In the darkness and high pressure of the 10,000-meter deep sea, submersibles need to complete complex tasks such as sample collection, terrain mapping, and biological observation. This relies on the "precise manipulation" of deep-sea thrusters — and at the core of all this is the intelligent control technology hidden in the propulsion system. Unlike the control environment of land-based equipment, the strong interference, complex ocean currents, and unknown terrain in the deep sea require the thruster's control system to have full-chain intelligent capabilities of "perception, decision-making, and execution." This technological revolution centered on "precision" is redefining the possibilities of deep-sea exploration.
Intelligent perception is the "eyes" of precise control, providing real-time environmental and self-status data for the thruster. Deep-sea thrusters are equipped with multi-dimensional sensing systems, including pressure sensors, ocean current sensors, attitude sensors, and position sensors. Pressure sensors real-time monitor changes in deep-sea pressure to provide a basis for adjusting the thruster's output power; ocean current sensors can capture ocean current speed and direction at the 0.1-meter per second level, allowing the control system to predict interference in advance; attitude sensors feed back the thruster's pitch and roll status at a millisecond-level frequency, ensuring synchronization between power output and attitude adjustment. The propulsion system of China's "Haidou-1" unmanned submersible, through a perception network composed of 12 sets of high-precision sensors, achieves comprehensive perception of the deep-sea environment, providing accurate data support for subsequent control decisions.
Intelligent decision-making is the "brain" of precise control, relying on algorithms to achieve dynamic adaptation to complex scenarios. The deep-sea environment changes rapidly, and fixed control modes cannot cope with all situations. Therefore, the thruster's control system embeds adaptive algorithms and deep learning models. When encountering sudden ocean currents, the adaptive algorithm can calculate the compensation thrust within 0.5 seconds, offsetting the ocean current interference by adjusting the output difference of multiple thrusters to keep the submersible stable; the deep learning model independently optimizes control parameters based on massive deep-sea mission data — for example, when operating in coral reef areas, the model will automatically reduce the thruster's response sensitivity to avoid damaging the environment due to excessive movement amplitude; when cruising in open sea areas, it increases the response speed to improve movement efficiency. This "context-aware" decision-making capability upgrades the thruster from "passive execution" to "active adaptation."
Intelligent execution is the "hands and feet" of precise control, achieving refined movements through multi-thruster coordination. Modern deep-sea thrusters generally adopt a multi-unit layout of "main thrusters + auxiliary fine-tuning thrusters." The control system realizes independent regulation and coordinated linkage of each thruster through distributed control technology. For example, the 10 thrusters equipped on the "Fendouzhe" (Striver) are uniformly dispatched by the central control system, enabling 16 complex movements such as "3D hovering," "in-place rotation," and "oblique translation." When collecting rock samples at the 10,000-meter seabed, the control system will simultaneously activate 4 auxiliary fine-tuning thrusters to offset the reaction force of the sampling tool with millinewton-level thrust precision, ensuring the submersible remains motionless; when quickly transferring operation areas, the main thrusters provide continuous thrust, and the auxiliary thrusters real-time correct the course, keeping the error within the centimeter-level range.
From the "all-round perception" of intelligent sensing, to the "situation assessment" of intelligent decision-making, and then to the "precise implementation" of intelligent execution, the intelligent control technology of deep-sea thrusters is essentially an extension of human wisdom in the deep-sea environment. With the integration of artificial intelligence and Internet of Things technologies, the future thruster control system will have stronger autonomous learning capabilities — it can independently identify different seabed terrains, predict equipment failures, and optimize power distribution strategies. This "smarter" control technology can not only reduce the operational difficulty of deep-sea missions but also allow submersibles to penetrate more unknown sea areas, providing "precise and controllable" power support for humanity to unlock the mysteries of the deep sea.
