Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes   This paper proposes a new class of real-time optimization schemes to overcome
system-model mismatch of uncertain processes. This work's novelty lies in
integrating derivative-free optimization schemes and multi-fidelity Gaussian
processes within a Bayesian optimization framework. The proposed scheme uses
two Gaussian processes for the stochastic system, one emulates the (known)
process model, and another, the true system through measurements. In this way,
low fidelity samples can be obtained via a model, while high fidelity samples
are obtained through measurements of the system. This framework captures the
system's behavior in a non-parametric fashion while driving exploration through
acquisition functions. The benefit of using a Gaussian process to represent the
system is the ability to perform uncertainty quantification in real-time and
allow for chance constraints to be satisfied with high confidence. This results
in a practical approach that is illustrated in numerical case studies,
including a semi-batch photobioreactor optimization problem.

33
The categories of this paper are: plasm-ph
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th