Title :
Improving central air conditioning energy saving control system through BP neural network and genetic algorithm
Author :
Zengdong, Zhang ; Ziwei, Ni ; Yi, Jiang ; Fan, Lin
Author_Institution :
Coll. of Inf. Sci. & Technol., Xiamen Univ., Xiamen, China
Abstract :
BP artificial neural network is a non-feedback network. This paper utilizes the initial weights of neural network to choose controller performance. Simultaneously according to the characteristics that process of central air-conditioning energy saving control is the system of multi-parameter and nonlinear time-varying complexity, we analysis and study its algorithm and system architecture. The experimental results demonstrate that new control system gets better results and energy saving.
Keywords :
air conditioning; backpropagation; genetic algorithms; neurocontrollers; nonlinear control systems; power control; time-varying systems; BP neural network; backpropagation; central air conditioning; energy saving control system; genetic algorithm; multi-parameter complexity; nonlinear time-varying complexity; Cooling; Optimization; Process control; Reliability engineering; BP Artificial Neural Network; Fuzzy PID Control Strategy; Genetic Algorithm; Robustness; Steady-state error;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5620656