This thesis is concerned with the factors that affect robot performance in positioning control. Specifically, we focus on the problem of fine end-point motion control of the robot end-effector about a nominal point where the linearized dynamics can be used. Performance is measured in the context of linear quadratic (LQ) theory. / An LQ based task-space performance index for robots is proposed. Several existing robots are examined for various transient tasks using this index and for each an optimum operating location is found. A cheap control (i.e. large actuator energies) analysis is done. The limits to performance are determined (i.e. singular optimal control). An explicit solution to performance was determined and an examination of the computed-torque control law is done. / An LQ based piecewise linear control (PLC) law is derived that increases the LQ gain in a piecewise-constant manner as the system trajectory converges towards the origin. This law uses a succession of invariant sets of decreasing size and for each an associated LQ gain. The formulation gives rise to an iteration function whose solution is a fixed point. The development of the PLC law led to the unveiling of a number of key properties, namely that the solution to the algebraic Riccati equation is concave with respect to both the actuator weighting and the state weighting matrices. A time-varying extension of the PLC law and an overshoot control scheme are also derived. / Issues regarding state estimation problem are studied. Noise is introduced to account for model uncertainty. A transient and steady state Kalman filter analysis is done. Sensor issues are examined for robots. The Kalman filter is used to fuse joint sensor data, Cartesian position sensor data, and tachometer data to provide a single best estimate of the state and to eliminate position offsets due to model error. / Finally, the effects of unmodeled dynamics, model error, and non-linearities on performance are examined. A Kalman filter is used to eliminate bias positioning errors at the robot's end-effector. Performance-uncertainty curves are generated using a numerical convex optimization method when the system is subject to parametric uncertainty. Describing functions are used to examine the backlash non-linearity.

This thesis examines the fundamental relationship between a continuous-time system and its discrete-time models. This involves a study of the conditions that the state space realization of a model must satisfy in order to be valid. While such a study has been performed for models whose order equals that of the continuous-time system, this thesis also includes "higher order discrete-time models", that is, models whose order is higher than the continuous-time system. A strict mathematical definition for models is presented based upon the convergence in a certain sense of the time responses of the continuous-time system and its model. Theorems are also presented which can be used to prove the validity of models, and shown are that many common discretization techniques, such as mapping models and hold equivalent models, are valid. Using these theorems some of these discretization techniques can be generalized. However, the aim of this thesis is not to prove the validity of common discretization techniques, but to understand the conditions which a model must satisfy in order to be valid. Common discretization techniques simply provide convenient examples for this understanding. / The definition of models is later expanded to consider discrete-time time-varying and multi-rate system. It is with multi-rate systems that the importance of higher order models becomes particularly apparent. Depending on the particular ratio of sampling rates between the plant input and output, some multi-rate systems must include inherently discrete-time operations, resulting in a higher order, for these systems to be considered valid. Also shown is that it is possible for a discrete-time periodically-time-varying system to model a time-invariant continuous-time system. / Finally, using the developed model concept, the practical problem of the multi-rate implementation of an analogue control system is considered. The method presented is an extension of the plant input mapping method which is the only method capable of guaranteeing the stability of the digital closed-loop system provided the sampling period is nonpathological. Simulation examples illustrate the effectiveness of the proposed methods, even for very slow sampling periods.

The fundamental motivation for the work in this thesis is the study of decentralized dynamical decision systems and their optimization properties. The design of competitive markets to substitute for traditional centralized regulation has been considered in many domains and a key feature of the decentralized decision mechanisms of competitive markets is that, subject to certain hypotheses, they maximize social welfare. Progressive auctions constitute a highly developed form of such market mechanisms and hence in this thesis we construct and analyze them as paradigm examples of decentralized dynamical decision making systems.In the work of Lazar and Semret (1999), a so-called Progressive Second Price auction mechanism (PSP) was proposed for both dynamic market-pricing and allocation of variable-size resources. In this thesis, three quantized versions of the PSP auction are developed. First, a so-called Quantized - PSP (Q-PSP) auction algorithm is analyzed where the agents have similar private demand functions and submit bids synchronously. It is shown that the nonlinear dynamics induced by this algorithm are such that the prices bid by the various agents and the quantities allocated to these agents converge in at most five iterations or oscillate indefinitely, with all prices converging to one price for all agents or to a limit cycle on just two prices for all agents. This behaviour is not only independent of the number of agents involved but is also independent of the number of quantization levels. Second, the Aggressive-Defensive Quantized - PSP (ADQ-PSP) auction algorithm is presented which improves upon the performance of the Q-PSP auction. For the ADQ-PSP auction applied to agent populations with randomly distributed demand functions, it is shown that the states of the corresponding dynamical systems rapidly converge with high probability to a quantized (Nash) equilibrium with a common price for all agents. Third, the Unique-limit Quantized - PSP (UQ-PSP) auction algorithm is developed as a modification of the ADQ-PSP; for this algorithm, (i) the limit price of all system trajectories is independent of the initial data, and (ii) modulo the quantization level, the limiting resource allocation is efficient (i.e., the corresponding social welfare function, or summed individual valuation functions, is optimal up to a quantized level).These quantized auction algorithms are, first, extended to supply auctions, that is to say, competitive markets where only sellers are assumed to exist, and then, second, extended to double-sided auctions where auctions are defined between both sellers and buyers separately and which interact in a well defined way. Finally, network based auctions are considered; this is motivated by the fact that agents in communication networks or social networks may not be able to access the bid information of all other agents or resource information over such networks and hence must make decisions based solely upon local information. In particular, a two-level network-based auction is developed and is formulated as a consensus UQ-PSP auction where suppliers in the upper network recursively follow consensus dynamics to allocate quantities which are the subject of UQ-PSP auctions at each network node. This configuration solves the corresponding discrete-time weighted-average consensus problem, converges to a unique network wide price and achieves social efficiency for the whole network. / La motivation première du travail accompli dans cette thèse est l'étude des systèmes dynamiques de décisions décentralisées et leurs propriétés d'optimisation. La conception des marchés compétitifs dans le but de remplacer la réglementation centralisée traditionnelle a été envisagée dans plusieurs domaines. L'élément clé des mécanismes de décisions décentralisés est que sous certaines hypothèses, ils maximisent le bien-être social. Les enchères progressives constituent une forme extrêmement développée de ces types de mécanismes de marchés. Cette thèse les construit et les analyse donc comme étant des exemples paradigmatiques de systèmes dynamiques de prise de décision décentralisés.Le travail de Lazar et Semret (1999), un mécanisme d'enchères au second prix progressif (PSP), ainsi nommé, a été envisagé pour la tarification en fonction des marchés ainsi que pour l'allocation des ressources de format variable. Dans cette thèse, trois versions quantifiées des enchères au second prix progressif ont été développées.Premièrement, un algorithme d'enchère PSP-quantifié ainsi nommé (Q-PSP) est analysé là où les agents ont des fonctions de demande privée similaires et font des offres simultanément. Il est démontré que la dynamique non linéaire causée par cet algorithme est tel que les offres faites par divers agents et les quantités allouées à ces agents convergent en cinq itérations au plus ou oscillent indéfiniment, tandis que tous les prix convergent vers un seul prix pour tous les agents ou vers un cycle limite de deux prix pour tous les agents. Ce comportement n'est pas seulement indépendant du nombre d'agents en jeu, mais est aussi indépendant du nombre de niveaux de quantification. Deuxièmement, l'algorithme de l'enchère PSP quantifié agressif-défensif (ADQ-PSP) est présenté, ce qui améliore la performance de l'enchère Q-PSP. Pour l'enchère ADQ-PSP mis en pratique dans les populations d'agents dont la fonction de demande est distribuée de façon aléatoire, il est démontré que les états des systèmes dynamiques correspondants convergent rapidement avec une forte probabilité d'atteindre un équilibre (de Nash) quantifié, avec un prix commun pour tous les agents. Troisièmement, l'algorithme d'enchère quantifié à limite unique-PSP (UQ-PSP) est développé en tant que modification de l'ADQ-PSP. Pour cet algorithme, (i) le prix limite de toutes les trajectoires de systèmes est indépendant des données initiales, et (ii) modulo le niveau de quantification, l'allocation restrictive est efficace, c'est-à-dire que la fonction correspondante du bien-être social, ou l'addition des fonctions d'évaluation individuelles, est optimisée à un certain niveau de quantification près.L'utilisation de ces algorithmes d'enchère quantifiées est, en premier lieu, étendue aux enchères inversées, c'est-à-dire, des marchés compétitifs où l'on présume qu'il existe seulement des vendeurs, et ensuite, aux double enchères, où les enchères sont définies séparément entre les vendeurs et les acheteurs, qui communiquent d'une façon bien définie. Finalement, les enchères sur réseau sont considérées. Cette analyse est motivée par le fait que les agents dans les réseaux de communication ou les réseaux sociaux ne peuvent pas accéder aux renseignements concernant les offres de tous les autres agents ou aux informations à propos des ressources à travers de tels réseaux et doivent donc fonder leurs décisions seulement sur des renseignements locaux. En particulier, une enchère basée sur un réseau à deux niveaux est mise au point et formulée comme consensus d'enchère UQ-PSP dans lequel les fournisseurs faisant partie du réseau supérieur suivent récursivement la dynamique de consensus afin d'allouer des quantités qui sont sujettes à des enchères UQ-PSP à chaque nœud du réseau. Cette configuration résout le problème du consensus de la moyenne pondérée à temps discret, converge vers un prix unique pour tout le réseau et atteint l'utilité sociale pour le réseau en entier.

Thesis (Ph.D.)--Lehigh University, 2007. / Adviser: George R. Wilson.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008. / Source: Dissertation Abstracts International, Volume: 69-11, Section: B, page: 7122. Advisers: Carolyn Beck; Srinivasa Salapaka. Includes bibliographical references (leaves 141-146) Available on microfilm from Pro Quest Information and Learning.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008. / Source: Dissertation Abstracts International, Volume: 69-07, Section: B, page: 4397. Adviser: C. Beck. Includes bibliographical references (leaves 116-122) Available on microfilm from Pro Quest Information and Learning.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 4081. Adviser: Deborah L. Thurston. Includes bibliographical references (leaves 148-157) Available on microfilm from Pro Quest Information and Learning.

Surveillance of a partially observable system is complex. There are many systems that can be considered as partially observable due to their unknown or partially known structures or the nature of their unknown products and/or partially known results. The impacts of the consumption of genetically modified food (GM) are an example of a system that is only partially observable. The safety of genetically modified foods (GM) products has caused much controversy. Absence of sufficient and reliable information prevents neither certain confidence about the harmlessness of product consumption, nor any certain conclusion to merit a ban for fear of harm. The lack of any reliable or conclusive post-market observation and consumption effects information, make it difficult to establish a global protocol for such products. This paper introduces a model for the analysis of partially observable information from the surveillance of post-market consumption of systems such as genetically modified foods (GM) products. This model uses Markov Chains, paired with a Bayesian updating function to estimate the statistical impacts of surveillance observations and modified surveillance policies. A case study on population health status is used as an illustrative example, which is modeled to demonstrate the impact of policy interventions on simulated data. A cost decision analysis model is also applied to illustrate the impact of policy intervention costs. The model uses a first order Markov chain to estimate the period-over-period change in health status and a Bayesian updating procedure to estimate the population health status based on observations from post-market surveillance. The results show how observation samples can be used to provide information on system changes and improvements.

Variable-step variable-order 2-stage Hermite-Birkhoff-Obrechkoff (HBO) methods, HBO(p)2, of order p = 3 to 14, named HBO(3-14)2, are constructed for solving nonstiff first-order differential equations. Forcing an expansion of the numerical solution to agree with a Taylor expansion of the true solution leads to multistep and Runge-Kutta type order conditions which are reorganized into linear Vandermonde-type systems of HBO type. Fast algorithms are developed for solving these systems in O( p2) operations to obtain Hermite-Birkhoff interpolation polynomials in terms of generalized Lagrange basis functions. The order and step size of these methods are controlled by four local error estimators. For numerical computation the lower order 3 is raised to 4 since HBO(4-14)2 produces better results. When programmed in Matlab, HBO (4-14) 2 is superior to Matlab's ode113 in solving several problems often used to test higher order ODE solvers on the basis of the number of steps, CPU time, and maximum global error. On the other hand, HBO (4-14)2 and the Dormand-Prince 13-stage nested Runge-Kutta pair DP(8,7)13M are programmed in C. In this case, DP(8,7) uses less CPU time, have smaller maximum global error but require a larger number of function evaluations than HBO(4-14)2 on nonexpensive problems. However, for expensive equations, such as the Cubicwave, HBO(4-14)2 is superior. Compared with previous results obtained by the 3-stage HBO(4-14)3 on Van der Pol equations with increasing value of epsilon, the new HBO(4-14)2 finally dominates.

This thesis describes the design and implementation of handheld Wi-Fi applications in ambulance systems, which propose a solution that allows ambulance staff to access remote resources in Emergent Medical Services (EMS) from any location, record life measurements on site by using handheld PCs, and transfer patients' life measurements to the Emergency Room (ER) on the way to the hospital. The handheld Wi-Fi applications aim to provide mobility and efficiency for ambulance staff when saving a life. The handheld Wi-Fi applications afford ambulance staff more flexibility and high performance in accessing and sharing the patient's life data between the ambulance centre and hospitals in time-sensitive circumstances. The handheld Wi-Fi applications provide instant information transportation support for both ambulance staff and healthcare staff. The patient's life measurements are received before the ambulance reaches the hospital.