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Dynamic Servoelastic (DSE) Network Control, Modeling, and Optimization

Description:


Lead Center:AFRC
Participating Center(s):LaRC,JPL,ARC
This subtopic addresses advanced control-oriented techniques for dynamic servoelastic (DSE) terrestrial, planetary, and space environment flight systems using distributed network sensor and control systems. Methods include modeling, simulation, optimization and stabilization of DSE systems to actively and/or adaptively control structural dynamic geometry/topology, vibration, atmospheric and intraspace disturbances, static/dynamic loads, and other structural dynamic objectives for enhanced dynamic servoelastic performance and stability characteristics. DSE control for performance enhancements while minimizing dynamic interaction. Flexible aircraft and spacecraft stabilization and performance optimization. Modeling and system identification of distributed DSE dynamics. Sensor/actuator developments and modeling for distributed DSE control. Uncertainty modeling of complex DSE system behavior and interactions. Distributed networked sensing and control for vehicle shape, vibration, and load control. This subtopic also addresses capabilities enabling design solutions for performance and environmental challenges of future air and space vehicles. Research in revolutionary aerospace configurations include lighter and more flexible materials, improved propulsion systems, and advanced concepts for high lift/performance and drag/energy reduction. This subtopic targets efficiency and environmental compatibilities requiring performance challenges and novel control-oriented techniques for aero-servoelastic considerations which are gaining prevalence in advanced aerospace flight vehicles, atmospheric and extra-terrestrial. Technical elements for the Phase I proposals may also include: Mission/maneuver adaptivity with dissipative optimal energy-force distribution. Data-driven multi-objective DSE control with physics-based sensing. Robust sensing-control-communication networks for sensor-based distributed control. Compressive information-based sensing and information structures. Evolving systems as applied to self-assembling and robotic maneuvering. Scalable and evolvable information networks with layering architectures. Modular architectures for distributed autonomous aerospace systems. Multi-objective, multi-level control and estimation architectures. Distributed multi-vehicle dynamics analysis and visualization with complex simulations. Reduced order modeling capable of substructure coupling of nonlinear materials Development of distributed sensory-driven control-oriented DSE systems is solicited to enable future flight vehicle concepts and designs that manage structural dynamic uncertainty on a vehicle's overall performance. Proposals should assist in revolutionizing improvements in performance to empower a new generation of air and space vehicles to meet the challenges of terrestrial and commercial space concerns with novel concepts and technology developments in systems analysis, integration and evaluation. Higher performance measures include energy efficiency to reduce fuel burn and operability technologies that enable information network decompositions that have different characteristics in efficiency, robustness, and asymmetry of information and control with tradeoff between computation and communication. Advanced mission applicability in Phase II should show the ability of aerospace GN&C systems to achieve mission objectives as a function of GN&C sensor performance, vehicle actuation/power/energy, and the ability to jointly design them as onboard-capable, real-time computing platforms with applicable environmental effects and robust guidance algorithms. Goals are to: Provide capabilities that would enable new projects/missions that are not currently feasible. Impact multiple missions in NASA space operations and science, earth science, and aeronautics. Be influential across aerospace and non-aerospace disciplines with dynamic interactions. New technologies proposed should have the potential to impact the following NASA missions: Data availability for science missions. Mission planning. Autonomous rendezvous/docking technology. Environmental monitoring for human habitation. Apart from NASA missions, the aeronautics technology could be adapted for development and use in autonomous operation of wind/ocean energy and smart space power grid systems in dynamic environments. There are number of advantages to exploring this subtopic technology: Increase in autonomy and fuel efficiency of coordinated robotic vehicles and sub-components. Improved science, atmospheric, and reconnaissance data. Cost, risk and reliability of flight vehicles for a terrestrial, planetary, or space mission. Inter-networks with improved dynamic behavior. Potential technical impacts are: Vehicle energy efficiency with passive/active dissipativity for control and dynamic stability with extreme power constraints. Weight minimization through dynamic servoelastic control. Mission adaptivity and robustness with real-time, consensus-coordinated control dealing with computation, communication, and dynamics.
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