| Título: | Construction Equipment Control Research Based on Predictive Technology |
| Autores: |
LI, Jiejia; Shenyang Jianzhu University, Shenyang QU, Rui; Shenyang Jianzhu University, Shenyang CHEN, Yang; Shenyang Jianzhu University, Shenyang |
| Fecha: | 2012-09-01 |
| Publicador: | TELKOMNIKA: Indonesian journal of electrical engineering |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| Tema: | No aplica |
| Descripción: | 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. |
| Idioma: | Inglés |