Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Extremum Seeking-based Iterative Learning Model Predictive Control
  (ESILC-MPC)   In this paper, we study a tracking control problem for linear time-invariant
systems, with model parametric uncertainties, under input and states
constraints. We apply the idea of modular design introduced in Benosman et al.
2014, to solve this problem in the model predictive control (MPC) framework. We
propose to design an MPC with input-to-state stability (ISS) guarantee, and
complement it with an extremum seeking (ES) algorithm to iteratively learn the
model uncertainties. The obtained MPC algorithms can be classified as iterative
learning control (ILC)-MPC.

23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th