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Cyber-Physical Systems Modeling and Analysis (CPSMA) Initiative
 

Cyber-Physical Systems (CPS) denotes the emerging class of physical systems that exhibit complex patterns of behavior due to highly capable embedded software components. Also known as hybrid systems (a hybrid of hardware and software), or mechatronic systems (mechanical + electronic), these include devices with content, or knowledge, that gives them unprecedented capabilities in interoperability and interaction, resilience, adaptivity, and emergent behavior.

CPS is discussed in the Space Technology Roadmap for TA11, Modeling, Simulation, Information Technology and Processing, under TABS 2.2.2.2, Integrated Hardware and Software Modeling. It is relevant to several other TABS elements in the TA11 Roadmap, as well as to several other Technology Areas, such as TA04, Robotics, Telerobotics, and Autonomous Systems; TA6, Human Health, Life Support, and Habitation Systems; TA7, Human Exploration Destination Systems; TA10, Nanotechnology; and TA13, Ground and Launch Systems Processing.

In order to take advantage of CPS advances to support key elements of NASA’s future space exploration mission, the Ames Center Chief Technologist (CCT) Office has established the “Cyber-Physical Systems Modeling and Analysis (CPSMA) Initiative. CPSMA will focus on propulsion, autonomy, and life-support, including key products and applications, technical approaches, mechanisms, and facilities. The anchor elements of the CPSMA Initiative are the unique ARC capabilities in biological technologies, synthetic biology, physics-based and data-based modeling, prognostics and system health management, and supercomputing.

The initial CPSMA objective is to apply these technologies to specific requirements for long-duration human spaceflight, including synthetic biological systems, launch propulsion, on-board autonomy for small-spacecraft, and next-generation human-exploration vehicles and habitats. In the future, the list of applications will be broadened to include:

  • Physical ensembles, equipped with sensors, actuators and knowledge about locality and resource constraints. Examples are real-time embedded systems, modular robots, and programmable devices. These systems combine discrete and continuous, non-linear behaviors and they exhibit complex interaction patterns among components. Coordination in space and time with limited power and communication resources is one of the major challenges faced by such ensembles.
  • Software and systems engineering methods and tools to address the challenge of designing ensembles of spacecraft and robots with coherent, autonomous behavior and with guaranteed levels of security and trust. Approaches to CPS engineering may use bio-inspired and swarm control heuristics, but they also include traditional software development techniques and hybrid-system models.
  • New computing paradigms to address the problem of composing systems in-situ from parts that were not necessarily designed to work together and may be only partially cooperative with one another. CPS blurs the distinctions among design, implementation, and deployment. Research in this area will have to investigate the dynamics of purposive interactions and the structure of stably evolving architectures, going beyond current machine-learning paradigms.

The immediate goals of the CPSMA Initiative are as follows:

  1. Develop an in-house capability in integrated physics-based and data-based modeling, taking advantage of the latest advances in symbolic math, supercomputing, data mining, and causal modeling;
  2. Demonstrate robust, space-qualified flight and ground systems, for example, adaptive control and system health management for small satellites; design of synthetic biological systems; adaptive scientific instruments, payloads, and components, including adaptive structures, and intelligence;
  3. Provide an environment where NASA and associated technologists, scientists, and researchers have a hands-on opportunity to advance their ideas from concept to reality;
  4. Serve as a model facility and capability for integrated, collaborative, multidisciplinary model-based design and analysis in diverse areas ranging from spacecraft design to space weather and climate modeling; and
  5. In collaboration with Networking and Information Technology Research and Development (NITRD) Program partners, leverage multi-Agency resources and expertise across NASA Centers, industry, academia, and international partners.

Expected Outcomes and Benefits

  • Increase capability to predict and control the behavior of systems across many orders of magnitude of physical and temporal scale;
  • Implementation of emergent system behaviors with local rules;
  • Validate resilience, adaptation, and controlled emergence in hybrid systems for space applications;
  • Operate in complex, remote environments, recognizing and exploiting opportunities autonomously;
  • Achieve high safety, verifiability, and formal verification of autonomous ensembles;
  • Enable multi-vendor collaboration in environments with provable and controllable multi-level security, including integration of heterogeneous and federated data

References:
http://www.nasa.gov/pdf/501321main_TA11-MSITP-DRAFT-Nov2010-A1.pdf
http://www.nasa.gov/pdf/501622main_TA04-Robotics-DRAFT-Nov2010-A.pdf
http://w3.isis.vanderbilt.edu/CST-HCCPS/papers/CST-HCCPS_Workshop_-_Raj.pdf
http://www.darpa.mil/Our_Work/TTO/Programs/System_F6.aspx


Download the CPSMA Overview: here