A Novel Fuzzy Controller Design Based-on PID Gains for HVAC Systems

被引：17

作者：

Hongli, Lv ^{[1
]}

Peiyong, Duan ^{[1
]}

Lei, Jia ^{[2
]}

机构：

[1] Shandong Jianzhu Univ, Sch Informat & Elect Engn, Jinan 250101, Shandong, Peoples R China

[2] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China

来源：

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年

关键词：

Fuzzy control; Structure analysis; Robustness; HVAC systems;

D O I：

10.1109/WCICA.2008.4593014

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The Heating, Ventilating. and Air-Conditioning systems (HVAC systems) are typical nonlinear time-variable multivariate systems with disturbances and uncertainties. A new fuzzy control strategy based on the PID parameters tuning to Control HVAC systems is proposed in this paper. It takes full advantage of mature technologies of PID controller to improve the design of fuzzy controller. The mathematical analytical expression of parameters between fuzz.), controllers and gains coefficients of PID controllers is got based on the structure analysis of fuzzy controllers. and the fuzzy controller is designed through gains tuning of PIT) controller based the analytical relations. Then this fuzzy controller was applied into temperature control in HVAC systems. The simulation test results showed it is effective and compared with the conventional PID control, the proposed fuzzy, control algorithm has less overshoot, shorter setting time and better robustness etc.

引用

页码：736 / +

页数：2

共 10 条

[1]

Astrom K. J., 1995, PID CONTROLLERS THEO

[2] Autotuning a PID controller: A fuzzy-genetic approach [J].

Bandyopadhyay, R ;

Chakraborty, UK ;

Patranabis, D .

JOURNAL OF SYSTEMS ARCHITECTURE, 2001, 47 (07) :663-673

[3] Advanced controller auto-tuning and its application in HVAC systems [J].

Bi, Q ;

Cai, WJ ;

Wang, QG ;

Hang, CC ;

Lee, EL ;

Sun, Y ;

Liu, KD ;

Zhang, Y ;

Zou, B .

CONTROL ENGINEERING PRACTICE, 2000, 8 (06) :633-644

[4] Fuzzy PID controller: Design, performance evaluation, and stability analysis [J].

Carvajal, J ;

Chen, GR ;

Ogmen, H .

INFORMATION SCIENCES, 2000, 123 (3-4) :249-270

[5]

DEFIGUERREDO RJP, 1993, NONLINEAR FEEDBACK C

[6] Multiple fuzzy model-based temperature predictive control for HVAC systems [J].

He, M ;

Cai, WJ ;

Li, SY .

INFORMATION SCIENCES, 2005, 169 (1-2) :155-174

[7] An improved robust fuzzy-PID controller with optimal fuzzy reasoning [J].

Li, HX ;

Zhang, L ;

Cai, KY ;

Chen, GR .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2005, 35 (06) :1283-1294

[8] APPLICATION OF FUZZY ALGORITHMS FOR CONTROL OF SIMPLE DYNAMIC PLANT [J].

MAMDANI, EH .

PROCEEDINGS OF THE INSTITUTION OF ELECTRICAL ENGINEERS-LONDON, 1974, 121 (12) :1585-1588

[9] PID plus fuzzy controller structures as a design base for industrial applications [J].

Reznik, L ;

Ghanayem, O ;

Bourmistrov, A .

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2000, 13 (04) :419-430

[10] OUTLINE OF A NEW APPROACH TO ANALYSIS OF COMPLEX SYSTEMS AND DECISION PROCESSES [J].

ZADEH, LA .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1973, SMC3 (01) :28-44

← 1 →