Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On Approximate Diagnosability of Nonlinear Systems   This paper deals with diagnosability of discrete-time nonlinear systems with
unknown inputs and quantized outputs. We propose a novel notion of
diagnosability that we term approximate diagnosability, corresponding to the
possibility of detecting within a finite delay and within a given accuracy if a
set of faulty states is reached or not. Addressing diagnosability in an
approximate sense is primarily motivated by the fact that system outputs in
concrete applications are measured by sensors that introduce measurement
errors. Consequently, it is not possible to detect exactly if the state of the
system has reached or not the set of faulty states. In order to check
approximate diagnosability on the class of nonlinear systems we use tools from
formal methods. We first derive a symbolic model approximating the original
system within any desired accuracy. This step allows us to check approximate
diagnosability of the symbolic model. We then establish the relation between
approximate diagnosability of the symbolic model and of the original nonlinear
system.

17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph