This is a state-of-the-art treatise on the problems of both nonlinearity and uncertainty in the dynamics and control of engineering systems. The concept of dynamics and control implies the combination of dynamic analysis and control synthesis. It is essential to gain insight into the dynamics of a nonlinear system with uncertainty if any new control strategy is designed to utilize nonlinearity.

Non-linear stochastic systems are at the center of many engineering disciplines and progress in theoretical research had led to a better understanding of non-linear phenomena. This book provides information on new fundamental results and their applications which are beginning to appear across the entire spectrum of mechanics. The outstanding points of these proceedings are Coherent compendium of the current state of modelling and analysis of non-linear stochastic systems from engineering, applied mathematics and physics point of view. Subject areas include: Multiscale phenomena, stability and bifurcations, control and estimation, computational methods and modelling. For the Engineering and Physics communities, this book will provide first-hand information on recent mathematical developments. The applied mathematics community will benefit from the modelling and information on various possible applications.

The Symposium brought together many of the world’s experts in fluid mechanics, microfabrication and control theory to discover the synergy that can lead to real advances and perhaps find ways in which collaborative projects may proceed. The high profile meeting was attended by keynote speakers who are leaders in their fields. A key driver was the improvement in flow efficiency to reduce drag, and thereby emissions arising from transport. About 65 papers were presented.

This volume contains the proceedings of the IUTAM Symposium on Computational Physics and New Perspectives in Turbulence, held at Nagoya University, Nagoya, Japan, in September 2006. With special emphasis given to fundamental aspects of the physics of turbulence, coverage includes experimental approaches to fundamental problems in turbulence, turbulence modeling and numerical methods, and geophysical and astrophysical turbulence.

The interest of the applied mechanics community in chaotic dynamics of engineering systems has exploded in the last fifteen years, although research activity on nonlinear dynamical problems in mechanics started well before the end of the Eighties. It developed first within the general context of the classical theory of nonlinear oscillations, or nonlinear vibrations, and of the relevant engineering applications. This was an extremely fertile field in terms of formulation of mechanical and mathematical models, of development of powerful analytical techniques, and of understanding of a number of basic nonlinear phenomena. At about the same time, meaningful theoretical results highlighting new solution methods and new or complex phenomena in the dynamics of deterministic systems were obtained within dynamical systems theory by means of sophisticated geometrical and computational techniques. In recent years, careful experimental studies have been made to establish the actual occurrence and observability of the predicted dynamic phenomena, as it is vitally needed in all engineering fields. Complex dynamics have been shown to characterize the behaviour of a great number of nonlinear mechanical systems, ranging from aerospace engineering applications to naval applications, mechanical engineering, structural engineering, robotics and biomechanics, and other areas. The International Union of Theoretical and Applied Mechanics grasped the importance of such complex phenomena in the Eighties, when the first IUTAM Symposium devoted to the general topic of nonlinear and chaotic dynamics in applied mechanics and engineering was held in Stuttgart (1989).

The increasing necessity to solve complex problems in Structural Dynamics and Earthquake Engineering requires the development of new ideas, innovative methods and numerical tools for providing accurate numerical solutions in affordable computing times. This book presents the latest scientific developments in Computational Dynamics, Stochastic Dynam

1. Introduction. 1.1. Motivation. 1.2. Background. 1.3. Scope of this document. 1.4. Original contributions -- 2. Solutions of systems of DDEs via the matrix Lambert W function. 2.1. Introduction. 2.2. Free systems of DDEs. 2.3. Forced systems. 2.4. Approach using the Laplace transformation. 2.5. Concluding remarks -- 3. Stability of systems of DDEs via the Lambert W function with application to machine tool chatter. 3.1. Introduction. 3.1. The Chatter equation in the turning process. 3.3. Solving DDEs and stability. 3.4. Concluding remarks -- 4. Controllability and observability of systems of linear delay differential equations via the matrix Lambert W function. 4.1. Introduction. 4.2. Controllability. 4.3. Observability. 4.4. Illustrative example. 4.5. Conclusions and future work -- 5. Eigenvalue assignment via the Lambert W function for control of time-delay systems. 5.1. Introduction. 5.2. Eigenvalue assignment for time-delay systems. 5.3. Design of a feedback Controller. 5.4. Conclusions -- 6. Robust control and time-domain specifications for systems of delay differential equations via eigenvalue assignment. 6.1. Introduction. 6.2. Robust feedback. 6.3. Time-domain specifications. 6.4. Concluding remarks -- 7. Design of observer-based feedback control for time-delay systems with application to automotive powertrain control. 7.1. Introduction. 7.2. Problem formulation. 7.3. Design of observer-based feedback controller. 7.4. Application to diesel engine control. 7.5. Conclusions -- 8. Eigenvalues and sensitivity analysis for a model of HIV pathogenesis with an intracellular delay. 8.1. Introduction. 8.2. HIV pathogenesis dynamic model with an intracellular delay. 8.3. Rightmost eigenvalue analysis. 8.4. Sensitivity analysis. 8.5. Concluding remarks and future work

Algorithms are a fundamental component of robotic systems. Robot algorithms process inputs from sensors that provide noisy and partial data, build geometric and physical models of the world, plan high-and low-level actions at different time horizons, and execute these actions on actuators with limited precision. The design and analysis of robot algorithms raise a unique combination of questions from many elds, including control theory, computational geometry and topology, geometrical and physical modeling, reasoning under uncertainty, probabilistic algorithms, game theory, and theoretical computer science. The Workshop on Algorithmic Foundations of Robotics (WAFR) is a single-track meeting of leading researchers in the eld of robot algorithms. Since its inception in 1994, WAFR has been held every other year, and has provided one of the premiere venues for the publication of some of the eld's most important and lasting contributions. This books contains the proceedings of the tenth WAFR, held on June 13{15 2012 at the Massachusetts Institute of Technology. The 37 papers included in this book cover a broad range of topics, from fundamental theoretical issues in robot motion planning, control, and perception, to novel applications.

This volume contains a collection of papers based on lectures and presentations delivered at the International Conference on Constructive Nonsmooth Analysis (CNSA) held in St. Petersburg (Russia) from June 18-23, 2012. This conference was organized to mark the 50th anniversary of the birth of nonsmooth analysis and nondifferentiable optimization and was dedicated to J.-J. Moreau and the late B.N. Pshenichnyi, A.M. Rubinov, and N.Z. Shor, whose contributions to NSA and NDO remain invaluable. The first four chapters of the book are devoted to the theory of nonsmooth analysis. Chapters 5-8 contain new results in nonsmooth mechanics and calculus of variations. Chapters 9-13 are related to nondifferentiable optimization, and the volume concludes with four chapters containing interesting and important historical chapters, including tributes to three giants of nonsmooth analysis, convexity, and optimization: Alexandr Alexandrov, Leonid Kantorovich, and Alex Rubinov. The last chapter provides an overview and important snapshots of the 50-year history of convex analysis and optimization.