Actuation of a technical system based on solutions of relaxed abduction

Patent metadata

Field	Value
Publication number	US-9449275-B2
Application number	US-201214232315-A
Country	US
Kind code	B2
Filing date	Jul 2, 2012
Priority date	Jul 12, 2011
Publication date	Sep 20, 2016
Grant date	Sep 20, 2016

Abstract

To enable efficient abduction even for observations that are faulty or inadequately modeled, a relaxed abduction problem is proposed in order to explain the largest possible part of the observations with as few assumptions as possible. On the basis of two preference orders over a subset of observations and a subset of assumptions, tuples can therefore be determined such that the theory, together with the subset of assumptions, explains the subset of observations. The formulation as a multi-criteria optimization problem eliminates the need to offset assumptions made and explained observations against one another. Due to the technical soundness of the approach, specific properties of the set of results (such as correctness, completeness etc.), can be checked, which is particularly advantageous in safety-critical applications. The complexity of the problem-solving process can be influenced and therefore flexibly adapted in terms of domain requirements through the selection of the underlying representation language and preference relations. The invention can be applied to any technical system, e.g. plants or power stations.

First claim

The invention claimed is:

1. A method of actuating a technical system, the method comprising:
receiving at least one observation from at least one sensor;
determining, by a computer which is configured to execute program code stored on a non-transitory computer-readable medium, a relaxed abduction problem;
solving, by the computer, the relaxed abduction problem, by determining tuples that are optimal with respect to two preference orders over subsets of assumptions and observations, wherein the determined optimal tuples comprise a subset of observations smaller than a complete set of observations, respectively, that concurrently minimize the subset of assumptions to explain the observations comprising the at least one observation received from the at least one sensor and maximize the subset of observations abductively explained by the subset of assumptions given a theory T, with the objective of determining a causal consequence of the largest possible portion of observations with as few assumptions as possible; and
actuating the technical system according to the solution of the relaxed abduction problem by communicating at least one actuator signal.

2. The method as claimed in claim 1 , in which the relaxed abduction problem is determined to be RAP=(T,A,O,∘ A ,∘ O ),
wherein:
a set of abducible axioms is A,
a set of observations is O
with
T′/O; and
further comprising taking orders of preference
∘ A ⊂ P ( A )× P ( A ) and

∘ O ⊂ P ( O )× P ( O )

as a basis for determining ∘-minimal tuples (A,O)εP(A)×P(O),
so that T∪A is consistent and T∪A′O holds.

3. The method as claimed in claim 1 , wherein the relaxed abduction problem is solved by transforming the relaxed abduction problem into a hypergraph, so that the tuples (A,O) are encoded by pareto-optimal paths in the hypergraph.

4. The method as claimed in claim 3 , wherein the pareto-optimal paths are determined via a label approach.

5. The method as claimed in claim 3 , further comprising inducing hyperedges of the hypergraph by transcriptions of prescribed rules.

6. The method as claimed in claim 5 , wherein the prescribed rules are determined as follows:

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Assignees

• Hubauer Thomas
• Lamparter Steffen
• Siemens Ag

Inventors

• Hubauer Thomas
• Lamparter Steffen

Classifications

• G05B23/0278

  Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA · CPC title

• G06F17/00

  Digital computing or data processing equipment or methods, specially adapted for specific functions (information retrieval, database structures or file system structures therefor G06F16/00) · CPC title

• G06N5/02 Primary

  Knowledge representation; Symbolic representation · CPC title

• G06F11/004

  Error avoidance (G06F11/07 and subgroups take precedence) · CPC title

• G05B23/0221

  Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods · CPC title