The identification research of nonlinear system based on PSO with fuzzy adaptive inertia weight

This paper introduces the particle swarm optimization (PSO) and provides the identification of the nonlinear system based on the PSO of inertia weight. Considering fuzzy logic rules and the last results of particle´s searching, it modifies dynamically the values of inertia weight in order to promote the convergent capability of the particle swarm. To select particle number can also accomplish this goal. It is one way to solve the antinomy between identification time and precision. The experimental results illustrate that the settle of the parameter´s initial value and the algorithm demonstrate the validity and the robust of the nonlinear system identification. Some conclusions can be achieved from it.