CDC2000 Agile Control of Military Operations

Agile Control of Military Operations
Home Full List of Titles 1: Proceedings of CDC2000 Discrete Event Systems Control in Communication Systems Optimal Control and Applications I Optimisation Approaches and Methods Model Predictive Control Advances in Linear Estimation Stochastic and Uncertain Systems Nonlinear Control and Applications Nonlinear Estimation and Filtering Formation Control and its Applications New Approaches to Fuzzy Control Manufacturing Systems Automotive Applications Stability Issues in Hybrid Control Recent Advances in Stochastic Networks Optimal Control and Applications II Robust Controller Design - mu, L1 and H2 Constrained and Receding Horizon Control Identification and Control around the World Markov Decision Processes Nonlinear Optimisation Observers for Nonlinear Systems Motion Planning Neural / Fuzzy Stability and Control Motor Control Control of Quantum Phenomena I Hybrid Systems Methods Control in Communication Networks Robustness and Optimisation Bumpless Transfer, Antiwindup and Saturation Adaptive Control: Linear Systems Estimation and Closed Loop Identification Control of Markov Processes Nonlinear Filtering and Control Modelling, Identification and Validation of Nonlinear Systems Differential Geometric Control Theory for Mechanical Systems Nonlinear Output Feedback Control Pneumatics and Compression Systems Control of Quantum Phenomena II Stability of Hybrid Systems Performance Analysis in Communication Networks Adaptive Control of Nonlinear Systems LMI Methods in Design Robust Control of Time Delay Systems Subspace Identification Methods Nonlinear Stochastic Filtering and Estimation Bifurcations, Chaos and Control I New Progress in Synthesis of Nonlinear Systems I Implementation Issues of Sliding Mode Control Theory Control of Mixing in Shear Flows Novel Neural Network Control Techniques for Industrial Motion Control Systems Physiological Control Systems Optimal Control of Hybrid Systems Stochastic Models for Communication Networks Control and Stabilisation of Nonlinear Systems New Directions in Robust Control Linear Systems Theory Advanced Topics in Systems Theory Estimation in Action Bifurcations, Chaos and Control II New Progress in Synthesis of Nonlinear Systems II Numerical Design and Analysis Techniques for Nonlinear Systems Analysis and Control of Underactuated Systems Sliding Mode Control I Challenges in the Application of Control to Computer Systems Estimation and Diagnosis of Discrete Event Systems Communications and Games Optimal Control Stochastic Systems Model Reduction Methodologies Identification and Subspace Methods Applications of Nonlinear Adaptive Control Advances in Nonlinear Output Feedback Design The Behavioural Approach to Systems and Control Vision Based Estimation and Control: Recent Advances and Open Problems Agile Control of Military Operations Sliding Mode Control II Model-based Fault Diagnosis of Industrial Processes Discrete Event Systems / Petri Nets System Identification and Confidence Estimation New Approaches to H-Infinity Control I Probabilistic Approaches to Robust Control Time Delay System Stabilisation Identification Methods Controlled Stochastic Processes Output Feedback of Nonlinear Systems Topics in Nonlinear Stabilisation Mobile Robots: Tracking Control Robust Control of Nonlinear Systems Power Systems Stabilisation and Control Disk Drive Control Hybrid Control Applications Discrete Time Systems New Approaches to H-Infinity Control II Linear Systems with Saturating Actuators New Theories in Distributed Parameter Systems Applications of Estimation and Identification Stochastic Control and Tuning Methodologies Control of Nonlinear Systems Iterative Learning and Control Coordinating Robot Systems Nonlinear Time Varying Systems Novel Applications of Neural Networks Aerospace Applications Switched Systems Implicit and Descriptor Systems LQG Periodic Systems and Disturbances New Horizons for Distributed Parameter Systems State Estimation Learning and Neuro-Control Nonlinear Control and Stabilisation I Tracking Vision Servoing Controllability of Nonlinear Systems Control of Flexible Systems Electro-Mechanical Systems Robust Control Methods and Applications Fault Detection and Diagnosis Optimisation and Applications Robust Stability Analysis Numerical Methods in Control Filtering in Continuous Time Stochastic Systems Interplay between Control and Signal Processing Fault Detection and Analysis Nonlinear Dynamical Systems Nonlinear Time Delay Systems Computational Issues in Nonlinear Control Disturbance Rejection Process Control Industry Applications Linear Parameter Varying Systems Linear Control Systems Dynamic and Nonlinear Programming Model Reduction Applications New Techniques for Control and Systems: Numerical Linear Algebra Estimation and Identification using Hidden Markov Models Applications of Stochastic Control Topics in Linear Design Nonlinear Control and Stabilisation II Ambulatory Robot Systems Chaotic and Oscillatory Systems Biomedical System Control Integrated Control and CPU Scheduling Linear Design Techniques Adaptive Disturbance / Noise Compensation Nonlinear Model Predictive Control Sensitivity Design, Analysis and Limitations Analysis of Linear Systems Linear Matrix Inequalities in Design Lyapunov's 2nd Method Robotics: Tracking Control Lagrangian and Hamiltonian Theory Variable Structure Control Machine Vision Signal Processing Methods in Control Applied Nonlinear Control Author Index A B C D E F G H I J K L M N O P Q R S T U V W X Y Z	The DARPA JFACC Program: Modeling and Control of Military Operations Authors: Sharon A. Heise, H. Stephen Morse, Volume: 1, Page 2551 Paper number 4606 Abstract: In the Introduction to this paper, the goals, scope, and structure of the DARPA JFACC program will be described, with emphasis on the flexibility given to investigators in problem definition and research objectives, and the wide variety of approaches that have been proposed. In Section 2, five major areas of research will be briefly summarized: active adversary and game theoretic techniques; stochastic optimization; model predictive control; finite state machines and discrete event systems; and emergent behavior. Section 3 will describe the major Concepts of Operation under consideration for application of this research: fully autonomous operation; state estimation and prediction; tracking and adaptive control; and on-line sensitivity analysis. Section 4 will present significant conclusions arising out of current research, and future directions. CD004606.PDF (From Author) TOP Game Theoretic Campaign Modeling and Analysis Authors: Debasish Ghose, Mikhail Krichman, Jason L. Speyer, Jeff S. Shamma, Volume: 1, Page 2556 Paper number 4601 Abstract: In this paper we address the modeling and analysis issues associated with a generic theater level campaign where two adversaries pit their military resources against each other over a long series of engagements. Specifically, we use the scenario of an air raid campaign using SEAD aircraft and bombers against enemy troops and air defense units. The problem is decomposed into a temporal and a spatial resource allocation problem. The temporal resource allocation problem is formulated as a multiple resource interaction problem in a game-theoretical framework and solved for linear attrition functions. The spatial resource allocation problem is posed as a risk minimization problem in which the two adversaries decide on the corridor of ingress and movement of the ground troops and air defense units. These two solutions are integrated using an aggregation/deaggregation approach to evaluate resource strengths and distribute losses. CD004601.PDF (From Author) CD004601.PDF (Scanned) TOP Model Predictive Control of Military Operations Authors: Jan Jelinek, Datta Godbole, Volume: 1, Page 2562 Paper number 4602 Abstract: Competitors in the marketplace or combatants on the battlefield face very similar challenges: Their resources, be they money or weapons, are gradually attrited in the mutual effort to push each other out of the field and dominate it. Even if the participants are deterministic in their decision-making, executing their decisions has random aspects, when the same, generally successful actions occasionally fail for no obvious reasons. The application of system and control theories to improve the planning as well as the execution of such processes requires models, which allow planners and managers to reliably predict the expected outcomes of various alternatives over a long horizon into the future. In this article, exact probabilistic models for several classes of battle scenarios are developed from the first principles, which accurately characterize the battle dynamics for arbitrarily long horizons. It is shown how the models are used for model predictive control of the battle dynamics CD004602.PDF (From Author) TOP Stochastic Games and Inverse Lyapunov Methods in Air Operations Authors: William M. McEneaney, Kazufumi Ito, Volume: 1, Page 2568 Paper number 4603 Abstract: A mathematical representation of the air operations command and control problem is developed. The size of the problem implies a need for reduction to subproblems. Two of these subproblems are discussed here. First, the development of an approach to the generation of approximate optimal aircraft routing through a hostile region is given. Once this is established, a stochastic game is solved to determine the time-ordering of aircraft engagements with surface-to-air missile batteries, for the ultimate purpose of engaging a strategic target. CD004603.PDF (From Author) TOP Game-Theoretic Linear-Quadratic Method for Air Mission Control Authors: Hiro Mukai, Akio Tanikawa, Ilker Tunay, I. Alpay Ozcan, I. Norman Katz, Heinz M. Schättler, P. Rinaldi, G.J. Wang, L. Yang, Y. Sawada, Volume: 1, Page 2574 Paper number 4604 Abstract: In this paper, we present a dynamic model of air operations for the military and formulate the problem of controlling its mission details as a differential game. We then present a numerical method for finding its Nash equilibrium solution. The method is an iterative process in which a linear-quadratic approximation of the original game is successively solved using the Riccati equation approach. CD004604.PDF (From Author) TOP Modeling and Control of Military Operations Against Adversarial Control Authors: Jose B. Cruz Jr, Marwan A. Simaan, Aca Gacic, Huihui Jiang, Bruno Letellier, Ming Li, Volume: 1, Page 2581 Paper number 4605 Abstract: In this paper we present a nonlinear state space mathematical model for a class of dynamical systems that can serve as the basis for a simulation test bed for the investigation of enterprise control. Dynamic complex enterprises generally include multiple control agents of a decision team. In addition, the enterprise is generally imbedded in a larger environment that has competing and even hostile decision teams that affect the enterprise. In such situations it is appropriate to model an extended enterprise that includes the competing decision teams. For example an enterprise might be a military command and control hierarchy with several levels of command. If a command and control enterprise is deployed in a military operation, the enterprise states may be affected by non-friendly commands. In order to develop acceptable and even optimal control strategies, it is important to consider the effect of the adversarial controls even at the control design stage. Before these control strategies can be designed or investigated, a model for the extended enterprise "plant" is needed. This extended plant should have inputs from the competing decision team, in addition to the decision team inputs to the enterprise. In our model the command hierarchy will be designated as the Blue Forces. The enterprise is imbedded in a larger system that includes a hostile command designated as the Red Forces. This extended enterprise will be designated as "Military Operations". In this paper, a discrete-time nonlinear state space model of a Military Operation is formulated and an example illustrating the implementation of the Nash strategies from non-zero sum game theory is presented. CD004605.PDF (From Author) TOP