Conflicts Versus Analytical Redundancy Relations: A Comparative Analysis of the Model Based Diagnosis Approach From the Artificial Intelligence and Automatic Control Perspectives

Abstract

Two distinct and parallel research communities have been working along the lines of the model-based diagnosis approach: the fault detection and isolation (FDI) community and the diagnostic (DX) community that have evolved in the fields of automatic control and artificial intelligence, respectively. This paper clarifies and links the concepts and assumptions that underlie the FDI analytical redundancy approach and the DX consistency-based logical approach. A formal framework is proposed in order to compare the two approaches and the theoretical proof of their equivalence together with the necessary and sufficient conditions is provided.

Statistical Properties and Design Criterions for AI-Based Fault Isolation

“…Further, we consider diagnostic tests in the view of hypothesis testing in accordance with [9]. It should be noted that this view is compatible with traditional fault isolation techniques from both FDI and AI, see [3].…”

“…In many papers, both from the control community [4,12,1] and especially in AI [6,3], the systems to be diagnosed are assumed not to contain noise. This means that an observation in the model is either deterministic given the states, or completely unknown, depending on if a fault is present and also which fault that is present.…”

“…In [9], FDI performance was studied in the framework of structured hypothesis tests. In [3] these issues were posed as open questions.…”

“…In several works [10,13,3], it has been recognized that fault isolation in FDI can be solved by using algorithms developed within the field of AI, see [7,14]. Advantages of these AI algorithms, compared to their counterpart from the control community, e.g.…”

The challenge of advanced model-based fdir techniques for aerospace systems: the 2011 situation

“…The paper will focus mostly on FDD. The FDD methods are classi¦ed generally into three categories, which include the knowledge or history based methods [15,21,22], analytical model based methods, and signal based methods [10]. In this paper, the focus is on analytical model based approaches.…”