Neurodynamics-Based Receding Horizon Control of an HVAC System

被引：0
|
作者：
Wang, Jiasen [1 ,3 ]
Wang, Jun [1 ,2 ,3 ]
Gu, Shenshen [4 ]
机构：
[1] City Univ Hong Kong, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China
[2] City Univ Hong Kong, Sch Data Sci, Kowloon, Hong Kong, Peoples R China
[3] City Univ Hong Kong, Shenzhen Res Inst, Shenzhen, Peoples R China
[4] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2019, PT II | 2019年 / 11555卷
基金：
中国国家自然科学基金;
关键词：
HVAC; Receding horizon control; Neurodynamic optimization;
D O I：
10.1007/978-3-030-22808-8_13
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper addresses receding horizon control of a heating, ventilation, and air-conditioning (HVAC) system based on neurodynamic optimization. The receding horizon control problem for the HVAC system is formulated as sequential quadratic programs, which are solved by using a neurodynamic optimization model. Simulation results on temperature setpoint regulation of the HVAC system are discussed to substantiate the efficacy of the approach.
引用
收藏
页码：120 / 128
页数：9
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