System analysis via performance maps

Alpigini, James J.; Russell, David W.

doi:10.1016/s0967-0661(02)00145-4

Cited by 9 publications

(6 citation statements)

References 7 publications

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“…Internal combustion engine performance maps are combined with electric motor performance maps to arrive at a combined control strategy. In [33], Alpigni and Rusell use performance maps for system analysis. They describe a methodology to visually describe the performance map (rise time, delay time, and settling time) of a second-order linear system.…”

Section: The Need For Performance Mapsmentioning

confidence: 99%

The Need for a Performance Map Based Decision Process

Ashok

Tesar

2013

IEEE Systems Journal

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This paper presents a mathematical framework to create a unique decision process based on multiple performance maps of varying functional value and volatility to aid in complex decisions for highly nonlinear and coupled systems by involving human visualization and direct algebraic computations. This map-based process is intended to extend other decision tools, such as fuzzy logic and classical optimization (through cost functions) by embedding in-depth measurement certification, lessons learned, and data uncertainty in geometric map representations. As systems become ever more complex with more human intervention, reliable decisions must be made in less and less time (i.e., a few milliseconds). This decision framework is best carried out with selected maps combined into envelopes as functional/proven decision surfaces. Its potential for data-driven decisions of broad applicability is illustrated in several unique domains ranging from an intelligent actuator, a sensored soldier, health care provider management, a venture capital firm, and in human guided design/synthesis processes for parametrically dense systems. We also show that there is a geometrical structure (serial, parallel, or hybrid) to these decision processes which guides the efficient formulation of the most useful forward or inverse computation.Index Terms-Forward/inverse decision making, performance map, system decision theory, visualization.

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Section: The Need For Performance Mapsmentioning

confidence: 99%

The Need for a Performance Map Based Decision Process

Ashok

Tesar

2013

IEEE Systems Journal

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“…It has been demonstrated that the Julia set method can be adapted to visualize control and other dynamic systems [17,18]. Such a technique addresses the problem of visualizing automatically the state values of some system as its parameters are varied.…”

Section: Performance Mapsmentioning

confidence: 99%

Controller tuning via performance maps

Piovoso

Alpigini

2007

ISA Transactions

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“…The Julia set method can be adapted to visualize control and other dynamic systems. 2,3 Such a technique addresses the problem of visualizing automatically the state values of some system as its controller, or other, parameters are varied. In effect, the technique produces a color-coded performance map that reflects the dynamic performance of the system across intervals of system parameters.…”

Section: Performance Map Generationmentioning

confidence: 99%

“…The performance map (PM) is derived from the Julia set and is designed to visualize the behavior of a system's dynamic performance across variations in system parameters. 2,3 In the context of this research, a system represents a set of differential or difference equations, as would be found in the numerical model of a feedback control or other dynamical system. Such systems often exhibit motions that are nonlinear or even chaotic.…”

Section: Introductionmentioning

confidence: 99%

Dynamical System Visualization and Analysis Via Performance Maps

Alpigini

2004

Information Visualization

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Visualization techniques are common in the study of chaotic motion. These techniques range from simple time graphs and phase portraits to robust Julia sets, which are familiar to many as ‘fractal images.’ The utility of the Julia sets rests not in their considerable visual impact, but rather, in the color-coded information that they display about the dynamics of an iterated function. In this paper, a paradigm termed the performance map is presented, which is derived from the familiar Julia set. Performance maps are generated automatically for control or other dynamical system models over ranges of system parameters. The resulting visualizations require a minimum of a priori knowledge of the system under evaluation. By the use of color-coding, these images convey a wealth of information to the informed user about dynamic behaviors of a system that may be hidden from all but the expert analyst.

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System analysis via performance maps

Cited by 9 publications

References 7 publications

The Need for a Performance Map Based Decision Process

The Need for a Performance Map Based Decision Process

Controller tuning via performance maps

Dynamical System Visualization and Analysis Via Performance Maps

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