This study delves into the realm of system identification, a crucial sub-field in control
engineering, aimed at constructing mathematical models of systems based on input/output …

A novel nature-inspired meta-heuristic optimization algorithm, named artificial ecosystem-
based optimization (AEO), is presented in this paper. AEO is a population-based optimizer …

Artificial Intelligence (AI) techniques are known for its ability in tackling problems found to be
unyielding to traditional mathematical methods. A recent addition to these techniques are …

In practical system identification it is often desirable to simultaneously handle several
objectives and constraints. In some cases, these objectives and constraints are often non …

Nonlinear system identification of complex and nonlinear unit operations and unit processes
requires accurate modelling approaches. For this, first-principles based models were initially …

In the field of digital filter design and system identification, accurately modeling Infinite
Impulse Response (IIR) systems is of utmost importance. This paper introduces a new …

Most real-time systems are nonlinear in nature, and their optimization is very difficult due to
inherit stiffness and complex system representation. The computational intelligent algorithms …

Abstract Through System Identification techniques, it is possible to obtain a mathematical
model for a dynamic system from its input/output data. Due to their intrinsic dynamic …

Nowadays, the use of meta-heuristic algorithms (MAs) for tackling complicated engineering
issues has shown significant promise, therefore applying MAs to optimum model parameters …

In this chapter, we describe an important class of engineering problem called system
identification which is an essential requirement for obtaining models of system of concern …