A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Qualitative analysis of MOS circuits
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Diagnostic reasoning based on structure and behavior
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Modeling digital circuits for troubleshooting
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
CLP( R ) and some electrical engineering problems
Journal of Automated Reasoning
Reasoning about linear circuits in sinusoidal steady state
Reasoning about linear circuits in sinusoidal steady state
Complex fans: a representation for vectors in polar form with interval attributes
ACM Transactions on Mathematical Software (TOMS)
Qualitative multiple-fault diagnosis of continuous dynamic systems using behavioral modes
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Industrial applications of model-based reasoning
AI Communications
Qualitative order of magnitude energy-flow-based failure modes and effects analysis
Journal of Artificial Intelligence Research
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Most of the work on behavior prediction in the field of Qualitative Reasoning has focused on transient behavior and responses to perturbations; very little has been done regarding systems in steady state. A large class of systems, especially in the area of power systems, are designed for sinusoidal steady‐state operation. Thus, an understanding of the steady state behavior of electrical circuits is very important.This article presents a framework for reasoning about linear electrical circuits in sinusoidal steady state. The reasoning process relies on a constraint‐based model of the circuit, derived from electro‐magnetic theory and generated automatically from the structure of the circuit. In a linear circuit operating in steady state, all quantities are sinusoidals of the same frequency as the source. Since any sinusoidal can be expressed as the real part of a complex exponential, we use the complex form, which simplifies computations; this complex form, characterized by magnitude and angle, is called a phasor. In order to capture magnitude and phase angle information in the model, all constraints operate on phasor variables.Constraint Propagation (CP) is the main inference mechanism. The CP module reasons with as much information and precision as the user provides, ranging from qualitative to quantitative. Intervals provide a general representation mechanism.The framework presented in this article has been implemented in a program called Qualitative Phasor Analysis (QPA), which performs circuit analysis, parameter design, diagnosis, control design, and structure simplification. Circuits with multiple sources are solved using the superposition principle.