# Temperature Regulation of Hot Vapor Preservation Treatment of Litch Based on PSO-Fuzzy PID
## 1 Introduction  
Litchi (Litchi chinensis Som) is a subtropical evergreen tree belonging to the Sapindaceae family and Litchi genus. Its peel is covered in scalp protrusions, while the rip fruit is typically bright red. The pulp is semi-transparent; rich in nutrients such as sugar, organic acids, and amino acids; and encases seeds in a flesly aril. The shape of the litchi fruit varies, with most being irregular spheres or ellipses, and their diameter ranges from 22-36 mm depending on the variety of litchi. Litchi is an important cash crop in China, and its planting area and output rank first in the world [1]. It can easily be infected by microorganisms or bacteria after harvest, causing deterioration, browning, and corruption. This is due to the high sugar content and vigorous metabolism of litchi [2, 3], which makes the storage and transportation process of litchi difficult and complicated. Therefore, it is necessary to keep litchi fresh in time after harvest. Hot vapor treatment is one of the important methods in the process of litchi preservation. It can effectively avoid or reduce the browning, dehydration, and deterioration of litchi after harvest, and extend the shelf life and storage period of litchi. By adjusting the treatment temperature and duration in the machinery to suit the various types of litchi andcoordinating with post-treatments such as acid leaching and refrigeration [4]. The hot vapor processing equipment requires precise control of the steam temperature to quickly reach and remain stable at the set point. If the treatment time is certain and the treatment temperature is lower than the set value, the expected fresh-keeping effect will not be achieved. If the treatment temperature is higher than the set value, the browning degree of the peel and the flavor of the pulp will change [5]. It is difficult to control the temperature of vapor stably and accurately because of its nonlinearity, time-varying and hysteresis [6]. In recent years, there has been significant progress in the development of intelligent optimization algorithms, such as the genetic algorithm (GA) [7; 8; 9], particle swarm optimization algorithm (PSO) [10; 11; 12], and ant colony algorithm (ACO) [13; 14]. As a result, a large number of scholars at both domestic and international levels have carried out extensive research on the use of these algorithms in temperature control. [PERSON] [15] designed a new Human-Simulated Intelligent Control (HSIC) controller based on genetic optimization designed for industrial temperature systems, which can improve adaptivity and control accuracy. [PERSON] et al. [16] used a genetic algorithm to adjust the PID parameters and control the temperature in the fermentation tank. The measured system has a fast response speed, small overshoot, and short adjustment time. Scholars from Indian [PERSON] et al. [17] proposed an adaptive neural fuzzy reasoning system based on genetic algorithm (GA-ANFIS) by comparing various intelligent technologies for the temperature control of a water bath system. [PERSON] et al. [18] also combined PSO with ANFIS to form an adaptive neuro-fuzzy inference system based on particle swarm optimization (PSO-ANFIS) for a water bath system. It was found that the controller had better regulation and tracking performance after using particle swarm optimization compared with ANFIS and GA-ANFIS. [PERSON] et al. [19] compared the adaptive fuzzy PID controller with the pole-placement adaptive PID controller and applied it to the saturated vapor temperature regulation. In contrast, the fuzzy PID requires more adjustment time and the pole-placement adaptive PID can show better stability. [PERSON] et al. [20] used PSO tuning PI control as a solution to the greenhouse control system. The integral square error (ISE) was selected as the fitness function. The stability time, peak overshoot, and rise time were used as the controller performance indicators. The results showed that the PSO-PI tuning algorithm in this paper possesses better performance. [PERSON] et al.