A ship micro-grid virtual direct-current generator model-free adaptive control method

Abstract

The application discloses a kind of ship microgrid virtual direct-current generator model-free adaptive control method, mainly for improving the stability of ship microgrid direct-current bus voltage, including the following steps: collecting ship microgrid direct-current bus voltage, establishing ship virtual direct-current generator model and discretization processing to armature equation;Establish only with the tight format dynamic linearization data model related to input rotational inertia and output direct-current bus voltage and calculate rotational inertia pseudo partial derivative estimation rate;Design rotational inertia model-free adaptive control algorithm, realize the adaptive regulation of virtual direct-current generator rotational inertia;By controlling ship microgrid Buck / Boost converter, simulate direct-current generator external characteristic, stabilize direct-current bus voltage.The application effectively suppresses the fluctuation of ship microgrid direct-current bus voltage while optimizing the dynamic response speed of ship microgrid direct-current bus voltage regulation.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of micro-grid control, and particularly relates to a virtual direct-current generator model-free adaptive control method for a ship micro-grid. BACKGROUND

[0002] Unlike land micro-grids, due to the harsh operating environment of ships, complex control mechanisms, and a variety of power types, the direct-current power electronic converter of a ship micro-grid is prone to cause fluctuations and oscillations of the bus voltage of the ship micro-grid, and even cause instability of the ship power system when the unknown sea state load is frequently switched due to the lack of inertia and damping. Therefore, improving the inertia of the direct-current power electronic converter of the ship micro-grid through control technology and reducing the fluctuations of the bus voltage have become the focus of research by scholars in the relevant field.

[0003] To solve the fluctuations of the direct-current bus voltage caused by the random fluctuations of new energy generation and loads, Huang Di and Fan Shaosheng of Changsha University of Science and Technology proposed a virtual direct-current generator control technology, which applies the mechanical equation and armature equation of a direct-current generator to the control algorithm to simulate the inertia characteristics and damping characteristics of the direct-current generator, so that the direct-current bus voltage of the micro-grid can remain stable when new energy generation fluctuates and the load suddenly changes. However, this method uses a fixed rotational inertia and does not achieve flexible control of parameters, resulting in poor voltage regulation dynamic characteristics and making it difficult to apply to ship micro-grids with frequent load switching. Zhang Qinjin of Dalian Maritime University proposed a virtual direct-current generator control method for direct-current micro-sources based on parameter adaptation, which introduces a PI element into the design of the rotational inertia parameter and gives an adaptive regulation equation for the rotational inertia to achieve adaptive regulation of the rotational inertia of the virtual direct-current generator and improve the dynamic response speed of the voltage regulation of the micro-grid system. However, due to the introduction of error integral feedback in PID control, the voltage control process of the micro-grid system is prone to oscillation, which cannot meet the demand of sensitive loads of the ship micro-grid for stable voltage of the direct-current bus. Model-free adaptive control is a data-driven control method that processes the input and output data of the controlled system using a new dynamic linearization method, estimates the pseudo partial derivative or pseudo gradient of the system online, and then designs a weighted one-step forward controller. Model-free controller design only needs the input and output data of the controlled system and does not contain any mathematical model information of the controlled system, which is very suitable for application in the field of micro-grid control with unknown model structure.

[0004] Based on the above analysis, the application provides a ship micro-grid virtual direct-current generator model-free adaptive control method, which only uses input and output data of a ship direct-current micro-grid virtual direct-current generator control system, improves the virtual direct-current generator by a model-free adaptive control algorithm to realize adaptive adjustment of the moment of inertia, and further improves voltage fluctuation caused by load switching under complex sea conditions, and has the advantages of fast dynamic response speed of voltage regulation, and improves the stability of the ship direct-current micro-grid. SUMMARY

[0005] Therefore, the application aims to provide a ship micro-grid virtual direct-current generator model-free adaptive control method, which uses model-free adaptive control to improve virtual direct-current generator control, designs an adaptive adjustment control algorithm of the moment of inertia, dynamically adjusts the moment of inertia in virtual direct-current generator control, and stabilizes the direct-current bus voltage by controlling the ship micro-grid Buck / Boost converter to simulate the external characteristic of the direct-current generator. The dynamic response speed of the direct-current bus voltage regulation of the ship micro-grid is optimized, the voltage fluctuation is limited within a safe range, and the direct-current bus voltage fluctuation problem caused by load switching of the ship micro-grid under complex sea conditions is improved.

[0006] In order to achieve the above application purpose, the application adopts the following technical solutions:

[0007] S1: collecting the direct-current bus voltage of the ship micro-grid, establishing a ship virtual direct-current generator model and performing discretization processing on the armature equation;

[0008] S2: establishing a compact format dynamic linearization data model only related to the input moment of inertia and the output direct-current bus voltage, and calculating the moment of inertia pseudo-derivative estimation rate;

[0009] S3: designing a model-free adaptive control algorithm of the moment of inertia to realize adaptive adjustment of the moment of inertia of the virtual direct-current generator;

[0010] S4: stabilizing the direct-current bus voltage by controlling the ship micro-grid Buck / Boost converter to simulate the external characteristic of the direct-current generator;

[0011] Further, in step S1, the collection of the direct-current bus voltage of the ship micro-grid, the establishment of the ship virtual direct-current generator model and the discretization processing of the armature equation specifically include: simulating the output external characteristic of the direct-current generator by establishing the virtual direct-current generator model.

[0012] (1) The mechanical equation of the virtual direct-current generator is:

[0013]

[0014] wherein,

[0015] ωe = ωp, ω represents actual mechanical angular velocity; ω n represents rated electric angular velocity; J is moment of inertia; D represents damping torque; T m is mechanical torque; T e is electromagnetic torque; ω e represents actual electric angular velocity; p is the number of generator pole pairs; electromagnetic power P e = EI a ; E is armature electromotive force; I a is armature current;

[0016] The armature equation of the virtual DC generator is:

[0017]

[0018] wherein,

[0019] R a is armature resistance; C T is torque coefficient; Φ is magnetic flux; U is ship micro-grid DC bus voltage;

[0020] (2) Discretize the armature equation in combination with the mechanical equation of the virtual DC generator:

[0021]

[0022] wherein,

[0023] J(t) represents the moment of inertia at time t; U(t) represents the DC bus voltage at time t; U(t+1) represents the DC bus voltage at time t+1;

[0024] Further, the discretized armature equation of step (2) satisfies:

[0025] The partial derivative of the equation with respect to J(t) exists and is continuous;

[0026] The equation satisfies the generalized Lipschitz condition, that is, given any U(t1)≠U(t2) (t1≠t2 and t1, t2≥0), |J(t1+1)-J(t2+1)|≤m|U(t1)-U(t2)| can be obtained, where m is a normal number;

[0027] Further, in step S2, the establishment of the compact format dynamic linearization data model only related to the input moment of inertia and the output DC bus voltage and the calculation of the moment of inertia pseudo partial derivative estimation rate specifically include:

[0028] (1) By the compact format dynamic linearization method, a compact format dynamic linearization data model only related to the input moment of inertia and the output DC bus voltage is established:

[0029] U(t+1) = U(t) + ξ(t)ΔJ(t);

[0030] wherein,

[0031] J(t-1) represents the moment of inertia at t-1 time; ΔJ(t) = J(t)-J(t-1); ξ(t) represents the pseudo partial derivative of the system;

[0032] Further, step (1) specifically comprises the following steps:

[0033] The discrete-time nonlinear system is established as follows:

[0034] U(t+1) = f(U(t),…,U(t-n U ),J(t),…,J(t-n J ));

[0035] wherein, U(t) represents the DC bus voltage of the ship micro-grid at t time, J(t) represents the moment of inertia at t time, and U(t) and J(t) represent the input and output of the system at t time respectively; n U and n J are two unknown parameters; f(…) is an unknown nonlinear function;

[0036] The traditional model-free adaptive algorithm is used to analyze the system, considering that the next time ship DC micro-grid voltage variation of the system is related to the variation of the moment of inertia at the previous time, and the following is obtained:

[0037] f(…) exists continuous partial derivative for the system input variable J(t);

[0038] For the nonlinear system satisfying the above conditions, when ΔJ(t)≠0, there is a time-varying parameter vector ξ(t) that makes the system transform into the following dynamic linearization data model:

[0039] ΔU(t+1) = ξ(t)ΔJ(t);

[0040] (2) Calculate the moment of inertia pseudo partial derivative estimation rate under model-free adaptive control:

[0041]

[0042] is the estimated value of ξ(t); is the estimated value of ξ(t-1); λ∈(0,1] is a step factor, which makes the control algorithm more flexible; ρ>0 is a weight factor;

[0043] Further, step (2) specifically comprises the following steps:

[0044] (21) Establish a criterion function

[0045] (22) The extreme value of ξ(t) in the criterion function is found, and the estimation algorithm of pseudo partial derivative is:

[0046]

[0047] Further, in step S3, the design of the moment of inertia model-free adaptive control algorithm, the adaptive adjustment of the virtual DC generator moment of inertia is specifically as follows:

[0048] (1) The derivative of the tight format dynamic linearization data model U(t+1) = U(t) + ξ(t)ΔJ(t) with respect to J(t) is taken and set to 0, and the model-free adaptive control control rate is obtained:

[0049]

[0050] Wherein, μ ∈ (0, 1] is the step factor; η > 0 is the weight factor; U r (t+1) is the expected ship micro-grid DC bus voltage;

[0051] (2) According to the maximum power P max The design principle of the moment of inertia J is obtained:

[0052]

[0053] Assuming that there is a constant b, when the ship DC micro-grid is connected to a small load, the influence on the ship DC micro-grid voltage ΔU < b, select a smaller J0; when the ship DC micro-grid is connected to a large load ΔU > b, dU / dt < 0, the model-free adaptive control algorithm is used to select the appropriate moment of inertia J; when the load is removed ΔU > b, dU / dt > 0, in order to prevent the voltage fluctuation caused by dU / dt too large, select a larger moment of inertia J = 50;

[0054] The design of the moment of inertia model-free adaptive control algorithm is as follows:

[0055]

[0056] The model-free adaptive controller uses the output DC bus voltage from the ship virtual DC generator and the expected ship micro-grid DC bus voltage, and its output J(t) tracks the load adjustment demand in real time. The adaptive adjustment of the moment of inertia J is achieved by the model-free adaptive control algorithm design of the virtual DC generator control, so as to make up for the deficiency of the fixed moment of inertia of the virtual DC generator, and improve the response speed and stability of the ship DC micro-grid system voltage regulation.

[0057] Compared with the prior art, the beneficial effects of the present application are that: the control method adopted by the present application improves the control of the virtual direct current generator of the ship through model-free adaptive control, designs adaptive adjustment of the moment of inertia parameter, dynamically adjusts the moment of inertia of the virtual direct current generator of the ship, reduces the voltage fluctuation of the direct current micro-grid of the ship caused by frequent load switching under severe sea conditions, optimizes the response speed of the bus voltage regulation of the direct current micro-grid of the ship, and meets the requirements of voltage stability of the ship micro-grid operation. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 is the principle diagram of the model-free adaptive control method of the virtual direct current generator;

[0059] Figure 2 is the flow chart of an embodiment of the model-free adaptive control method of the virtual direct current generator of the ship micro-grid proposed by the present application;

[0060] Figure 3 is the direct current bus voltage curve of the model-free adaptive control method of the virtual direct current generator of the ship micro-grid proposed by the present application under load power mutation;

[0061] Figure 4 is the dynamic change curve of the moment of inertia of the model-free adaptive control method of the virtual direct current generator of the ship micro-grid proposed by the present application under load power mutation; DETAILED DESCRIPTION

[0062] For the purpose of more clearly illustrating the embodiments of the present application, the present application will be described below in combination with the drawings.

[0063] The present application considers the problems of the voltage fluctuation of the direct current bus of the ship caused by the frequent load switching of the ship micro-grid under complex sea conditions and the slow response speed of the voltage regulation of the traditional virtual direct current generator with fixed moment of inertia, and proposes a model-free adaptive control method of the virtual direct current generator of the ship micro-grid by combining the micro-grid direct current converter control mode of the virtual direct current generator. Next, the model-free adaptive control method of the virtual direct current generator of the ship micro-grid will be described in detail.

[0064] Please refer to Figures 1-4 For the model-free adaptive control method of the virtual direct current generator of the ship micro-grid, the method improves the control of the virtual direct current generator of the ship through model-free adaptive control, designs adaptive adjustment of the moment of inertia parameter, dynamically adjusts the moment of inertia of the virtual direct current generator of the ship, reduces the voltage fluctuation of the direct current micro-grid of the ship caused by frequent load switching under severe sea conditions, and optimizes the response speed of the bus voltage regulation of the direct current micro-grid of the ship.

[0065] Figure 2is a flow chart of a ship micro-grid virtual direct-current generator model-free adaptive control method, and specifically comprises the following steps:

[0066] Step one: collect the ship micro-grid direct-current bus voltage, establish a ship virtual direct-current generator model, and perform discretization processing on the armature equation.

[0067] (1) Virtual direct-current generator control

[0068] Figure 1 is a control block diagram of the virtual direct-current generator model-free adaptive control method. In the figure, U ref represents a bus voltage reference value; I ref represents a converter output current reference value; U1 represents a virtual direct-current generator output voltage; U2 represents a converter output voltage; I1 represents a virtual direct-current generator output current; I2 represents a converter output current; according to the power balance principle, U ref / U1 is used to convert I ref into an input current reference value, and finally the required control signal is obtained through the PI controller of the current loop and PWM modulation.

[0069] The virtual direct-current generator control simulates the external characteristic of the direct-current motor to provide additional inertia and damping support for the system, and stabilizes the direct-current bus voltage by controlling the micro-grid Buck / Boost converter to simulate the external characteristic of the direct-current motor. Therefore, through the model of the virtual direct-current generator, the mechanical equation of the virtual direct-current generator can be obtained as shown in the following formula:

[0070]

[0071] wherein ω e = ωp, ω represents an actual mechanical angular velocity; ω n represents a rated electrical angular velocity; ω n = ω0p, ω0 is a rated mechanical angular velocity; J is a rotational inertia; D represents a damping torque; T m is a mechanical torque; T e is an electromagnetic torque; ω e represents an actual electrical angular velocity; p is a number of generator pole pairs; electromagnetic power P e = EI a ; E is an armature electromotive force; I a is an armature current;

[0072] The armature equation of the virtual direct-current generator is:

[0073]

[0074] wherein R a is an armature resistance; C Tis the torque coefficient; Φ is the magnetic flux; and U is the DC bus voltage of the ship microgrid;

[0075] (2) The armature equation can be discretized by combining the mechanical equation of the virtual DC generator as follows:

[0076]

[0077] wherein,

[0078] J(t) represents the moment of inertia at time t; U(t) represents the DC bus voltage at time t; and U(t+1) represents the DC bus voltage at time t+1;

[0079] In order to improve the accuracy of the discretized equation of the armature of the virtual DC generator, the discretized equation (3) satisfies the following assumptions:

[0080] Assumption 1: the partial derivative of the equation with respect to J(t) exists and is continuous;

[0081] Assumption 2: the equation satisfies the generalized Lipschitz condition, that is, given any U(t1)≠U(t2) (t1≠t2 and t1, t2≥0), |J(t1+1)-J(t2+1)|≤m|E(t1)-E(t2)| can be obtained, wherein m is a normal number;

[0082] For the virtual moment of inertia in the control of the virtual DC generator, the variable is continuously differentiable, so assumption 1 is established. In addition, the change of the limited moment of inertia will not cause the violent fluctuation of the DC bus voltage of the ship microgrid, so assumption 2 is established.

[0083] Step two: establish a compact format dynamic linearization data model related only to the input moment of inertia and the output DC bus voltage and calculate the pseudo partial derivative estimation rate of the moment of inertia.

[0084] (1) A compact format dynamic linearization data model related only to the input moment of inertia and the output DC bus voltage is established by the compact format dynamic linearization method as follows:

[0085] The discrete-time nonlinear system is established as follows:

[0086] U(t+1)=f(U(t),…,U(t-n U ),J(t),…,J(t-n J )) (4)

[0087] wherein U(t) represents the DC bus voltage of the ship microgrid at time t, J(t) represents the moment of inertia at time t, and U(t) and J(t) represent the input and output of the system at time t, respectively; n U and n Jare two unknown parameters; f(…) is an unknown nonlinear function;

[0088] Using the traditional model-free adaptive algorithm to analyze the system, considering the next time of the system ship DC micro-grid voltage variation and the previous time of the moment of inertia of the variation, get:

[0089] f(…) exists for the continuous partial derivative of the system input variable J(t);

[0090] For the nonlinear system satisfying the above conditions, when ΔJ(t)≠0, there is always a time-varying parameter vector ξ(t) that makes the system transform into the following dynamic linearization data model:

[0091] ΔU(t+1)=ξ(t)ΔJ(t) (5)

[0092] (2) Calculate the inertia pseudo partial derivative estimation rate under model-free adaptive control:

[0093] Establish the input criterion function:

[0094]

[0095] The extreme value of ξ(t) in the criterion function is obtained, and the pseudo partial derivative estimation algorithm is:

[0096]

[0097] Step three: design the inertia model-free adaptive control algorithm to realize the adaptive adjustment of the virtual DC generator inertia:

[0098] (1) Derive the tight format dynamic linearization data model U(t+1)=U(t)+ξ(t)ΔJ(t) with respect to J(t) and set the equation to 0, get the model-free adaptive control control rate:

[0099]

[0100] Where, μ∈(0, 1] is the step factor; η>0 is the weight factor; U r (t+1) is the expected ship micro-grid DC bus voltage;

[0101] (2) According to the maximum power P max Get the design principle of the moment of inertia J:

[0102]

[0103] Assuming that there is a constant b, when the ship direct current micro grid accesses a small load, the voltage influence of the ship direct current micro grid is ΔU < b, a smaller J0 is selected; when the ship direct current micro grid accesses a large load ΔU > b, dU / dt < 0, the model-free adaptive control algorithm is used to select the appropriate moment of inertia J; when the load is removed ΔU > b, dU / dt > 0, in order to prevent the voltage fluctuation caused by too large dU / dt, a larger moment of inertia J = 50 is selected;

[0104] The model-free adaptive control algorithm of the moment of inertia is designed as follows:

[0105]

[0106] Therefore, by controlling the ship micro grid Buck / Boost converter to simulate the external characteristic of the direct current generator, the stability of the ship micro grid direct current bus voltage under complex sea conditions is realized by adjusting the moment of inertia.

[0107] Therefore, the model-free adaptive control method of the virtual direct current generator of the ship micro grid of the embodiment considers the ship direct current bus voltage fluctuation caused by the frequent switching of the ship micro grid load under complex sea conditions and the slow response speed problem of the traditional virtual direct current generator using fixed moment of inertia voltage regulation, improves the ship virtual direct current generator control through model-free adaptive control, designs adaptive adjustment of the moment of inertia parameter, dynamically adjusts the moment of inertia of the ship direct current virtual direct current generator, reduces the ship direct current micro grid voltage fluctuation caused by the frequent switching of the load under severe sea conditions, and optimizes the response speed of the ship direct current micro grid bus voltage regulation.

[0108] The control system of the embodiment is simulated and analyzed as follows.

[0109] The ship micro grid direct current bus reference of the Zhongyunteng flying roll loading wheel micro grid voltage is set to 1250V, the model-free adaptive control system of the ship micro grid virtual direct current generator is built by using MATLAB / Simulink and is analyzed, the distributed energy direct current converter parameter setting of the virtual direct current generator algorithm is as follows: the output side capacitor of the photovoltaic converter is 705μF; the input side inductance of the photovoltaic converter is 2.4Mh; the switching frequency is 50kHz; the damping coefficient D p 10 is taken. The total simulation duration is set to 18s, and when the ship micro grid is put into 8kW of direct current load at 11s. Figure 3 The model-free adaptive control method of the virtual direct current generator of the ship micro grid proposed by the embodiment is a direct current bus voltage curve under load power mutation, from Figure 3It can be seen that when the load switching occurs, the output voltage fluctuation range of the distributed energy DC converter using the virtual DC generator algorithm is only 35V, effectively inhibiting the DC bus voltage fluctuation, and the voltage regulation is realized in 0.4s, and the micro-grid DC bus voltage is stabilized at 1250V.

[0110] Figure 4 The application provides a virtual DC generator model-free adaptive control method for a ship micro-grid. Figure 4 It can be seen that the virtual DC generator model-free adaptive control method for the ship micro-grid can realize adaptive adjustment of the moment of inertia according to voltage fluctuation under load power mutation, and optimizes the voltage regulation speed of the virtual DC motor control method.

[0111] The application provides a virtual DC generator model-free adaptive control method for a ship micro-grid.

[0112] For those skilled in the art, corresponding changes and modifications, beautification, combination can be made according to the technical solutions and concepts described above, and all the changes, modifications, beautification and combination should belong to the protection scope of the application claims.

Claims

1. A ship micro-grid virtual DC generator model-free adaptive control method, characterized in that: The method comprises the following steps: S1: Collecting the DC bus voltage of the ship micro-grid, establishing a virtual DC generator model and discretizing the armature equation, specifically comprising: S11: Simulating the output external characteristic of the DC generator by establishing a virtual DC generator model: The mechanical equation of the virtual DC generator is: where ω e = ωp represents the actual electrical angular velocity; ω represents the actual mechanical angular velocity; ω n = ωr represents the rated electrical angular velocity; J is the moment of inertia; D represents the damping torque; T m is the mechanical torque; T e is the electromagnetic torque; p is the number of generator pole pairs; P e = EI a is the electromagnetic power; E is the armature electromotive force; I a is the armature current; The armature equation of the virtual DC generator is: wherein R a is the armature resistance; C T is the torque coefficient; Φ is the magnetic flux; U is the ship microgrid DC bus voltage; S12: Discretizing the armature equation in combination with the mechanical equation of the virtual DC generator to obtain a discretized armature equation: Wherein, J(t) represents the moment of inertia at time t; U(t) represents the DC bus voltage at time t; U(t+1) represents the DC bus voltage at time t+1; S2: Establishing a compact format dynamic linearization data model only related to the input moment of inertia and the output DC bus voltage and calculating the moment of inertia pseudo-derivative estimation rate, specifically comprising: S21: Establishing a compact format dynamic linearization data model only related to the input moment of inertia and the output DC bus voltage by a compact format dynamic linearization method: U(t+1) = U(t) + ξ(t)ΔJ(t); Wherein, J(t-1) represents the moment of inertia at time t-1; ΔJ(t) = J(t)-J(t-1); ξ(t) represents the pseudo-derivative of the system; S22: Calculating the moment of inertia pseudo-derivative estimation rate under model-free adaptive control: wherein is an estimate of ξ(t); is an estimate of ξ(t-1); λ ∈ (0, 1] is a step size factor that makes the control algorithm more flexible; and ρ > 0 is a weight factor. S3: Designing a moment of inertia model-free adaptive control algorithm to realize adaptive adjustment of the moment of inertia of the virtual DC generator; S4: Stabilizing the DC bus voltage by controlling the ship micro-grid Buck / Boost converter to simulate the external characteristic of the DC generator.

2. The method of claim 1, wherein: In step S3, the design of the moment of inertia model-free adaptive control algorithm to realize adaptive adjustment of the moment of inertia of the virtual DC generator specifically comprises: S21: Deriving the compact format dynamic linearization data model U(t+1) = U(t) + ξ(t)ΔJ(t) with respect to J(t) and setting the equation to 0 to obtain the model-free adaptive control rate as: where μ ∈ (0, 1] is a step size factor; η > 0 is a weight factor; U r (t+1) is the desired ship microgrid DC bus voltage; S22: The maximum power P output by the ship micro-grid DC converter is determined according to the ship micro-grid DC converter max The design principle of the moment of inertia J is obtained: Assuming that there is a constant b, when the ship DC micro-grid accesses a small load, the influence on the ship DC micro-grid voltage ΔU < b, select a smaller J0; when the ship DC micro-grid accesses a large load ΔU > b, dU / dt < 0, use the model-free adaptive control algorithm to select a suitable moment of inertia J; when the load is removed ΔU > b, dU / dt > 0, in order to prevent voltage fluctuation caused by too large dU / dt, select a larger moment of inertia J = 50; The design of the moment of inertia model-free adaptive control algorithm is as follows:

3. The method of claim 1, wherein: The discretized armature equation of step S12 satisfies: The partial derivative of the equation with respect to J(t) exists and is continuous; The equation satisfies the generalized Lipschitz condition, that is, given any U(t1) ≠ U(t2) (t1 ≠ t2 and t1, t2 ≥ 0), |J(t1+1)-J(t2+1)| ≤ m|U(t1)-U(t2)| can be obtained, where m is a normal number.

4. The method of claim 1, wherein: Step S21 specifically comprises the following steps: A discrete-time nonlinear system is established as follows: U(t+1) = f(U(t),..., U(t-n U ), J(t),..., J(t-n J )) ; Wherein, U(t) represents the DC micro-grid voltage of the ship at time t, J(t) represents the moment of inertia at time t, and and represent the input and output of the system at time t, respectively; n U and n J are two unknown parameters; f(L) is an unknown nonlinear function; The traditional model-free adaptive algorithm is used to analyze the system. The next time variation of the ship DC micro-grid voltage is related to the previous time variation of the moment of inertia. The following equation is obtained: f(L) has a continuous partial derivative with respect to the system input variable J(t); For a nonlinear system satisfying the above conditions, when ΔJ(t)≠0, there is a time-varying parameter vector ξ(t) that can transform the system into the following dynamic linearization data model: ΔU(t+1)=ξ(t)ΔJ(t).

5. The method of claim 2, wherein: Step S22 specifically includes the following steps: A criterion function is established: The extreme value of ξ(t) in the criterion function is found, and the estimation algorithm of the pseudo partial derivative is obtained as follows:

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