Sail control system and method based on distributed flexible sensing

Abstract

The application provides a kind of based on distributed flexible sensing sail control system and method, belong to ship engineering and automatic control technical field, its system includes: sail;Distributed flexible sensor array, for real-time synchronous measurement of the pressure signal of different positions of sail surface;Signal acquisition and processing unit, electrically connected with the distributed flexible sensor array, for processing the pressure signal collected, and calculating a set of characteristic parameters;Sail health monitoring and early warning unit, for analyzing strain signal, evaluating the structural health state of sail surface and generating early warning;Intelligent controller is used to generate attitude adjustment instruction according to the deviation between the set of characteristic parameters calculated in real time and the set of target parameters, combined with the intelligent identification result of aerodynamic state;Sail surface driving structure, for adjusting the attitude of the sail according to the attitude adjustment instruction generated by the intelligent controller.The application improves the aerodynamic efficiency of the sail, the control accuracy and the sailing safety.

Description

Technical Field

[0001] This invention relates to the fields of marine engineering and automatic control technology, specifically to a sail control system and method based on distributed flexible sensing. Background Technology

[0002] In the field of marine engineering, sails, as a long-established renewable energy utilization device, have long relied primarily on the experience of crew members for operation. With the development of automation technology, rudimentary automatic control systems have emerged that automatically adjust the sail angle by collecting macroscopic environmental signals such as wind speed and wind direction. These systems can be regarded as early prototypes of intelligent sail control systems, aiming to reduce the intensity of manual operation while maintaining basic sail efficiency.

[0003] However, existing automatic sail control schemes still have several significant limitations. First, at the sensing level, the systems generally rely on anemometers installed on the mast or hull, which can only acquire macroscopic information about the incoming flow and cannot directly obtain detailed information about the aerodynamic pressure distribution on the sail itself in real time. This indirect sensing method makes it impossible for the system to identify changes in microscopic aerodynamic states such as localized sail stall and airflow separation. Second, at the execution level, the control strategies are mostly based on preset sail angle-wind speed tables or simple feedback control, which are open-loop or semi-open-loop adjustments and are difficult to cope with the complex and transient real airflow fields in actual navigation.

[0004] Therefore, the existing technology still faces the following pressing technical challenges: how to achieve high-precision, high-reliability real-time sensing of the aerodynamic pressure distribution across the entire surface of the sail without interfering with its aerodynamic shape; how to construct an adaptive closed-loop control strategy capable of dynamically tracking the optimal operating point based on the refined aerodynamic data obtained from real-time sensing; and how to ensure reliable and durable integration of the entire sensing system with the flexible sail to adapt to real-world marine operating environments. Furthermore, existing solutions lack the capability for real-time online monitoring and assessment of the sail structure's health status under complex loads, failing to provide early warnings of localized overloads or early damage, thus posing safety hazards. Summary of the Invention

[0005] In view of this, it is necessary to provide a sail control system and method based on distributed flexible sensing to solve the technical problems of poor sail control accuracy and reliability and lack of sail structure health monitoring capability caused by the existing method of using preset feedback control and weak aerodynamic state perception.

[0006] To address the aforementioned technical problems, in a first aspect, the present invention provides a sail control system based on distributed flexible sensing, comprising: sails; A distributed flexible sensor array, embedded inside or on the surface of the sail, contains multiple independent sensing units arranged in a spatial array, used to measure pressure or strain signals at different positions on the sail surface in real time and output a digital image characterizing the two-dimensional pressure distribution on the sail surface. The signal acquisition and processing unit is electrically connected to the distributed flexible sensor array and is used to process the acquired pressure or strain signals and calculate a set of characteristic parameters reflecting the overall aerodynamic state of the sail surface. The aerodynamic state intelligent identification unit is connected to the signal acquisition and processing unit. It is used to receive the processed pressure distribution data or feature parameter set, and perform real-time analysis through the built-in machine learning model to identify specific aerodynamic state modes such as "optimal lift", "airflow separation" and "precursor to stall". The sail health monitoring and early warning unit is connected to the signal acquisition and processing unit. It is used to receive and analyze strain distribution data and its historical sequence, evaluate the integrity of the sail structure through anomaly detection, threshold comparison and fatigue analysis algorithms, and output a health status quantification index and local overload and damage early warning signals. The intelligent controller is communicatively connected to the signal acquisition and processing unit, the aerodynamic state intelligent identification unit, the sail health monitoring and early warning unit, and the sail drive structure. It is used to generate attitude adjustment commands based on the comprehensive deviation between the real-time feature parameter set, the intelligently identified aerodynamic state, the health early warning information, and the target parameter set. The sail-driven structure is used to adjust the attitude of the sail according to the attitude adjustment command generated by the intelligent controller, forming a closed-loop control loop with the intelligent controller and the distributed flexible sensor array.

[0007] In one possible implementation, the sail includes a mainsail and a foresail, and the distributed flexible sensor array is at least embedded in the surface of the mainsail.

[0008] In one possible implementation, each sensing unit in the distributed flexible sensor array is a multilayer composite flexible thin film structure with a total thickness on the sub-millimeter scale, conformally fitted to the sail surface.

[0009] In one possible implementation, the sensitive unit includes an upper flexible encapsulation layer, an upper electrode layer, a flexible dielectric layer, a lower electrode layer, and a lower flexible encapsulation layer arranged sequentially from top to bottom; the surface of the flexible dielectric layer in contact with the upper electrode layer is provided with periodic microstructures.

[0010] In one possible implementation, the periodic microstructure is an array of cylindrical protrusions with a height of 10-100 micrometers.

[0011] In one possible implementation, the sail drive structure includes a servo motor connected to the sail mast and an electric winch that controls the sail cables.

[0012] In one possible implementation, the set of characteristic parameters includes at least one of pressure center coordinates, resultant force coefficient, and moment coefficient; The coordinates of the pressure center are calculated based on the following formula:

[0013]

[0014] in, Location in the digital image The pressure value at that location, and The coordinates of the pressure center ( ).

[0015] In one possible implementation, the intelligent controller calculates the attitude adjustment command using a proportional-integral-derivative control law:

[0016] in, , The deviation between the feature parameter set and the target parameter set. For the target parameter set, For the feature parameter set, , , This is the gain coefficient.

[0017] In one possible implementation, the sail control system based on distributed flexible sensing includes a navigation management unit connected to the intelligent controller, which is used to dynamically set the target parameter set based on waypoints and sea state information.

[0018] On the other hand, the present invention also provides a sail control method based on distributed flexible sensing, comprising: The two-dimensional pressure distribution on the sail surface is acquired in real time by a distributed flexible sensor array embedded in the sail surface; Calculate the set of characteristic parameters reflecting the aerodynamic state of the sail surface based on the two-dimensional pressure distribution; The set of feature parameters calculated in real time is compared with the target parameter set, and attitude adjustment commands are generated based on the deviation. According to the attitude adjustment command, the sail drive structure is driven to adjust the sail attitude to form a closed-loop control.

[0019] The beneficial effects of this invention are as follows: The distributed flexible sensing-based sail control system provided by this invention, by embedding a distributed flexible sensor array inside or on the surface of the sail, synchronously measures pressure or strain signals at different positions on the sail in real time, outputs a two-dimensional digital image of pressure distribution, and achieves transparent perception of the aerodynamic state across the entire field, providing a real-time data foundation for precise control; the signal acquisition and processing unit processes the signals, calculates a set of characteristic parameters reflecting the overall aerodynamic state of the sail, and transforms the distribution information into quantifiable and evaluable aerodynamic parameters; the intelligent controller generates attitude adjustment commands based on the deviation between the real-time characteristic parameter set and the target parameter set, realizing dynamic decision-making based on real-time data; the sail drive structure adjusts the sail attitude according to the commands, thereby forming a closed-loop control loop, realizing real-time monitoring and automatic optimization of the sail's aerodynamic state, and effectively improving wind energy utilization efficiency and navigation control precision. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram illustrating an embodiment of the wind turbine control system based on distributed flexible sensing provided by the present invention. Figure 2 A cross-sectional schematic diagram of a single sensing unit in one embodiment of the distributed flexible sensing-based sail control system provided by the present invention; Figure 3 A planar schematic diagram of a single sensing unit in one embodiment of the wind turbine control system based on distributed flexible sensing provided by the present invention; Figure 4 A schematic diagram of the structure of an embodiment of the wind turbine control system based on distributed flexible sensing provided by the present invention; Figure 5 This is a schematic flowchart of an embodiment of the sail control method based on distributed flexible sensing provided by the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0023] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0024] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] This invention provides a sail control system and method based on distributed flexible sensing. The technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention. For ease of explanation, Figure 1 , Figure 2 , Figure 3 A specific application scenario illustration of one embodiment of this application is provided. Figures 1 to 3 In the diagram, 1 represents the hull, 2 the mainsail, 3 the foresail, 4 the distributed flexible sensor array, 5 the signal acquisition and processing unit, 6 the intelligent controller, 10 the mast, 20 the sail drive structure, 21 the sail mast (connected to the servo motor), and 22 the sail cable (controlled by an electric winch).

[0027] Figure 4 A schematic diagram of an embodiment of the wind turbine control system based on distributed flexible sensing provided by the present invention is shown below. Figure 4 As shown, the sail control system based on distributed flexible sensing includes: Sail 401; The distributed flexible sensor array 402 is embedded inside or on the surface of the sail 401. It contains multiple independent sensitive units arranged in a spatial array to measure pressure or strain signals at different positions on the sail surface in real time and synchronously, and outputs a digital image characterizing the two-dimensional pressure distribution on the sail surface and synchronous two-dimensional strain distribution data. The signal acquisition and processing unit 403 is electrically connected to the distributed flexible sensor array 402 and is used to process the acquired pressure signals or strain signals and calculate the set of characteristic parameters reflecting the overall aerodynamic state of the sail surface. The aerodynamic state intelligent identification unit 406 is connected to the signal acquisition and processing unit 403. This unit has a built-in pre-trained machine learning model. It receives pressure distribution images or feature parameters from unit 403, classifies and identifies them in real time, and outputs the current aerodynamic state label of the sail surface (e.g., "high-efficiency adhesion flow", "slight separation", "severe stall"). The identification results are provided to the intelligent controller 404 for adaptive adjustment of the gain parameters of the PID controller or fine-tuning of the target parameter set, enabling the control system to have the "intelligence" of condition adaptation.

[0028] The sail health monitoring and early warning unit 407 is connected to the signal acquisition and processing unit 403. This unit is dedicated to analyzing strain data, and its core functions include: (1) Real-time early warning of local overload: continuously monitoring the strain value of each sensitive unit. When the strain value or its rate of change of any unit exceeds the preset safety threshold, an alarm is immediately triggered and the specific sail surface area is located. (2) Structural damage anomaly detection: by analyzing the strain distribution pattern of the entire sail and comparing it with the historical baseline model under normal working conditions, using anomaly detection algorithms such as isolated forest, anomaly patterns such as strain concentration and asymmetrical distribution are identified, and possible structural damage is warned. (3) Fatigue life estimation: the strain-time history of key stress areas is recorded, the load spectrum is obtained by rainflow counting, and the cumulative fatigue damage degree and remaining life of the area are estimated by combining the material SN curve model. The output of unit 407 is connected to the intelligent controller 404 with high priority. The intelligent controller 404 is communicatively connected to the signal acquisition and processing unit 403, the aerodynamic state intelligent identification unit 406, the sail health monitoring and early warning unit 407, and the sail drive structure 405. Its operating logic is as follows: First, it comprehensively evaluates the health status from unit 407. If a high-level early warning is received, it may override the original aerodynamic optimization goals and instead generate a protective adjustment command with "unloading the stress in this area" as its primary task. Under normal conditions, the controller receives the aerodynamic state identification results from unit 406 and the real-time characteristic parameter set from unit 403. The controller can dynamically select or adjust a set of PID parameters based on different aerodynamic conditions, or fine-tune the target parameter set Starget issued by the navigation management unit. Subsequently, the deviation between the adjusted target and the real-time characteristic parameters is calculated. The final attitude adjustment command is generated through a PID control law. .

[0029] The sail drive structure 405 is used to adjust the attitude of the sail 401 according to the attitude adjustment commands generated by the intelligent controller 404, forming a closed-loop control loop with the intelligent controller 404 and the distributed flexible sensor array 402. This embodiment aims to achieve real-time accurate perception and automatic optimization control of the sail's aerodynamic state, constructing a closed-loop control loop. This closed-loop control loop begins with the direct measurement of the sail's physical state, undergoes data analysis and decision-making by the central processing unit, and finally acts on the sail itself through the actuator, forming a continuously feedback and adjustment automated process.

[0030] The system's sensing layer consists of a distributed flexible sensor array 402. This array is embedded inside or on the surface of the sail 401, and its core features are its distributed and flexible nature.

[0031] Specifically, the distributed flexible sensor array 402 consists of a large number of independent sensing units arranged in a spatial array on the sail surface, forming a dense sensing network. Each unit can measure minute pressure or strain changes at its local location in real time and synchronously. The measurement data of all units are synchronously collected and integrated, and jointly output as a two-dimensional digital image of pressure distribution that dynamically reflects the stress situation on the entire sail surface. This distributed measurement method, directly attached to the sail, fundamentally changes the traditional method of indirectly inferring the sail surface state through wind speed and direction, and for the first time realizes intuitive real-time monitoring of the aerodynamic loads on the sail surface across the entire field.

[0032] The processing of the raw sensor signals is accomplished by a dedicated signal acquisition and processing unit 403. This unit is directly electrically connected to the sensor array and is responsible for receiving the raw electrical signals from each sensing unit. Its processing flow typically includes signal amplification, filtering to remove noise, and analog-to-digital conversion. Afterward, the unit performs calculations and analysis on the digitized pressure distribution image according to a preset algorithm, extracting a set of characteristic parameters that summarize the overall aerodynamic performance of the sail. These characteristic parameters are macroscopic evaluation indicators condensed from microscopic distribution information, providing a quantitative basis for subsequent intelligent control decisions.

[0033] The intelligent controller 404 maintains communication connections with both the signal acquisition and processing unit 403 and the sail drive structure 405. Its core function is to implement a closed-loop control algorithm: continuously comparing the current set of characteristic parameters acquired in real-time from the signal processing unit with a target parameter set preset or dynamically generated according to the navigation strategy. By calculating the deviation between the two, the controller uses its internal control law model to generate specific, quantified attitude adjustment commands. This step realizes the transition from state perception to control decision-making, enabling the system to automatically determine the gap between the current sail shape and the optimal state, and plan an adjustment path.

[0034] The sail drive structure 405 is used to execute control commands. This structure receives attitude adjustment commands from the intelligent controller 404 and converts them into mechanical actions that drive the sail control mechanisms such as the mast and rigging. After the sail shape changes, the aerodynamic pressure distribution on its surface changes immediately. This change is captured by the distributed flexible sensor array 402 and transmitted to the system as a new round of feedback signals.

[0035] In some embodiments of the present invention, the sail drive structure 405 includes a servo motor connected to the sail mast and an electric winch for controlling the sail cables.

[0036] Specifically, the sail drive structure 405 works in conjunction with two types of core actuators to control different degrees of freedom of the sail: Angle of attack adjustment mechanism: This part typically consists of a servo motor (or high-precision hydraulic servo motor) connected to and driving the mast. The servo motor receives adjustment commands (usually angle values ​​or position signals) regarding the target angle of attack from the intelligent controller 404, and precisely drives the output shaft to rotate through its internal closed-loop control system (such as encoder feedback). The rotational motion of the output shaft is transmitted to the mast via mechanical linkages, gearboxes, or direct drive, thereby causing the entire sail to rotate around the mast, changing the angle between the sail surface and the wind direction (i.e., the angle of attack). This is the most important and direct means of adjusting the aerodynamic performance of the sail.

[0037] Sail Curve Adjustment Mechanism: This part typically consists of an assembly of electric winches (or linear servo actuators) that control the individual sail lines (such as the main winding line and the lead winding line). Each electric winch controls the winding and unwinding length of a specific sail line. The intelligent controller 404 calculates, based on an optimization algorithm, the required combination of sail line tension adjustments to achieve optimal pressure distribution. Each electric winch receives the commands synchronously, precisely winding or unwinding the lines to apply varying tensions to the sail's edge. This change in tension finely controls the sail's curvature and three-dimensional surface shape, such as making the sail flatter or fuller, thereby optimizing airflow adhesion, which is crucial for improving sail efficiency.

[0038] In the actual workflow, a composite attitude adjustment command generated by the intelligent controller 404 (e.g., "adjust the angle of attack to 35 degrees and increase the trailing edge tension of the mainsail by 10%) is decoupled and synchronously sent to the corresponding servo motor and the corresponding electric winch. These actuators act almost simultaneously, quickly and accurately implementing the digital command into changes in the angle of the mast and the length of the rigging, thereby collaboratively completing a fine-tuned adjustment of the overall attitude of the sail.

[0039] Therefore, the sail drive structure 405 is essentially an integrated electromechanical actuation system combining a servo motor and an electric winch. By receiving control commands from higher levels, it drives the traditional mast and rigging—two physical interfaces—thereby achieving automatic, precise, and coordinated control of the sail angle of attack and sail shape. This provides reliable physical execution capabilities for the closed-loop control of the entire intelligent sail system, fully utilizing existing sail manipulation interfaces. This allows the intelligent control system of this invention to be integrated and modified in a modular manner with traditional sailboat architectures.

[0040] By embedding a distributed flexible sensor array inside or on the surface of the sail, pressure or strain signals at different locations on the sail are measured synchronously in real time, and a two-dimensional digital image of pressure distribution is output, achieving transparent perception of the aerodynamic state across the entire field and providing a real-time data foundation for precise control. The signal acquisition and processing unit processes the signals and calculates a set of characteristic parameters reflecting the overall aerodynamic state of the sail, converting the distribution information into quantifiable aerodynamic parameters. The intelligent controller generates attitude adjustment commands based on the deviation between the real-time characteristic parameter set and the target parameter set, realizing dynamic decision-making based on real-time data. The sail drive structure adjusts the sail attitude according to the commands, thus forming a closed-loop control loop, realizing real-time monitoring and automatic optimization of the sail's aerodynamic state, effectively improving wind energy utilization efficiency and navigation control precision.

[0041] In some embodiments of the present invention, the sail 401 includes a mainsail and a foresail, and the distributed flexible sensor array 402 is at least embedded in the surface of the mainsail.

[0042] In some embodiments of the present invention, each sensing unit in the distributed flexible sensor array 402 is a multilayer composite flexible thin film structure with a total thickness on the sub-millimeter scale, conformally fitted to the sail surface.

[0043] In some embodiments of the present invention, the sensitive unit includes an upper flexible encapsulation layer, an upper electrode layer, a flexible dielectric layer, a lower electrode layer, and a lower flexible encapsulation layer arranged sequentially from top to bottom; the surface of the flexible dielectric layer in contact with the upper electrode layer is provided with periodic microstructures.

[0044] In some embodiments of the present invention, the periodic microstructure is an array of cylindrical protrusions, and the height of the microstructure is 10-100 micrometers.

[0045] This embodiment further defines and optimizes the specific implementation of the distributed flexible sensor array, aiming to improve the reliability, sensitivity, and integration of the sensing system with the sail.

[0046] Regarding the sensor array deployment strategy, a typical implementation embodies the sail as a composite sail system comprising a mainsail and a foresail. In such implementations, the distributed flexible sensor array is preferentially, and at least embedded within the mainsail's surface. The mainsail is chosen as the core sensing carrier because it plays a major role in propulsion, and its aerodynamic state has a decisive impact on sailing efficiency. By deploying the sensor array in key aerodynamic regions of the mainsail (such as the leading edge, the point of maximum curvature, and the trailing edge), the core aerodynamic load distribution information can be captured most effectively, providing the most critical data input for the control system's decision-making. This focused deployment method optimizes system complexity and cost while ensuring sensing effectiveness.

[0047] To achieve seamless integration with the sail and ensure long-term reliability, each sensing unit in the sensor array is constructed as a multi-layered, flexible thin-film structure. Its overall thickness is controlled to the sub-millimeter level (e.g., between 0.05 mm and 0.8 mm), giving the sensing film excellent flexibility. Conformal bonding means that the thin-film structure can adhere tightly to the curved surface of the sail, deforming with the sail's bending and wrinkling without peeling or creating hard protrusions. This characteristic is achieved by using specific flexible materials (such as polydimethylsiloxane PDMS and thermoplastic polyurethane TPU) as the substrate and encapsulation layer, combined with a low-modulus bonding process. This completely avoids the disruption to the original aerodynamic shape of the sail caused by traditional rigid sensor installations, ensuring smooth airflow across the sail surface; simultaneously, its extremely thin and flexible form allows it to withstand repeated bending and stretching of the sail surface during use, significantly improving structural durability in dynamic marine environments.

[0048] Furthermore, the internal structure of the sensing unit adopts a multi-layer stacked architecture, including, from top to bottom, an upper flexible encapsulation layer, an upper electrode layer, a flexible dielectric layer, a lower electrode layer, and a lower flexible encapsulation layer. The upper and lower electrode layers, serving as the two plates of a capacitor, are typically fabricated from flexible conductive materials such as silver nanowires or conductive polymers using patterning processes (e.g., screen printing). The flexible dielectric layer, sandwiched between the two plates, is typically made of elastomers such as PDMS or Ecoflex. This layer is the core of pressure sensing, and its elastic modulus determines the unit's sensitivity. To improve the response to minute pressures, an effective optimization method is to create periodic microstructures on the surface where the flexible dielectric layer contacts the upper electrode layer. These microstructures artificially create a regularly arranged microstructure on the surface of the dielectric layer.

[0049] One preferred implementation of the periodic microstructure is a cylindrical protrusion array.

[0050] Specifically, the array consists of countless micro-cylinders with diameters ranging from tens of micrometers to 10 to 100 micrometers in height, arranged in a regular pattern. When external pressure is applied to the sensing unit, these protruding structures undergo elastic deformation first, causing a significant change in the dielectric layer thickness locally, thereby resulting in a larger change in the unit capacitance. Compared to a completely flat dielectric layer, this microstructure design can produce a larger rate of capacitance change under the same applied pressure, thus significantly improving the sensor's sensitivity. For example, an array of cylindrical protrusions with a height of 50 micrometers can increase the unit sensitivity several times. This allows the system to more accurately sense subtle changes in airflow pressure on the sail surface, providing a more precise data foundation for refined aerodynamic optimization control.

[0051] This embodiment achieves a significant improvement in the spatial resolution and measurement sensitivity of aerodynamic pressure sensing while ensuring high-performance and high-reliability mechanical integration and electrical connection between the sensor and the flexible sail, thereby providing high-quality field data for upper-level intelligent control algorithms.

[0052] In some embodiments of the present invention, the set of characteristic parameters includes at least one of pressure center coordinates, resultant force coefficient, and moment coefficient; The coordinates of the pressure center are calculated based on the following formula:

[0053]

[0054] in, Location in digital image The pressure value at that location, and The coordinates of the pressure center ( ).

[0055] In some embodiments of the present invention, the intelligent controller 404 calculates the attitude adjustment command through a proportional-integral-derivative control law:

[0056] in, , The deviation between the feature parameter set and the target parameter set. For the target parameter set, For the feature parameter set, , , This is the gain coefficient.

[0057] In some embodiments of the present invention, the sail 401 control system based on distributed flexible sensing includes a navigation management unit, which is connected to an intelligent controller 404 and is used to dynamically set a set of target parameters based on waypoints and sea state information.

[0058] The navigation management unit dynamically sets a set of target parameters based on waypoints and sea state information. Specifically, the navigation management unit integrates waypoint sequences from GPS and electronic charts, as well as sea state information (such as wind speed, wind direction, and wave height) from meteorological sensors or forecasts, and makes decisions based on preset navigation strategies (such as shortest time, most fuel-efficient, and most comfortable). For example, when sailing against the wind, the unit may set the goal to maximize the lateral thrust coefficient; when sailing downwind and in bad sea conditions, the primary goal may be to reduce sail load and heel moment, dynamically adjusting the target value of the resultant force coefficient.

[0059] This embodiment combines the real-time closed-loop control at the lower level with the navigation mission and environmental situation at the higher level to achieve adaptive dynamic planning of the control objective, thereby globally optimizing the ship's overall navigation performance and economy in complex multi-objective and multi-constraint navigation scenarios.

[0060] Figure 5 A schematic flowchart of an embodiment of the sail control method based on distributed flexible sensing provided by the present invention is shown below. Figure 5 As shown, the sail control method based on distributed flexible sensing includes: S501: Synchronous Data Acquisition. A distributed flexible sensor array embedded in the sail surface is used to synchronously acquire the two-dimensional pressure distribution matrix across the entire sail surface in real time. With the two-dimensional strain distribution matrix ε( ).

[0061] S502: Parallel Processing and Feature Extraction. This step consists of two parallel paths: S502A: Aerodynamic feature extraction. Based on the pressure distribution matrix. P Calculate the set of macroscopic aerodynamic characteristic parameters S(t) Including but not limited to: pressure center ( ), resultant force coefficient CF(t) Torque coefficient CM(t) .

[0062] S502B: Structural health diagnosis. Based on the two-dimensional strain distribution matrix ε and historical data, a health monitoring algorithm is executed to output a health status index. H(t) And possible early warning signals (such as “Area A3 strain exceeds limit”, “strain mode abnormal”).

[0063] S503: Intelligent Recognition and Decision-Making. This step is the core of intelligent control. S503A: Intelligent pneumatic condition recognition. It identifies the pressure distribution matrix. P or feature parameter set S(t) Input a pre-trained aerodynamic state recognition model and output the current state classification (e.g., "State: Optimal Lift").

[0064] S503B: Multi-objective integrated decision-making. Intelligent controller receives... S(t), H(t) The identification results are then used. First, the decision to enter "safety protection mode" is based on the health warning level. In normal mode, the current target parameter set Starget is dynamically determined or fine-tuned based on the aerodynamic identification results. Finally, the deviation is calculated. And invoke the adaptive PID control law (its parameters) , , It can dynamically adjust according to the identified aerodynamic state and generate detailed attitude adjustment commands. ΔC(t) This includes the target angle of attack and the tension of each sail target.

[0065] S504: Command execution and closed-loop feedback. The sail-driven structure (servo motor, electric winch) executes commands. ΔC (t) The sail attitude is precisely adjusted. The change in attitude directly causes changes in the pressure and strain distribution on the sail surface. This change is captured again by the sensor array and fed back to step S501, thus forming a closed-loop control loop that is continuously optimized and has safety monitoring capabilities.

[0066] Step S501 acquires aerodynamic load distribution information through a sensor system integrated into the sail. Specifically, this embodiment achieves this through a distributed flexible sensor array embedded inside or on the surface of the sail.

[0067] This distributed flexible sensor array consists of multiple independent sensing units arranged in a spatial array to form a sensing network covering key areas of the sail surface (such as the leading edge, belly, and trailing edge).

[0068] Each sensing unit employs a multi-layered, flexible thin-film structure with a total thickness on the sub-millimeter scale. This allows it to conformally fit the sail surface, measuring minute pressure or strain changes at its location in real time without interfering with the original aerodynamic shape. These raw signals collectively form a two-dimensional digital image of the pressure distribution over time, enabling, for the first time, direct, visualized, and real-time monitoring of the entire aerodynamic state of the sail. This overcomes the perception blind spots of traditional indirect macroscopic measurements, providing precise data support for subsequent accurate control.

[0069] After acquiring the two-dimensional pressure distribution data, step S502 processes it to extract key quantitative indicators characterizing the overall aerodynamic performance. This step is completed by the signal acquisition and processing unit, which first performs preprocessing such as filtering, amplification, and digitization on the raw signal, and then calculates the set of characteristic parameters reflecting the overall aerodynamic state of the sail surface according to a preset algorithm.

[0070] The feature parameter set includes at least one of the following: pressure center coordinates, resultant force coefficient, and moment coefficient. Taking the pressure center coordinates as an example, the calculation method is as follows: based on the pressure value at each coordinate point in the pressure distribution image, the coordinates of the point of application of the resultant force on the sail surface are calculated using a formula. This step refines massive amounts of distribution data into a small number of control parameters with clear physical meaning, realizing the transformation from perception to quantification. By tracking the dynamic changes of parameters such as the pressure center in real time, the system can accurately determine the current aerodynamic efficiency state of the sail surface, such as whether the pressure center is in an ideal position, thereby identifying potential stall or inefficient regions.

[0071] Based on the feature parameter set obtained through real-time calculation, step S503 implements closed-loop decision-making to generate control commands. This step is executed by the intelligent controller, which compares the real-time feature parameter set with a target parameter set dynamically generated based on the current navigation objective (such as pursuing maximum thrust or minimum roll) and environmental information, and calculates the deviation between the two. To eliminate this deviation, the intelligent controller uses a closed-loop control law, such as a proportional-integral-derivative (PID) control law, to generate specific attitude adjustment commands. This control law, by adjusting the proportional, integral, and derivative gain coefficients, can systematically eliminate steady-state errors, suppress overshoot, and accelerate response speed, thereby achieving smooth, precise, and adaptive adjustment of the sail attitude. This approach allows control decisions to no longer rely on preset fixed rules or human experience, but rather on dynamic optimization based on real-time aerodynamic state feedback, effectively solving the problems of coarseness and lag in traditional control methods.

[0072] Finally, step S504 translates the decision into physical actions, completing the execution phase of the closed-loop control. Attitude adjustment commands are sent to the sail drive structure, which typically includes servo motors driving the mast and electric winches controlling the rigging. Upon receiving the commands, these components precisely adjust the mast angle or rigging tension, thereby altering the sail's angle of attack and sail shape to approach the optimal aerodynamic state. After adjustment, the aerodynamic pressure distribution on the sail surface changes accordingly. This change is immediately sensed again by the distributed flexible sensor array and fed back to the signal processing unit, initiating a new "sensing-decision-execution" cycle. This forms a continuously operating, automatically optimizing closed-loop control system, ensuring the sail dynamically maintains itself near its efficient operating point under various complex sea conditions.

[0073] This embodiment achieves refined perception, intelligent decision-making, and precise execution of the aerodynamic state of the sail through the organic connection and iterative iteration of the above four steps, significantly improving the efficiency of wind energy capture and conversion and reducing the reliance on manual operation for navigation. At the same time, the conformal integration of the flexible sensor array ensures the long-term environmental reliability of the system, while the real-time full-field pressure monitoring function provides data support for the health status assessment of the sail structure, thereby enhancing navigation safety while improving economy.

[0074] The above provides a detailed description of the sail control system and method based on distributed flexible sensing provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A sail control system based on distributed flexible sensing, characterized in that, include: sails; A distributed flexible sensor array, embedded inside or on the surface of the sail, contains multiple independent sensing units arranged in a spatial array, used to measure pressure or strain signals at different positions on the sail surface in real time and output a digital image characterizing the two-dimensional pressure distribution on the sail surface. The signal acquisition and processing unit is electrically connected to the distributed flexible sensor array and is used to process the acquired pressure or strain signals and calculate a set of characteristic parameters reflecting the overall aerodynamic state of the sail surface. The sail health monitoring and early warning unit is communicatively connected to the signal acquisition and processing unit. It is used to receive and analyze the strain signals and historical data, execute the structural health assessment algorithm, and output the sail health status index and early warning signal. The intelligent controller is communicatively connected to the signal acquisition and processing unit, the sail health monitoring and early warning unit, and the sail drive structure. It is used to receive the feature parameter set, health status index, and early warning signal. Based on the deviation between the real-time calculated feature parameter set and the preset or dynamically generated target parameter set, and by integrating the aerodynamic state intelligent recognition results and health early warning information, it generates attitude adjustment commands. The sail-driven structure is used to adjust the attitude of the sail according to the attitude adjustment command generated by the intelligent controller, forming a closed-loop control loop with the intelligent controller and the distributed flexible sensor array.

2. The sail control system according to claim 1, characterized in that, The sail includes a mainsail and a foresail, and the distributed flexible sensor array is at least embedded in the surface of the mainsail.

3. The sail control system according to claim 1, characterized in that, Each sensing unit in the distributed flexible sensor array is a multi-layered composite flexible thin film structure with a total thickness on the sub-millimeter scale, conformally fitted to the sail surface.

4. The sail control system according to claim 3, characterized in that, The sensitive unit includes, from top to bottom, an upper flexible encapsulation layer, an upper electrode layer, a flexible dielectric layer, a lower electrode layer, and a lower flexible encapsulation layer; the surface of the flexible dielectric layer that contacts the upper electrode layer is provided with periodic microstructures.

5. The sail control system according to claim 4, characterized in that, The periodic microstructure is an array of cylindrical protrusions, with a height of 10-100 micrometers.

6. The sail control system according to claim 1, characterized in that, The sail drive structure includes a servo motor connected to the sail mast and an electric winch that controls the sail cables.

7. The sail control system according to claim 1, characterized in that, The set of characteristic parameters includes at least one of pressure center coordinates, resultant force coefficient, and moment coefficient; The coordinates of the pressure center are calculated based on the following formula: in, Location in the digital image The pressure value at that location, and The coordinates of the pressure center ( ).

8. The sail control system according to claim 1, characterized in that, The intelligent controller calculates the attitude adjustment command using a proportional-integral-derivative control law: in, , The deviation between the feature parameter set and the target parameter set. For the target parameter set, For the feature parameter set, , , This is the gain coefficient.

9. The sail control system according to claim 1, characterized in that, The evaluation algorithm executed by the sail health monitoring and early warning unit includes: performing local overload early warning based on spatiotemporal pattern analysis of the two-dimensional strain distribution data; performing abnormal damage detection by comparing with historical strain baseline data; and estimating material fatigue life based on the cyclic load spectrum of key locations.

10. A sail control method based on distributed flexible sensing, characterized in that, The sail control method based on distributed flexible sensing, applied to any one of claims 1 to 9, comprises: The two-dimensional pressure distribution data and two-dimensional strain distribution matrix of the sail surface are acquired in real time by a distributed flexible sensor array embedded in the sail surface. The characteristic parameter set reflecting the aerodynamic state of the sail is calculated based on the two-dimensional pressure distribution data, and the sail structure health monitoring algorithm is executed based on the two-dimensional strain distribution data to generate a health status index and early warning signal as the intelligent aerodynamic state identification result. By combining the results of intelligent aerodynamic state recognition, the set of feature parameters calculated in real time is compared with the target parameter set, and attitude adjustment commands are generated based on the deviation. According to the attitude adjustment command, the sail drive structure is driven to adjust the sail attitude to form a closed-loop control.

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