A fault compensation method for a single-suspension module of a maglev train based on multiple models

Abstract

The application provides a fault compensation method for a single-suspension module of a maglev train based on multiple models, and comprises the following steps: establishing a state space equation of a single-suspension module system balance point based on electromagnet parameters of the maglev train; establishing a fault system model according to the state space equation and a fault mode; designing a controller set corresponding to the fault mode based on an actuator driving redundancy condition and a backstepping method; performing stable filtering and reconstruction processing on the fault system model to obtain a reconstruction error; selecting a target controller from the controller set according to a control switching mechanism of a value function established according to the reconstruction error; and controlling the single-suspension module system to keep stable operation in the fault mode through a control signal generated by the target controller. The application can ensure stable suspension of the suspension system when the fault signal is uncertain, and improves the stability of the maglev train.

Description

Technical Field

[0001] This invention relates to the field of magnetic levitation train technology, and in particular to a fault compensation method for a single suspension module of a magnetic levitation train based on a multi-model approach. Background Technology

[0002] Maglev trains are a modern, high-tech rail transit system that uses electromagnetic force to achieve contactless levitation and guidance between the train and the track, and then utilizes the electromagnetic force generated by a linear motor to propel the train. During operation, a specific levitation gap must be maintained between the electromagnets and the track. In the event of a power outage or actuator failure, the levitation electromagnets cannot generate levitation force, disrupting the vertical balance and making the vehicle prone to instability. To meet the requirements of normal commercial operation and widespread adoption, one of the key research areas for maglev trains is reliability design, ensuring sufficient robustness and stability to minimize the failure rate. Furthermore, in the event of a failure, it must possess rapid maintenance capabilities to quickly restore the train to normal operation, thereby minimizing losses caused by the malfunction.

[0003] In recent years, domestic scholars have proposed a series of methods for diagnosing faults in suspension systems and designed specialized controllers for specific faults. However, most fault-tolerant control methods in existing technologies assume that the fault signal is known and design the controller based on the known fault signal, without considering the situation where the fault information is uncertain. When multiple faults occur or the fault information is unknown, the suspension gap of the train cannot be adjusted in a timely and accurate manner, so the suspension system cannot guarantee stable suspension when the fault signal is uncertain, resulting in poor stability of maglev trains. Summary of the Invention

[0004] In view of this, the present invention provides a fault compensation method for a single suspension module of a maglev train based on a multi-model approach to solve the above problems.

[0005] According to a first aspect of the present invention, a fault compensation method for a single suspension module of a maglev train based on a multi-model approach is provided, comprising: establishing a state-space equation for the equilibrium point of the single suspension module system based on the electromagnet parameters of the maglev train; establishing a fault system model based on the state-space equation and fault modes; designing a set of controllers corresponding to the fault modes based on actuator drive redundancy conditions and backstepping method; performing stability filtering and reconstruction processing on the fault system model to obtain reconstruction error; selecting a target controller from the set of controllers based on a control switching mechanism using a value function established by the reconstruction error; and controlling the single suspension module system to maintain stable operation under fault modes through control signals generated by the target controller.

[0006] In another implementation of the present invention, the state-space equation of the equilibrium point of the single suspension module system is established based on the electromagnet parameters of the maglev train, including: establishing a dynamic model of the single suspension module system based on the electromagnet parameters of the maglev train; and linearizing the dynamic model near the equilibrium point of the single suspension module system to obtain the state-space equation.

[0007] In another implementation of the present invention, a fault compensation method for a single suspension module of a maglev train based on multiple models further includes: combining fault modes to generate a fault set; and determining actuator drive redundancy conditions by combining the fault set and the operating status of the single suspension module system under the fault modes.

[0008] In another implementation of the present invention, the actuator drive redundancy condition is:

[0009] rank(Bσ)=2

[0010] Where σ is the fault mode matrix, σ=diag{σ1,σ2,σ3,σ4}, and B is the characteristic matrix of the single-module suspension system.

[0011] In another implementation of the present invention, the controller set is represented as:

[0012]

[0013] Where k1 and k2 are user-defined parameters, k1 > 0. (Bσ (i) ) + It is Bσ (i) The generalized inverse, i.e. (Bσ) (i) ) + =I2, where I2 is the two-dimensional identity matrix, A is the characteristic matrix of the single-module suspension system, α1 is the virtual control signal, and x 1e To output the tracking error, x 2e This refers to the virtual signal tracking error.

[0014] In another implementation of the present invention, the fault system model is subjected to stabilization filtering and reconstruction processing to obtain reconstruction error, including: performing stabilization filtering processing on the fault system model to obtain a stable filtered fault system model; reconstructing the state variables in the stable filtered fault system model based on the fault mode matrix obtained from the fault mode to obtain a reconstructed fault system model; and performing error reconstruction processing on the reconstructed fault system model to obtain reconstruction error.

[0015] In another implementation of the present invention, the control switching mechanism based on the value function established by the reconstruction error selects a target controller from the controller set, including: constructing a value function based on the reconstruction error; calculating and comparing the value function to determine the minimum value function; and selecting the controller corresponding to the minimum value function from the controller set as the target controller.

[0016] In the fault compensation method for a single suspension module of a maglev train based on multiple models in this invention, considering the condition of actuator drive redundancy, a mode matrix is ​​given for each possible fault mode. Based on each fault mode, a corresponding controller is designed to form a multi-controller set to ensure the stability and asymptotic tracking performance of the system. Since the occurrence of actuator faults is random, in order to ensure that the electromagnet suspension gap can still maintain the expected distance after the actuator fault, the multiple model technology of stabilizing filter is used to compensate for the electromagnet fault, and the most suitable controller is selected by using the value function based on the reconstruction error, so that the suspension system can maintain stable suspension even when the fault signal is uncertain, thereby improving the stability of the maglev train. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. By reading the detailed description of the embodiments below, the advantages and benefits of the solutions will become clear to those skilled in the art. The accompanying drawings are only for illustrating preferred embodiments and are not intended to limit the present invention. In the accompanying drawings:

[0018] Figure 1 This is a flowchart illustrating the steps of a fault compensation method for a single suspension module of a maglev train based on a multi-model approach, according to an embodiment of the present invention.

[0019] Figure 2 This is a block diagram of a single-module suspension control structure for a maglev train according to another embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram of the controller switching principle according to another embodiment of the present invention.

[0021] Figure 4 The time curves of the levitation gaps c1 and c2 of electromagnets 1 and 4 according to another embodiment of the present invention are shown.

[0022] Figure 5 This is a control switching index based on a multi-model switching method, which is another embodiment of the present invention.

[0023] Figure 6 This is a time curve of the value function based on a multi-model switching method according to another embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and thoroughly 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 should fall within the protection scope of the present invention.

[0025] Figure 1 A flowchart illustrating the steps of a fault compensation method for a single suspension module of a maglev train based on a multi-model approach, as provided in this embodiment of the invention, is shown below. Figure 1 As shown, this embodiment mainly includes the following steps:

[0026] S101. Based on the electromagnet parameters of the maglev train, establish the state-space equation of the equilibrium point of the single suspension module system.

[0027] S102. Based on the state-space equations and fault modes, establish a fault system model.

[0028] S103. Based on actuator drive redundancy conditions and backstepping method, design the controller set corresponding to the fault mode.

[0029] S104. Perform stabilization filtering and reconstruction processing on the faulty system model to obtain the reconstruction error.

[0030] S105. Based on the value function established by the reconstruction error, a control switching mechanism is used to select the target controller from the set of controllers.

[0031] S106. Control the single suspension module system to maintain stable operation in fault mode by using the control signal generated by the target controller.

[0032] In the fault compensation method for a single levitation module of a maglev train based on multiple models in this invention, considering the condition of actuator drive redundancy, a mode matrix is ​​given for each possible fault mode. Based on each fault mode, a corresponding controller is designed to form a multi-controller set to ensure the stability and asymptotic tracking performance of the system. Since the occurrence of actuator faults is random, in order to ensure that the electromagnet levitation gap can still maintain the expected distance after the actuator fault, the multi-model technique of stabilizing filter is used to compensate for the electromagnet fault. The most suitable controller is selected by using the value function based on the reconstruction error, so that the single levitation module system can also ensure stable levitation when the fault signal is uncertain, thereby improving the safety of the single levitation module system.

[0033] In another implementation of the present invention, the state-space equation of the equilibrium point of the single suspension module system is established based on the electromagnet parameters of the maglev train, including: establishing a dynamic model of the single suspension module system based on the electromagnet parameters of the maglev train; and linearizing the dynamic model near the equilibrium point of the single suspension module system to obtain the state-space equation.

[0034] For example, when ignoring disturbances such as the secondary system, for bogie M B The following dynamic relationships exist. First, for the translational motion of the system, the dynamic equation of the bogie in the vertical direction is:

[0035]

[0036] Where, m B This is the equivalent mass of the train bogie on a single electromagnet module, where c1 and c2 represent the levitation gaps of electromagnets 1 and 4, respectively, and M... c The load on the carriage is determined by the electromagnetic forces of the four electromagnets, F1, F2, F3, and F4.

[0037] Secondly, for the rotation of the system, the equation of angular momentum of the bogie relative to the center of mass is (counterclockwise is positive):

[0038]

[0039] Where, m B It is the equivalent mass of the train bogie on a single electromagnet module. c1 and c2 represent the suspension gaps of electromagnets 1 and 4, respectively, and F1, F2, F3, and F4 are the electromagnetic forces of the four electromagnets.

[0040] When the system is in equilibrium, the following relationship can be obtained from the dynamic equation of the bogie in the vertical direction:

[0041] (M c +M B g = F 10 +F 20 +F 30 +F 40

[0042] When in equilibrium, the currents and gaps of the four electromagnets can be considered equal, i.e., the equilibrium gap is c0 and the equilibrium current is i0. Therefore, the electromagnetic forces of the four electromagnets are also equal, F0, which can be expressed as F0. 10 F 20 F 30 F 40 .

[0043] By combining the dynamic equations of the bogie in the vertical direction and the equation of the angular momentum of the bogie relative to the center of mass, the following can be obtained:

[0044]

[0045] For the electromagnetic force F, considering different air gaps and currents of different electromagnets, among which...

[0046]

[0047] Where μ0 is the vacuum permeability, N is the number of turns in a single electromagnet module winding, and i1, i2, i3, and i4 are the currents of the four electromagnets, respectively.

[0048] It is evident that the electromagnetic force equation is nonlinear. Therefore, to obtain a linearized equation, a Taylor expansion needs to be performed at the equilibrium position (c0, i0). We can obtain:

[0049]

[0050] Furthermore, taking Δi = i - i0 and Δc = c - c0, we can further simplify the equation by substituting the above equation into... The following state-space equations can be obtained:

[0051]

[0052] x2=Ax1+Bu

[0053] Where x1 = [Δc1, Δc2] T , U=[Δi1, Δi2, Δi3, Δi4] T A and B are the feature matrices of a single-module suspension system:

[0054]

[0055]

[0056] In another implementation of the present invention, the method further includes: combining fault modes to generate a fault set; and combining the fault set with the operating status of the single floating module system under the fault modes to determine the actuator drive redundancy conditions.

[0057] In another implementation of the present invention, the actuator drive redundancy condition is:

[0058] rank(Bσ)=2

[0059] Where σ is the fault mode matrix, σ=diag{σ1,σ2,σ3,σ4}, and B is the characteristic matrix of the single-module suspension system.

[0060] For example, a corresponding mode matrix is ​​established for each possible failure mode. For a single electromagnet, its failure can be modeled as follows:

[0061] u j =σ j i j j = 1, 2, 3, 4

[0062] Among them, u j For control signals, i j For current signals, σ j For fault diagnosis signals:

[0063]

[0064] Considering that all four electromagnets may fail, the system model after a failure is as follows:

[0065]

[0066] x2=Ax1+Bσu

[0067] Where σ = diag{σ1, σ2, σ3, σ4} is the fault mode matrix.

[0068] It should be understood that, as Figure 2 As shown, when one of the four electromagnets fails, the remaining electromagnets can still maintain system stability. Furthermore, considering that magnets 1 and 2, and magnets 3 and 4 operate in pairs, the system cannot maintain balance when magnets 1 and 2, or magnets 3 and 4, or three or more magnets fail. Therefore, the set of faults that the system can compensate for is:

[0069] σ (0) =diag{1,1,1,1}

[0070] σ (1) =diag{0,1,1,1}

[0071] σ (2) =diag{1,0,1,1}

[0072] σ (3) =diag{1,1,0,1}

[0073] σ (4) =diag{1,1,1,0}

[0074] σ (5) =diag{0,1,0,1}

[0075] σ (6) =diag{0,1,1,0}

[0076] σ (7) =diag{1,0,0,1}

[0077] σ (8) =diag{1,0,1,0}

[0078] In summary, after a failure, the system must meet the following actuator drive redundancy conditions:

[0079] rank(Bσ)=2

[0080] This condition ensures the controllability of the system after a failure.

[0081] In another implementation of the present invention, the controller set is represented as:

[0082]

[0083] Where k1 and k2 are user-defined parameters, k1 > 0. i = 0, 1, 2, ..., 8, (Bσ) (i) ) + It is Bσ (i) The generalized inverse, i.e. (Bσ) (i) ) + =I2, where I2 is the two-dimensional identity matrix, A is the characteristic matrix of the single-module suspension system, α1 is the virtual control signal, and x 1e To output the tracking error, x 2e This refers to the virtual signal tracking error.

[0084] For example, such as Figure 3 As shown, the post-fault system model is treated as a virtual control variable. A virtual control signal α1 is designed for the post-fault system model such that when x2 = x1, the control objective is achieved. For each σ in the post-fault system model... (i) For i = 0, 1, ..., 8, design a corresponding control signal u. (i) such that when σ = σ (i) hour, Ultimately, this forms a multi-controller set.

[0085] Based on each fault mode, a corresponding control signal was designed using the backstepping method to form a multi-controller set, and the output tracking error was defined as:

[0086] x 1e =x1-x 1d

[0087] The error system is then:

[0088]

[0089] At this point, the virtual control signal α1 is designed as follows:

[0090]

[0091] Where k1>0.

[0092] To analyze the control performance of the virtual control signal in advance, a positive definite function is chosen as follows:

[0093]

[0094] The virtual signal tracking error is defined as:

[0095] x 2e =x2-α1

[0096] From the post-fault system model and error system, we can obtain:

[0097]

[0098] Substituting the virtual control signal α1 in the designed positive definite function into the above equation, we get:

[0099]

[0100] Assumption Then there is This will allow us to achieve the desired system performance. Therefore, the next step will be to design the control signal u to implement this. and

[0101] The virtual signal tracking error system can be derived from the virtual signal tracking error as follows:

[0102]

[0103] From the virtual control signal, we can obtain:

[0104]

[0105] For any possible fault condition σ in the set of system faults (i) For i = 0, 1, ..., 8, the following control signals can be designed:

[0106]

[0107] Where k1 and k2 are user-defined parameters, k1 > 0. i = 0, 1, ..., 8., (Bσ) (i) ) + It is Bσ (i) The generalized inverse, i.e., (Bσ) (i) ) +=I2, where I2 is the two-dimensional identity matrix, A is the characteristic matrix of the single-module suspension system, α1 is the virtual control signal, and x 1e To output the tracking error, x 2e This refers to the virtual signal tracking error.

[0108] (Bσ (i) ) + It is usually obtained by the following formula:

[0109] (Bσ (i) ) + =(Bσ) (i) ) T (Bσ (i) (Bσ (i) ) T ) -1

[0110] Analysis using Lyapunov functions The control performance of the control signal is demonstrated by the Lyapunov function as follows:

[0111]

[0112] We can obtain:

[0113]

[0114] When σ=σ (i) When i = 0, 1, ..., 8, the control signal u in the virtual signal tracking error will be defined. (i) Substituting into the above formula, we get:

[0115]

[0116] The above formula shows that x 1e, x 2e ∈L 2 ∩L ∞ L 2 and L ∞ The definition can be found in the reference [G. Tao, Adaptive Control Design and Analysis, John Wiley & Sons, New Jersey, 2003].

[0117] Furthermore, from the error system, the tracking error system, and the control signal, we can obtain: Finally, according to Barbalat's lemma, we can obtain and The following lemma can then be obtained:

[0118] When the system failure mode is known, i.e., σ = σ (i)The designed control signal u, i = 0, 1, ..., 8. (i) This ensures the stability and asymptotic tracking performance of the single-module suspension system under the corresponding fault conditions in the system model after a failure, namely: and

[0119] For each fault mode in the fault set, corresponding control signals were designed to ensure the stability and asymptotic tracking performance of the system, forming a multi-controller set.

[0120] In another implementation of the present invention, the fault system model is subjected to stabilization filtering and reconstruction processing to obtain reconstruction error, including: performing stabilization filtering processing on the fault system model to obtain a stable filtered fault system model; reconstructing the state variables in the stable filtered fault system model based on the fault mode matrix obtained from the fault mode to obtain a reconstructed fault system model; and performing error reconstruction processing on the reconstructed fault system model to obtain reconstruction error.

[0121] For example, a stabilizing filter is first introduced. By filtering both sides of the faulty system model, we can obtain:

[0122]

[0123] Add to both sides of the above formula We can obtain:

[0124]

[0125] Since the fault mode matrix σ in the fault system model after stabilization filtering is uncertain, in order to solve the problem of how to select a suitable control signal, it is necessary to determine which σ the system is currently in. (i) For each possible failure mode matrix σ, i = 0, 1, ..., 8, i = 0, 1, ..., 8. (i) Reconstruct the state variable x2(t):

[0126]

[0127] Where i = 0, 1, ..., 8.

[0128] For the reconstructed multiple signals in the above equation, the reconstruction error is defined as:

[0129]

[0130] The reconstructed multi-signal can be divided into two categories: one signal that matches the actual system and the remaining signals that do not match the actual system.

[0131] When a fault occurs in the actual system, σ = σ (a)When the reconstruction error is defined by the above formula, the reconstruction error that matches the actual system can be obtained as:

[0132]

[0133] The reconstruction error that does not match the actual system is:

[0134]

[0135] Where b≠a, b=0,1,...,8.

[0136] In another implementation of the present invention, the control switching mechanism based on the value function established by the reconstruction error selects a target controller from the controller set, including: constructing a value function based on the reconstruction error; calculating and comparing the value function to determine the minimum value function; and selecting the controller corresponding to the minimum value function from the controller set as the target controller.

[0137] For example, to achieve control signal switching, the following value function is introduced:

[0138]

[0139] Where i = 0, 1, ..., 8.

[0140] When σ=σ (a) At that time, based on the above "reconstruction error", the value function that matches the actual system can be obtained as follows:

[0141]

[0142] Value functions that do not match the actual system include:

[0143]

[0144] Where b≠a, b=0,1,...,8.

[0145] Furthermore, all value functions are calculated and compared, and the control signal corresponding to the smallest value function is selected and applied to the actual system.

[0146]

[0147] u(t)=u (k) (t)

[0148] For practical systems, to prevent system instability caused by multiple rapid switchings of control signals, a minimum waiting time T(T) can be forcibly added between two switchings. min >0).

[0149] In another implementation of the present invention, the above control method is applied to a single suspension module model of the CMS-3 maglev train, and system parameters and initial simulation values ​​are configured, fault information is injected, and simulation is performed in MATLAB / Simulink.

[0150] The characteristic matrices A and B of the single-module suspension system of the maglev train are:

[0151]

[0152]

[0153] The simulation can be selected in the following three working modes:

[0154] u1=0,u j =i j j=2,3,4,σ (1) =diag{0,1,1,1},t>100;

[0155] u2=0,u3=0,u j =i j j=1,4,σ (7) =diag{1,0,0,1},t>400;

[0156] u j =i j j = 1, 2, 3, 4, σ (0) =diag{1,1,1,1}, or other times.

[0157] Figure 4 The graph shows the time curves of the suspension gaps c1 and c2 of electromagnets 1 and 4. It can be seen that faults occurred at 100s and 400s, causing changes in c1 and c2. Especially at 400s, the simultaneous failure of actuators 2 and 3 had a greater impact on the suspension gaps c1 and c2 than the single actuator failure at 100s. However, after a period of time, the system returned to stability.

[0158] Figure 5 It is a control switching index based on a multi-model switching method. Figure 6 This is a time curve of the value function based on the multi-model switching method. Among them, Figure 5 The switching index values ​​0, 1, ..., 8 correspond to u in the multi-controller set, respectively. (i) ,i=0,1,...,8 and J in the set of value functions (i) (t), i = 0, 1, ..., 8. It can be seen that J0 is minimum between 0s and 100s, and the control signal is selected as u = u. (0)During the period from 100s to 400s, J1 is at its minimum, and the control signal is selected as u = u. (1) During the 400s-700s interval, J7 is at its minimum, and the control signal is selected as u = u. (7) .

[0159] It should be understood that the simulation results show that the design scheme of the present invention can guarantee system stability and asymptotic tracking performance after a fault occurs, and in all three simulation scenarios, the control switching mechanism selects a controller that matches the actual system.

[0160] Specific embodiments of the invention have now been described. Other embodiments are within the scope of the appended claims. In some cases, the actions described in the claims can be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing can be advantageous.

[0161] It should be noted that all directional indicators (such as up, down, left, right, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicator will also change accordingly.

[0162] In the description of this invention, the terms "first" and "second" are used only for convenience in describing different components or names, and should not be construed as indicating or implying a sequential relationship, relative importance, or implicitly specifying the number of technical features indicated. Thus, a feature defined with "first" and "second" may explicitly or implicitly include at least one of that feature.

[0163] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0164] It should be noted that although specific embodiments of the present invention have been described in detail with reference to the accompanying drawings, this should not be construed as limiting the scope of protection of the present invention. Various modifications and variations that can be made by those skilled in the art without inventive effort within the scope described in the claims still fall within the scope of protection of the present invention.

[0165] The examples of the embodiments of the present invention are intended to concisely illustrate the technical features of the embodiments of the present invention, so that those skilled in the art can intuitively understand the technical features of the embodiments of the present invention, and are not intended to be an improper limitation of the embodiments of the present invention.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fault compensation method for a single suspension module of a maglev train based on a multi-model approach, characterized in that, include: Based on the electromagnet parameters of the maglev train, the state-space equation of the equilibrium point of the single suspension module system is established. Based on the state-space equations and fault modes, a fault system model is established; Based on actuator drive redundancy conditions and backstepping method, design the controller set corresponding to the fault mode; The actuator drive redundancy condition is: , σ This is the fault mode matrix. , B For the input matrix of a single suspension module system, For fault diagnosis signals: ; The controller set is represented as follows: in, For control signals, For custom parameters, i=0,1,2,…,8 yes The generalized inverse, that is , It is a two-dimensional identity matrix. A The state matrix of a single-floating module system. For virtual control signals, x 1e To output the tracking error, x 2e This refers to the tracking error of the virtual signal. This refers to the deviation in the suspension gap. The faulty system model is subjected to stabilization filtering and reconstruction processing to obtain the reconstruction error; The control switching mechanism based on the value function established by the reconstruction error selects a target controller from the controller set, including: constructing a value function based on the reconstruction error; calculating and comparing the value function to determine the minimum value function; and selecting the controller corresponding to the minimum value function from the controller set as the target controller. The single suspension module system is controlled to maintain stable operation in the fault mode by the control signal generated by the target controller.

2. The method according to claim 1, characterized in that, The state-space equations for the equilibrium point of the single levitation module system, based on the electromagnet parameters of the maglev train, include: A dynamic model of a single suspension module system is established based on the electromagnet parameters of a maglev train. The dynamic model is linearized near the equilibrium point of the single suspension module system to obtain the state-space equation.

3. The method according to claim 1, characterized in that, Also includes: Based on the aforementioned fault modes, a fault set is generated; Based on the set of faults and the operating status of the single-floating module system under the fault modes, the actuator drive redundancy conditions are determined.

4. The method according to claim 1, characterized in that, The process of performing stabilization filtering and reconstruction on the faulty system model yields the reconstruction error, including: The fault system model is subjected to stabilization filtering to obtain a stable fault system model; Based on the fault mode matrix obtained from the fault modes, the state variables in the stable filtered fault system model are reconstructed to obtain the reconstructed fault system model. The reconstructed fault system model is subjected to error reconstruction processing to obtain the reconstruction error.

Images