An intelligent course keeping active disturbance rejection controller based on double deep Q‐network for towing system of unpowered cylindrical drilling platform

Abstract

Towing is a widely used mode of transportation in offshore engineering, and towing of unpowered platforms is of particular significance. However, the addition of unpowered facilities has increased the difficulty of ship maneuvering. Moreover, the marine environment is complex and changeable, and sudden winds or waves can have unpredictable effects on the towing process. Therefore, it is of great significance to overcome the influence of the harsh marine environment while navigating the towing system following a planned course to a target sea area. To tackle the time-varying disturbances, a course control method for a towing system of unpowered cylindrical drilling platform is designed based on double deep Q-network (DQN) optimized linear active disturbance rejection control (LADRC). To be specific, to tackle the difficulty of LADRC tuning, double DQN is applied to select the best parameters of the LADRC at any time according to the states of the system, without relying on the specific information of the model and the controller. The course control performance of the towing system is evaluated in a simulation environment under various disturbances. Moreover, the Monte Carlo experiment is used to test the robustness of the controller when the ship's mass changes and the robustness of the proposed method is verified by testing with various heading angles. The results show that the LADRC with adaptive parameters optimized by double DQN performs well under external interference and inherent uncertainty, and compared with the traditional LADRC, the proposed method has better course control effects.

Controllable 3D Flower-Like Ag-CF Electrodes as Flexible Marine Electric Field Sensors with High Stability

“…For the marine environment, to realize large-area rapid measurement, it is necessary to use the towing system for continuous testing. 18 Both the field source and receiver electrodes must be towed in seawater (or seabed), which requires flexible electrodes to deal with various possible impact situations. 19,20 CFs are well studied as an electrode substrate material in double-layer CCEs, in which the main reaction depends on the charge adsorbed electrostatically on the electrode−electrolyte interface.…”

“…For the marine environment, to realize large-area rapid measurement, it is necessary to use the towing system for continuous testing . Both the field source and receiver electrodes must be towed in seawater (or seabed), which requires flexible electrodes to deal with various possible impact situations. , CFs are well studied as an electrode substrate material in double-layer CCEs, in which the main reaction depends on the charge adsorbed electrostatically on the electrode–electrolyte interface. − Compared with the Ag/AgCl ECEs, − the CF electrode showed stronger application potential in marine exploration because of their high flexibility, long-term stability, long service life, and low cost. , Nevertheless, the drawbacks of low activity and poor hydrophilicity of bare CFs are non-negligible. , It is imperative to develop high electrochemical activity materials to combine with CFs.…”

Event-Sampled Adaptive Neural Course Keeping Control for USVs Using Intermittent Course Data

“…This implies that L Vo is bounded and its upper bound can be adjusted to be as small as desired. Furthermore, from (15), one can understand that χ1 , χ2 , and θ are bounded, which indicates that the NN-based state observer (10) can estimate the states of the CKC system (1) in real time as long as Equation ( 24) can be held. Thus, Theorem 1 is proved.…”

“…For the issue of CKC, many effective design approaches have been reported, such as active disturbance rejection control (ADRC) [10], PID [11], backstepping [12], sliding mode control (SMC) [13], and H∞ [14]. Furthermore, intelligent ADRC [15], fuzzy PID [16,17], neural PID [18], adaptive backstepping [19], and non-fragile H∞ [20] are proposed to resolve the issue of CKC for USVs. Under these control schemes, the desired control performance was obtained.…”

An intelligent control for reducing third-party interference in oil and gas pipeline using Deep Q-Networks (DQN)

“…In terms of theory, Chen [14] and Wang [15] provided proof of the stability of LADRC. LADRC has demonstrated its control advantages in applications such as power system load frequency control (LFC) [16], heading angle control [17], path-following control [18,19], and an electromechanical servo system [20]. For example, Li et al [21] proposed a guidance law based on a ship's nonlinear combination of lateral error and heading angle error, and LADRC was used to estimate and eliminate the disturbances.…”