CN-115859652-B - All-backing-up air cushion ship vector thrust level distribution method based on improved hawk optimization algorithm

CN115859652BCN 115859652 BCN115859652 BCN 115859652BCN-115859652-B

Abstract

The invention belongs to the technical field of ship thrust distribution, and particularly relates to a vector thrust level distribution method of a full-lifting air cushion ship based on an improved hawk optimization algorithm. According to the method, the priority distribution sequence of each propeller is reasonably planned, the hierarchy distribution strategy and the multi-optimization target method are used, the problem of uneven thrust distribution of each propeller of the all-backing air cushion ship is solved to a large extent, the problem of execution efficiency of each propeller is fully considered, the execution efficiency and the service life of the propeller are improved, and the overall fuel consumption of the air cushion ship is reduced; the improved multi-objective gold hawk optimization algorithm provided by the invention can be used for obtaining the Pareto optimal solution by distributing the strategy loss function to the hierarchy in a limited step, and carrying out level differentiation on the multi-objective function, so that the calculation efficiency of the multi-objective gold hawk optimization algorithm is improved.

Inventors

WANG YUANHUI
ZHOU HUA
ZHANG CHI
LIU CHONG
ZHANG XIAOYUE
ZHANG HAOLUN
CHENG JITAO
E Jiyang

Assignees

哈尔滨工程大学

Dates

Publication Date: 20260508
Application Date: 20221214

Claims (4)

1. The full-backing air cushion ship vector thrust level distribution method based on the improved hawk optimization algorithm is characterized by comprising the following steps of: Step 1, determining the layout of a propulsion device of a full-lift hovercraft, establishing a full-lift hovercraft angle mathematical model, and loading parameters of each propeller, wherein the parameters of the propeller comprise the types and the number of the propellers, a variable thrust direction range, a variable thrust size range, a variable thrust direction change rate range and a variable thrust size change rate range; Wherein, the Is the moment of the rudder of the air, In order to provide a rotor torque which is equal to the rotor torque, Is the moment of the bow spray pipe, Respectively is The moment of inertia of the shaft, Respectively the yaw angular speed and the pitch angular speed; step 2, designing virtual control input based on active disturbance rejection control technology ; Wherein, the Environmental interference and total uncertainty of the system observed for the observer; Proportional feedback gain for tracking error; , Is a desired angular velocity; Step 3, designing a hierarchical allocation strategy of a propeller of the hovercraft; Setting the difference between the virtual control input and the actual controller output as a loss function K simulation time series: The propeller constraint of the air cushion ship is rudder angle constraint and thrust vector constraint which are respectively that ; For the actual control output of the hovercraft, Is a virtual control input; a deflection angle range for the rudder; for propeller thrust restraint and bow nozzle is limited by the thrust and deflection angles; Step 1 of hierarchical allocation, namely, as the air rudder rotation efficiency of the air cushion ship is highest, the effect of preferentially allocating the air rudders is better, and the loss function of the allocated air rudders is recorded as : The stage distribution step2 is that on the premise of the stage distribution step1, the rotation efficiency of the propeller and the bow spray pipe is lower, the thrust vector of the propeller and the bow spray pipe is optimized, and the thrust vector is recorded as a loss function : Representing the optimal solution using hierarchy allocation step 1; Step 3, minimizing the thrust of the propeller and the bow spray pipe on the premise of step 2, reducing the energy consumption of the engine and the gas turbine, and designing an energy minimization function as : Representing the optimal solution using hierarchy allocation step 2; The propeller force is the magnitude; The force of the bow spray pipe is; step 4, designing a hierarchy allocation weight coefficient to make a hierarchy allocation strategy more practical with the optimal allocation of the thrusters in actual sailing of the hovercraft due to different execution efficiency of each thruster of the hovercraft at different sailing speeds; Step 5, solving a hierarchical distribution step loss function by using an improved multi-objective gold hawk optimization algorithm; Step 5.1, confirming the objective function of the multi-objective gold eagle algorithm as The weight coefficient of the objective function is The cruise vector in the eagle optimization algorithm is The attack vector is The hunting is the optimal variable ; Initializing the number of eagles and estimating the loss function And Energy minimization function Initializing a eagle memory bank and initializing attack coefficients And cruising coefficient Wherein, the attack coefficient increases with the increase of the iteration times, the cruising coefficient decreases with the increase of the iteration times, and the transition from cruising to attack of the hawk is simulated, and the process of approaching the target hunting object from the initial position is simulated; Step 5.2 for each iteration Updating And Calculating the crowding distance of the existing memory bank members, gradually transferring the eagle from the cruising mode to the attacking mode, and updating And The method of (1) is as follows: Wherein, the As a result of the total number of iterations, For the current iteration of the process, And As the initial coefficient of the coefficient, And Setting the current time position as the final target value Terminating in an optimal variable The attack model of gold hawk is expressed as ; Step 5.3, cruising the hawk to move to a new position, the new position is described as: Wherein, the Is golden eagle At the position of Step length changing in the iteration; calculating a loss function of a new position according to a certain priority by combining a hierarchical allocation strategy 、、 If the new position is a Pareto non-inferior solution relative to the existing library members and the external library is not full, adding the new solution into the library, otherwise, calculating the sparse distance, selecting an outgoing member by using a roulette method with sparse distance weight, replacing the outgoing member by using the new position, and iterating until the algorithm requirement is met.
2. The method for distributing vector thrust levels of the all-backing air cushion ship based on improved hawk optimization algorithm as claimed in claim 1, wherein the all-backing air cushion ship in step 1 is provided with 2 air propellers, 2 synchronous linkage air rudders are arranged behind each propeller, and 1 bow spray pipe is arranged on the front of two sides of the ship and can be used for distributing vector thrust levels of all-backing air cushion ship Full rotation; Wherein, the 、 For the forces of the monolithic rudder in the x and y directions, ; 、 The aerodynamic coefficient is obtained from aerodynamic test data of the vertical rudder; rudder inflow speed brought by the wake of the air propeller; Is the vertical rudder area; Is air density; The distance between the gravity center position of the air rudder in the x, y and z directions; Is the distance between the pressure center and the rudder shaft; Wherein, the 、 Is positioned at the center of gravity of the propeller Shaft and method for producing the same The distance of the axis; Wherein, the A deflection angle for the bow nozzle; 、、 the distance of the bow spray pipe in the x, y and z directions; the moment of inertia of the x, y and z axes respectively.
3. The method for distributing vector thrust levels of the all-backing-up hovercraft based on the improved hawk optimization algorithm as claimed in claim 2, wherein the step 2 is specifically as follows: Writing the angular velocity equation as In the form of a pharmaceutical composition, , The method is characterized by comprising the following steps of (1) performing total model uncertainty and total environmental interference for the transverse tilting, longitudinal tilting and bow turning of the hovercraft; the relationship with the actual control input is noted: Wherein, the ; ; According to the Lagrangian median theorem, the air rudder moment is transformed as follows: Wherein, the For Lagrange expansion point And end point At any point in between, the above equation of angular velocity is combined to obtain: Combining an angular velocity equation and a propeller and bow spray pipe moment equation, extracting a moment arm to obtain: Wherein, the ; A second-order extended state observer is designed by using a bandwidth method, nonlinear uncertainty and total environmental interference of an angular velocity control system are compensated, For the bandwidth of the system, Respectively is Directional bandwidth control targeting angular velocity tracking time-varying reference signals : Wherein, the , Compensating uncertainty of a angular speed control system and system environment interference, and designing to obtain a virtual control rate by using error proportion feedback control: the gain is proportional feedback for tracking error.
4. The method for distributing vector thrust levels of the all-backing-up hovercraft based on the improved hawk optimization algorithm as claimed in claim 1, wherein the step 4 is specifically: the weight coefficient of the hierarchy allocation step 1 is set as follows: Wherein, the Is on the whole-lift hovercraft Transverse speed and longitudinal speed at time; The weight coefficient of the hierarchy allocation step2 is set as follows: The weight coefficient of the hierarchy allocation step 3 is always 1.

Description

All-backing-up air cushion ship vector thrust level distribution method based on improved hawk optimization algorithm Technical Field The invention belongs to the technical field of ship thrust distribution, and particularly relates to a vector thrust level distribution method of a full-lifting air cushion ship based on an improved hawk optimization algorithm. Background The all-lift hovercraft is an amphibious special ship which is suspended on the water surface, land, marsh and other complex environments through a lift system, and is widely applied to naval equipment, civil rescue and the like. The thrust distribution technology is used as an important guarantee for safe sailing of the hovercraft, and mainly aims at matching an air rudder and a propeller in a coordinated manner in the prior study, but has defects or incomplete parts. Firstly, rudder propeller coordination does not consider the use of a bow spray pipe of another propeller of the air-cushion ship, when the air-cushion ship sails or rotates at a low speed, lateral rotation moment can be generated by utilizing the flexibility of the bow spray pipe, the rotation efficiency of the air-cushion ship is improved, secondly, thrust distribution fails to consider the execution efficiency of the propeller of the air-cushion ship, and the same optimization sequence is used for different actuators, however, the fact is that when the air-cushion ship sails at a high speed, the rotation efficiency of an air rudder is very high, and when the air-cushion ship sails at a low custom, more coordination matching of the propeller and the bow spray pipe is needed. Disclosure of Invention The invention aims to solve the problem that the conventional thrust distribution problem only relates to the control of the transverse inclination and longitudinal inclination angle speed of a hovercraft and omits the condition of low head plough-in which is easy to occur in a full-lift hovercraft, and provides a full-lift hovercraft vector thrust level distribution method based on an improved gold hawk optimization algorithm. A vector thrust level distribution method of a full-backing air cushion ship based on an improved hawk optimization algorithm comprises the following steps: Step 1, determining the layout of a propulsion device of a full-lift hovercraft, establishing a full-lift hovercraft angle mathematical model, and loading parameters of each propeller, wherein the parameters of the propeller comprise the types and the number of the propellers, a variable thrust direction range, a variable thrust size range, a variable thrust direction change rate range and a variable thrust size change rate range; Wherein, the Is the moment of the rudder of the air,In order to provide a rotor torque which is equal to the rotor torque,Is the moment of the bow spray pipe,The rotational inertia of the x, y and z axes are respectively,Respectively the yaw angular speed and the pitch angular speed; step 2, designing virtual control input based on active disturbance rejection control technology Wherein, the Environmental interference and total uncertainty of the system observed for the observer; k p,kq,kr is the tracking error proportional feedback gain; ψis the desired angular velocity; Step 3, designing a hierarchical allocation strategy of a propeller of the hovercraft; Setting the difference between the virtual control input and the actual controller output as a loss function Γ, k emulating a time sequence: The propeller constraint of the air cushion ship is rudder angle constraint and thrust vector constraint, which are omega A,k∈ΘA,k,ΩF,k∈ΘF,k;HuXT respectively for the actual control output of the air cushion ship, Is a virtual control input; The hierarchical allocation step 1 is that the air rudder is preferentially allocated because the air rudder turning efficiency of the air cushion ship is highest, the air rudder allocation effect is better, and the loss function of the air rudder allocation is marked as gamma 1,k: In the stage distribution step 2, on the premise of the stage distribution step 1, the rotation efficiency of the propeller and the bow spray pipe is lower, the thrust vector of the propeller and the bow spray pipe is optimized, and the thrust vector is recorded as a loss function as gamma 2,k: representing the optimal solution using hierarchy allocation step 1; and 3, minimizing the thrust of the propeller and the bow spray pipe on the premise of the step 2 of the hierarchy allocation, reducing the energy consumption of the engine and the gas turbine, and designing an energy minimization function to be E k: Representing the optimal solution using hierarchy allocation step 2; step 4, designing a hierarchy allocation weight coefficient to make a hierarchy allocation strategy more practical with the optimal allocation of the thrusters in actual sailing of the hovercraft due to different execution efficiency of each thruster of the hovercraft at different sailing speeds;