CPS: Breakthrough: Toward Revolutionary Algorithms for Cyber-Physical Systems Architecture Optimization

National Science Foundation

Design optimization of cyber-physical systems (CPS) includes optimizing the system architecture (topology) in addition to the system variables. Optimizing the system architecture renders the dimension of the design space variable (the number of design variables to be optimized is a variable.) This class of Variable-Size Design Space (VSDS) optimization problems arises in many CPS applications including (1) microgrid design, (2) automated construction, (2) optimal grouping, and (3) space mission design optimization.

Evolutionary Algorithms (EAs) present a paradigm for statistical inference that implements a simplified computational model of the mechanisms embedded in natural evolution, with potential to solve this problem. However, existing EAs cannot optimize among solutions of different architectures because of the inherent strategy for coding the variables in EAs. Existing EAs resembles natural evolution in which a given architecture can evolve by improving the state of its variables but cannot be revolutionized. Inspired by the concept of hidden genes in biology, this project investigates revolutionary optimization algorithms that can optimize among different solution architectures and autonomously develop new architectures that might not be known a priori, yet are more fit solution architectures. Efficacy of the new algorithms for CPS is evaluated in the context of space mission design optimization.

Intellectual Merit:
There is an increasing demand in the scientific community for autonomous design optimization tools that can revolutionize systems designs and capabilities. Most existing optimization algorithms can only search for optimal solutions in a fixed-size design space; and hence they cannot be used for solution architecture optimization. Few existing algorithms can search for optimal solutions in VSDS problems; however these are problem-specific algorithms and cannot be used as a general framework for VSDS optimization. This project investigates the novel concept of hidden genes in coding the variables in evolutionary algorithms so that the resulting algorithms can be used for optimizing VSDS problems. The key innovation in these new algorithms is the new coding strategies. In addition, in this project, the standard operations in EAs will be replaced by new operations that are defined to enable revolutionizing a current population of solution architectures using the new coding strategy. The Pl’s recent research results, in the context of space mission design optimization, demonstrate that the hidden genes optimization algorithms can search for optimal solutions among different solution architectures, revolutionize an initial population of solutions, and construct new solution architectures that are more fit than the initial population solutions.

Investigator: Ossama Abdelkhalik

Control System Design for Cargo Transfer from Offshore Supply Vessels to Large Deck Vessels

Craft Engineering Associates

Introduction
There is a wide range of hydraulic extending-boom and knuckle-boom cranes in use on marine vessels. These cranes are often used in dynamic motion environments for cargo transfer and small boat handling. The ability to safely launch and recover small boats in elevated sea states for naval, Coast Guard and oceanographic purposes is currently a focus of investigation within these communities.

The purpose of this investigation is to extend the research begun under SBIR topic N06-
057, “Cargo Transfer from Offshore Supply Vessels to Large Deck Vessels” to improve the performance of hydraulic marine cranes in the dynamic offshore environment. In addition, the lessons learned during the development of the Integrated Rider Block Tagline System (IRBTS), the Platform Motion Compensation System (PMC) and the Pendulation Control System (PCS) for the rigid-boom, level-luffing marine cranes used for container handling on sealift ships will be incorporated into a final integrated, modular kit to improve cargo transfer with these extending-boom and knuckle-boom cranes.

Phase II Technical Objectives
The goal of Phase II is to develop and demonstrate a modular solution for crane pendulation and motion control suitable for a wide range of existing U.S. Navy ship cranes. Phase I clearly showed that pendulation control can be modularized by implementing ship motion cancellation using the crane’s existing drive system and active load damping using a retrofit damping device. In that work, a specific crane design was considered and the study was strictly proof-of-concept through simulation.

Phase II focuses on identifying the range of cranes for which the modular approach is feasible, developing the analysis and design work flow needed to design and deploy the modular solution, and demonstrating both the process and the performance on a particular crane. The incremental technical objectives of Phase II are listed below.

1. The analysis and design process for implementing modular pendulation and motion control on any crane,
2. The development of a modular crane control system (MCCS) “kit” including refinement of the key subsystems (sensors, actuation, algorithms),
3. A phased demonstration of MCCS using 1/12th and larger scale testbeds.

At the conclusion of Phase II, the objective is to have a fully functioning MCCS system demonstrating ship motion cancellation, active payload damping on an articulated crane similar to those currently deployed on numerous U.S. Navy and civilian ships. The Phase II Option will focus this development on a design that can be implemented on the hydraulic extending-boom crane, currently proposed for use on the JHSV.

Investigators: Gordon Parker

Mark Vaughn

xdJJr3eLPtUPZrpPVx4z3KTToTZm8-h2bIOB7P4spj0Dr. Vaughn has joined Michigan Tech as a research professor after retiring from Sandia National Laboratories. His research expertise is in the area of mechanical and electromechanical design, stress analysis, dynamics, and innovative applications. He has over 10 patents, and has been the lead on a broad array of projects for the military.

Areas of Expertise

  • Electro-Mechanical Analysis and Design
  • Energy Storage
  • Hydrogen Peroxide Systems
  • Advanced Payloads
  • Robotic Vehicles
  • Biomedical Devices

Vehicle – to – Vehicle Resource Sharing

Mississippi State University / U.S. DoD TARDEC

The existing communication layer for Vehicle to Grid (V2G) operations has sufficient throughput and capabilities for basic connectivity, but may not have enough for tasks such as operating military vehicle systems remotely. They cyber security approach to V2G operations has had some development in industry; however military vehicles demand more scrutiny from a cyber security perspective.

Vehicle-to-Vehicle (V2V) resource sharing would enable a greatly expanded flexibility for utilization of assets for forward operating bases (FOB). Consider a FOB with a variety of vehicle assets, each with different levels of functionality. The ability to daisy-chain the vehicle assets together (including partially disabled vehicles), have the vehicles automatically determine their net capability and then share resources to accomplish a common goal (force protection for example), would enable a level of capability not currently available.

Specific Tasks: Vehicle-to-Grid Simulation, Connection Protocol Assessment, Connection Protocol Development, Throughput Assessment, and Simulation Studies.

Investigators: Gordon Parker, Wayne Weaver, Steven Y. Goldsmith

 

Nina Mahmoudian

Nina Mahmoudian_Fall2013-1Dr. Mahmoudian’s general research interests lie in the area of dynamics, stability, and control of nonlinear systems. Specifically, she is interested in dynamic modeling, motion planning, and developing cooperative control algorithms to autonomous vehicles. Design and control of autonomous vehicles based on the principles used by nature is another area of interest.  She works on developing analytical and computational tools for the cooperative control of a network of autonomous vehicles in complex environment using nonlinear control and stochastic analysis. The application will be for air, ground, and sea autonomous vehicles.

Areas of Expertise

  • Nonlinear Control and Dynamics
  • Cooperative Control of Multi Agent Systems
  • Autonomous Vehicles with Special Interest in Underwater Gliders

Prepositioned Power Research

Overview

Prepositioned Power RobotsResearch is focused on developing technology to create systems that can autonomously create a microgrid, for situations that require the ability to preposition a basic level of energy infrastructure such as areas damaged by natural or man-made disasters, and autonomously deploying forward operating bases. Modeling and control of robotics and power conversion systems provides the ability to create such prepositioned electric power networks.

Active Projects

Applications

Autonomous Robots can carry a variety of power equipment:

  • Intelligent power electronics for energy conversion
  • Power connection hardware
  • Generation sources, both traditional and renewable
  • Energy storage

 

Prepositioned Power

Prepositioned Power

Four autonomous microgrid robots, each with different power network functionality. Two have renewable energy generation and storage capability, another has a conventional diesel genset, and the third contains intelligent power electronics for conversion and hard-line interconnection, and switchgear. After assessing the power requirements and available resources they would physically organize and electrically interconnect to form a micro-grid.