Proceedings of the IUTAM Symposium on Optimal Guidance and Control for Autonomous Systems 2023 (IUTAM Bookseries, 40)

Contents
Part I Guidance, Navigation and  Control, and Sensor Technologies
1 Force Estimation and Control Enhanced by a Force-Derivative Sensor
	1.1 Introduction
	1.2 Plant Model and an ESO
	1.3 Integrated Force Estimator (IFE)
	1.4 Experimental Study
		1.4.1 Experimental Setup and System Identification
		1.4.2 Implementation of the ESO
		1.4.3 Design and Implementation of Integrated Force Estimator (IFE)
		1.4.4 Force Control and Discussion on the IFEs’ Performance
	1.5 Conclusions
	References
2 Iterative Control Framework with Application to Guidance and Attitude Control of Spacecraft Rendezvous and Docking
	2.1 Introduction
	2.2 Iterative Control Framework
	2.3 Control of Spacecraft Rendezvous and Docking
		2.3.1 Guidance Control
		2.3.2 Attitude Control
	2.4 Numerical Simulations
	2.5 Conclusion
	References
3 ESA Technology Developments in Vision-Based Navigation
	3.1 Introduction
	3.2 Missions and Methods
		3.2.1 Rendezvous
		3.2.2 Descent and Landing
		3.2.3 ``Classic\'\' Approach Versus Machine Learning
	3.3 Hardware Development
		3.3.1 Cameras
		3.3.2 Processing—GMVISION
	3.4 Realistic Images for Training and Validation
		3.4.1 Actual Space Images Acqusition—LIRIS
		3.4.2 Synthetic Images Generation—PANGU
		3.4.3 Robotic Test Bench—GRALS
	3.5 Conclusion
	References
4 Extending Explicit Guidance Methods to Higher Dimensions, Additional Conditions, and Higher Order Integration
	4.1 Introduction
	4.2 Original Formulation for E Guidance
	4.3 Description of E Guidance Extensions
		4.3.1 Desired Intermediate Positions and Velocities
		4.3.2 Final Desired Jerk Vector
		4.3.3 Four Integrations of the F Matrix
		4.3.4 Three Integrations of the F Matrix
	4.4 Simulation Results
		4.4.1 Roll Maneuver
		4.4.2 Takeoff Maneuver
		4.4.3 Waypoint Maneuver
	4.5 Conclusion
	References
Part II Robotic Technologies
5 Identifying Consumer Drones via Encrypted Traffic
	5.1 Introduction
	5.2 Background and Related Work
		5.2.1 WPA2-Personal Encryption in 802.11 Standards
		5.2.2 Micro Air Vehicle Link (MAVLink) Protocol
		5.2.3 Existing Methods for Encrypted WiFi Traffic Classification
	5.3 System Overview
		5.3.1 Traffic Capture and Preprocessing
		5.3.2 Pattern Identification and Profiling
		5.3.3 Drone Classification
	5.4 Performance Evaluation
		5.4.1 Setup and Preprocessing
		5.4.2 Evaluation of Method 1: Scoring-Based Classification Scheme
		5.4.3 Evaluation of Method 2: Feature-Based Classification Scheme
		5.4.4 Comparison to Related Work
	5.5 Conclusions and Future Work
	References
6 Development of a Simulator for Operator Proficiency Training for Seafloor Exploration by Remotely Operated Vehicle
	6.1 Introduction
	6.2 Development of a Simulator
		6.2.1 Components of the Simulator
		6.2.2 The Base Software of the Simulator
		6.2.3 Function to Express Ocean Current
	6.3 Application Data
		6.3.1 Application of ROV Model
		6.3.2 Application of 3D Seafloor Data
		6.3.3 Screen Configuration During Operation Experiment
	6.4 Experiments
		6.4.1 Experiment 1
		6.4.2 Experiment 2
	6.5 Conclusion
	References
7 Optimization of the Four Coil Configuration for Single Magnet Levitation from Below
	7.1 Introduction
	7.2 Background
	7.3 Modeling
		7.3.1 Active Force and Torque
		7.3.2 Passive Force and Torque
		7.3.3 Variable Coil and Magnet Positions
	7.4 Results and Discussion
	7.5 Conclusion
	References
8 Mathematical Simulation of Dynamics for Exoskeleton Including Variable-Length Links with Adjustable Stiffness
	8.1 Introduction
	8.2 Model of One Link of Variable Length with Adjustable Stiffness in Space
	8.3 Model of Two Links of Variable Length with Adjustable Rigidity in Space
	8.4 Exoskeleton Model with Three Links of Variable Length and Adjustable Rigidity in Space
	8.5 Generalization of the Exoskeleton Model to the Case of an Arbitrary Finite Number of Links of Variable Length with Adjustable Stiffness
	8.6 Conclusion
	References
Part III Stochastic Systems and Game Theory
9 Theoretical Guarantees for Satisfaction of Terminal State Constraints for Nonlinear Stochastic Systems
	9.1 Introduction
	9.2 Deterministic Case Revisited
	9.3 The Stochastic Versions of the ``Fixed\'\' Endpoint Problem
	9.4 Constraining the Family of Conditional Expectations of the Terminal State
		9.4.1 Terminally Constrained Stochastic Minimum Principle (TC–SMP)
		9.4.2 TC-SMP for Linear Quadratic Problems
		9.4.3 Numerical Illustrations
	9.5 Constraining the Probability Distribution of the Terminal State
		9.5.1 Convex Duality and the Associated Hamilton–Jacobi (HJ) Inequalities
		9.5.2 Numerical Illustration
	9.6 Concluding Remarks
	References
10 Applications of the Π-Strategy When Players Move with Acceleration
	10.1 Introduction
	10.2 Formulation of the Problem
	10.3 Applying the Π-Strategy in Case 1
		10.3.1 Solution of the Pursuit Problem in Case 1
		10.3.2 The Attainability Domain of the Evader in Case 1
	10.4 Applying the Π-Strategy in Case 2
		10.4.1 Solution of the Problem 1
		10.4.2 Estimating the Distance Between the Players in [0,θ]
		10.4.3 Solution of the Pursuit Problem for the Case tθ
		10.4.4 The Attainability Domain of the Evader in Case 2
	References
11 Optimal Number of Pursuers in the Game on the 1-Skeleton of 4D Cube
	11.1 Introduction
	11.2 Statement of Problem
	11.3 Main Result
		11.3.1 Pursuit Differential Game
		11.3.2 Evasion Differential Game
	11.4 Conclusion
	References
Part IV Optimal Control and Applications
12 Development of an Operation Support Device for Portable Underwater Vehicles
	12.1 Introduction
	12.2 Design and Development of the Control Device
		12.2.1 Control Device Concept
		12.2.2 Designed and Developed Control Device
	12.3 Haptic Shared Control for Underwater Vehicles
	12.4 Experiments
		12.4.1 Experiment Setup
		12.4.2 Manual Control
		12.4.3 Haptic Shared Control
	12.5 Discussion and Future Work
	12.6 Conclusion
	References
13 Optimal Control Problems for the Whitham Type Nonlinear Differential Equations with Impulse Effects
	13.1 Formulation of the Problem
	13.2 Reducing the Problem (13.1)–(13.3) to a Functional-Integral Equation
	13.3 Solvability of the Functional-Integral Equation (13.13)
	13.4 Determination of the Control Function
	13.5 Conclusion
	References
14 Hamiltonian Optimal Control of Distributed Lagrangian Systems
	14.1 Introduction
	14.2 Distributed Lagrangrian System
	14.3 Hamiltonian Control
	14.4 Distributed Optimal Control
	14.5 Aircraft Flight Control Application
	14.6 Conclusion
	References
15 Stabilization of Optimal Trajectories of Dynamical Systems
	15.1 Introduction
	15.2 Problem Statement
	15.3 Stabilization of Partial Integrals of Equations of Dynamics of a Controlled System
	15.4 Motion Control of a Point Mass in the Central Force Field
	15.5 Stabilization of First Integrals
	15.6 Stabilization of the First Two Integrals of Optimal Motion
	15.7 Conclusion
	References
Part V Modeling and Data Analytics
16 Koopman Operator Based Modeling and Control of Quadrotors
	16.1 Introduction
	16.2 Preliminaries
		16.2.1 Notation
		16.2.2 The Koopman Operator
		16.2.3 Quadrotor Nonlinear Dynamics
	16.3 Koopman Lifted Linear Dynamics
		16.3.1 Derivation of Observables
		16.3.2 Koopman Linearized System
		16.3.3 Koopman Control
	16.4 Simulations
		16.4.1 Model Comparison
		16.4.2 Controlled Dynamics
		16.4.3 Comparison with Prior Methods
	16.5 Conclusions
	References
17 On the Vertical and Horizontal Integration of Robotics Within Engineering and Computing Education
	17.1 Introduction
	17.2 K-12 Outreach
		17.2.1 The Recruitment Pipeline
		17.2.2 Collaborations with Area Schools
		17.2.3 Student Experience: William Denham
		17.2.4 Camps
	17.3 Undergraduate Education
		17.3.1 Example Curricular Revisions to Support Undergraduate Education in Robotics
		17.3.2 Mechanical Design
		17.3.3 Student Experience: Emina Sinanovic
		17.3.4 Extracurricular Activities and Undergraduate Research
		17.3.5 Student Experience: Violetta Rostobaya
	17.4 Graduate Education
		17.4.1 Bachelors-Accelerated Masters Programs
		17.4.2 Cross-Disciplinary PhDs
		17.4.3 Student Experience: Vanessa Barth
		17.4.4 Translational AI
		17.4.5 Seminar Series
		17.4.6 Student Experience: Dinesh Karri
	17.5 Faculty Recruitment and Development
		17.5.1 Faculty Recruitment
		17.5.2 Faculty Experience: Quentin Sanders
		17.5.3 Faculty Experience: Missy Cummings
	17.6 Conclusions
	References
18 Generalization of the Boundary Uniqueness Theorem for A(z)—Analytic Functions
	18.1 Introduction
	18.2 Some Classes and Concepts for A(z)—Analytic Functions
		18.2.1 Angular Limit for A(z)—Analytic Functions
		18.2.2 The Nevanlinna Classes for A(z)—Analytic Functions
	18.3 Boundary Uniqueness Theorem for A(z)—Analytic Functions
		18.3.1 Privalov\'s Ice-Cream Cone Construction for A(z)—Analytic Functions
		18.3.2 Use of Egoroff\'s Theorem for A(z)—Analytic Functions
		18.3.3 Generalization of the Boundary Uniqueness Theorem for A(z)—Analytic Functions
	References
19 Control of an Upper-Stage Rocket with Partially Filled Fuel Tanks via Takagi-Sugeno Fuzzy Model
	19.1 Introduction
	19.2 Mathematical Model
	19.3 Takagi-Sugeno (T-S) Fuzzy Model
		19.3.1 T-S Fuzzy Model for Systems with Disturbance
		19.3.2 Parallel Distributed Compensation Control
	19.4 Fuzzy Controller Design
		19.4.1 Fuzzy Controller Design for System with Disturbances
		19.4.2 Numerical Simulation
		19.4.3 Optimal Fuzzy Control
		19.4.4 Numerical Simulation
	19.5 Conclusion
	References
20 Microwave Thermal Rocket Engine-Based Orbital Launch System Implementation
	20.1 Introduction
		20.1.1 The Problem of Space Launch and the Need for a Step-Up from Chemical Propulsion
		20.1.2 Beamed Energy Space Launch Technology
	20.2 Benefits of Beamed Energy Propulsion Based on Microwave Thermal Rockets
	20.3 Implementation Problems of Microwave Thermal Launch Systems and Proposed Solutions
		20.3.1 Suggested Components of the Concept and System Description
		20.3.2 Launch Control and Monitoring
		20.3.3 Economic Problems of Microwave Thermal Launch Systems
	20.4 Conclusions and Recommendations
	References
21 Models and Algorithms Script of Intellectual Dialog Systems
	21.1 Introduction
	21.2 A Method of Constructing an Ontology of Specific Subject Domain Objects
		21.2.1 The Second Stage
	21.3 Algorithm for Constructing Intelligent Conversation Scenarios and an Algorithm to Help Form Queries Based on Them.
	21.4 Conclusion
	References
Part VI Nonlinear Control Systems and Machine Learning
22 Data-Driven Reinforcement Learning for Mission Engineering and Combat Simulation
	22.1 Introduction
	22.2 Background
		22.2.1 Mission Engineering
		22.2.2 Reinforcement Learning for Mission Engineering
		22.2.3 Offline Reinforcement Algorithms
		22.2.4 Combat Simulation Software
	22.3 Data and Methodology
		22.3.1 Scenario
		22.3.2 Data
		22.3.3 Environment Design
		22.3.4 Model Selection
	22.4 Results and Discussion
	22.5 Conclusions and Future Work
		22.5.1 Complexity
		22.5.2 Simulation Software
		22.5.3 Explainable AI for Mission Engineering
	References
23 Initial Development of Cooperative Control and Localization of Multiple Spacecraft Using a Multi-Agent Mission Operations System
	23.1 Introduction
	23.2 iCOSMOS™ Description
		23.2.1 Functional Architecture
		23.2.2 iCOSMOS™ Primary Tools
	23.3 iCOSMOS™ Design
	23.4 Baseline Mission
	23.5 Cooperative Control and Localization
		23.5.1 Multi-agent Coordination (MAC) Module
		23.5.2 Hierarchical Cooperative Localization (HCL) Module
	23.6 Conclusion
	References
24 Application of Cybenko’s Theorem and Algebraic Geometry in Solving Modified E-Guidance Equations
	24.1 Introduction
	24.2 Background
	24.3 Problem Preliminaries
	24.4 Problem Statement
	24.5 Cybenko’s Theorem
	24.6 Problem Set-Up
	24.7 Difference Between Analytical Guidance and Numerico-Analytic Guidance
	24.8 Conclusion
	References
25 A Novel Dynamic and Aerodynamic Intelligent Morphing System (DA-IMS) for the Stability of an Autonomous Utility Truck with the Boom Equipment
	25.1 Introduction
	25.2 Utility Truck—Aerodynamics and—Road Dynamics (Two-Domain) Interactive Models
		25.2.1 Aerodynamic Forces and Moments
		25.2.2 Utility Truck’s Road-Dynamics
	25.3 Stability of Motion
		25.3.1 Stability Assessment
	25.4 DA-IMS Smart Morphing Devices
	25.5 Results and Discussion
	25.6 Conclusions
	25.7 Future Work
	References