Abstract
Abstract:
This paper presents an intelligent generalized predictive
controller (GPC) based on particle swarm optimization
(PSO) for linear or nonlinear process with constraints. We
propose several constraints for the plants from the engineering
point of view and the cost function is also simplified. No
complicated mathematics is used which originated from the
characteristics ofPSO. This method is easy to be used to control
the plants with linear or/and nonlinear constraints. Numerical
simulations are used to show the performance of this control
technique for linear and nonlinear processes, respectively. In
the first simulation, the control signal is computed based
on an adaptive linear model. In the second simulation, the
proposed method is based on a fixed neural network model
for a nonlinear plant. Both of them show that the proposed
control scheme can guarantee a good control performance.