A neuro-fuzzy decoupling approach for real-time drying room control in meat manufacturing. Issue 3 (15th February 2015)

• Record Type: Journal Article
• Authors: Zhang, Wei; Ma, Hong; Yang, Simon X.
• Is Part Of: Expert systems with applications. Volume 42:Issue 3(2015)
• Page Start: 1039
• Page End: 1049
• Publication Date: 2015-02-15
• Subjects: Relative humidity measurement -- Decoupling control -- Temperature -- Relative humidity -- Neuro-fuzzy system -- Control accuracy; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2014.09.013
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: A coupling model of temperature and relative humidity was proposed using ANFIS. Decoupling control of temperature and relative humidity in drying room was developed. The decoupling approach was developed for a large real-time meat drying room. The simulation results show the fluctuation of relative humidity was reduced to ±0.6%. Abstract: This paper proposes a method to resolve a strong coupling between temperature and relative humidity in drying room control systems. The coupling issue not only affects the control accuracy but also causes system instability, unnecessary adjustment, and extra energy consumption. A real-time temperature and relative humidity decoupling control method is reported in this paper. An improved aspirated psychrometer was used as a relative humidity measurement unit, which achieved relative humidity measurement accuracy of ±0.7%. The decoupling approach was developed based on a large real-time drying room, whose physical size was 22 × 15 × 3.5 m. A decoupling approach was developed using the adaptive neuro-fuzzy inference system for the control of temperature and relative humidity in the drying room. The simulated result shows that after the decoupling treatment, the relative humidity fluctuation was reduced from ±2.5% to ±0.6%.