. The dynamics are combined with Quaternion based kinematics to form an intricate yet realistic LST attitude model. The attitude of the nonlinear LST model is stabilized using a state feedback controller and the LST model is shown to track a time varying attitude reference. Structure configuration is an imperative task in the design of MIMO control systems. In order to make use of interactions between multiple channels so that the system can deal with vulnerability due to actuator degradation, a novel interaction measure is proposed. It is defined as Relative Dependency Index (RDI) and is based on H∞ norms. Such a measurement is effective in understanding the influence of the jth input on the ith output of a system. RDI based guidelines are outlined for configuring a system towards coupling/decoupling. RDI is further extended to the Input Impact Index (i.i.i.) which helps in determining how much an actuator degradation would affect the output of a system. The validity of RDI and i.i.i. is illustrated by simulation results and tested on the linearized spacecraft attitude model presented in the former part of the thesis.