Recent Developments in Cooperative Control and Optimization

by Butenko, Sergiy; Murphey, Robert; Pardalos, Panos M.

• ISBN13: 9781402076442
• ISBN10: 1402076444
• Format: Hardcover
• Copyright: 2003-11-01
• Publisher: Kluwer Academic Pub

Summary

Over the past several years, cooperative control and optimization has unquestionably been established as one of the most important areas of research in the military sciences. Even so, cooperative control and optimization transcends the military in its scope - having become quite relevant to a broad class of systems with many exciting commercial applications. One reason for all the excitement is that research has been so incredibly diverse - spanning many scientific and engineering disciplines. This latest volume in the "Cooperative Systems" book series clearly illustrates this trend towards diversity and creative thought. It's no wonder, cooperative systems are among the hardest systems control science has endeavored to study, hence creative approaches to modeling, analysis, and synthesis are a must. Audience: This volume is suitable for faculty, graduate students, and researchers in optimization and control, computer science and engineering.

Table of Contents

Preface	xiii
A Hybrid Projected Gradient-Evolutionary Search Algorithm for Capacitated Multi-Source Multi-UAVs Scheduling with Time Windows	1	(22)
Ali Ahmadzadeh
Bijan Sayyar-Roudsari
Abdollah Homaifar
Introduction	2	(2)
Mathematical Programming Formulation For Capacitated Multi-UAV Routing With Time Windows	4	(3)
Hybrid Projected Gradient-Evolutionary Search Algorithm	7	(9)
Simulation Results	16	(2)
Conclusion	18	(5)
Progress in Cooperative Volume Holographic Imaging	23	(22)
George Barbastathis
Arnab Sinha
Introduction	23	(3)
Formation of Volume Holographic Images	26	(5)
Volume Holographic Imaging with Planar Reference holograms	31	(7)
Cooperative Processing of Volume Holographic Images Using the Pseudo--Inverse Method	38	(5)
Conclusions and Future Work	43	(2)
Properties of No-Depot Min-Max 2-Traveling-Salesmen Problem	45	(16)
Vladimir Bugera
Introduction	45	(2)
Characteristic Function for No-Depot Min-Max 2-TSP	47	(3)
Threshold Characteristic Function	50	(3)
Constant Graphs	53	(1)
Interpretation of Threshold Self-Dual Monotonic Boolean Functions	54	(4)
Conclusion	58	(3)
A New Heuristic for the Minimum Connected Dominating Set Problem on Ad Hoc Wireless Networks	61	(14)
Sergiy Butenko
Xiuzhen Cheng
Carlos A.S Oliveira
P. M. Pardalos
Introduction	62	(2)
Algorithm for the MCDS Problem	64	(2)
A Distributed Implementation	66	(2)
Numerical Experiments	68	(3)
Concluding Remarks	71	(4)
A Platform for Cooperative and Coordinated Control of Multiple Vehicles: The Caltech Multi-Vehicle Wireless Testbed	75	(30)
Timothy Chung
Lars Cremean
William B. Dunbar
Zhipu Jin
Eric Klavins
David Moore
Abhishek Tiwari
Dave van Gogh
Stephen Waydo
Introduction	75	(5)
Vehicle Hardware	80	(6)
Lab Positioning System	86	(1)
Onboard Sensing	87	(2)
Electronics	89	(3)
Software Environment	92	(2)
Communications	94	(1)
Modeling and Control	95	(6)
Future Directions	101	(1)
Conclusion	102	(3)
Churning: Repeated Optimization and Cooperative Instability	105	(12)
J. Willard Curtis
Introduction	105	(1)
Problem Formulation	106	(2)
Receding Horizon Instability and Churning	108	(1)
Churning Instability	109	(2)
Limiting Churn	111	(1)
Example	112	(2)
Discussion and Conclusion	114	(3)
A Hospitability Map Approach for Estimating a Mobile Targets Location	117	(8)
Martin Eilders
Jeff Layne
Zaher M. Kassas
Umit Ozguner
Introduction	118	(1)
Approach	119	(1)
Simulation Results	120	(3)
Future Research	123	(2)
Information Theoretic Organization Principles for Autonomous Multiple-Agents	125	(20)
Deniz Erdogmus
Jose C. Principe
Rajvignesh Thogulua
Introduction	125	(2)
Background on Information Theory	127	(1)
Nonparametric Estimation of Renyi's Entropy	128	(1)
Information Particles	129	(3)
Self-Organization of Multiple Agents Using Particle Interaction Principles	132	(3)
Case Study Using a Particular Implementation	135	(6)
Conclusions	141	(4)
Distributed Agreement Strategies for Cooperative Control: Modeling and Scalability Analysis	145	(22)
Sriram Ganapathy
Kevin M. Passino
Multi-UAV Cooperative Control Problem Model	146	(12)
Cooperative Agreement Strategies	158	(5)
Concluding Remarks	163	(4)
An Integer Programming Model for Assigning Unmanned Air Vehicles to Tasks	167	(8)
Michael J. Hennebry
Ahmed Kamel
Kendall E. Nygard
Model	168	(1)
Model Characteristics	169	(1)
Solution Method	170	(1)
Computational Experiments	170	(5)
A Theoretical Foundation for Cooperative Search, Classification, and Target Attack	175	(32)
David R. Jacques
Meir Pachter
Introduction	176	(2)
Modelling	178	(3)
Scenario 1	181	(7)
Scenario 2	188	(3)
Scenario 3	191	(4)
Scenario 4	195	(2)
Scenario 5	197	(4)
Scenario 6	201	(2)
Cooperative Control	203	(1)
Conclusion	204	(3)
Cooperative Real-Time Task Allocation Among Groups of UAVs	207	(18)
Yan Jin
Marios M. Polycarpou
Ali A. Minai
Introduction	208	(7)
Algorithm Description	215	(2)
Performance Measures	217	(1)
Simulation Results	218	(1)
Decentralization Approach	218	(3)
Conclusion and Future Work	221	(4)
Appendix: Derivation of Top Update Equations	222	(3)
Use of Conditional Value-at-Risk in Stochastic Programs with Poorly Defined Distributions	225	(18)
Pavlo Krokhmal
Robert Murphey
Panos Pardalos
Stanislav Uryasev
Deterministic Weapon-Target Assignment Problem	227	(4)
Two-Stage Stochastic WTA Problem	231	(1)
Two-Stage WTA Problem with Uncertainties in Specified Distributions	232	(4)
Case Study	236	(7)
Sensitivity Analysis of Partially Deployed Slowdown Warning Mechanisms for Vehicle Platoons	243	(18)
Vishwesh Kulkarni
Jan De Mot
Nicola Elia
Eric Feron
James Paduano
Introduction	244	(1)
Notation and Problem Formulation	245	(2)
DP and NDP Formulations	247	(2)
Main Results	249	(3)
Complexity Reduction: Multilevel Path Planning	252	(1)
Discussion	253	(1)
Conclusion and Future Directions	254	(7)
Appendix: Proof of Lemma 4.1	255	(6)
Multi-Target Assignment and Path Planning for Groups of UAVs	261	(12)
Theju Maddula
Ali A. Minai
Marios M. Polycarpou
Introduction	262	(7)
Simulation Results	269	(1)
Conclusion and Future Work	269	(4)
Objective Functions for Bayesian Control-Theoretic Sensor Management, II: MHC-Like Approximation	273	(44)
Ronald Mahler
Introduction	273	(5)
Single-Sensor, Single-Target Bayesian Control	278	(8)
Multisensor-Multitarget Bayesian Control	286	(8)
Single-Step Objective Functions	294	(6)
Multistep Objective Functions	300	(4)
Sensor Management With MHC-Like Filters	304	(6)
Mathematical Proofs	310	(4)
Conclusions	314	(3)
Tracking Environmental Level Sets with Autonomous Vehicles	317	(16)
Daniel Marthaler
Andrea L. Bertozzi
Introduction	317	(2)
Energy Minimizing Curves in Image Processing	319	(1)
Agent Based Motion via ``Virtual'' Contours	320	(2)
Implementation and Communication	322	(3)
Cooperative Motion Simulations	325	(1)
Boundary Tracking without Communication	326	(2)
Robustness under Sensor Noise	328	(2)
Conclusions and Future Work	330	(3)
Cyclic Linearization and Decomposition of Team Game Models	333	(16)
Athanasios Migdalas
Introduction	333	(3)
General Properties	336	(2)
The Cyclic Linearization Algorithm	338	(3)
Inaccurate Linearized Realizations of the Cyclic Decomposition	341	(8)
Optimal Path Planning in a Threat Environment	349	(58)
Rob Murphey
Stanislav Uryasev
Michael Zabarankin
Introduction	350	(4)
Model Development	354	(3)
Calculus of Variations Approach	357	(18)
Network Flow Optimization Approach	375	(11)
Numerical Experiments	386	(11)
Analysis of Computational Results	397	(3)
Conclusions	400	(7)
Appendix: Minimization of a Functional with Nonholonomic Constraint and Movable End Point	402	(5)
Nonlinear Dynamics of Sea Clutters and Detection of Small Targets	407	(20)
Panos M. Pardalos
Vitaliy A. Yatsenko
Don A. Grundel
Introduction	408	(1)
Method	409	(9)
Simulation Results	418	(3)
Experimental Results	421	(2)
Mathematical and Physical Models of Sea Clutter	423	(1)
Discussion and Conclusion	424	(3)
Tree-Based Algorithms for the Multidimensional Assignment Problem	427	(22)
Eduardo L. Pasiliao
Introduction	427	(4)
Tree Representations	431	(3)
Branch and Bound Algorithms	434	(5)
Greedy Randomized Adaptive Search Procedure	439	(6)
Concluding Remarks	445	(4)
Predicting Pop Up Threats From An Adaptive Markov Model	449	(1)
Shankar K. Subramanian
Jose B. Cruz
Phillip R. Chandler
Meir Pachter
Introduction	450	(1)
Modeling of Pop Up Targets	450	(1)
Adaptive Markov Model	451	(2)
Modeling of UAVs	453	(2)
Generating Data for Red Pop Up Locations	455	(1)
Experimental Results	456	(2)
Conclusion	458