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CN-121979340-A - Multi-target intelligent control system and method for hydrodynamic performance of underwater vehicle

CN121979340ACN 121979340 ACN121979340 ACN 121979340ACN-121979340-A

Abstract

The invention belongs to the technical field of hydrodynamics and flow control, and discloses a multi-target intelligent control system and method for hydrodynamic performance of an underwater vehicle, comprising the following steps: the control target is of an axisymmetric structure, the tail of the control target is provided with at least one active blowing jet outlet, and the execution unit is connected with the jet outlet of the control target and is used for adjusting the blowing state of the jet according to a control instruction output by the control logic module. The sensing unit is arranged on the tail surface of the axisymmetric body and used for collecting key parameters reflecting the flow control effect and the energy cost. The control logic module is used for receiving the flow information output by the sensing unit and carrying out real-time or periodic optimization on the control parameters based on a preset optimization algorithm. The optimized control parameters are sent to the execution unit by the control logic module, so that the system forms closed-loop operation. The technical scheme of the invention can realize the cooperative optimization of resistance reduction and blowing energy consumption reduction, and improves the adaptability and the overall energy efficiency of the control system to different working conditions.

Inventors

  • ZHOU YU
  • SONG YUKUAN
  • ZHANG HOUHUI

Assignees

  • 宁波东方理工大学

Dates

Publication Date
20260505
Application Date
20260124

Claims (10)

  1. 1. An underwater vehicle hydrodynamic performance multi-target intelligent control system, comprising: the tail part of the axisymmetric body is provided with a plurality of independently arranged blowing jet outlets, and the blowing jet outlets are used for injecting jet into the tail part bypass area so as to change tail part separation characteristics and pressure distribution; the sensing module is arranged at the tail part of the axisymmetric body and used for collecting flow information of the axisymmetric body in real time, and the flow information comprises a tail surface pressure coefficient and a total blowing momentum coefficient; The control logic module is connected with the sensing module and is used for optimizing control parameters of each blowing jet outlet according to flow information and a preset optimization algorithm, wherein the control parameters comprise a gas supply pressure ratio, a duty ratio, an excitation frequency and a phase difference; The execution module is connected with the control logic module and each blowing jet outlet and is used for adjusting the jet blowing state of each blowing jet outlet according to the optimized control parameters so as to realize real-time regulation and control of the tail flow state of the axisymmetric body.
  2. 2. The underwater vehicle hydrodynamic performance multi-target intelligent control system of claim 1, wherein the blowing jet outlet comprises an air flow inlet, a blowing cavity and a jet outlet which are sequentially arranged.
  3. 3. The underwater vehicle hydrodynamic performance multi-target intelligent control system of claim 2, wherein the sensing module comprises a speed measuring device and a plurality of groups of pressure taps, wherein each pressure tap is arranged on the tail surface of the axisymmetric body for acquiring a tail surface pressure coefficient, and the speed measuring device is arranged at the jet outlet for acquiring a total blowing momentum coefficient.
  4. 4. An underwater vehicle hydrodynamic performance multi-target intelligent control system as claimed in claim 3, wherein said speed measuring device employs a hot wire probe.
  5. 5. The underwater vehicle hydrodynamic performance multi-objective intelligent control system of claim 2, wherein the execution module comprises a gas source in communication with the gas flow inlet and a control valve set disposed on a connecting line between the gas source and the gas flow inlet.
  6. 6. The underwater vehicle hydrodynamic performance multi-target intelligent control system of claim 5, wherein the air source employs an air compressor.
  7. 7. The underwater vehicle hydrodynamic performance multi-target intelligent control system of claim 5, wherein the control valve group comprises an electric proportional valve and a solenoid valve.
  8. 8. An underwater vehicle hydrodynamic performance multi-target intelligent control method applied to the underwater vehicle hydrodynamic performance multi-target intelligent control system as claimed in any one of claims 1 to 7, comprising: Step S1, initializing a control logic module, generating an initial population by taking initial control parameters as individuals, transmitting the initial control parameters corresponding to the individuals in the initial population to an execution unit, and applying the initial control parameters to axisymmetric bodies by the execution unit; S2, acquiring flow information of the axisymmetric body in real time through a sensing module, and feeding back the flow information to a control logic module as a performance evaluation index to improve tail pressure recovery capability and reduce blowing energy consumption as objective functions so as to construct a multi-objective optimization problem; step S3, carrying out repeated iteration update on each body in the initial population based on a non-dominant ranking genetic algorithm, stopping iteration when a preset termination condition is met, and outputting optimized control parameters; And S4, adjusting jet blowing states of all blowing jet outlets according to the optimized control parameters, and realizing real-time regulation and control of the tail flow state of the axisymmetric body.
  9. 9. The method according to claim 8, wherein the control logic module in step S1 generates the initial population within a predetermined control parameter range by using latin hypercube sampling.
  10. 10. The method for intelligent control of hydrodynamic performance of an underwater vehicle according to claim 8, wherein the step S3 specifically comprises: Step S31, performing non-dominant ranking and crowding degree distance calculation on the previous generation population based on performance evaluation indexes corresponding to each body in the previous generation population, and generating a child population through selection, intersection and mutation operation based on calculation results; step S32, applying control parameters corresponding to each body in the child population to the axisymmetric body through an execution unit, and acquiring corresponding performance evaluation indexes by a sensing module; S33, merging the previous generation population and the offspring population to form an intermediate population, carrying out rapid non-dominant sorting on the intermediate population, carrying out elite screening by combining a crowding degree distance criterion, and leading the screened individuals to enter the next generation population; and repeating the steps S31 to S33 for iterative updating, stopping iteration when a preset termination condition is met, outputting the optimized control parameters, and realizing the self-adaptive iterative optimization of the control parameters.

Description

Multi-target intelligent control system and method for hydrodynamic performance of underwater vehicle Technical Field The invention belongs to the technical field of hydrodynamics and flow control, and particularly relates to an underwater vehicle hydrodynamic performance multi-target intelligent control system and method. Background The design of drag reduction of equiaxial symmetry or submarine shape of an aircraft and an underwater vehicle is a key link for improving the hydrodynamic performance and the propulsion efficiency of the aircraft and the underwater vehicle. Currently, drag reduction techniques associated with such profiles can be broadly divided into two broad categories, passive control and active control. The passive control generally improves the flow characteristics by optimizing the shape, arranging a vortex generator or adjusting the surface roughness, and the active control mainly relies on the means of jet blowing, sucking, plasma excitation and the like to directly interfere the near-wall flow so as to inhibit or delay flow separation. In the field of active flow control, tail blow-in techniques have been demonstrated to effectively improve tail flow field structure, thereby significantly improving tail pressure recovery performance. In the prior art, experimental research is carried out on an Ahmed vehicle body model, a single jet outlet and a multi-jet outlet flow distribution scheme optimized based on an ant colony algorithm are compared by the system, and the result shows that the optimized multi-jet distribution strategy can further promote tail pressure recovery and reduce aerodynamic resistance. However, the research object is an automobile outer body with remarkable three-dimensional asymmetric characteristics, and the wake structure of the research object is basically different from that of a typical axisymmetric body, so that the applicability and popularization of related conclusions in axisymmetric body flow control scenes are still limited. There are also studies to try to introduce a genetic algorithm into the active control of the mechanical profile, apply the genetic algorithm to the active control of the D-shaped cylindrical flow field, obtain the optimal control parameters under the maximum drag reduction condition by searching, and verify the feasibility of the genetic algorithm in the aspect of optimizing the flow control parameters. However, the optimization usually only aims at drag reduction rate, and the blowing energy consumption or other control performance indexes are not taken into comprehensive consideration, so that the problem of low control energy efficiency is easily caused in engineering application. To further improve the control efficiency, attempts have been made in the prior art to introduce energy factors into the objective function. For example, in two-dimensional curved ramp flow separation control studies, a learner optimized the distribution of the blowing flow rates of multiple jets using a genetic algorithm and combined the maximum drag reduction rate with the blowing energy consumption linearly in an objective function by a weighting factor, constructed as an index of j=j 1+αJ2, achieving an approximately 30% reduction in energy consumption with substantially equivalent drag reduction effects. However, the method still belongs to weighted single-objective optimization in nature, the result is highly sensitive to the selection of the weight coefficient alpha, the pareto optimal solution set reflecting the trade-off relation between different drag reduction performances and energy consumption cannot be given, and the method still has the defects in the aspects of multi-objective collaborative optimization and scheme selection flexibility. For active control of the tail of the axisymmetric body, researches show that six steady tangential jet outlets are circumferentially arranged at the tail of the model, so that the tail flow separation can be obviously inhibited, and the drag reduction effect of about 24% is realized. However, the method generally adopts a steady open-loop control strategy, the control parameters are set by manual experience, a parameter optimization and self-adaptive adjustment mechanism of the system is lacked, and drag reduction performance and energy utilization efficiency are difficult to be considered under different working conditions. In summary, in the aspect of active control of axisymmetric tail jet blowing, the prior art lacks a multi-objective optimization method capable of simultaneously considering drag reduction effect and energy consumption index and giving the pareto optimal solution set systematically, and lacks a special control structure and parameter design thought for an axisymmetric model, so that further improvement and perfection are needed. Disclosure of Invention The invention aims to provide a multi-target intelligent control system and method for hydrodynamic performance of an underwater vehicl