Construction Equipment Control Research Based on Predictive Technology

Jiejia LI, Rui QU, Yang CHEN,

Indonesian Journal of Electrical Engineering and Computer Science, Vol 10, No 5: September 2012 , pp. 960-967

Abstract

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on T-S fuzzy model. Through T-S fuzzy recursive neural network predictor on line established controlled object’s mathematical model, and using neural network controller on line corrected information we get, thus to improve control effect. The simulation results show that T-S fuzzy recursive neural network predictive control has stronger robustness and adaptive ability, high control precision, better and reliable control effect and other advantages.  DOI:http://dx.doi.org/10.11591/telkomnika.v10i5.1277