Optimization and Dynamical Systems by Uwe Helmke
This work is aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control sys- tems, signal processing, and linear algebra. The motivation for the results developed here arises from advanced engineering applications and the emer- gence of highly parallel computing machines for tackling such applications. The problems solved are those of linear algebra and linear systems the- ory, and include such topics as diagonalizing a symmetric matrix, singular value decomposition, balanced realizations, linear programming, sensitivity minimization, and eigenvalue assignment by feedback control. The tools are those, not only of linear algebra and systems theory, but also of differential geometry. The problems are solved via dynamical sys- tems implementation, either in continuous time or discrete time, which is ideally suited to distributed parallel processing. The problems tackled are indirectly or directly concerned with dynamical systems themselves, so there is feedback in that dynamical systems are used to understand and optimize dynamical systems. One key to the new research results has been the recent discovery of rather deep existence and uniqueness results for the solution of certain matrix least squares optimization problems in geomet- ric invariant theory. These problems, as well as many other optimization problems arising in linear algebra and systems theory, do not always admit solutions which can be found by algebraic methods.-
Inverse Optimal Control and Inverse Noncooperative Dynamic Game Theory
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Robust Filtering for Uncertain Systems
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Adaptive Control
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Distributed Coordination of Multi-agent Networks
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Control of Higher-Dimensional PDEs
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Stochastic Reachability Analysis of Hybrid Systems
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Congestion Control in Data Transmission Networks
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Adaptive Dynamic Programming for Control
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Stability and Stabilization of Nonlinear Systems
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Optimal Design of Distributed Control and Embedded Systems
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Learning and Robust Control in Quantum Technology
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Randomized Algorithms for Analysis and Control of Uncertain Systems
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Cooperative Control of Multi-Agent Systems
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Stability Theory of Switched Dynamical Systems
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Sampled-Data Models for Linear and Nonlinear Systems
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Discrete-Time and Discrete-Space Dynamical Systems
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Simulation-Based Algorithms for Markov Decision Processes
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Control of Wave and Beam PDEs
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Stabilization, Optimal and Robust Control
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Loop Transfer Recovery: Analysis and Design
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Iterative Learning Control
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Model Reduction for Control System Design
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Functional Adaptive Control
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Interactive System Identification: Prospects and Pitfalls
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Dynamic Surface Control of Uncertain Nonlinear Systems
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Nonsmooth Mechanics
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Stability and Stabilization of Infinite Dimensional Systems with Applications
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Analysis and Control of Boolean Networks
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Stabilization of Navier-Stokes Flows
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Control of Nonlinear Dynamical Systems
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Non-Adaptive and Adaptive Control of Manipulation Robots
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Theory of Robot Control
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Direct Adaptive Control Algorithms:
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Control of Complex and Uncertain Systems
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Applied Dynamics and CAD of Manipulation Robots
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Kinematics and Trajectory Synthesis of Manipulation Robots
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Analysis of Periodically Time-Varying Systems
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Modelling and Control of Dynamic Flows in Communication Networks
Brian D. O. Anderson and John B. Moore are the authors of Dover's Optimal Filtering and are both on the faculty of The Australian National University, Canberra.
| SKU | Unavailable |
| ISBN 13 | 9781447134695 |
| ISBN 10 | 1447134699 |
| Title | Optimization and Dynamical Systems |
| Author | Uwe Helmke |
| Series | Communications And Control Engineering |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer London Ltd |
| Year published | 2014-04-09 |
| Number of pages | 403 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |