Commonsense reasoning about causality: deriving behavior from structure
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Arc and path consistence revisited
Artificial Intelligence
Artificial Intelligence
Constraint propagation with interval labels
Artificial Intelligence
Comments on Mohr and Henderson's path consistency algorithm
Artificial Intelligence
Artificial Intelligence
A knowledge-based system for troubleshooting real-time models
Artificial intelligence, simulation & modeling
Control Systems Design: An Introduction to State-Space Methods
Control Systems Design: An Introduction to State-Space Methods
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Perturbation analysis deals with the relationships between small changes in a system's inputs or model and changes in its outputs. Reverse simulation is of particular interest, determining how to achieve desired outputs by perturbing inputs or model parameters. Some applications of this type of analysis are suggested. Perturbation analysis is developed in the context of continuous systems whose dynamics, over small ranges of the system's behaviour, can be represented by linear models. All variables and signals are represented by intervals with qualitative end points. Qualitative linear models are introduced to represent time-varying systems. These representations permit the use of network consistency algorithms to solve perturbation analysis problems.