scholarly journals Modeling, Identification, and Control of Large-Scale Dynamical Systems

2006 ◽  
Author(s):  
S. Haykin ◽  
A.O. Hero ◽  
E. Moulines
Keyword(s):  
Dynamical Systems ◽  
Large Scale ◽  
And Control

Conclusion

2011 ◽  
Author(s):  
Wassim M. Haddad ◽  
Sergey G. Nersesov
Keyword(s):  
Dynamical Systems ◽  
Large Scale ◽  
Multiple Equilibria ◽  
Nonlinear Models ◽  
Dynamical Behavior ◽  
Transportation Systems ◽  
Network Systems ◽  
Grid Systems ◽  
Feedback Interconnections ◽  
And Control

This book has described a general stability analysis and control design framework for large-scale dynamical systems, with an emphasis on vector Lyapunov function methods, vector dissipativity theory, and decentralized control architectures. The large-scale dynamical systems are composed of interconnected subsystems whose relationships are often circular, giving rise to feedback interconnections. This leads to nonlinear models that can exhibit rich dynamical behavior, such as multiple equilibria, limit cycles, bifurcations, jump resonance phenomena, and chaos. The book concludes by discussing the potential for applying and extending the results across disciplines, such as economic systems, network systems, computer networks, telecommunication systems, power grid systems, and road, rail, air, and space transportation systems.

Introduction

2011 ◽  
Author(s):  
Wassim M. Haddad ◽  
Sergey G. Nersesov
Keyword(s):  
Dynamical Systems ◽  
Finite Time ◽  
Lyapunov Functions ◽  
Large Scale ◽  
Interconnected Systems ◽  
Large Scale Systems ◽  
Vector Lyapunov Functions ◽  
Finite Time Stabilization ◽  
And Control ◽  
Interconnected Dynamical Systems

This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, with an emphasis on vector Lyapunov function methods and vector dissipativity theory. It examines large-scale continuous-time interconnected dynamical systems and describes thermodynamic modeling of large-scale interconnected systems, along with the use of vector Lyapunov functions to control large-scale dynamical systems. It also discusses finite-time stabilization of large-scale systems via control vector Lyapunov functions, coordination control for multiagent interconnected systems, large-scale impulsive dynamical systems, finite-time stabilization of large-scale impulsive dynamical systems, and hybrid decentralized maximum entropy control for large-scale systems. This chapter provides a brief introduction to large-scale interconnected dynamical systems as well as an overview of the book's structure.

Stability and Control of Large-Scale Dynamical Systems

2011 ◽  
Author(s):  
Wassim M. Haddad ◽  
Sergey G. Nersesov
Keyword(s):  
Dynamical Systems ◽  
Decentralized Control ◽  
Finite Time ◽  
Large Scale ◽  
Synthesis Methods ◽  
Network Systems ◽  
Finite Time Stability ◽  
Analysis And Design ◽  
And Control ◽  
Interconnected Dynamical Systems

Modern complex large-scale dynamical systems exist in virtually every aspect of science and engineering, and are associated with a wide variety of physical, technological, environmental, and social phenomena, including aerospace, power, communications, and network systems, to name just a few. This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, and presents the most complete treatment on vector Lyapunov function methods, vector dissipativity theory, and decentralized control architectures. Large-scale dynamical systems are strongly interconnected and consist of interacting subsystems exchanging matter, energy, or information with the environment. The sheer size, or dimensionality, of these systems necessitates decentralized analysis and control system synthesis methods for their analysis and design. Written in a theorem-proof format with examples to illustrate new concepts, this book addresses continuous-time, discrete-time, and hybrid large-scale systems. It develops finite-time stability and finite-time decentralized stabilization, thermodynamic modeling, maximum entropy control, and energy-based decentralized control. This book will interest applied mathematicians, dynamical systems theorists, control theorists, and engineers, and anyone seeking a fundamental and comprehensive understanding of large-scale interconnected dynamical systems and control.

Collaboration, Power, Participation and Control on a Large Scale Research Team: Multiple Perspectives from the Oxford House Research Project

2001 ◽  
Author(s):  
Bradley Olson ◽  
Leonard Jason ◽  
Joseph R. Ferrari ◽  
Leon Venable ◽  
Bertel F. Williams ◽  
...  
Keyword(s):  
Large Scale ◽  
Research Team ◽  
Multiple Perspectives ◽  
Research Project ◽  
Oxford House ◽  
And Control

Interference mitigation in point to point wireless sensor networks using LSP protocol and time division multiplexing approach

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Control Parameter ◽  
Interference Mitigation ◽  
Wireless Sensor ◽  
Point To Point ◽  
A Minor ◽  
Two Stages ◽  
Time Division ◽  
And Control

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.

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