Model order reduction techniques for circuit simulation

Includes bibliographical references (p. 156-160).Supported in part by the Semiconductor Research Corporation. SRC 93-SJ-558 Supported in part by the National Science Foundation / Advanced Research Projects Agency. MIP 91-17724Luis Miguel Silveira

Model order reduction techniques for circuit simulation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references.by ?Luís Miguel Silveira.Ph.D

Humanoid Robot Soccer Locomotion and Kick Dynamics: Open Loop Walking, Kicking and Morphing into Special Motions on the Nao Robot

Striker speed and accuracy in the RoboCup (SPL) international robot soccer league is becoming increasingly important as the level of play rises. Competition around the ball is now decided in a matter of seconds. Therefore, eliminating any wasted actions or motions is crucial when attempting to kick the ball. It is common to see a discontinuity between walking and kicking where a robot will return to an initial pose in preparation for the kick action. In this thesis we explore the removal of this behaviour by developing a transition gait that morphs the walk directly into the kick back swing pose. The solution presented here is targeted towards the use of the Aldebaran walk for the Nao robot. The solution we develop involves the design of a central pattern generator to allow for controlled steps with realtime accuracy, and a phase locked loop method to synchronise with the Aldebaran walk so that precise step length control can be activated when required. An open loop trajectory mapping approach is taken to the walk that is stabilized statically through the use of a phase varying joint holding torque technique. We also examine the basic princples of open loop walking, focussing on the commonly overlooked frontal plane motion. The act of kicking itself is explored both analytically and empirically, and solutions are provided that are versatile and powerful. Included as an appendix, the broader matter of striker behaviour (process of goal scoring) is reviewed and we present a velocity control algorithm that is very accurate and efficient in terms of speed of execution

Resource optimization and dynamic state management in a collaborative virtual environment.

Yim-Pan Chui.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 126-132).Abstracts in English and Chinese.Abstract --- p.iiAcknowledgments --- p.vChapter 1 --- Introduction --- p.1Chapter 1.1 --- Introduction to Collaborative Virtual Environments --- p.1Chapter 1.2 --- Barriers to Resource Management and Optimization --- p.3Chapter 1.3 --- Thesis Contributions --- p.5Chapter 1.4 --- Application of this Research Work --- p.6Chapter 1.5 --- Thesis Organization --- p.6Chapter 2 --- Resource Optimization - Intelligent Server Partitioning --- p.9Chapter 2.1 --- Introduction --- p.9Chapter 2.2 --- Server Partitioning --- p.13Chapter 2.2.1 --- Related Works --- p.15Chapter 2.2.2 --- Global Optimization Approaches --- p.17Chapter 2.3 --- Hybrid Genetic Algorithm Paradigm --- p.17Chapter 2.3.1 --- Drawbacks of traditional GA --- p.18Chapter 2.3.2 --- Problem Modeling --- p.19Chapter 2.3.3 --- Discussion --- p.24Chapter 2.4 --- Results --- p.25Chapter 2.5 --- Concluding Remarks --- p.28Chapter 3 --- Dynamic State Management - Dead Reckoning of Attitude --- p.32Chapter 3.1 --- Introduction to Dynamic State Management --- p.32Chapter 3.2 --- The Dead Reckoning Approach --- p.35Chapter 3.3 --- Attitude Dead Reckoning by Quaternion --- p.37Chapter 3.3.1 --- Modeling of the Paradigm --- p.38Chapter 3.3.2 --- Prediction Step --- p.39Chapter 3.3.3 --- Convergence Step --- p.40Chapter 3.3.4 --- Overall Algorithm --- p.46Chapter 3.4 --- Results --- p.47Chapter 3.5 --- Conclusion --- p.51Chapter 4 --- Polynomial Attitude Extrapolation --- p.52Chapter 4.1 --- Introduction --- p.52Chapter 4.2 --- Related Works on Kalman Filtering --- p.53Chapter 4.3 --- Historical Propagation of Quaternion --- p.54Chapter 4.3.1 --- Cumulative Extrapolation --- p.54Chapter 4.3.2 --- Method I. Vandemonde Approach --- p.55Chapter 4.3.3 --- Method II. Lagrangian Approach --- p.58Chapter 4.4 --- History-Based Attitude Management --- p.60Chapter 4.4.1 --- Multi-order Prediction --- p.60Chapter 4.4.2 --- Adaptive Attitude Convergence --- p.63Chapter 4.4.3 --- Overall Algorithm --- p.67Chapter 4.5 --- Results --- p.69Chapter 4.6 --- Conclusion --- p.77Chapter 5 --- Forward Difference Approach on State Estimation --- p.78Chapter 5.1 --- Introduction --- p.78Chapter 5.2 --- Positional Forward Differencing --- p.79Chapter 5.3 --- Forward Difference on Quaternion Space --- p.80Chapter 5.3.1 --- Attitude Forward Differencing --- p.83Chapter 5.3.2 --- Trajectory Blending --- p.84Chapter 5.4 --- State Estimation --- p.86Chapter 5.5 --- Computational Efficiency --- p.87Chapter 5.6 --- Results --- p.88Chapter 5.7 --- Conclusion --- p.96Chapter 6 --- Predictive Multibody Kinematics --- p.98Chapter 6.1 --- Introduction --- p.98Chapter 6.2 --- Dynamic Management of Multibody System --- p.100Chapter 6.2.1 --- Multibody Representation --- p.100Chapter 6.2.2 --- Paradigm Overview --- p.101Chapter 6.3 --- Motion Estimation by Joint Extrapolation --- p.102Chapter 6.3.1 --- Individual Joint Extrapolation --- p.102Chapter 6.3.2 --- Forward Propagation of Joint State --- p.104Chapter 6.3.3 --- Pose Correction --- p.107Chapter 6.4 --- Limitations on Predictive Articulated State Management --- p.108Chapter 6.5 --- Implementation and Results --- p.109Chapter 6.6 --- Conclusion --- p.112Chapter 7 --- Complete System Architecture --- p.113Chapter 7.1 --- Server Cluster Model --- p.113Chapter 7.1.1 --- Peer-Server Systems --- p.114Chapter 7.1.2 --- Server Hierarchies --- p.114Chapter 7.2 --- Multi-Level Resource Management --- p.115Chapter 7.3 --- Aggregation of State Updates --- p.116Chapter 7.4 --- Implementation Issues --- p.117Chapter 7.4.1 --- Medical Visualization --- p.117Chapter 7.4.2 --- Virtual Walkthrough Application --- p.118Chapter 7.5 --- Conclusion --- p.119Chapter 8 --- Conclusions and Future directions --- p.121Chapter 8.1 --- Conclusion --- p.121Chapter 8.2 --- Future Research Directions --- p.122Chapter A --- Quaternion Basis --- p.124Chapter A.1 --- Basic Quaternion Mathematics --- p.124Chapter A.2 --- The Exponential and Logarithmic Maps --- p.125Bibliography --- p.12

A dynamic model of the extravehicular mobility unit (EMU) : human performance issues during EVA

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1997.Includes bibliographical references (leaves 97-99).by David B. Rahn.M.S

Research in nonlinear structural and solid mechanics

Nonlinear analysis of building structures and numerical solution of nonlinear algebraic equations and Newton's method are discussed. Other topics include: nonlinear interaction problems; solution procedures for nonlinear problems; crash dynamics and advanced nonlinear applications; material characterization, contact problems, and inelastic response; and formulation aspects and special software for nonlinear analysis