In this chapter, the motivations in the use of metaheuristic methods in the
Automatic Control field are presented. Compared with traditional approaches,
the use of these methods does not require the reformulation of the initial
control problem and allows the optimization of the control laws. A brief
description of the book contents is also provided.
1.1. Introduction: automatic control and optimization
Links between automatic control and optimization are very strong
as optimization methods are often the core of automatic control
methodologies. Indeed, optimization has traditionally brought efficient
methods to identify system models, to compute control laws, to
analyze system stability and robustness, etc.
Because of the required tractability of the corresponding
optimization problems, traditional approaches are usually based on the
definition of a simplified model of the plant to control. The simplified
model may rely, for instance, on the use of a linearized plant about an
equilibrium point and neglected dynamics. Making these
simplifications, the model is expressed by a linear and low-order
system. Such a simplified model can be used for the computation of
the control law using a particular mathematical framework. In parallel,
an optimization problem expressing the desired performance and
constraints is defined. Special attention is paid to the structures of the
model and the optimization problem so as to be able to solve it with