The Multiple parameters double fuzzy decoupling PID algorithm for pig breeding system
In order to avoid the swine problems such as the outbreak of widespread disease, inferior meat and aquaculture pollution, and improve the self-regulation ability of pig farming system, in this paper, the problems of strong coupling among parameters and single control parameters in conventional PID a...
Saved in:
| Published in | 2019 6th International Conference on Systems and Informatics (ICSAI) pp. 649 - 654 |
|---|---|
| Main Authors | , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.11.2019
|
| Subjects | |
| Online Access | Get full text |
| DOI | 10.1109/ICSAI48974.2019.9010089 |
Cover
| Summary: | In order to avoid the swine problems such as the outbreak of widespread disease, inferior meat and aquaculture pollution, and improve the self-regulation ability of pig farming system, in this paper, the problems of strong coupling among parameters and single control parameters in conventional PID algorithm control are optimized, and combined with the pig farming system, a multiple parameter double fuzzy decoupling PID algorithm is designed. In view of the problems of temperature and humidity control system, such as time delay and strong coupling, this algorithm makes the originally coupled temperature and humidity variables equivalent to two independent temperature and humidity control subsystems, thus solving the problem of strong coupling of temperature and humidity. At the same time, this algorithm solves the problem that temperature and humidity, ammonia, carbon dioxide, hydrogen sulfide and other parameters can only be regulated by a single controller through the design of Double Fuzzy Controller. Under the same experimental simulation environment, the comparing with the conventional PID algorithm, this algorithm to get the temperature of the conventional PID algorithm control overshoot amount is 0.2%, humidity overshoot amount is 0.1%, harmful gas overshoot amount is 0.2% 0.4%, the maximum overshoot basic to 0 and the algorithm and accuracy increased by 0.23%, the maximum overshoot smaller, so the algorithm can achieve faster stability range. |
|---|---|
| DOI: | 10.1109/ICSAI48974.2019.9010089 |