The IUTAM Symposium on Optimal Guidance and Control for Autonomous Systems 2023 invites papers representing the results of research and studies in optimal guidance and control, and the utilities of these theoretical developments in the performance of autonomous systems.

Over the last two decades, the theories, concepts, and methods of optimal control, calculus of variations, dynamic systems, motion stability, sensor fusion, optimal guidance, and machine learning have contributed to paving the way to or leveraging the autonomy of controllable systems, including space, air, surface, and underwater vehicles, and swarm networks. Design, analysis, and development of such systems have been associated with safety, stability, accuracy, autonomy, maneuverability, navigation and guidance problems, and their real-time or near real-time solutions, especially for performance in uncertain environments. These problems have been investigated via such conventional and non-conventional solutions methods and approaches as Lagrange and Hamilton-Jacobi- Bellmann’s formalisms, direct and indirect methods, and formalisms based on the sufficient conditions of absolute optimality. Analytical integrability of canonical systems, solvability of the Hamilton-Jacobi equation, completeness of necessary and sufficient conditions of optimality, the existence of Pontryagin minimum, synthesis of control regimes, real-time integration of optimal control, guidance, navigation, and targeting are only some of the still remaining and underlying fundamental issues and challenges of leveraging the autonomy and optimization of the controllable systems. These solutions are critical to not only mission design and analysis, but also to the systems’ satisfactory performance. Utilities of these solutions have led to increased and strengthened requirements for motion planning, dynamics, and performance of the onboard control systems or their components.

The symposium intends to bring together leading scientists, experts, and engineers engaged in the development and application of novel concepts, theories, and methods of optimal guidance and control, nonlinear dynamic systems and motion stability, sensor fusion, and machine learning to discuss and address the issues relevant to theory and performance autonomous and other controllable systems. As such, this meeting represents a wide range of research and studies involving the theories and methods in the areas mentioned above, fundamental issues of autonomy and approaches to their solutions, and the utility and implementation of these solutions in leveraging the autonomy of the controllable systems.

Areas of the symposium include, but are not limited to:

– Autonomous Systems

– Motion Planning

– Vehicle guidance

– Feedback control

– Machine Learning

– Reinforcement Learning

– Swarm Network Control

– Centralized or Decentralized Control

– Guidance, Navigation, and Control

– Stability

– Targeting

– Data Processing

– Sensor Fusion

– On-board Control Systems

– Optimal Control