Cross coupling cooperative control method for double permanent magnet synchronous motors of aviation airborne suspension lifting system

Abstract

The invention provides a cross-coupling cooperative control method for double permanent magnet synchronous motors of an aviation airborne suspension lifting system. The cross-coupling cooperative control method comprises the following steps: acquiring a global instruction and real-time state feedback of the double motors; based on the global instruction and the real-time state feedback, constructing a dynamic topology and dynamically adjusting the weight to obtain the weight of the dynamic topology; generating a collaborative correction based on the weight of the dynamic topology and a consistency protocol; dynamic error balanced distribution under load disturbance is carried out based on the collaborative correction amount; and controlling the double motors based on an error balanced distribution result. According to the method, dynamic weight distribution and dynamic error balanced distribution are combined, multi-source interference working conditions such as mechanical unbalance loading, dynamic coupling and parameter disturbance can be dealt with, synchronous errors and disturbance fluctuation in a dual-motor system can be accurately monitored and coordinated, and high-precision stability of cooperative driving is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of aviation airborne suspension lifting systems, and in particular relates to a cross-coupling cooperative control method for dual permanent magnet synchronous motors of an aviation airborne suspension lifting system. Background Art

[0002] As modern aviation equipment evolves toward high maneuverability, high payload capacity, and multi-mission capabilities, high-performance airborne suspension lifting systems have become a core subsystem of military platforms such as fighter jets and bombers, fulfilling critical tasks such as the rapid mounting and precise delivery of weapons, ammunition, and equipment. In the civilian sector, large cargo aircraft, specialized lifting vehicles, and heavy machinery also rely on highly reliable lifting systems for efficient cargo transfer. However, my country's current technology lags behind internationally advanced technologies in terms of high power density and reliability under extreme operating conditions. On the one hand, traditional single-motor drive solutions are limited by power limits and a lack of redundancy, making them incapable of rapidly lifting heavy ammunition (such as supersonic missiles) or large cargo (≥5 tons). Furthermore, their complex mechanical transmission structures lead to high failure rates. On the other hand, cross-coupling interference, common in the coordinated control of dual or multiple motors (such as torsional vibrations in the mechanical transmission chain, electromagnetic torque fluctuations, and speed deviations caused by parameter mismatches), can easily lead to accumulated synchronization errors, resulting in instability during the lifting process and even mechanism seizure. According to relevant research reports, suspension system failures caused by motor coordination failure account for as much as 37%, severely restricting the combat effectiveness of equipment and the economic viability of civil aviation cargo transport. Therefore, breaking through the high-precision synchronous control and dynamic anti-interference technology of dual motors and building a new airborne suspension lifting system with improved power density and enhanced reliability has become an urgent need for my country's aerospace equipment upgrade and military-civilian integration industry expansion.

[0003] Achieving high-precision coordinated control in an airborne suspension lifting system driven by dual permanent magnet synchronous motors requires overcoming two core challenges: first, dynamic interference suppression under cross-coupling effects. When the two motors are mechanically coupled via a gearbox or rigid coupling, load disturbances and backlash nonlinearity can cause torque fluctuations to be transmitted to each other, resulting in strong coupled interference. Furthermore, electromagnetic coupling between the motor stator windings further exacerbates current harmonics and speed oscillations. Second, ensuring coordinated consistency under multi-objective constraints. In scenarios such as ammunition loading, the two motors must synchronously track position / velocity commands while meeting multiple constraints such as torque balance, temperature rise suppression, and efficiency optimization. Existing methods, such as PID-based master-slave control strategies, can achieve basic synchronization but struggle to dynamically compensate for time-varying coupled interference. Distributed cooperative algorithms (such as the leader-follower architecture) can improve robustness but lack explicit modeling of the mechanical-electromagnetic coupling mechanism, resulting in significant overshoot in transient processes. Summary of the Invention

[0004] In response to the problems existing in the prior art, the present invention provides a cross-coupling collaborative control method for dual permanent magnet synchronous motors in an aviation airborne suspension lifting system to solve the problem of synchronization error accumulation in the prior art, which leads to instability in the lifting process.

[0005] The present disclosure provides a method for cross-coupling coordinated control of dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system, comprising:

[0006] Obtain global instructions and real-time status feedback of dual motors;

[0007] Based on global instructions and real-time state feedback, dynamic topology and dynamic adjustment weights are constructed to obtain the weights of the dynamic topology;

[0008] Generate collaborative corrections based on dynamic topology weights and consensus protocols;

[0009] Dynamic error balancing distribution under load disturbance based on cooperative correction;

[0010] The dual motors are controlled based on the error balance distribution results.

[0011] Optionally, obtaining global instructions and real-time status feedback of the dual motors includes:

[0012] Align the time of the acquired global command signal and the real-time status feedback signal;

[0013] The global instruction includes a speed reference value and a position reference value;

[0014] It is real-time status feedback, including actual speed, position angle and load torque disturbance.

[0015] Optionally, the constructing of a dynamic topology and dynamically adjusting weights based on global instructions and real-time state feedback to obtain the weights of the dynamic topology includes:

[0016] The difference in speed and position angle of the two motors is integrated through nonlinear functions, and the weight value of the connection between the motors is updated in real time.

[0017] After the weight values ​​are calculated, the Laplace matrix of the corresponding communication topology is generated, and the strong connectivity of the topology is verified through the Laplace matrix algebraic connectivity eigenvalue.

[0018] Optionally, generate coordinated modifiers based on dynamic topology weights and consensus protocols, including:

[0019] Based on the weights of the dynamic topology, the speed coordination error vector and position coordination error term of the dual motors are calculated. The coordination error vector and coordination error term are input into the consistency protocol to generate the coordination control compensation.

[0020] Optionally, the dynamic error balancing distribution under load disturbance based on the collaborative correction amount includes:

[0021] Based on the synergistic compensation amount, an error dynamic model is established;

[0022] Error distribution is performed based on the inertia ratio of the two motors and the error dynamic model;

[0023] The gain is dynamically adjusted based on the error dynamic model after error distribution to generate balanced compensation terms, so that the dual motors maintain synchronous performance under dynamic loads.

[0024] Optionally, controlling the dual motors based on the error balance distribution result includes:

[0025] The error balance distribution result is input into the motor control layer, and the permanent magnet synchronous motor is controlled through the motor control layer;

[0026] The motor control layer includes a control synthesis module and a PMSM control channel, and the output signal of the control synthesis module is input into the PMSM control channel;

[0027] The PMSM control channel includes a fuzzy active disturbance rejection controller tracking differentiator, an extended state observer and a nonlinear error feedback. The output signal of the fuzzy active disturbance rejection controller tracking differentiator is input into the extended state observer, the output signal of the extended state observer is input into the nonlinear error feedback, and the output signal of the nonlinear error feedback is input into a control synthesis module.

[0028] Optionally, controlling the dual motors based on the error balance distribution result includes:

[0029] A PMSM mathematical model is established, and the PMSM mathematical model formula is:

[0030] ,

[0031] in, is the electromagnetic torque; P is the number of pole pairs of the permanent magnet synchronous motor, J is the moment of inertia of the PMSM, is the load torque, is the rotor mechanical angular velocity, B is the viscous friction coefficient, and t is time.

[0032] Optionally, the formula of the extended state observer is:

[0033] ,

[0034] Among them, z1 is The estimated value of z2 is The estimated value of ; z3 is the estimated total disturbance term; , , is the observer gain, To control the gain.

[0035] Optionally, the fuzzy active disturbance rejection controller tracks a differentiator, comprising:

[0036] The motor speed error and speed error differential are used as the input of the fuzzy controller, and fuzzy reasoning is used to perform real-time correction on the three parameters β0, β1, and β2 of the extended state observer to obtain the corresponding integral gain correction coefficient Δβ0, proportional gain correction coefficient Δβ1, and differential gain correction coefficient Δβ2.

[0037] Optionally, include the gain coefficient for the extended state observer , , Make adjustments, the specific adjustments are as follows:

[0038] When the speed error amplitude is greater than the set condition, the proportional gain β1 and its correction value Δβ1 are increased, while the differential gain β2 is reduced to prevent the correction value Δβ2 from being oversaturated and causing overshoot, and the integral gain β0 and the correction value Δβ0 are set to zero;

[0039] When the speed error and its rate of change are both within the set conditions, reduce β1 and Δβ1 and set β0 to the set medium value;

[0040] When the speed error is less than the set error value, increase the integral gain β0 and proportional gain β1 and their corresponding correction values ​​Δβ0 and Δβ1;

[0041] If the error change rate is greater than the first set error change rate, β1, β2 and their corrections Δβ1, Δβ2 are reduced, and the values ​​of the integral gains β0 and Δβ0 are increased; when the change rate is less than the second set error change rate, β2 and Δβ2 are increased, and the adjustments to β0, β1 and their corrections Δβ0, Δβ1 are combined to achieve more balanced dynamic and steady-state performance, and the second set error change rate is less than the first set error change rate.

[0042] The cross-coupling collaborative control method for dual permanent magnet synchronous motors in an aviation airborne suspension lifting system provided by the present invention, combined with dynamic weight distribution and dynamic error balance distribution, can cope with multi-source interference conditions such as mechanical overload, dynamic coupling and parameter disturbance, and can accurately monitor and coordinate synchronization errors and disturbance fluctuations in the dual-motor system to ensure high-precision stability of collaborative drive.

[0043] The overall architecture of this control method consists of two layers: the upper layer generates synchronization corrections in real time through a dynamic weighting protocol to balance load differences and coupling effects; the lower layer utilizes a fuzzy active disturbance rejection controller that integrates command smoothing, disturbance observation, and dynamic parameter optimization modules. Combined with cross-coupling compensation, this composite control law achieves bidirectional speed-position error suppression. This method, through a hierarchical coordination mechanism and a multimodal regulation strategy, effectively improves the synchronization accuracy and interference rejection capabilities of the dual-motor system under complex disturbances. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure with reference to the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0045] Figure 1 A flow chart of cross-coupling coordinated control of dual permanent magnet synchronous motors provided in an embodiment of the present disclosure;

[0046] Figure 2 A diagram showing the consistent cross-coupling collaborative control logic structure and dynamic interaction relationship provided by an embodiment of the present disclosure;

[0047] Figure 3 A diagram showing a three-closed-loop control structure of a single permanent magnet synchronous motor provided in an embodiment of the present disclosure;

[0048] Figure 4 The membership function curves provided in the embodiments of the present disclosure are as follows: a is the membership function curve of the speed error, b is the membership function curve of the speed error differential, c is the membership function curve of the correction coefficients Δβ0 and Δβ1, and d is the membership function curve of the correction coefficient Δβ2;

[0049] Figure 5 This is a structural diagram of the fuzzy anti-disturbance control system for the speed loop of a permanent magnet synchronous motor provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0050] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0051] It should be clear that the following embodiments of the present disclosure are described through specific specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other in the absence of conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0052] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on this disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement an apparatus and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this apparatus and / or practice this method.

[0053] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The illustrations only show components related to the present disclosure and are not drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component can be changed at will, and the component layout type may also be more complicated.

[0054] Additionally, in the following description, specific details are provided to provide a thorough understanding of the examples. However, one skilled in the art will appreciate that the aspects described can be practiced without these specific details.

[0055] In order to achieve high-performance cooperative drive of dual permanent magnet synchronous motors in aircraft suspension lifting systems, the method proposed in this paper adopts a layered fusion architecture. Its core is divided into two modules: upper-layer consistent cross-coupling cooperative control and lower-layer fuzzy active disturbance rejection control. First, the upper layer calculates the position deviation of the dual motors according to their real-time position deviation e. θ , load eccentricity ΔT L And the global speed command ω ref , calculate a by dynamic weight ij (t) Generate synchronization error correction Δθ adj, forming a collaborative benchmark that takes into account both mechanical offset load compensation and dynamic coupling enhancement; subsequently, this correction value is sent down together with the global command to the independent control channels of the two motors at the bottom layer. In the bottom-level control loop, each motor speed loop uses a fuzzy active disturbance rejection controller, which is internally composed of a tracking differentiator, an extended state observer, and nonlinear error feedback: the tracking differentiator smoothes the input command and extracts the differential signal to suppress command jumps. The extended state observer compresses internal and external disturbances such as load fluctuations and parameter perturbations into the linear range by observing the rotor speed z1, acceleration z2, and total disturbance z3 in real time; the nonlinear error feedback combines the nonlinear characteristics of the function fal(•) to generate the basic control quantity u 0i At the same time, the cross-coupling module calculates the synergistic compensation term u according to the real-time speed ω1, ω2 of the dual motors and the upper correction value. cc =K cc (ω j -ω i )+K cθ Δθ adj , and the fuzzy ADRC output synthesizes the final control signal u i , forming a "feedforward-feedback-synergy" composite control law. This method achieves multi-objective optimization through dynamic interaction: fuzzy rules adaptively adjust the observation gain of the extended state observer according to the error size and change trend, enhancing parameter robustness; the consistency protocol effectively balances the load differences between the two motors by dynamically allocating synchronization weights; and the cross-coupling structure compensates for position and speed errors in both directions, significantly reducing synchronization lag. Its multi-level collaborative mechanism improves dynamic response speed while achieving high-precision synchronous control of the two motors under complex disturbances.

[0056] The control method of the present invention adopts a hierarchical architecture to realize the cooperative drive of dual motors. The upper consistency cross-coupling cooperative control layer generates the synchronization correction value based on the load deviation, speed difference and position difference through dynamic weight protocol calculation, and dynamically balances the mechanical offset load and coupling effect; each motor in the bottom layer is equipped with a fuzzy anti-disturbance controller, which tracks the differentiator to smooth the instruction signal and extract the differential; the extended state observer dynamically adjusts the observer gain through fuzzy rules to accurately identify the total disturbance in real time; the nonlinear feedback generates the basic control quantity through adjustment. The cross-coupling module integrates the speed difference and correction value of the two machines to form a cooperative compensation, and synthesizes the final control signal together with the load eccentricity and disturbance compensation terms to form a "feedforward-feedback-cooperation" composite structure to achieve multi-objective optimization: the fuzzy mechanism adaptive parameters enhance robustness, the dynamic weight protocol balances the load difference, the two-way compensation suppresses the synchronization lag, and the hierarchical collaboration maintains high-precision synchronization and dynamic response under disturbance.

[0057] This embodiment proposes a cross-coupling cooperative control method for dual permanent magnet synchronous motors in an aviation airborne suspension lifting system. Based on a dynamic communication topology, it aims to solve the cross-coupling interference that is prevalent in the cooperative control of dual motors or multiple motors, which causes the accumulation of synchronization errors and leads to instability in the lifting process. This method combines the advantages of hierarchical dynamic weight distribution and fuzzy self-anti-disturbance control technology, and can cope with multi-source interference conditions such as mechanical overload, dynamic coupling and parameter disturbances. It can accurately monitor and coordinate the synchronization error and disturbance fluctuations in the dual motor system to ensure the high-precision stability of the cooperative drive. The overall architecture of this control method is divided into two levels: the upper layer generates synchronization corrections in real time through a dynamic weight protocol to balance load differences and coupling effects; the bottom layer adopts a fuzzy self-anti-disturbance controller, which integrates instruction smoothing, disturbance observation and parameter dynamic optimization modules, and combines cross-coupling compensation to form a composite control law to achieve bidirectional suppression of speed-position errors. This method effectively improves the synchronization accuracy and anti-interference ability of the dual motor system under complex disturbances through a hierarchical cooperative mechanism and a multi-modal adjustment strategy. The overall control flow chart is shown in the figure. Figure 1 As shown:

[0058] The specific control process is as follows:

[0059] (1) Input global command and state feedback initialization. The control process first receives the external input speed reference value ω through the top module ref and the position reference value θ ref This data serves as a global command and simultaneously obtains real-time status feedback from both motors, including actual speed, position angle, and load torque disturbance. These input parameters serve as the foundation for coordinated control, and all subsequent dynamic adjustments and error corrections are based on this data set. The input module's core task is to align the timing of the command signal with the feedback signal, ensuring synchronization and real-time performance of subsequent calculations.

[0060] (2) Dynamic topology construction and dynamic weight adjustment. Based on the speed difference and position deviation of the two motors, the adjacency weight parameters of the communication topology are dynamically adjusted. Specifically, the control system integrates the degree of speed and position difference through nonlinear functions and updates the weight values ​​of the connections between the motors in real time. After the weight values ​​are calculated, the Laplace matrix of the corresponding communication topology is generated, and the strong connectivity of the topology is verified by its algebraic connectivity eigenvalues. Its core purpose is to ensure that the interaction relationship between the two motors changes adaptively with the operating status, avoiding synchronization loss due to the failure of a single information channel.

[0061] (3) The consensus protocol generates collaborative corrections. Based on the weight a of the dynamic topology ij (t), calculate the speed coordination error vector ξ of the dual motors i (t) and the position coordination error term Δθ i , input the error term into the consensus protocol to generate the cooperative control compensation u cc,i.

[0062] (4) Dynamic error balance distribution under load disturbance. After receiving the cooperative compensation amount u cc,i Then, the error dynamic model is established first. The error ratio is allocated according to the inertia ratio of the two machines η = J1 / J2, and the constraint satisfies e ω,1 / e ω,2 =η and the sum of the drive speed errors converges to zero asymptotically, thereby offsetting the impact of load disturbance on the synchronization of the two machines. Further, by dynamically adjusting the gain α, a balanced compensation term is generated. , so that the dual motors can still maintain synchronous performance under dynamic loads.

[0063] (5) Bottom-layer control execution and closed-loop state feedback. The final equilibrium compensation term The disturbance rejection compensation u injected into the underlying motor control loop and the output of the fuzzy ADRC 01 and u 02 Signal synthesis is achieved through linear superposition, ultimately output to the inverter to generate a PWM modulated signal. This drives the two permanent magnet synchronous motors to adjust their actual output torque and speed. Sensors provide real-time feedback to the top-level input module regarding the motor's actual operating status, forming a closed-loop control loop consisting of "dynamic weight update → coordinated correction → error allocation → execution feedback." This closed-loop mechanism, through real-time iteration of dynamic topology and disturbance rejection balancing, ensures global synchronous tracking performance of the two motors under sudden load changes or parameter perturbations.

[0064] Consistent cross-coupling cooperative control

[0065] In the cross-coupling cooperative control method of dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system based on dynamic communication topology, the consistent cross-coupling cooperative control layer serves as the central decision-making unit of the dual motors in the system, and undertakes the core functions of global synchronization optimization and dynamic cooperative compensation. The core functions of this control layer can be decomposed into three logical levels, and its logical structure and dynamic interaction relationship are as follows: Figure 2 As shown:

[0066] The first level (information interaction architecture): through the dynamic adjacency matrix a ij (t) Construct a weighted communication topology to define the coupling strength between the motors in the system. In actual operation, the weight matrix is ​​calculated based on the speed difference between the two motors |ω i -ω j |with position deviation|θ i -θ j |Perform nonlinear dynamic adjustments. The Laplace matrix L=DA is used as a mathematical abstraction of the communication topology. By updating the angle matrix D in real time, it ensures strong network connectivity and avoids control failures caused by isolated nodes.

[0067] The second level (collaborative protocol generation): according to the global reference instruction ω ref , θ ref With the error dynamic model, the consistency correction term u is derived cc,i .

[0068] The third level (error balance distribution): Targeting the dynamic balancing requirements of an aircraft's suspension lift system under load disturbances, a speed error proportional constraint is established. This involves dynamically distributing the error components by introducing a proportional factor, η, while assuming the total error converges to zero. This mechanism achieves on-demand decomposition of the load disturbance torque by constructing an error distribution equation.

[0069] Within this framework, when a sudden load is applied to a single motor, the permissible error range is expanded in proportion to its moment of inertia. Adjacent motors actively share the disturbance by increasing the strength of the synergistic compensation term, thereby maximizing global disturbance rejection. The resulting closed-loop architecture characterizes the system's synchronous convergence rate through the minimum eigenvalue of the Laplace matrix, ultimately ensuring robust coordinated operation of the dual permanent magnet synchronous motors in aircraft suspension hoist systems under complex operating conditions.

[0070] In a dual-motor driven eccentric load lifting system, the two motors drive the boom in a rigid shaft linkage. During the synchronization process, the eccentric load will introduce a torque offset ΔT. L,i , requiring the motors to dynamically adjust their speed and angular position to suppress oscillations. To achieve this goal, a communication topology model needs to be established to transmit the status information of the two motors in real time.

[0071] (1) Communication topology modeling:

[0072] The physical connections are extracted into a graph theory model, and the graph structure of the communication topology is defined as:

[0073] (1)

[0074] In the formula, the node set v = {1, 2} corresponds to two permanent magnet synchronous motors; the edge set ε∈v×v, if the two can communicate directly, then (i, j)∈ε. Due to the symmetry of the system, the two motors are neighbors, that is, ε = {(1, 2), (2, 1)}; the adjacency matrix A = [a ij ], whose element a ij (t) represents the communication weight from node j to i, which dynamically reflects the intensity of information interaction.

[0075] Communication weight a ij (t) can be dynamically adjusted according to the real-time error between the two motors, and the weight function can be defined as:

[0076] (2)

[0077] Where kω With k θ is the synchronization weight coefficient of speed and position; μ is the minimum constant; γ is the position difference attenuation factor.

[0078] Based on the adjacency matrix A(t), construct the degree matrix D(t)=diag(d1,d2), where the diagonal elements are the out-degrees of the nodes:

[0079] (3)

[0080] Due to the symmetrical communication of the two motors, d1(t)=d2(t)=a 12 (t)+a 21 (t)=2a 12 (t). We can further obtain the Laplace matrix:

[0081] (4)

[0082] (2) Consistency protocol design:

[0083] The cooperative error signal of the permanent magnet motor is defined as the weighted sum of the speed differences of the neighbors:

[0084] (5)

[0085] The collaborative amendments generated by the agreement are:

[0086] (6)

[0087] Where K cc is the speed synchronization gain; K cθ is the position synchronization coupling gain.

[0088] (3) Establish error dynamic equation:

[0089] (7)

[0090] Where, ω ref is the speed reference value; θ ref is the position reference value; ΔT L,i is the load disturbance difference; B is the motor viscous friction coefficient; J is the motor moment of inertia.

[0091] (4) Co-allocation goals:

[0092] The goal of the synchronous error distribution mechanism is to dynamically balance the tracking errors of each motor according to the physical load distribution to prevent the cascading loss of synchronization caused by overload of a single motor. Based on the establishment of the error dynamic model, the "demand distribution" principle is proposed, that is, the total disturbance ΔT L =ΔT L,1 +ΔT L,2The inertia is shared by the two motors according to the ratio J1 / J2=η, and the error must satisfy e ω,1 / e ω,2 =η. To achieve this goal, the equalization compensation term is designed as:

[0093] (8)

[0094] Where α is the error distribution gain; η is the motor inertia ratio.

[0095] During actual operation, if the load on Motor 1 suddenly increases, the coordination layer automatically adjusts the η value, increasing the permissible error for Motor 1. Motor 2 then actively outputs greater torque to compensate for the synchronization error, thus achieving dynamic load balancing. This mechanism not only suppresses cumulative displacement deviation through position feedback but also utilizes relative error proportional distribution to achieve "more work for those who are able," effectively extending the life of the machine. For example, in a crane's dual-motor winch system, if the left motor's wire rope wears, causing an increase in friction, the system will increase the η value, allowing the left motor to operate at a lower speed while the right motor increases its output, ultimately maintaining the hoisted object level.

[0096] Based on the dynamic topological structure of the Laplace matrix, the consistency correction term u cc,i The core goal is to achieve global synchronization of the speed and position of the dual motors in the aircraft suspension lifting system through weighted error feedback of the communication topology. This design allows each motor to communicate only with its neighboring nodes, that is, through a ij (t) The connected motors exchange information and achieve synchronization without the intervention of the global central controller; at the same time, the dynamic speed difference and position difference can be feedback-adjusted through the linear proportional gain to suppress the influence of external disturbances on the synchronization accuracy. Based on the synchronization error allocation mechanism, the error allocation equation Dynamic optimization based on physical load distribution is added to the consistency correction term. By introducing the moment of inertia proportional factor η, the total error is distributed to each motor according to the η value, realizing "the motor with large inertia allows for larger tracking error". At the same time, through the integral term ∫e θ,i dt suppresses accumulated position deviations and enhances dynamic matching under load fluctuations through the proportional parameter α. The consistency correction term provides fundamental error convergence capability, ensuring global system stability through a graph-theoretic structure. The error allocation mechanism refines the dynamic adjustment strategy and optimizes resource allocation efficiency under load disturbances through a physical model. These two mechanisms form a closed loop through dynamic weight matrices and parameter linkage, ultimately achieving high-precision, robust coordinated control of the dual-motor system.

[0097] In order to realize the high-performance coordinated drive of dual permanent magnet synchronous motors in the aircraft suspension lifting system, the PMSM speed loop fuzzy anti-disturbance control adopts the same control structure and control method for dual motor control in the underlying motor control. Here, the control structure of a single permanent magnet synchronous motor is used as an example. Figure 3The three-loop cascade control structure shown in the figure consists of a current loop, a speed loop, and a position loop, wherein the speed loop uses a fuzzy active disturbance rejection controller to control the motor speed.

[0098] Figure 3 In the system, the current loop is located in the inner layer and primarily implements decoupled control of the d-axis and q-axis currents. It drives the inverter via PWM modulation signals to ensure that the motor outputs a current that matches the target torque. The speed loop, based on the dynamic characteristics of the current loop, compares rotor speed feedback with the reference speed. After adjustment by the speed loop's fuzzy anti-disturbance control controller, it generates a control signal. This signal is then linearly superimposed with the balanced collaborative control signal issued by the upper-layer consistency cross-coupling collaborative control layer to further generate the current command. The position loop is located in the outermost layer and outputs a speed reference signal to the speed loop via the position controller based on rotor angle feedback, enabling the onboard suspension hoist system to accurately track position and speed information. This cascade structure significantly improves the system's robustness to external disturbances while ensuring the stability of the inner loop's current and speed.

[0099] (1) PMSM mathematical model:

[0100] The PMSM stator voltage equation is:

[0101] (9)

[0102] In a two-phase rotating coordinate system, the d-axis and q-axis of a permanent magnet synchronous motor are usually represented as the magnetic field direction axis and its perpendicular axis, respectively. d =L q ), so the control design can be simplified, and effective control of the motor magnetic field can be achieved by only considering the components of the magnetic field on the d-axis and q-axis.

[0103] Stator flux equation:

[0104] (10)

[0105] The electromagnetic torque equation is:

[0106] (11)

[0107] Where, T e is the electromagnetic torque; P is the number of pole pairs of the permanent magnet synchronous motor. Write the mechanical motion equation for the motor:

[0108] (12)

[0109] Where, the moment of inertia of PMSM is J; the load torque is T L ;The rotor mechanical angular velocity is ω m; The viscous friction coefficient is B, ω e =P•ω m .

[0110] (1) Fuzzy controller design

[0111] The motor speed error e ω,i and the speed error differential de ω,i / dt is used as the input of the fuzzy controller, and fuzzy reasoning is used to perform real-time correction on the three parameters β0, β1, and β2 of the extended state observer to obtain the corresponding integral gain correction coefficient Δβ0, proportional gain correction coefficient Δβ1, and differential gain correction coefficient Δβ2.

[0112] The fuzzy controller designed in this invention uses the same seven fuzzy subsets at both the input and output ends: {"Negative Large (NB)", "Negative Medium (NM)", "Negative Small (NS)", "Zero (ZO)", "Positive Small (PS)", "Positive Medium (PM)", and "Positive Large (PB)"}. All membership functions are arranged in a bell-shaped pattern at both ends and a triangle in the middle. The domains of the input and output variables are set as follows:

[0113] (13)

[0114] According to the domain of each input and output variable in the above fuzzy controller, the corresponding membership function curve can be obtained as follows: Figure 4 shown.

[0115] In order to cope with the external disturbances, load mutations, and speed mutations suffered by the permanent magnet synchronous motor in the airborne suspension lifting system during operation, the following control law is summarized by adjusting the gain coefficients β0, β1, and β2 of the extended state observer:

[0116] a) When the speed error is large, in order to speed up the system response, the proportional gain β1 and its correction value Δβ1 can be appropriately increased, while the differential gain β2 can be slightly reduced to prevent Δβ2 from being oversaturated and causing overshoot, and the integral gain β0 and Δβ0 can be temporarily set to zero to ensure closed-loop stability.

[0117] b) When both the speed error and its rate of change are at moderate levels, overshoot can be suppressed by reducing β1 and Δβ1, setting β0 to a moderate value, and fine-tuning Δβ0 and Δβ2 to improve response speed. Fine-tuning the differential gain β2 has the most significant impact on dynamic performance.

[0118] c) When the speed error is small, in order to enhance the system's resistance to disturbances, the integral gain β0 and proportional gain β1 and their corresponding corrections Δβ0 and Δβ1 should be appropriately increased, and the differential gain β2 should be optimized to suppress or reduce overshoot while improving the system's resistance to disturbances.

[0119] d) If the error change rate is large, it is necessary to reduce β1, β2, and their corrections Δβ1 and Δβ2 to maintain system stability, and increase the values ​​of integral gains β0 and Δβ0. Conversely, when the error change rate is small, β2 and Δβ2 can be increased, and combined with adjustments to β0, β1, and their corrections Δβ0 and Δβ1, to achieve more balanced dynamic and steady-state performance.

[0120] According to the above fuzzy control strategy, the Mandani fuzzy inference method is used to construct the fuzzy control rule table for Δβ0, Δβ1 and Δβ2, and generate the corresponding fuzzy lookup table, as shown in Tables 1 to 6 for details.

[0121] Table 1 Fuzzy control rules of Δβ0

[0122]

[0123] Table 2 Fuzzy control query table of Δβ0

[0124]

[0125] Table 3 Fuzzy control rules of Δβ1

[0126]

[0127] Table 4 Fuzzy control query table of Δβ1

[0128]

[0129] Table 5 Fuzzy control rules of Δβ2

[0130]

[0131] Table 6 Fuzzy control query table of Δβ2

[0132]

[0133] The centroid method is used to defuzzify the membership values ​​of the speed error and its derivative calculated by the membership function, and the specific values ​​of the correction coefficients Δβ0, Δβ1 and Δβ2 can be obtained. Subsequently, these corrections are added to the initial gain of the extended state observer. 、 and On the basis of the above, we can get the expression of the overall gain of the system:

[0134] (14)

[0135] (3) Establishment of Active Disturbance Rejection Control Model

[0136] Tracking Differentiator Design:

[0137] The tracking differentiator is used to arrange the transition process to avoid the speed command ω ref Overshoot and oscillation caused by the jump. The equation is:

[0138] (15)

[0139] Where v1 is the speed reference value after tracking; v2 is the speed differential after tracking; and λ is the tracking differentiator bandwidth parameter, which determines the tracking speed.

[0140] Extended State Observer Design:

[0141] Expand the total disturbance (load disturbance, parameter perturbation, etc.) into the system state and design a second-order extended state observer:

[0142] (16)

[0143] Where z1 is ω m The estimated value of z2 is The estimated value of ; z3 is the estimated total disturbance term; β0, β1, β2 are the observer gains; To control the gain.

[0144] Nonlinear error feedback control law:

[0145] Combining the outputs of the tracking differentiator and the extended state observer, a nonlinear error feedback control law is designed:

[0146] (17)

[0147] (18)

[0148] Where fal(e, α, δ) is a nonlinear function, and its form is shown in formula (17). e1=v1−z1 is the velocity tracking error; e2=v2−z2 is the acceleration error; α1, α2∈(0,1) are nonlinear factors that determine the convergence speed; δ is the linear region threshold to prevent high-frequency chattering; k p , k d are the proportional and derivative gains.

[0149] According to the above analysis, the fuzzy active disturbance rejection control structure of the permanent magnet synchronous motor in the airborne suspension lifting system can be obtained as follows: Figure 5 shown.

[0150] The control synthesis module is the execution hub of the dual permanent magnet synchronous motor cooperative control system. Its core task is to integrate the local fuzzy anti-disturbance control and the global consistency correction signal to generate a dynamically optimized drive command. Specifically, this module receives the local control quantity from each motor at the bottom layer, such as the anti-disturbance compensation u output by the fuzzy anti-disturbance controller. 01 and u 02 Coordinated correction items with the equalization issued by the upper layer and , signal synthesis is completed through linear superposition, and finally output to the inverter to generate PWM modulation signal.

[0151] The core equation controlling the synthesis module is:

[0152] (19)

[0153] This embodiment discloses a cross-coupling cooperative control method for dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system, including:

[0154] S1. Design of a consistency protocol based on dynamic weight matrix and cross-coupling error allocation. Its core innovation lies in combining the dynamic adjacency matrix topology with the dual-motor cross-coupling error allocation mechanism to construct a nonlinear consistency protocol, breaking through the limitations of traditional fixed weight algorithms. By defining the weight function as a ij (t), dynamically integrate the speed difference and position difference parameters, and adjust the information coupling strength between the motors in real time. At the same time, an error distribution method based on the load inertia ratio J1 / J2=η is proposed. ω,1 / e ω,2 =η, utilizing the proportional factor η to achieve dynamic disturbance balancing and significantly mitigate the risk of single-motor overload. Compared to traditional combination methods, the dynamic characteristics of the adjacency matrix synergize with the physical constraints of error distribution, enabling the algorithm to ensure rapid convergence of the total error even under sudden load changes. The tight coupling of these technical features results in functional gains in enhanced load adaptability and improved synchronization accuracy.

[0155] S2. Logical indivisibility of the fully closed-loop control architecture. The technical closed loop consists of four links: "global reference input → dynamic topology update → consistency correction term generation → dynamic error balance distribution → fuzzy active disturbance rejection control compensation output". Its logical indivisibility is reflected in the following:

[0156] a) The adjacency matrix weights are calculated in real time based on the rotation speed and position difference;

[0157] b) Consistency correction term u cc，iBased on the Laplace matrix, an error dynamic model is generated and injected. The error ratio is distributed according to the inertia ratio of the two machines to offset the impact of load disturbances on the synchronization of the two machines. Furthermore, by dynamically adjusting the gain α, a balanced compensation term is generated and injected into the lower-level controller.

[0158] c) Fuzzy active disturbance rejection control compensates for high-frequency disturbances that are not eliminated by the consistency layer through an extended state observer.

[0159] Deleting any link will result in closed-loop failure. For example, if fuzzy ADRC is used independently without the consistency layer, low-frequency synchronization errors cannot be suppressed. Removing dynamic weights will make it difficult to adapt to sudden load changes. The strong interconnectedness of the multi-level control architecture enables the complementary functions of "high-frequency disturbance suppression" and "low-frequency synchronization error elimination," creating a composite control effect that cannot be achieved by a single module.

[0160] S3 uses an extended state observer to compensate for system load disturbances and the asymmetric friction and pulsating torque of the motor itself. The consistency layer uses compensation terms generated by the Laplace matrix to address low-frequency synchronization errors and load distribution. This collaborative division of labor overcomes the bottleneck of traditional collaborative control, where high-frequency disturbance suppression and low-frequency error regulation interfere with each other.

[0161] S4. This method is specifically designed for electromechanical systems with dynamic loads and rigid linkage constraints. It achieves cross-level optimization through a distributed architecture of "global reference-local execution" and solves two key problems:

[0162] a) Dynamic coupling error between axes: Avoid excessive stress in the mechanical connection by adjusting the error distribution coefficient η based on the load eccentricity;

[0163] b) Asynchronous communication delay: Introduce a time lag compensation term in the dynamic weight function ij (t-τ), eliminating the phase lag caused by network transmission.

[0164] The synergistic effect of the weight dynamics and actuator robustness in the technical features enables the system to maintain trajectory tracking accuracy under complex working conditions. Compared with traditional master-slave control strategies, its anti-interference ability and life cycle are significantly improved.

[0165] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this disclosure are merely illustrative and not restrictive, and should not be construed as necessarily possessed by each embodiment of the present disclosure. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, rather than as limitations. These details do not limit the present disclosure to necessarily being implemented using these specific details.

[0166] In the present disclosure, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. The block diagrams of the devices, devices, equipment, and systems involved in the present disclosure are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "including," "comprising," "having," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0167] Additionally, as used herein, "or" used in a list of items beginning with "at least one" indicates a separate list, so that, for example, a list of "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not mean that the example described is preferred or better than other examples.

[0168] It should also be noted that in the system and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0169] Various changes, substitutions, and modifications may be made to the technology described herein without departing from the teachings defined by the appended claims. Moreover, the scope of the claims of this disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of things, means, methods, and actions described above. Currently existing or later developed processes, machines, manufactures, compositions of things, means, methods, or actions that perform substantially the same function or achieve substantially the same results as the corresponding aspects described herein may be utilized. Accordingly, the appended claims include within their scope such processes, machines, manufactures, compositions of things, means, methods, or actions.

[0170] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0171] The above description has been provided for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A cross-coupling cooperative control method for dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system, characterized in that: include: Obtain global instructions and real-time status feedback of dual motors; Based on global instructions and real-time state feedback, dynamic topology and dynamic adjustment weights are constructed to obtain the weights of the dynamic topology; Generate collaborative corrections based on dynamic topology weights and consensus protocols; Dynamic error balancing distribution under load disturbance based on cooperative correction; The dual motors are controlled based on the error balance distribution results.

2. The cross-coupling cooperative control method of dual permanent magnet synchronous motors for an aircraft-mounted suspension lifting system according to claim 1, characterized in that: The acquisition of global instructions and real-time status feedback of the dual motors includes: Align the time of the acquired global command signal and the real-time status feedback signal; The global instruction includes a speed reference value and a position reference value; It is real-time status feedback, including actual speed, position angle and load torque disturbance.

3. The cross-coupling cooperative control method of dual permanent magnet synchronous motors for an aircraft-mounted suspension lifting system according to claim 2, characterized in that: The method of constructing a dynamic topology and dynamically adjusting weights based on global instructions and real-time state feedback to obtain the weights of the dynamic topology includes: The difference in speed and position angle of the two motors is integrated through nonlinear functions, and the weight value of the connection between the motors is updated in real time. After the weight values ​​are calculated, the Laplace matrix of the corresponding communication topology is generated, and the strong connectivity of the topology is verified through the Laplace matrix algebraic connectivity eigenvalue.

4. The cross-coupling cooperative control method of dual permanent magnet synchronous motors for an aircraft-mounted suspension lifting system according to claim 3, characterized in that: Generate collaborative corrections based on dynamic topology weights and consensus protocols, including: Based on the weights of the dynamic topology, the speed coordination error vector and position coordination error term of the dual motors are calculated. The coordination error vector and coordination error term are input into the consistency protocol to generate the coordination control compensation.

5. The cross-coupling cooperative control method of dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system according to claim 4, characterized in that: The dynamic error balancing distribution under load disturbance based on the collaborative correction amount includes: Based on the synergistic compensation amount, an error dynamic model is established; Error distribution is performed based on the inertia ratio of the two motors and the error dynamic model; The gain is dynamically adjusted based on the error dynamic model after error distribution to generate balanced compensation terms, so that the dual motors maintain synchronous performance under dynamic loads.

6. The cross-coupling cooperative control method of dual permanent magnet synchronous motors for an aircraft-mounted suspension lifting system according to claim 5, characterized in that: The controlling of the dual motors based on the error balance distribution result includes: The error balance distribution result is input into the motor control layer, and the permanent magnet synchronous motor is controlled through the motor control layer; The motor control layer includes a control synthesis module and a PMSM control channel, and the output signal of the control synthesis module is input into the PMSM control channel; The PMSM control channel includes a fuzzy active disturbance rejection controller tracking differentiator, an extended state observer and a nonlinear error feedback. The output signal of the fuzzy active disturbance rejection controller tracking differentiator is input into the extended state observer, the output signal of the extended state observer is input into the nonlinear error feedback, and the output signal of the nonlinear error feedback is input into a control synthesis module.

7. The cross-coupling cooperative control method of dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system according to claim 6, characterized in that: The controlling of the dual motors based on the error balance distribution result includes: A PMSM mathematical model is established, and the PMSM mathematical model formula is: ， in, is the electromagnetic torque; P is the number of pole pairs of the permanent magnet synchronous motor, J is the moment of inertia of the PMSM, is the load torque, is the rotor mechanical angular velocity, B is the viscous friction coefficient, and t is time.

8. The cross-coupling cooperative control method of dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system according to claim 7, characterized in that: The formula of the extended state observer is: ， Among them, z1 is The estimated value of z2 is The estimated value of ; z3 is the estimated total disturbance term; , , is the observer gain, To control the gain.

9. The cross-coupling cooperative control method of dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system according to claim 8, characterized in that: The fuzzy active disturbance rejection controller tracking differentiator includes: The motor speed error and speed error differential are used as the input of the fuzzy controller, and fuzzy reasoning is used to perform real-time correction on the three parameters β0, β1, and β2 of the extended state observer to obtain the corresponding integral gain correction coefficient Δβ0, proportional gain correction coefficient Δβ1, and differential gain correction coefficient Δβ2.

10. The cross-coupling cooperative control method of dual permanent magnet synchronous motors in an aircraft-mounted suspension lifting system according to claim 9, characterized in that: Including the gain coefficient of the extended state observer , , Make adjustments, the specific adjustments are as follows: When the speed error amplitude is greater than the set condition, the proportional gain β1 and its correction value Δβ1 are increased, while the differential gain β2 is reduced to prevent the correction value Δβ2 from being oversaturated and causing overshoot, and the integral gain β0 and the correction value Δβ0 are set to zero; When the speed error and its rate of change are both within the set conditions, reduce β1 and Δβ1 and set β0 to the set medium value; When the speed error is less than the set error value, increase the integral gain β0 and proportional gain β1 and their corresponding correction values ​​Δβ0 and Δβ1; If the error change rate is greater than the first set error change rate, β1, β2 and their corrections Δβ1, Δβ2 are reduced, and the values ​​of the integral gains β0 and Δβ0 are increased; when the change rate is less than the second set error change rate, β2 and Δβ2 are increased, and the adjustments to β0, β1 and their corrections Δβ0, Δβ1 are combined to achieve more balanced dynamic and steady-state performance, and the second set error change rate is less than the first set error change rate.

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