Edwin L. Zivi

Integrated shipboard power and automation control challenge problem

Control system requirements for highly automated and survivable future electric warships are presented herein to stimulate and unify interdisciplinary research conducted under the joint NSF/ONR Electric Power Networks Efficiency and Security (EPNES) initiative. This ONR challenge problem focuses on continuity of control for interdependent shipboard engineering and damage control systems under hostile conditions. The mission statement for these Hull, Mechanical, Electrical & Damage Control (HME&DC) systems may be summarized as: Provide continuous mobility, power, and thermal management for shipboard combat systems despite major disruptions involving cascading failures. This challenge problem is prototypical of analogous complex, interdependent systems including the national power grid, military and civilian infrastructure, and transport systems. These nonlinear, distributed, heterogeneous, variable structure systems contain dynamically interdependent subsystems. Mission/life critical system integrity and fault tolerance requirements demand dependable continuity of service. Innovative, dependable, and affordable control system architectures, strategies, algorithms, methods and tools are sought. After a brief problem statement and discussion of shipboard control systems, the ONR control challenge problem and reference system are presented.

Evolutionary Algorithms for Minimax Problems in Robust Design

Many robust design problems can be described by minimax optimization problems. Classical techniques for solving these problems have typically been limited to a discrete form of the problem. More recently, evolutionary algorithms, particularly coevolutionary optimization techniques, have been applied to minimax problems. A new method of solving minimax optimization problems using evolutionary algorithms is proposed. The performance of this algorithm is shown to compare favorably with the existing methods on test problems. The performance of the algorithm is demonstrated on a robust pole placement problem and a ship engineering plant design problem.

Estimating Regions of Asymptotic Stability of Power Electronics Systems Using Genetic Algorithms

Electric power distribution systems composed of power electronics converters are susceptible to instabilities under certain conditions. Small-signal impedance approaches to stability analysis are incapable of predicting large-signal stability properties. Herein, a practical and scalable genetic algorithm based procedure for the estimation of regions of asymptotic stability of power electronics systems is proposed. The procedure is demonstrated on six nonlinear models that range from 6 to 75 state variables. The models represent the dynamics of Naval power electronics-based system components and systems.

Design of robust shipboard power automation systems

Emergent power and automation technologies provide new opportunities and challenges for multi-disciplinary ship design. In particular, these dynamically interdependent systems require dependable, fault-tolerant control to efficiently manage limited resources and to respond to casualty conditions. Design of an electric warship engineering and damage control system of systems is considered as an illustrative example. In this context, cost and survivability can be considered as either deterministic or probabilistic independent variables. In the stochastic formulation, design robustness is defined with respect to uncertainties including technology readiness, mission creep, and operational environment. # 2005 Published by Elsevier Ltd.

Performance Metrics for Electric Warship Integrated Engineering Plant Battle Damage Response

In military applications, it is important for a platform (warship, aircraft, etc.) or an installation (airbase, etc.) to maintain war-fighting ability after being damaged. In particular if the unit requires electric power, cooling, or other resources to perform its mission, then these resources must be available following a weapon detonation event. The integrated engineering plant (IEP) is responsible for providing these services to the mission-critical loads in a unit. Novel continuity-of-service metrics for IEPs are set forth herein. These metrics provide a means of predicting the average and worst-case level of service the plant can provide as well as the worst-case scenario over a class of disruptions. This provides a method of making meaningful comparisons between different designs. The computation and meaning of the proposed metrics are explored using a notional warship IEP.

Evolutionary Optimization of PowerElectronics Based Power Systems

This paper sets forth and demonstrates an approach to the design of power electronics based power systems using evolutionary computing techniques. Key features of the paper are the use of evolutionary computing in the context of classical control design, construction of appropriate multievent based performance metrics, and the use of multiobjective evolutionary computing in the selection of control parameters based on system performance versus control effort. The proposed approach is demonstrated in a power electronics based power distribution system similar to those being designed for next generation warships.

Metric Optimization-Based Design of Systems Subject to Hostile Disruptions

In many applications, engineering systems are required to operate acceptably well in hostile environments. In the past, survivability engineering has addressed this requirement using heuristic rule-based design approaches followed by analysis to determine if survivability constraints have been satisfied. The treatment of survivability as a constraint rather than an independent design objective hinders the ability of system engineers to trade off survivability with other design objectives, such as cost and performance. Herein, the survivability problem is posed in terms of maximizing expected performance and minimizing the risk of unacceptable performance. Design metrics that allow optimal selection of systems on the basis of these survivability dimensions are presented. The metrics are part of a systematic approach to system engineering in which survivability concerns are quantified and individual systems and entire classes of systems can be compared objectively. These metrics are a necessary step toward an integrated design process wherein tradeoffs between all design objectives can be identified. This methodology is demonstrated on the design of a notional electric warship integrated engineering plant (IEP) that is subject to hostile disruptions posed by antiship missiles. By use of this method, the performance of the IEP is shown to be improved.

An optimization approach to estimating stability regions using genetic algorithms

The problem of estimating regions of asymptotic stability for nonlinear dynamic systems is considered as an optimization problem. Genetic algorithms are then proposed to solve the resulting optimization problems. Three test systems are used to evaluate the performance of the proposed genetic algorithms. The test systems are 6th, 8th, and 17th order nonlinear power electronics systems. The performance of the genetic algorithms are also compared with that of the classical Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm and the simplex method of Nelder and Mead. Time domain simulations of the test systems are performed to validate the results of the optimization algorithms. Issues involved with the successful implementation of genetic algorithms to estimate regions of attraction are discussed. It is observed that genetic algorithms outperform the classical optimization algorithms in estimating regions of asymptotic stability.

A linear programming approach to shipboard electrical system modeling

Operability and dependability metrics can be a valuable tool in early ship design by providing a quantitative analysis of the robustness of the ships integrated engineering plant (IEP). However, the use of these metrics involves large numbers of time domain simulations of the IEP. The simulation of such a complex system, which includes electrical and thermal subsystems, can be problematic in terms of computational efficiency. In this paper, a simplified modeling approach based on the fundamental power limitations is set forth. The power flow problem is posed as a linear programming problem which is solved using a simplex method.

Early-stage shipboard power system simulation of operational vignettes for dependability assessment

A principle motivation for the development of early-stage shipboard power system simulation techniques is the need to perform time-domain simulation during the early design stage. In particular, there is a need to understand the performance of a candidate system during challenging situations involving dynamic load profiles and disruptive conditions in order to assess the system dependability. An early-stage simulation technique is applied to simulate the performance of a candidate system for given operational vignettes. Using this early-stage approach allows simulations to be performed very quickly, allowing many vignettes to be considered and the overall system dependability to be assessed.