  Nowadays, data are richly accessible to accumulate, and the increasingly
powerful computing capability offers reasonable ease of handling big data. This
remarkable scenario leads to a new way of solving some control problems that
were previously challenging to analyze and solve. This paper proposes a new
control approach, namely control with patterns (CWP), to handle data sets
corresponding to nonlinear dynamical systems, where the feature abstraction
must be considered for unstructured data feedback. For data sets of this kind,
a new definition, namely exponential attraction on data sets, is proposed to
describe nonlinear dynamical systems under consideration. Based on the data
sets and parameterized Lyapunov functions, the problem for exponential
attraction on data sets is converted to a pattern classification one.
Furthermore, D-learning is proposed to perform CWP without knowledge of the
system dynamics.
