This paper presents mathematical modeling and system identification of Ninho da Águia, a
Small Hydropower Plant, considering as input the power production and as output the …

In this paper, we are proposing an approach for integrating evolutionary computation
applied to the problem of system identification in the well-known statistical signal processing …

The genetic algorithm approach is widely recognized as an effective and flexible
optimization method for system identification. The flexibility of a genetic algorithm allows …

The knacks of evolutionary and swarm computing paradigms have been exploited to solve
complex engineering and applied science problems, including parameter estimation for …

The rest of this paper is organized as follows. Section 2 describes traditional System
Identification and introduces the use of Particle Swarm Optimization (PSO) for determining …

A system identification problem can be formulated as an optimization task where the
objective is to find a model and a set of parameters that minimize the prediction error …

There have been many algorithms created and introduced in the literature inspired by
various events observable in nature, such as evolutionary phenomena, the actions of social …

Because of the nonlinear and recursive nature of the physical systems, system identification
is a challenging and complex optimization problem. Infinite impulse response (IIR) and …

The identification of real-world plants and processes, which are nonlinear in nature,
represents a challenging problem. Currently, the Hammerstein model is one of the most …

This paper mainly focuses on the optimal design of a grid-dependent and off-grid hybrid
renewable energy system (RES). This system consists of Photovoltaic (PV), Wind Turbine …