Valve control method and system based on deep sea environment pressure self-adaptive adjustment

Abstract

The application relates to the field of automatic control, and discloses a valve regulation method and system based on deep-sea environmental pressure self-adaptive regulation, which comprises the following steps: synchronously collecting flow field disturbance state, external hydrostatic pressure evolution characteristics and speed change information in the diving process of a water area where a valve is located, and generating environmental response characteristic parameters; performing disturbance level division on pressure change behavior, and forming a hierarchical linkage control structure; combining the hierarchical linkage control structure, determining the disturbance level of the current water area, and generating subsystem trigger instruction information; when the disturbance level corresponding to the subsystem trigger instruction information satisfies a preset switching condition, corresponding pressure regulation control instructions are generated; in the process of executing pressure regulation by the regulation execution subsystem according to the pressure regulation control instructions, a feedback regulation mechanism is formed by combining valve internal and external pressure difference feedback information and safety pressure interval constraints. The application has the advantages of improving the hierarchical response and self-adaptive regulation capability of the valve to deep-sea transient pressure difference disturbance.

Description

Technical Field

[0001] This invention relates to the field of automatic control, specifically to a valve control method and system based on adaptive adjustment of deep-sea environmental pressure. Background Technology

[0002] In deep-sea oil and gas transportation and subsea equipment pressure balance control scenarios, valves are typically used to achieve fluid isolation and pressure regulation between different cavities. As the equipment is gradually lowered from shallow water to the target operating depth, the external hydrostatic pressure shows a continuous upward trend. The pressure inside the valve cavity is mostly maintained by the initial filling state or a relatively lagging regulation mechanism. During this dynamic descent, especially in the transient transition zone where pressure changes rapidly, a mismatch can easily occur between the rate of increase of external hydrostatic pressure and the rate of response of internal pressure. This can lead to abrupt fluctuations in the pressure difference between the inside and outside of the valve in a short period of time. Such transient pressure difference changes are usually characterized by short duration and high rate of change. Even if the overall pressure has not exceeded the structural design limit, it may still create local impact loads or microscopic leakage risks at the valve sealing interface.

[0003] Existing valve control methods are mostly based on fixed opening control or a single pressure threshold triggering mechanism. They lack fine-grained response capabilities to the dynamic disturbance characteristics and differential pressure change rate during pressure changes, making it difficult to effectively suppress sudden changes in internal and external pressure differences under short-term transient conditions. At the same time, existing technologies usually adopt a unified control strategy for regulation, lacking a mechanism for hierarchical regulation and strategy switching based on differences in disturbance states, resulting in insufficient stability of valve regulation process under complex seabed conditions.

[0004] Therefore, existing technologies are unable to promptly identify and respond to transient pressure imbalances caused by rapid pressure changes during deep-sea dynamic diving and complex disturbance environments, which in turn affects the long-term stability and reliable operation of valve sealing structures. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a valve control method and system based on adaptive adjustment of deep-sea environmental pressure. This method has the advantages of improving the valve's graded response and adaptive control capability to transient pressure difference disturbances in the deep sea, thus solving the problems mentioned in the background technology.

[0006] To achieve the aforementioned goal of improving the valve's graded response and adaptive control capability to transient pressure differential disturbances in the deep sea, this invention provides the following technical solution: a valve control method based on adaptive adjustment of deep-sea environmental pressure, comprising the following steps: The flow field disturbance state, external hydrostatic pressure evolution characteristics, and velocity change information during the submersion process of the water area where the valve is located are collected simultaneously. Combined with historical operating data, the multi-source information is coupled and analyzed to generate environmental response characteristic parameters that characterize the water pressure disturbance characteristics. Based on environmental response characteristic parameters, the pressure change behavior is classified into disturbance levels, a control strategy cluster that is adaptively updated with the historical control response effect is constructed, and an independent control execution subsystem is preset for the control strategy cluster, forming a hierarchical linkage control structure driven by disturbance level and mediated by strategy group. Based on environmental response characteristic parameters and combined with a hierarchical linkage control structure, the disturbance level of the current water area is determined, and a target strategy is selected from the control strategy cluster according to the disturbance level to generate corresponding subsystem trigger indication information. When the disturbance level corresponding to the subsystem trigger indication information meets the preset switching conditions, the subsystem switches to the adjustment execution subsystem corresponding to the target strategy through the control signal, and generates the corresponding pressure adjustment control command without the need to perform pressure trend analysis. During the process of pressure regulation executed by the regulation execution subsystem according to the pressure regulation control command, the pressure regulation control command is limited and its stability is checked by combining the feedback information of the pressure difference inside and outside the valve and the safety pressure range constraint, thus forming a feedback regulation mechanism for the correction of the regulation control command.

[0007] Preferably, the process of generating environmental response characteristic parameters that characterize the water pressure disturbance properties is as follows: By installing pressure acquisition units, flow velocity acquisition units, and motion state acquisition units outside the valve body and in the surrounding water area, the flow field disturbance, hydrostatic pressure, and submersion speed are acquired synchronously. The acquired data is time-aligned and mapped according to a unified coordinate system; The real-time collected data is matched, calculated and fused with historical operating condition data; Extract pressure fluctuation characteristics, flow velocity changes, and motion state correlation parameters to generate environmental response characteristic parameters.

[0008] Preferably, the process of constructing a cluster of control strategies that adaptively updates with historical adjustment response effects is as follows: Calculate the pressure change amplitude and rate of change based on environmental response characteristic parameters; Input the pressure change amplitude and rate of change into the preset level classification rules to determine the corresponding disturbance level; A set of corresponding adjustment strategies is generated based on the disturbance level, and the set of adjustment strategies is classified to form an initial control strategy cluster; Based on the pressure regulation deviation and response results obtained during the regulation process, the strategy weights and strategy distributions in the initial regulation strategy cluster are updated and adjusted to form an updated regulation strategy cluster.

[0009] Preferably, the process of forming a hierarchical linkage control structure driven by disturbance levels and mediated by strategy groups is as follows: Based on the differences in pressure regulation targets under different disturbance levels, the control strategy clusters are functionally divided into steady-state regulation strategy group, rapid pressure relief strategy group and buffer balance strategy group. Based on the regulation characteristics and response requirements of each strategy group, the corresponding valve execution subsystem is configured respectively; By combining the mapping relationship between disturbance levels and adjustment targets, a corresponding mapping relationship between disturbance levels and each strategy group is established; Furthermore, a binding relationship is established between each strategy group and the corresponding valve execution subsystem, forming a hierarchical linkage control structure driven by disturbance level and mediated by strategy group.

[0010] Preferably, the process for determining the disturbance level of the current water area is as follows: By inputting environmental response characteristic parameters into the disturbance identification process associated with the hierarchical linkage control structure, the pressure change trend score, flow field disturbance intensity score, and velocity coupling effect score are calculated. The disturbance level is initially determined by matching the multidimensional scoring results with the preset level threshold range in the hierarchical linkage control structure. By combining historical strategy group execution feedback data, the disturbance level is probability-corrected and confidence-evaluated to obtain the corrected disturbance level distribution results; A time-sliding window mechanism consistent with the strategy group switching rhythm is introduced to perform time-series smoothing on the corrected perturbation level distribution results and output the final perturbation level.

[0011] Preferably, the process of generating the corresponding subsystem trigger indication information is as follows: Based on the mapping relationship between disturbance levels and strategy groups, the target strategy group is determined from the control strategy cluster; The execution parameters corresponding to the target strategy group are encapsulated into a subsystem trigger instruction package, including the target pressure range, response priority, and execution timing window; By combining system security constraints, the trigger command packet is subjected to consistency verification and redundancy filtering to generate corresponding subsystem trigger indication information.

[0012] Preferably, the process of switching to the adjustment execution subsystem corresponding to the target strategy via control signals is as follows: Upon receiving a subsystem trigger indication, the system performs real-time monitoring and evaluation of the current operating status and load changes of the executing subsystem. Based on the current pressure regulation deviation, the trend of disturbance level changes, and the load status of the execution subsystem, determine whether the switching conditions for the execution subsystem are met. When the switching conditions are met, the process of transferring control between the primary and backup execution subsystems is triggered. The control signal is switched from the current execution subsystem to the execution subsystem corresponding to the target strategy, forming a dynamic switching control result for the execution subsystem.

[0013] Preferably, the process of generating the corresponding pressure regulation control command is as follows: Based on the desired pressure range output by the target strategy group corresponding to the dynamic switching control result, calculate the target valve opening and pressure regulation increment parameters. Based on the current pressure difference feedback value inside and outside the valve, real-time pressure error correction is performed; Based on the corrected pressure error, segmented control calculations are performed, and safety pressure boundary constraints are integrated. The control commands are then subjected to amplitude limiting and stability verification to generate corresponding pressure regulation control commands.

[0014] Preferably, the process of forming a feedback adjustment mechanism for adjusting control commands is as follows: During the valve's pressure regulation process, based on environmental response characteristic parameters and pressure regulation control commands, internal and external pressure difference feedback data and environmental response characteristic parameter change information are continuously collected; The actual adjustment results are dynamically compared with the target pressure range to calculate the adjustment deviation and convergence trend. Based on the adjustment deviation, the parameters of the control strategy cluster and the execution subsystem are updated and adaptively corrected online to form a feedback control mechanism for adjusting control commands.

[0015] A valve control system based on adaptive adjustment of deep-sea environmental pressure includes: Environmental perception module: synchronously collects and couples the information on flow field disturbance, hydrostatic pressure and submersion velocity of the water area where the valve is located, and generates environmental response characteristic parameters; Disturbance classification module: Based on environmental response characteristic parameters, the disturbance level of pressure change behavior is classified, and a cluster of control strategies and corresponding control execution subsystems are constructed to form a hierarchical linkage control structure; Strategy matching module: Determines the current disturbance level based on environmental response characteristic parameters and hierarchical linkage control structure, and selects target strategies from the control strategy cluster to generate subsystem trigger indication information; Execution switching module: When the switching conditions are met, switch to the adjustment execution subsystem corresponding to the target strategy and generate pressure regulation control commands; Feedback correction module: During execution, it combines differential pressure feedback and safety pressure constraints to limit and correct the control commands and verify their stability, thus forming a feedback regulation mechanism.

[0016] Compared with existing technologies, the present invention provides a valve control method and system based on adaptive adjustment of deep-sea environmental pressure, which has the following advantages: This invention constructs a disturbance level classification and control strategy cluster mapping mechanism based on environmental response characteristic parameters. This enables valves to achieve graded identification and differentiated control of complex pressure fluctuations caused by flow field disturbances, hydrostatic pressure changes, and submersion velocity changes in the deep-sea environment. Furthermore, it introduces a multi-regulation execution subsystem switching structure driven by strategy clusters, allowing the system to dynamically select matching control strategies based on the disturbance level. This avoids the response lag problem of traditional single control modes under complex operating conditions. Simultaneously, during pressure regulation execution, the system incorporates feedback information on the valve's internal and external pressure differences and safety pressure range constraints to perform amplitude limiting correction and stability verification on the pressure regulation control commands. This allows the regulation process to promptly suppress transient pressure difference fluctuations, reducing the impact of sudden changes in internal and external pressure differences on the sealing interface. Through these mechanisms, rapid perception, graded response, and adaptive adjustment of transient pressure difference disturbances in the deep sea are achieved, thereby improving the valve's regulation accuracy, operational stability, and sealing reliability under complex dynamic submersion conditions. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the method of the present invention; Figure 2 This is a schematic diagram of the structure of the present invention. Detailed Implementation

[0018] 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 some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1: Please refer to Figure 1 As shown in the embodiment of the present invention, the valve control method based on adaptive adjustment of deep-sea environment pressure includes the following steps: S1: The flow field disturbance state, external hydrostatic pressure evolution characteristics, and velocity change information during the submersion process of the water area where the valve is located are collected synchronously. Combined with historical operating data, the multi-source information is coupled and analyzed to generate environmental response characteristic parameters that characterize the water pressure disturbance characteristics.

[0020] The process of generating environmental response characteristic parameters that characterize the water pressure disturbance properties in S1 is as follows: By installing pressure acquisition units, flow velocity acquisition units, and motion state acquisition units on the outside of the valve body and in the surrounding waters, the flow field disturbance, hydrostatic pressure, and submersion speed are simultaneously acquired. The environmental conditions of the target water area are also simultaneously acquired by these same units. The pressure acquisition unit utilizes a high-frequency hydrostatic pressure sensor array deployed around the circumference of the valve body shell to acquire local hydrostatic pressure distribution data. The flow velocity acquisition unit employs a multi-point ultrasonic flow velocity sensor or a Doppler flow velocity detection device to acquire flow velocity change information at different spatial locations. The motion state acquisition unit acquires acceleration, attitude angle, and velocity change information during the valve body's submersion process via an inertial measurement unit (IMU). All acquisition units perform synchronous sampling through a unified time triggering mechanism, enabling the flow field disturbance data, hydrostatic pressure data, and motion state data within the same time section to establish a corresponding relationship, thereby obtaining a multi-source raw environmental data set. The acquired data is time-aligned and mapped according to a unified coordinate system. The multi-source raw environmental data acquired synchronously is time-aligned using a unified timestamp method to map pressure data, flow velocity data, and motion state data to the same sampling time. Linear interpolation or sliding window compensation is performed on data with sampling delay to eliminate time deviation caused by acquisition delay. Subsequently, a three-dimensional spatial coordinate system with the geometric center of the valve body as the origin is constructed, and the spatial positions of each acquisition unit are calibrated. The flow velocity vector, pressure distribution value, and motion state parameters are uniformly transformed into this coordinate system for expression, thus forming a standardized data structure that is consistent in time and space, providing a unified data foundation for subsequent fusion calculations. Real-time acquired data is matched and fused with historical operating condition data. Real-time environmental data, after time alignment and coordinate mapping, is matched with standard operating condition data in the historical operating condition database. The historical operating condition data is classified and stored according to different depth ranges, different flow field disturbance levels, and different diving speed ranges. The matching process adopts an operating condition matching method based on similarity calculation. By calculating the multidimensional distance between real-time data and historical samples in pressure change curves, flow velocity change gradients, and motion trajectory, the most similar historical operating condition subset is determined. The real-time data and historical data are then weighted and fused. The weight of real-time data is dynamically adjusted with the disturbance intensity, while historical data is used to provide a stable benchmark reference, thereby reducing the impact of instantaneous noise and enhancing data robustness. The system extracts pressure fluctuation characteristics, flow velocity changes, and motion state correlation quantities to generate environmental response characteristic parameters. After data fusion, the system performs feature extraction processing on the fused multi-source data. This includes calculating pressure fluctuation characteristics based on pressure data to characterize the amplitude and rate of change of static pressure per unit time; calculating flow velocity changes based on flow velocity data to characterize the intensity and direction of local flow field disturbances; and extracting motion state correlation quantities based on motion state data to characterize the coupling relationship between valve body submersion velocity changes and pressure changes. These three types of characteristic quantities are then vectorized and normalized to form environmental response characteristic parameters. These parameters are used to uniformly characterize the current pressure disturbance state of the water area, providing input for disturbance level classification and control strategy selection.

[0021] S2: Based on environmental response characteristic parameters, the disturbance level of pressure change behavior is divided, a control strategy cluster that is adaptively updated with the historical control response effect is constructed, and an independent control execution subsystem is preset for the control strategy cluster, forming a hierarchical linkage control structure driven by disturbance level and mediated by strategy group.

[0022] The process of constructing a cluster of control strategies in S2 that adaptively updates with historical control response effects is as follows: The pressure change amplitude and rate of change are calculated based on environmental response characteristic parameters. The collected environmental response characteristic parameters are reconstructed into a time series. The environmental response characteristic parameters include at least external hydrostatic pressure, flow field disturbance intensity, and structural force feedback value. Time synchronization and noise reduction processing are performed on each parameter. Then, a pressure sampling sequence within a continuous time window is selected, and the difference between the current pressure value and the reference steady-state pressure value is calculated to obtain the pressure change amplitude. At the same time, the pressure change gradient per unit time, i.e., the pressure change rate, is obtained by performing first-order difference operation or sliding window linear fitting on continuous sampling points. The pressure signals from different sources are weighted and fused to reduce the influence of single measurement point errors. Finally, the standardized pressure change amplitude and rate of change, which characterize the current environmental disturbance intensity, are output. The pressure change amplitude and rate of change are input into a preset level classification rule to determine the corresponding disturbance level. A multi-level disturbance level classification rule library is pre-constructed. The rule library is determined based on the statistical results of historical operating data and the system safety threshold. It includes at least slight disturbance, moderate disturbance, strong disturbance and extreme disturbance levels. The pressure change amplitude and rate of change are used as two-dimensional judgment input parameters and input into the level classification mapping model. The mapping model is implemented by partition threshold judgment or classification method based on cluster center. When the pressure change amplitude and rate of change fall into the preset threshold range or the nearest level center, the corresponding disturbance level is determined. At the same time, in order to avoid misjudgment by a single threshold, a dynamic correction factor is introduced to adaptively fine-tune the threshold for the range with large historical errors, so as to achieve stable classification and robust judgment of disturbance levels under different operating conditions. A set of corresponding adjustment strategies is generated based on the disturbance level, and the adjustment strategy set is categorized to form an initial control strategy cluster. A strategy mapping database is pre-built for different disturbance levels, with each disturbance level corresponding to multiple executable adjustment strategies. The adjustment strategies include at least valve opening adjustment strategies, pressure release path switching strategies, and flow suppression strategies. When the current disturbance level is determined, the strategy combination matching the level is called from the strategy database to form an initial control strategy set. The strategy set is structured and categorized according to the strategy's objective and execution characteristics to form a hierarchical initial control strategy cluster. In this strategy cluster, each strategy node contains strategy parameters, applicable operating condition range, and execution constraints, thereby realizing the modular organization and callability of the strategies. Based on the pressure regulation deviation and response results obtained during the regulation process, the strategy weights and distributions in the initial regulation strategy cluster are updated and adjusted to form an updated regulation strategy cluster. During the actual execution of the regulation strategy, the adjusted system pressure output value is collected in real time and compared with the target stable pressure range. The pressure regulation deviation value and convergence time are calculated as response indicators. The magnitude of the regulation deviation, overshoot, and recovery time are used as evaluation factors for the strategy effect. A strategy effect scoring function is constructed to quantitatively evaluate the performance of each strategy in the initial regulation strategy cluster. The strategy weights are dynamically corrected using an exponential moving average or reinforcement learning update mechanism, which increases the weight of better-performing strategies and decreases the weight of poor-performing strategies. At the same time, the strategy cluster structure is rearranged and optimized according to the frequency of strategy use and the distribution of effectiveness under different disturbance levels. Long-term inefficient strategies are eliminated and the coverage of highly adaptable strategies is strengthened. Finally, an updated regulation strategy cluster that can continuously evolve with historical regulation effects is formed, realizing the adaptive evolution and closed-loop optimization of the strategy system.

[0023] The process of forming a hierarchical linkage control structure driven by disturbance levels and mediated by strategy groups in S2 is as follows: Based on the differences in pressure regulation objectives under different disturbance levels, the control strategy clusters are functionally divided into a steady-state regulation strategy group, a rapid pressure relief strategy group, and a buffer balance strategy group. Cluster analysis is performed on the pressure change curves corresponding to different disturbance levels in historical operating data to extract the dominant characteristics of pressure change at each level, including the rate of change, fluctuation amplitude, and recovery time. Different characteristic combinations are then classified based on a preset objective function. For disturbance levels with slow pressure changes and small fluctuation amplitudes, the corresponding strategies are classified into the steady-state regulation strategy group, with maintaining pressure stability as the main control objective. For disturbance levels where pressure rises rapidly in a short period of time and exceeds the safety threshold, the corresponding strategies are classified into the rapid pressure relief strategy group, with rapidly reducing the pressure peak as the control objective. For disturbance levels where pressure is in the fluctuation transition range, the corresponding strategies are classified into the buffer balance strategy group, with suppressing pressure abrupt changes and smoothing the transition as the control objective. This achieves a hierarchical strategy structure based on the differences in disturbance levels. Based on the regulation characteristics and response requirements of each strategy group, corresponding valve execution subsystems are configured. According to the control frequency requirements and response delay requirements of each strategy group, the valve actuators are configured in a functional hierarchy. The steady-state regulation strategy group corresponds to the low-frequency fine regulation execution subsystem, which uses a small-step opening regulation method combined with proportional-integral control to achieve slow pressure correction. The rapid pressure relief strategy group corresponds to the high-response execution subsystem, which achieves instantaneous pressure reduction by rapidly opening the control valve or bypass pressure relief valve with a large opening and uses an event-triggered control mode to reduce response delay. The buffer balance strategy group corresponds to the medium-frequency continuous regulation execution subsystem, which suppresses pressure oscillation by continuously adjusting the main valve opening and combining a damping control algorithm. Each execution subsystem is equipped with an independent control interface and feedback acquisition channel to receive control commands and transmit pressure response data. By combining the mapping relationship between disturbance levels and regulation targets, a corresponding mapping relationship between disturbance levels and each strategy group is established. The disturbance level is divided into multiple level intervals, such as low disturbance level, medium disturbance level and high disturbance level, and the pressure change characteristics corresponding to each level interval are quantitatively modeled. The low disturbance level is mapped to the steady-state regulation strategy group, the medium disturbance level is mapped to the buffer balance strategy group, and the high disturbance level is mapped to the rapid pressure relief strategy group. A dynamic correction mechanism is introduced to update the mapping relationship based on the historical regulation effect. When the regulation error of a certain strategy group under the corresponding disturbance level exceeds the preset threshold, the mapping relationship is readjusted to improve the adaptability and robustness of level-strategy matching. A binding relationship is established between each strategy group and its corresponding valve execution subsystem, forming a hierarchical linkage control structure driven by disturbance level and mediated by strategy groups. A control mapping table is constructed to realize the one-to-one or one-to-many binding relationship between strategy groups and execution subsystems. Each strategy group corresponds to at least one main execution subsystem and one backup execution subsystem. During control execution, the target strategy group is determined according to the disturbance level, and the corresponding execution subsystem is called through the mapping table and a standardized control instruction set is issued to it. At the same time, a state feedback closed-loop mechanism is introduced during the execution process. By collecting valve opening, pressure change rate and flow response data in real time, the output effect of the execution subsystem is evaluated. When the execution deviation exceeds the limit, the system automatically switches to the backup execution subsystem or adjusts the control parameters, thus forming a three-level linkage control structure with disturbance level as the core driver, strategy group as the intermediate scheduling layer, and execution subsystem as the execution terminal.

[0024] S3: Based on environmental response characteristic parameters and combined with a hierarchical linkage control structure, determine the disturbance level of the current water area, select the target strategy from the control strategy cluster according to the disturbance level, and generate the corresponding subsystem trigger indication information.

[0025] The process for determining the disturbance level of the current water area in S3 is as follows: The environmental response characteristic parameters are input into the disturbance identification process associated with the hierarchical linkage control structure to calculate the pressure change trend score, flow field disturbance intensity score, and velocity coupling effect score. The environmental response characteristic parameters are normalized and a state vector is constructed according to the time series. Local change features are extracted using a sliding time window. The pressure change trend score is obtained by performing first-order difference and slope fitting on the pressure fluctuation sequence to characterize the overall trend intensity of pressure rise or fall. The flow field disturbance intensity score is obtained by weighting the velocity dispersion, turbulence intensity index, and local velocity variance to characterize the stability of water flow. The velocity coupling effect score is calculated based on the correlation coefficient between the submersion velocity and pressure change to reflect the degree of coupling influence of the motion state on the pressure field. Finally, the three types of scores are combined according to preset weights to form a multidimensional score vector.

[0026] The disturbance level is initially determined by matching the multidimensional scoring results with the preset level threshold range in the hierarchical linkage control structure. The multidimensional scoring vector is then input into the hierarchical judgment module and compared with the pre-built level threshold library level by level. The threshold library is based on historical operating condition samples and is defined by partitioning into low disturbance, medium disturbance, high disturbance and extreme disturbance. Vector distance matching or weighted scoring interval landing point judgment method is used to determine the level interval to which the current score belongs and output the corresponding preliminary disturbance level. At the same time, the degree of deviation between the score and the threshold boundary is recorded to provide a basis for correction. By combining historical strategy group execution feedback data, the perturbation level is probabilistically corrected and confidence is assessed to obtain the corrected perturbation level distribution. The execution effect data of the historical strategy group under different perturbation levels are retrieved, including pressure adjustment error, response time and stable convergence time, and a perturbation level-execution effect mapping probability model is constructed. When there is a deviation between the current preliminary perturbation level and similar working conditions in historical feedback, the probability of level assignment is adjusted through Bayesian update or probability weighted correction mechanism to generate multiple perturbation level probability distribution results. At the same time, the confidence index is calculated. When the confidence is low, the weight of neighboring levels is increased, thereby avoiding the risk of misjudgment caused by a single threshold judgment. A time-sliding window mechanism consistent with the strategy group switching cycle is introduced to perform time-series smoothing on the corrected disturbance level distribution results and output the final disturbance level. The sliding window length is set according to the strategy group switching cycle, and the probability distribution of disturbance levels in multiple consecutive time slices is accumulated and statistically analyzed. An exponentially weighted moving average or majority voting mechanism is used to fuse historical window data to suppress level jumps caused by instantaneous fluctuations. Combined with the strategy group switching cycle constraint, the output results are aligned with the cycle, and the final disturbance level is updated only when the switching cycle condition is met, thereby ensuring the timing consistency and control stability between disturbance level determination and execution subsystem switching.

[0027] The process of generating the corresponding subsystem trigger indication information in S3 is as follows: Based on the mapping relationship between disturbance level and strategy group, the target strategy group is determined from the control strategy cluster; the final disturbance level output by the disturbance identification module is received and entered into the preset level-strategy group mapping table for index matching. This mapping table is generated by the statistics of historical operating condition adjustment effect and updated in real time. When the disturbance level falls into the corresponding range, the corresponding strategy group set is called from the strategy cluster, and each strategy group is adapted and scored in combination with the current environmental response characteristic parameters. The scoring indicators include the pressure regulation error prediction value, the response delay prediction value, and the stability coefficient. Finally, the strategy group with the highest comprehensive score is selected as the target strategy group, and its structured parameter set is output for subsequent instruction encapsulation. The execution parameters corresponding to the target strategy group are encapsulated into a subsystem trigger instruction package, including the target pressure range, response priority, and execution timing window. A set of control parameters is extracted from the target strategy group. The target pressure range consists of upper and lower pressure thresholds, which are used to limit the adjustment target range. The response priority is used to identify the scheduling weight of the current strategy in the execution queue. It is usually dynamically assigned according to the severity of the disturbance level. The execution timing window is determined based on the strategy execution cycle and the system control cycle, and is used to limit the time boundaries of subsystem startup, execution, and exit. The above parameters are standardized and encapsulated according to a preset data structure to form a structured trigger instruction package containing identification fields, control fields, and timing fields. By combining system safety constraints, the trigger command package undergoes consistency verification and redundancy filtering to generate corresponding subsystem trigger indication information. The target pressure range in the trigger command package is compared with the current valve safety pressure range to determine whether there is a risk of exceeding the limit. At the same time, conflict detection is performed on the response priority and the current running task queue to prevent high-priority commands from overriding critical safety tasks. At the timing window level, a timestamp verification mechanism is introduced to ensure that the command execution cycle is consistent with the system control cycle. For duplicate or highly similar trigger command packages, a redundancy filtering algorithm is used to merge or suppress them, retaining only valid control commands. Finally, the command package that passes the consistency verification is converted into standardized subsystem trigger indication information and sent to the control interface of the corresponding execution subsystem, realizing safe mapping and reliable triggering from the target strategy group to the execution unit.

[0028] S4: When the disturbance level corresponding to the subsystem trigger indication information meets the preset switching conditions, the subsystem switches to the adjustment execution subsystem corresponding to the target strategy through the control signal, and generates the corresponding pressure adjustment control command without the need to perform pressure trend analysis.

[0029] The process in S4 of switching to the adjustment execution subsystem corresponding to the target strategy via control signals is as follows: Upon receiving a subsystem trigger indication, the system monitors and evaluates the current operating status and load changes of the execution subsystem in real time. After receiving the subsystem trigger indication, the system continuously collects data on the motor drive current, valve opening response delay, actuator displacement feedback signal, and hydraulic / electric drive load pressure of the current execution subsystem through operating status monitoring modules deployed within each valve execution subsystem. A status data stream is formed with a fixed sampling period. Combined with the real-time load change rate obtained from the load sensors within the subsystem, short-term load fluctuations and long-term load trends are separated and analyzed. A sliding time window is used to suppress abnormal fluctuations, thereby obtaining a stable operating status evaluation result. This enables real-time identification of whether the execution subsystem is in a high-load, low-response, or stable operating state. Based on the current pressure regulation deviation, disturbance level change trend, and execution subsystem load status, it is determined whether the execution subsystem switching conditions are met. The current pressure regulation deviation is defined as the difference between the target pressure range and the actual internal and external pressure difference feedback value. Combined with its rate of change, a deviation convergence feature is constructed. The disturbance level change trend is represented as the transition frequency and change direction of the disturbance level within adjacent time windows, which is used to characterize the intensity of external environmental changes. Combined with the execution subsystem load status assessment results, a three-dimensional judgment vector is constructed, and a set of preset switching condition thresholds is set, including the maximum allowable regulation deviation threshold, disturbance transition threshold, and load upper limit threshold. When the three types of parameters simultaneously meet or exceed the preset threshold combination relationship, it is determined that the current execution subsystem cannot meet the current regulation response requirements, thereby triggering the execution subsystem switching condition to be met. Otherwise, the current execution subsystem continues to operate, realizing the stability constraint of the switching behavior. When the switching conditions are met, the control transfer process between the primary and backup execution subsystems is triggered. After confirming that the switching conditions are met, the control transfer mechanism between the primary and backup execution subsystems is initiated. The system control unit sends a degraded operation instruction to the current execution subsystem, causing it to enter a controlled maintenance state. Non-essential parameter updates within the current control cycle are frozen, and only the basic pressure maintenance function is retained. At the same time, a pre-activation instruction is sent to the backup execution subsystem corresponding to the target strategy, causing it to enter the parameter preloading and state synchronization stage in advance, including target pressure range initialization, control parameter loading, and actuator zero-point calibration. After the consistency verification of the states of the two is completed, the control transfer operation is performed, switching the master control authority from the current execution subsystem to the target execution subsystem. The control signal is ensured to be continuous and uninterrupted at the moment of switching, thereby avoiding sudden changes or control gaps during pressure regulation and achieving a smooth transition of execution subsystem takeover. The control signal is switched from the current execution subsystem to the execution subsystem corresponding to the target strategy, forming a dynamic switching control result for the execution subsystem. The original control signal channel is rerouted from the current execution subsystem to the execution subsystem corresponding to the target strategy. At the same time, the control signal is remapped according to the target strategy parameters, including the target pressure range mapping relationship, valve opening gain coefficient, and response timing adjustment parameters. After receiving the control signal, the target execution subsystem immediately performs pressure regulation action according to the preset control law and continuously receives feedback data from internal and external differential pressure sensors for fine-tuning and correction, so that the system gradually enters a new stable regulation state. Finally, the changes in the control signal path, the switching time point of the execution subsystem, and the regulation response process during the switching process are recorded as dynamic switching control results for strategy optimization and system performance evaluation, thereby realizing the adaptive switching and continuous control capability improvement of the execution subsystem under different disturbance levels.

[0030] The process of generating the corresponding pressure regulation control command in S4 is as follows: Based on the desired pressure range output by the target strategy group corresponding to the dynamic switching control result, the target valve opening and pressure regulation increment parameters are calculated. After the dynamic switching control result is determined, the target strategy group outputs the corresponding desired pressure range, and this pressure range is used as the control target input to the valve control process. By establishing a corresponding mapping relationship between pressure and valve opening, the upper and lower limits of the target pressure are converted into the upper and lower boundary values ​​of the valve opening, respectively. At the same time, combined with the current actual valve opening state, the target opening offset is calculated, and the pressure change rate prediction parameter is introduced to estimate the short-term pressure change trend, thereby calculating the pressure regulation increment parameter. The pressure regulation increment parameter is used to characterize the adjustment range of the valve opening per unit time, so that the pressure transitions smoothly from the current state to the target pressure range, avoiding system oscillation caused by step adjustment, and realizing feedforward adjustment of valve opening and rapid approximation of target pressure. By combining the current differential pressure feedback value inside and outside the valve, real-time pressure error correction is performed. After obtaining the target opening degree and pressure regulation increment parameters, differential pressure sensors deployed inside and outside the valve collect the internal and external pressure feedback values ​​in real time. Based on the feedback value, the error deviation between the current actual pressure and the median of the expected pressure range is calculated. The historical pressure regulation error sequence is introduced to perform weighted correction processing on the current error to eliminate the influence of sensor noise and transient disturbances. The specific correction methods include low-pass filtering of the error and abnormal suppression of abrupt errors, thereby obtaining a stable pressure error correction value, enabling the control system to more accurately reflect the true pressure deviation state.

[0031] Based on the corrected pressure error, segmented control calculations are performed, incorporating safety pressure boundary constraints. Control commands are then limited and stability-checked to generate corresponding pressure regulation control commands. The pressure regulation process is divided into three stages: rapid adjustment, slow convergence, and stable holding, based on the error amplitude and rate of change. Different control gain coefficients are used for calculations at each stage. Safety pressure boundary constraints are introduced as hard constraints into the control calculation process. The calculated target opening change and pressure regulation increment parameters are limited to ensure they do not exceed the system's maximum allowable adjustment range. The limited control commands undergo stability checks by judging whether the gradient of the control command within a continuous time window meets the stable convergence condition, thereby eliminating abnormal control quantities that may cause oscillations or overshoot. Finally, pressure regulation control commands that meet safety constraints and dynamic stability requirements are generated to drive the valve actuator to complete the pressure regulation action, thus achieving a control output process with both high reliability and adaptive capability.

[0032] S5: During the process of pressure regulation executed by the regulation execution subsystem according to the pressure regulation control command, the pressure regulation control command is limited and its stability is checked by combining the feedback information of the pressure difference inside and outside the valve and the safety pressure range constraint, thus forming a feedback regulation mechanism for the correction of the regulation control command.

[0033] The process of forming a feedback control mechanism in S5 for correcting control commands is as follows: During the valve's pressure regulation process, based on environmental response characteristic parameters and pressure regulation control commands, internal and external pressure difference feedback data and environmental response characteristic parameter change information are continuously collected. During the valve's pressure regulation process, high-frequency differential pressure sensors, hydrostatic pressure sensors, and structural stress auxiliary sensors are respectively deployed on both sides of the valve inlet and outlet to acquire internal and external pressure difference change data in real time. At the same time, environmental response characteristic parameters such as flow field disturbance intensity, external hydrostatic pressure change, and temperature change rate are collected synchronously on the environmental side. All collected signals are time-aligned through a unified timestamp module, and a sliding time window mechanism is used to continuously segment and buffer the data. The time window length is set to a fixed interval or an adaptive interval according to the operating condition fluctuation characteristics. In the data preprocessing stage, abnormal pulse data is limited and removed, and high-frequency noise is weakened by exponential smoothing, thereby forming a continuous, stable, and time-consistent feedback data stream, providing a reliable basis for deviation calculation. The actual adjustment results are dynamically compared with the target pressure range to calculate the adjustment deviation and convergence trend. The upper and lower limits of the target pressure range are used as reference boundaries and compared point by point with the instantaneous pressure value obtained by sampling. When the current pressure value is outside the target range, the excess deviation relative to the upper or lower boundary is calculated. When the pressure value is inside the target range, the offset from the center of the range is calculated to characterize the stability level. A trend calculation method based on time series difference is introduced. By performing first-order difference operation on continuous sampling points, the pressure change rate is obtained. Combined with the moving average method, the influence of instantaneous fluctuations is weakened, thus forming a trend index characterizing the pressure convergence or divergence state. At the same time, the deviation and trend index are weighted and fused to generate a comprehensive adjustment deviation parameter to reflect the overall adjustment demand and stability of the current system from the target pressure range. Based on the adjustment deviation, the parameters of the control strategy cluster and execution subsystem are updated and adaptively corrected online, forming a feedback control mechanism for adjusting control commands. According to the comprehensive adjustment deviation parameters, the current system operating state is divided into different adjustment level ranges, such as a fast convergence zone, a slow approach zone, and an oscillation suppression zone. Corresponding control strategy groups are preset for different levels. At the execution level, the valve opening adjustment step size, adjustment frequency, and response delay parameters are configured in a graded manner to achieve differentiated control. When the system is in a stage with large deviation, the opening adjustment step size is increased to accelerate the approach to the target range. When the system enters the vicinity of the target range, the adjustment step size is decreased and the adjustment frequency is increased to suppress overshoot. At the same time, based on the adjustment effect data stored in the historical adjustment result recording module, the execution parameters of each strategy group are periodically corrected. For example, the gain parameter is reduced for strategies with frequent overshoot, and the response weight is appropriately increased for strategies with insufficient convergence speed. This forms a closed-loop adaptive feedback correction mechanism to achieve continuous optimization and stable output of valve control commands.

[0034] Example 2: As Figure 2 As shown, the valve control system based on adaptive adjustment of deep-sea environmental pressure includes: Environmental perception module: synchronously collects and couples the information on flow field disturbance, hydrostatic pressure and submersion velocity of the water area where the valve is located, and generates environmental response characteristic parameters; Disturbance classification module: Based on environmental response characteristic parameters, the disturbance level of pressure change behavior is classified, and a cluster of control strategies and corresponding control execution subsystems are constructed to form a hierarchical linkage control structure; Strategy matching module: Determines the current disturbance level based on environmental response characteristic parameters and hierarchical linkage control structure, and selects target strategies from the control strategy cluster to generate subsystem trigger indication information; Execution switching module: When the switching conditions are met, switch to the adjustment execution subsystem corresponding to the target strategy and generate pressure regulation control commands; Feedback correction module: During execution, it combines differential pressure feedback and safety pressure constraints to limit and correct the control commands and verify their stability, thus forming a feedback regulation mechanism.

[0035] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0036] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A valve control method based on adaptive adjustment of deep-sea environmental pressure, characterized in that, Includes the following steps: The flow field disturbance state, external hydrostatic pressure evolution characteristics, and velocity change information during the submersion process of the water area where the valve is located are collected synchronously. The multi-source information is coupled and analyzed in combination with historical operating data to generate environmental response characteristic parameters that characterize the water pressure disturbance characteristics. Based on environmental response characteristic parameters, the pressure change behavior is classified into disturbance levels, a control strategy cluster that is adaptively updated with the historical control response effect is constructed, and an independent control execution subsystem is preset for the control strategy cluster, forming a hierarchical linkage control structure driven by disturbance level and mediated by strategy group. Based on environmental response characteristic parameters and combined with a hierarchical linkage control structure, the disturbance level of the current water area is determined, and a target strategy is selected from the control strategy cluster according to the disturbance level to generate corresponding subsystem trigger indication information. When the disturbance level corresponding to the subsystem trigger indication information meets the preset switching conditions, the subsystem switches to the adjustment execution subsystem corresponding to the target strategy through the control signal, and generates the corresponding pressure adjustment control command without the need to perform pressure trend analysis. During the process of pressure regulation executed by the regulation execution subsystem according to the pressure regulation control command, the pressure regulation control command is limited and its stability is checked by combining the feedback information of the pressure difference inside and outside the valve and the safety pressure range constraint, thus forming a feedback regulation mechanism for the correction of the regulation control command.

2. The valve control method based on adaptive adjustment of deep-sea environmental pressure according to claim 1, characterized in that, The process of generating environmental response characteristic parameters that characterize the properties of water pressure disturbance is as follows: By installing pressure acquisition units, flow velocity acquisition units, and motion state acquisition units outside the valve body and in the surrounding water area, the flow field disturbance, hydrostatic pressure, and submersion speed are acquired synchronously. The acquired data is time-aligned and mapped according to a unified coordinate system; The real-time collected data is matched, calculated and fused with historical operating condition data; Extract pressure fluctuation characteristics, flow velocity changes, and motion state correlation parameters to generate environmental response characteristic parameters.

3. The valve control method based on adaptive adjustment of deep-sea environmental pressure according to claim 2, characterized in that, The process of constructing a cluster of control strategies that adaptively updates with historical adjustment response effects is as follows: Calculate the pressure change amplitude and rate of change based on environmental response characteristic parameters; Input the pressure change amplitude and rate of change into the preset level classification rules to determine the corresponding disturbance level; A set of corresponding adjustment strategies is generated based on the disturbance level, and the set of adjustment strategies is classified to form an initial control strategy cluster; Based on the pressure regulation deviation and response results obtained during the regulation process, the strategy weights and strategy distributions in the initial regulation strategy cluster are updated and adjusted to form an updated regulation strategy cluster.

4. The valve control method based on adaptive adjustment of deep-sea environmental pressure according to claim 3, characterized in that, The process of forming a hierarchical linkage control structure driven by disturbance levels and mediated by strategy groups is as follows: Based on the differences in pressure regulation targets under different disturbance levels, the control strategy clusters are functionally divided into steady-state regulation strategy group, rapid pressure relief strategy group and buffer balance strategy group. Based on the regulation characteristics and response requirements of each strategy group, the corresponding valve execution subsystem is configured respectively; By combining the mapping relationship between disturbance levels and adjustment targets, a corresponding mapping relationship between disturbance levels and each strategy group is established; Furthermore, a binding relationship is established between each strategy group and the corresponding valve execution subsystem, forming a hierarchical linkage control structure driven by disturbance level and mediated by strategy group.

5. The valve control method based on adaptive adjustment of deep-sea environmental pressure according to claim 4, characterized in that, The process for determining the current disturbance level of the water area is as follows: By inputting environmental response characteristic parameters into the disturbance identification process associated with the hierarchical linkage control structure, the pressure change trend score, flow field disturbance intensity score, and velocity coupling effect score are calculated. The disturbance level is initially determined by matching the multidimensional scoring results with the preset level threshold range in the hierarchical linkage control structure. By combining historical strategy group execution feedback data, the disturbance level is probability-corrected and confidence-evaluated to obtain the corrected disturbance level distribution results; A time-sliding window mechanism consistent with the strategy group switching rhythm is introduced to perform time-series smoothing on the corrected perturbation level distribution results and output the final perturbation level.

6. The valve control method based on adaptive adjustment of deep-sea environmental pressure according to claim 5, characterized in that, The process of generating the corresponding subsystem trigger indication information is as follows: Based on the mapping relationship between disturbance levels and strategy groups, the target strategy group is determined from the control strategy cluster; The execution parameters corresponding to the target strategy group are encapsulated into a subsystem trigger instruction package, including the target pressure range, response priority, and execution timing window; By combining system security constraints, the trigger command packet is subjected to consistency verification and redundancy filtering to generate corresponding subsystem trigger indication information.

7. The valve control method based on adaptive adjustment of deep-sea environmental pressure according to claim 6, characterized in that, The process of switching to the adjustment execution subsystem corresponding to the target strategy via control signals is as follows: Upon receiving a subsystem trigger indication, the system performs real-time monitoring and evaluation of the current operating status and load changes of the executing subsystem. Based on the current pressure regulation deviation, the trend of disturbance level changes, and the load status of the execution subsystem, determine whether the switching conditions for the execution subsystem are met. When the switching conditions are met, the process of transferring control between the primary and backup execution subsystems is triggered. The control signal is switched from the current execution subsystem to the execution subsystem corresponding to the target strategy, forming a dynamic switching control result for the execution subsystem.

8. The valve control method based on adaptive adjustment of deep-sea environment pressure according to claim 7, characterized in that, The process of generating the corresponding pressure regulation control command is as follows: Based on the desired pressure range output by the target strategy group corresponding to the dynamic switching control result, calculate the target valve opening and pressure regulation increment parameters. Based on the current pressure difference feedback value inside and outside the valve, real-time pressure error correction is performed; Based on the corrected pressure error, segmented control calculations are performed, and safety pressure boundary constraints are integrated. The control commands are then subjected to amplitude limiting and stability verification to generate corresponding pressure regulation control commands.

9. The valve control method based on adaptive adjustment of deep-sea environmental pressure according to claim 8, characterized in that, The process of forming a feedback control mechanism for adjusting control commands is as follows: During the valve's pressure regulation process, based on environmental response characteristic parameters and pressure regulation control commands, internal and external pressure difference feedback data and environmental response characteristic parameter change information are continuously collected; The actual adjustment results are dynamically compared with the target pressure range to calculate the adjustment deviation and convergence trend. Based on the adjustment deviation, the parameters of the control strategy cluster and the execution subsystem are updated and adaptively corrected online to form a feedback control mechanism for adjusting control commands.

10. A valve control system based on adaptive adjustment of deep-sea environmental pressure, applied to the method described in any one of claims 1-9, characterized in that, include: Environmental perception module: synchronously collects and couples the information on flow field disturbance, hydrostatic pressure and submersion velocity of the water area where the valve is located, and generates environmental response characteristic parameters; Disturbance classification module: Based on environmental response characteristic parameters, the disturbance level of pressure change behavior is classified, and a cluster of control strategies and corresponding control execution subsystems are constructed to form a hierarchical linkage control structure; Strategy matching module: Determines the current disturbance level based on environmental response characteristic parameters and hierarchical linkage control structure, and selects target strategies from the control strategy cluster to generate subsystem trigger indication information; Execution switching module: When the switching conditions are met, switch to the adjustment execution subsystem corresponding to the target strategy and generate pressure regulation control commands; Feedback correction module: During execution, it combines differential pressure feedback and safety pressure constraints to limit and correct the control commands and verify their stability, thus forming a feedback regulation mechanism.

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