# An Innovative System of Deep In Situ Environment Reconstruction and Core Transfer
## 2 Related Works  
Deep in situ environment reconstruction is mainly used in the field of deep Earth and deep sea science research to build the deep in situ environment with specific temperature and pressure [5]. Researchers in the United States, Japan, Russia, South Korea, etc., began their study early in this field and have achieved significant results [6]. As early as 1951, a U.S. naval shipyard built a deep sea pressure simulation device, achieving a cyclic pressurization of 0.1-4 MPa with a maximum pressure of 4.2 MPa [7]. After that, a device with a maximum pressure of 82.75 MPa was developed [8]. A periodic pressure test device with a maximum pressure of 156 MPa was developed in Japan [9]. Furthermore, a medium-sized chamber was subsequently developed to simulate the dynamic pressure environment up to 154.9 MPa, and its maximum working pressure in the circulation mode could reach 113.7 MPa [10]. Researchers in Russia developed a series of deep sea environment simulation platforms, which could realize the test pressure up to 150 MPa [11]. The above equipment only focused on the pressure loading, and the influence of temperature was not considered. In the fields of P-T control and core test under the in situ fidelity environment, researchers in the U.K., E.U., U.S. and China have achieved impressive results [12]. The MSCL system developed by Geotek in 2003 could be used for parametric analysis of cores or seafloor sediments. Although this system was not strictly a fidelity system, it helped to accumulate rich experience in core transfer under in situ fidelity environment [13; 14]. In 2009, Geotek developed the PCATS system on the basis of MSCL, which could achieve a maximum pressure of 35 MPa and a temperature control of 4-20 \({}^{\circ}\)C. The HYACINTH system developed in Europe could cut, transfer and test samples in an in situ pressure environment with a maximum pressure of 25 MPa [15]. The pressure-holding transfer device for natural gas hydrate developed by Zhejiang University in China could achieve fidelity testing at a temperature of 2-4 \({}^{\circ}\)C and a pressure of up to 30 MPa [16]. In temperature and pressure control, many control methods have been produced. The earlier temperature control methods such as fuzzy logic controller [17], intelligent control [18] and cascade controller [19] all have good performance, but their computational efficiency and stability need to be further improved. Recently, temperature control methods based on prediction began to attract attention. The prediction-based methods have a good performance in improving response speed and reducing overshoot. [PERSON] et al. proposed an intelligent random model prediction method, which used path integration method and particle swarm optimization algorithm to achieve optimal control of temperature [20]. [PERSON] et al. proposed a delay-range-dependent robust constrained model predictive control method, which had better track and anti-interference performance for temperature control [21]. [PERSON] et al. proposed a dual input and dual output predictive control strategy, which improved the production efficiency of temperature control [22]. In terms of pressure control, on the basis of the early standard PID control method, a lot of improved methods, such as fuzzy PID control, BP neural network control, and PID control based on ant colony algorithm, have been developed [23; 24]. These methods generally have better performance than the conventional PID method. In the decoupling control of pressure and temperature, researchers in the chemical industry adopted the pressure-compensated temperature control method for the temperature and pressure control of mixed gas [25; 26]. [PERSON] et al. proposed a dynamic pressure control method based on LPLD, which created a scheduling table by pre calculated PID parameters, performed PID compensation under different temperature and pressure conditions, and realized stable pressure control [27].