Optimization method and device of magnetic suspension positioning platform, equipment and storage medium

Abstract

The invention relates to the technical field of structure optimization, in particular to an optimization method and device of a magnetic suspension positioning platform, equipment and a storage medium. The method comprises the following steps: constructing a target function based on a to-be-optimized parameter and generating an initial quantum code; measuring the initial quantum code and obtaining an initial fitness value; updating and measuring a preset left antenna code and a preset right antenna code according to the initial fitness value, and obtaining a left fitness value and a right fitness value based on a measurement result; updating the initial quantum code according to the left fitness value and the right fitness value, and obtaining an updated fitness value; if the updated fitness value is smaller than the preset fitness value, replacing the preset fitness value with the updated fitness value, returning to execute the operation of measuring the initial quantum code by adopting the preset measurement rule, and repeating iteration to obtain an optimal solution; according to the optimization method disclosed by the invention, the optimal solution of the to-be-optimized parameters can be quickly obtained, and the energy use efficiency of the magnetic suspension positioning platform is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of structural optimization, and particularly to an optimization method, device, equipment and storage medium for a magnetic levitation positioning platform. Background Art

[0002] Industrial equipment has an increasing demand for multi-degree-of-freedom precise positioning of workpieces or workpiece tables, and magnetic levitation technology has become a key technology for achieving high-precision positioning. For example, in a lithography machine, key components such as a wafer stage and a mask stage need to achieve high-precision multi-degree-of-freedom positioning. However, traditional drive motor support systems face many challenges in these applications. If a drive motor support is directly adopted, it will not only increase the load and heat generation of the motor, but also may lead to a decrease in positioning accuracy. Especially in high-precision measurements, the overheating phenomenon of the motor may cause non-contact measurement errors.

[0003] The magnetic levitation ultra-precision platform, by adopting a non-contact gravity compensation structure of permanent magnets, can effectively avoid the problems of friction and wear in traditional air-floating systems and rail supports, and at the same time improve the system stiffness. In addition, the magnetic levitation positioning platform does not require complex precision machining and is suitable for a vacuum environment, which makes it have a wide application prospect in high-precision applications such as semiconductor manufacturing and lithography.

[0004] However, the existing magnetic levitation positioning platforms still have certain limitations. Although they avoid the mechanical contact problems of traditional support systems and improve stability and accuracy, they still rely on electromagnetic force to maintain the levitation state. To ensure stability and high-frequency response during the movement process, the platform must provide sufficient current to adjust the magnetic field strength. Especially during rapid movement processes such as startup, stop or acceleration, the current demand will increase significantly. This not only results in high energy consumption, but also may generate significant thermal effects, thereby affecting the stability, lifespan and power supply requirements of the system. At the same time, large currents may cause electromagnetic interference, affecting surrounding electronic devices and measuring instruments.

[0005] The existing research solutions for optimizing magnetic levitation platforms mainly focus on the optimization of the structure of magnetic levitation positioning platforms, especially the design that is easy to maintain, easy to control and has high precision, and less involve the optimization problem of platform size. It can be seen that the existing technology still needs to be improved. Summary of the Invention

[0006] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide an optimization method for a magnetic levitation positioning platform, which can quickly obtain the optimal solutions of the coil parameters and array parameters to be optimized, and achieve the goals of improving energy utilization efficiency and optimizing the platform structure size.

[0007] The first aspect of the present invention provides an optimization method for a magnetic levitation positioning platform, including: constructing an objective function based on the coil parameters to be optimized and the array parameters to be optimized, and generating an initial quantum encoding based on the coil parameters to be optimized and the array parameters to be optimized; measuring the initial quantum encoding using a preset measurement rule to obtain an initial binary encoding, and obtaining an initial fitness value based on the initial binary encoding and the objective function; updating the preset left antenna encoding and right antenna encoding according to the initial binary encoding and the initial fitness value using a preset update rule; measuring the updated left antenna encoding and the updated right antenna encoding respectively to obtain a left binary encoding and a right binary encoding, and obtaining a left fitness value and a right fitness value based on the left binary encoding, the right binary encoding and the objective function; updating the initial quantum encoding using a preset update rule according to the updated left antenna encoding, the updated right antenna encoding and the corresponding left fitness value and right fitness value respectively to obtain an updated quantum encoding, and obtaining an updated fitness value based on the updated quantum encoding and the objective function; if the updated fitness value < the preset fitness value, then replacing the preset fitness value with the updated fitness value, and returning to execute measuring the initial quantum encoding using the preset measurement rule; when a preset iteration stop condition is satisfied, obtaining the best fitness value, and outputting an optimal solution corresponding to the best fitness value.

[0008] Optionally, in the first implementation manner of the first aspect of the present invention, the constructing an objective function based on the coil parameters to be optimized and the array parameters to be optimized, and generating an initial quantum encoding based on the coil parameters to be optimized and the array parameters to be optimized includes: constructing a calculation formula for magnetic flux density and a calculation formula for suspension force output based on the coil parameters to be optimized and the array parameters to be optimized, and constructing a maximization optimization function based on the calculation formula for magnetic flux density and the calculation formula for suspension force output; performing an inversion process on the maximization optimization function to obtain the objective function; each coil parameter to be optimized and each array parameter to be optimized are respectively expressed by k quantum bits, and each quantum bit expresses a superposition state of two quantum states; integrating all the quantum bits to obtain the initial quantum encoding.

[0009] Optionally, in the second implementation manner of the first aspect of the present invention, the measuring the initial quantum encoding using a preset measurement rule to obtain an initial binary encoding, and obtaining an initial fitness value based on the initial binary encoding and the objective function includes: obtaining a preset value selection range, and randomly selecting a random number from the preset value selection range; measuring the initial quantum encoding based on the selected random number to obtain the initial binary encoding; converting the initial binary encoding into a real number encoding, and performing an anti-normalization process on the real number encoding to obtain an initial solution; substituting the initial solution into the objective function to obtain the initial fitness value.

[0010] Optionally, in the third implementation manner of the first aspect of the present invention, the updating of the preset left antenna encoding and right antenna encoding according to the initial binary encoding and the initial fitness value includes: obtaining a preset initial search distance, calculating a search quantum rotation gate angle according to the initial position corresponding to the initial solution and the initial search distance; and updating the preset left antenna encoding and right antenna encoding based on the calculated search quantum rotation gate angle and the initial binary encoding according to a preset updating rule.

[0011] Optionally, in the fourth implementation manner of the first aspect of the present invention, the measuring of the updated left antenna encoding and the updated right antenna encoding respectively to obtain a left binary encoding and a right binary encoding, and obtaining a left fitness value and a right fitness value based on the left binary encoding, the right binary encoding and the objective function includes: measuring the updated left antenna encoding and the updated right antenna encoding respectively to obtain a left binary encoding and a right binary encoding; respectively converting the left binary encoding and the right binary encoding into a left real encoding and a right real encoding, and respectively performing an anti-normalization process on the left real encoding and the right real encoding to obtain a left solution and a right solution; and respectively substituting the left solution and the right solution into the objective function to obtain a left fitness value and a right fitness value.

[0012] Optionally, in the fifth implementation manner of the first aspect of the present invention, the updating of the initial quantum encoding according to the updated left antenna encoding, the updated right antenna encoding and the corresponding left fitness value and right fitness value respectively to obtain an updated quantum encoding, and obtaining an updated fitness value based on the updated quantum encoding and the objective function includes: obtaining a preset initial moving distance, calculating a moving quantum gate rotation angle according to the initial position corresponding to the initial solution and the preset initial moving distance; updating the initial quantum encoding based on the calculated moving quantum rotation gate angle, the initial binary encoding, the left fitness value and the right fitness value according to a preset updating rule to obtain an updated quantum encoding; measuring the updated quantum encoding to obtain an updated binary encoding; converting the updated binary encoding into an updated real encoding, and performing an anti-normalization process on the updated real encoding to obtain an updated solution; and substituting the updated solution into the objective function to obtain an updated fitness value.

[0013] Optionally, in the sixth implementation manner of the first aspect of the present invention, if the updated fitness value < the preset fitness value, then the updated fitness value is used to replace the preset fitness value, and the execution is returned to measure the initial quantum encoding using the preset measurement rule, including: if the updated fitness value < the preset fitness value, then the updated fitness value is used to replace the preset fitness value, and the initial search distance and the initial moving distance are updated based on the preset update rule, and then the execution is returned to measure the initial quantum encoding using the preset measurement rule; if the updated fitness value ≥ the preset fitness value, then the initial search distance and the initial moving distance are updated based on the preset update rule, and the execution is returned to measure the initial quantum encoding using the preset measurement rule.

[0014] The second aspect of the present invention provides an optimization device for a maglev positioning platform, including: a construction module, configured to construct an objective function based on the coil parameters to be optimized and the array parameters to be optimized, and generate an initial quantum encoding based on the coil parameters to be optimized and the array parameters to be optimized; a first measurement module, configured to measure the initial quantum encoding using a preset measurement rule to obtain an initial binary encoding, and obtain an initial fitness value based on the initial binary encoding and the objective function; a first update module, configured to update the preset left antenna encoding and right antenna encoding according to the initial binary encoding and the initial fitness value using a preset update rule; a second measurement module, configured to measure the updated left antenna encoding and the updated right antenna encoding respectively to obtain a left binary encoding and a right binary encoding, and obtain a left fitness value and a right fitness value based on the left binary encoding, the right binary encoding and the objective function; a second update module, configured to update the initial quantum encoding according to the updated left antenna encoding, the updated right antenna encoding and the corresponding left fitness value and right fitness value respectively using a preset update rule to obtain an updated quantum encoding, and obtain an updated fitness value based on the updated quantum encoding and the objective function; a judgment module, configured to if the updated fitness value < the preset fitness value, then use the updated fitness value to replace the preset fitness value, and return to execute the measurement of the initial quantum encoding using the preset measurement rule; an output module, configured to when a preset iteration stop condition is satisfied, obtain the best fitness value, and output an optimal solution corresponding to the best fitness value.

[0015] The third aspect of the present invention provides an optimization device for a maglev positioning platform, where the optimization device for the maglev positioning platform includes: a memory and at least one processor, and instructions are stored in the memory; at least one of the processors invokes the instructions in the memory so that the optimization device for the maglev positioning platform executes each step of the optimization method for the maglev positioning platform described in any one of the above.

[0016] A fourth aspect of the present invention provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, each step of the optimization method of the magnetic levitation positioning platform described in any one of the above is implemented.

[0017] In the technical solution of the present invention, by combining quantum coding technology to optimize coil parameters and array parameters, an optimal solution for the coil parameters to be optimized and the array parameters to be optimized can be quickly obtained, that is, an optimization solution for the coil size structure and an optimization solution for the Halbach array size structure can be quickly obtained. While meeting the requirements of levitation force and stability, the optimized magnetic levitation positioning platform significantly reduces the working energy consumption, improves the energy use efficiency of the magnetic levitation positioning platform, that is, achieves the goal of reducing the working power consumption and optimizing the platform structure size, thereby improving the overall performance of the magnetic levitation positioning platform in multiple aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a logical flowchart of the optimization method of the magnetic levitation positioning platform provided by an embodiment of the present invention;

[0019] Figure 2 is a schematic structural diagram of the optimization device of the magnetic levitation positioning platform provided by an embodiment of the present invention;

[0020] Figure 3 is a schematic structural diagram of the optimization device of the magnetic levitation positioning platform provided by an embodiment of the present invention;

[0021] Figure 4 is a schematic structural diagram of the magnetic levitation positioning platform provided by an embodiment of the present invention;

[0022] Figure 5 is a schematic diagram of the coil parameters to be optimized and the array parameters to be optimized provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The present invention provides an optimization method, device, device and storage medium for a magnetic levitation positioning platform. In the present invention, the terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order different from that shown or described herein. In addition, the term "comprising" or "having" and any variation thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0024] To more clearly illustrate the optimization process of the present invention, Figure 4 An example of a magnetic levitation positioning platform is shown. The overall platform consists of a moving platform and a base. In the design, the decoupling of levitation motion and in-plane driving motion is achieved; the levitation motion is completed by the cooperation of four Halbach arrays installed on the mover and inductive coils on the stator; these four Halbach arrays are symmetrically distributed at the four corners of the moving platform. Theoretically, each array can compensate for one-fourth of the gravity and simultaneously control three degrees of freedom, including the vertical direction (z-axis) and rotations about the x-axis (θx) and y-axis (θy); in addition, to balance the self-weight of the platform, four small permanent magnets are arranged on the base and cooperate with the Halbach arrays to generate sufficient levitation force for compensation, thereby reducing the current demand during subsequent loading; the driving in the horizontal plane is achieved by four voice coil motors, and each direction is powered by two voice coil motors respectively to ensure the smooth movement of the platform; in Figure 4 , the front and rear arranged voice coil motors are responsible for the motion control in the x-direction and rotation about the z-axis (θz), while the left and right arranged voice coil motors are responsible for the motion control in the y-direction and θz; to avoid heat transfer to the loading area and reduce cable interference between the moving platform and the base, all coils are designed to be installed on the base, and the corresponding mover components are fixed to the moving platform.

[0025] For ease of understanding, the specific process of the embodiment of the present invention is described below. Please refer to Figure 1 , an embodiment of the optimization method of the magnetic levitation positioning platform in the embodiment of the present invention includes:

[0026] 101. Construct an objective function based on the coil parameters to be optimized and the array parameters to be optimized, and generate an initial quantum encoding based on the coil parameters to be optimized and the array parameters to be optimized;

[0027] 102. Measure the initial quantum encoding using a preset measurement rule to obtain an initial binary encoding, and obtain an initial fitness value based on the initial binary encoding and the objective function;

[0028] 103. Update the preset left antenna encoding and right antenna encoding according to the initial binary encoding and the initial fitness value using a preset update rule;

[0029] 104. Measure the updated left antenna encoding and the updated right antenna encoding respectively to obtain a left binary encoding and a right binary encoding, and obtain a left fitness value and a right fitness value based on the left binary encoding, the right binary encoding and the objective function;

[0030] 105. Update the initial quantum encoding using a preset update rule based on the updated left antenna encoding, the updated right antenna encoding, and their respective corresponding left fitness value and right fitness value to obtain an updated quantum encoding, and obtain an updated fitness value based on the updated quantum encoding and the objective function;

[0031] 106. If the updated fitness value < the preset fitness value, then replace the preset fitness value with the updated fitness value, and return to execute measuring the initial quantum encoding using the preset measurement rule;

[0032] 107. When the preset iteration stop condition is satisfied, obtain the best fitness value, and output the optimal solution corresponding to the best fitness value;

[0033] In this embodiment, the preset iteration stop condition may be the preset maximum number of iterations, and the preset maximum number of iterations can be preset by the designer according to the accuracy requirements of the solution; the best fitness value is the smaller value after the last iteration comparison, that is, in the last iteration, if the updated fitness value < the fitness value of the previous iteration, then the best fitness value is the updated fitness value, if the updated fitness value ≥ the fitness value of the previous iteration, then the best fitness value is the fitness value of the previous iteration; the optimal solution x best (={a, b, c, d, e, f}) and its corresponding optimal fitness value G'(x best ), that is, the formula (5) is successfully solved. This optimal solution corresponds to the optimal Halbach array size and coil size, and thus the magnetic levitation positioning platform can be processed according to the parameter values.

[0034] This application discloses an optimization method for a magnetic levitation positioning platform. By combining quantum encoding technology, the coil parameters and array parameters are optimized, and the optimal solutions of the coil parameters to be optimized and the array parameters to be optimized can be quickly obtained, that is, the optimization solutions of the coil size structure and the Halbach array size structure can be quickly obtained. The optimized magnetic levitation positioning platform can significantly reduce the working energy consumption while meeting the requirements of levitation force and stability, improve the energy use efficiency of the magnetic levitation positioning platform, that is, achieve the goals of reducing the working power consumption and optimizing the platform structure size, thereby improving the overall performance of the magnetic levitation positioning platform in multiple aspects.

[0035] In this embodiment, the constructing the objective function based on the coil parameters to be optimized and the array parameters to be optimized, and generating the initial quantum encoding based on the coil parameters to be optimized and the array parameters to be optimized specifically includes:

[0036] 201. Construct the calculation formula of magnetic flux density and the calculation formula of suspension force output based on the coil parameters to be optimized and the array parameters to be optimized, and construct the maximization optimization function based on the calculation formula of magnetic flux density and the calculation formula of suspension force output;

[0037] In this embodiment, let the magnetic flux density per unit converter mass be f1, and let the suspension force output per unit power be f2, then:

[0038]

[0039] Among them, R is the coil resistance, which is related to the resistivity ρ, perimeter L, and cross-sectional area S of the coil, as shown in Equation (3); please refer to Figure 5 , the perimeter L = 4a, where a is the outer diameter of the coil, and the cross-sectional area S = (a 2 -b 2 ) * 0.2, where b is the inner diameter of the coil, that is, the coil parameters to be optimized include the outer diameter a and the inner diameter b of the coil.

[0040] Furthermore, m is the mass of the magnetic levitation positioning platform, is the magnetic flux density, is the generated Lorentz force, and |·| is the modulus operation; represents the current density, which is a known given value in this embodiment; please refer to Figure 5 , the Halbach array consists of two identical small magnets and one large magnet, and the array parameters to be optimized include the length c of the three magnets (the three magnets have the same length), the height d of the small magnet, the height e of the large magnet, and the width f of the three magnets (the three magnets have the same width); the size of the Halbach array affects the mass m of the entire magnetic levitation positioning platform and the distribution of the magnetic field, that is, the magnetic flux density which in turn affects the force on the coil in the magnetic field, that is, the Lorentz force Therefore, by optimizing the size structure of the Halbach array, the energy consumption of the magnetic levitation positioning platform can be optimized; in this embodiment, the magnetic flux density and the Lorentz force

[0041] Multiply the magnetic flux density f1 and the suspension force output f2 to obtain the maximization optimization function G,

[0042]

[0043] Since general intelligent optimization methods are oriented towards minimizing the objective, therefore, it is necessary to perform an inversion process on the maximum optimization function to obtain the objective function.

[0044] 202. Perform an inversion process on the maximization optimization function to obtain the objective function;

[0045]

[0046] Among them, Take a fixed value.

[0047] 203. Each coil parameter to be optimized and each array parameter to be optimized are respectively expressed by k qubits, and each qubit represents a superposition state of two quantum states;

[0048] In this embodiment, to solve the optimization problem shown in Equation (5), the present application proposes a variant of the beetle antenna algorithm based on three mechanisms: quantum state encoding, variable normalization, and adaptive step size; the beetle antenna algorithm is an intelligent optimization algorithm that simulates the foraging behavior of beetles. By simulating the foraging process of beetles, the two antennae (left antenna and right antenna) of the beetle are used to sense the food odor concentration, so as to determine the forward direction and finally find the location of the food; in the algorithm implementation, the two antennae are defined as two solutions, and the food odor concentration is expressed by a specific objective function, and the concentration size is expressed by the fitness value.

[0049] In this embodiment, an initial quantum encoding is generated. Each design variable, that is, the parameter to be optimized, is expressed by k qubits. Each qubit can simultaneously represent a superposition state of two quantum states, and the probabilities of being in different superposition states add up to 1, as shown in Equations (6) and (7); among them, |0> and |1> respectively represent the superposition states of spin up and spin down. Therefore, a qubit can simultaneously contain the information of |0> and |1>. The quantum encoding essentially records the occurrence probabilities of the two superposition states. Therefore, using α and β to represent the choices of |0> and |1>, it can be denoted as (α, β);

[0050] |φ> = α|0> + β|1> (6)

[0051] |α| 2 + |β| 2 = 1 (7)

[0052] In the formula, |α| 2 and |β| 2 respectively represent the actual probabilities of taking the superposition states of |0> and |1>.

[0053] Then when there are n design variables in a problem, which is 6 in this embodiment, the corresponding k - qubit encoding can be written as Equation (8):

[0054]

[0055] where, q t represents the initial quantum encoding.

[0056] 204. Integrate all qubits to obtain the initial quantum encoding;

[0057] In this embodiment, by taking the negation of the maximization optimization function, an objective function for finding the minimum value is obtained, which not only simplifies the problem but also enables the quantum algorithm to search and optimize more efficiently. When dealing with such problems, the quantum algorithm can utilize characteristics such as quantum superposition and entanglement to explore multiple possible solutions simultaneously, significantly improving the efficiency of the optimization process. Further, each coil parameter and array parameter to be optimized is expressed by k qubits, and each qubit can represent the superposition state of two quantum states. This expression method greatly expands the representation range of the parameters, enabling the algorithm to search for the optimal solution in a broader parameter space. This flexibility not only improves the optimization accuracy but also increases the possibility of finding the global optimal solution.

[0058] In this embodiment, measuring the initial quantum encoding using a preset measurement rule to obtain an initial binary encoding, and obtaining an initial fitness value based on the initial binary encoding and the objective function specifically includes:

[0059] 301. Obtain a preset value selection range, and randomly select a random number from the preset value selection range;

[0060] In this embodiment, the preset value selection range can be the range [0, 1].

[0061] 302. Measure the initial quantum encoding based on the selected random number to obtain an initial binary encoding;

[0062] In this embodiment, at the t-th iteration, the probability that the j-th qubit of the i-th design variable (i = 1,..., n; j = 1,..., k) takes the |0> superposition state is less than the random number, then the binary encoding corresponding to this position is assigned 1, otherwise assigned 0, that is:

[0063]

[0064] By measuring each qubit once, a binary encoding can be obtained

[0065]

[0066] 303. Convert the initial binary encoding to a real number encoding, and perform an inverse normalization process on the real number encoding to obtain an initial solution;

[0067] In this embodiment, let the real number encoding be then:

[0068]

[0069] Then, according to the upper and lower bounds LB and UB of each dimension of the design variables, the real number coding can be inverse-normalized to obtain the actual parameter value x t , specifically:

[0070]

[0071] The actual parameter value x t i.e., the initial solution, where

[0072]

[0073] 304. Substitute the initial solution into the objective function to obtain the initial fitness value.

[0074] In this embodiment, according to the initial binary coding and the initial fitness value, the preset left antenna coding and right antenna coding are updated by using a preset update rule, specifically including:

[0075] 401. Obtain the preset initial search distance, and calculate the search quantum rotation gate angle according to the initial position corresponding to the initial solution and the initial search distance;

[0076] In this embodiment, the search distance of the longhorn beetle antenna at time t is δ t , and the calculation method of the search quantum rotation gate angle θ ij is:

[0077]

[0078] where represents the directionality of the quantum coding, that is, the initial position corresponding to the initial solution.

[0079] 402. Update the preset left antenna coding and right antenna coding based on the calculated search quantum rotation gate angle and the initial binary coding according to the preset update rule;

[0080] In this embodiment, Equation (13) is used to update the left antenna coding Equation (14) is used to update the right antenna coding U(θ ij ) is the implementation formula of the quantum rotation gate. Essentially, it is a transformation matrix, representing the coordinate update matrix after a point in the two-dimensional coordinate system rotates around the origin by an angle θ ij . In this algorithm, it is the longhorn beetle antenna rotating around the current position of the longhorn beetle; and from the comparison of Equations (13) and (14), it can be seen that and the update rules only change the directionality of the rotation angle;

[0081]

[0082] Among them, represents the updated left antenna code, represents the updated right antenna code.

[0083] In this embodiment, the updated left antenna code and the updated right antenna code are respectively measured to obtain a left binary code and a right binary code, and a left fitness value and a right fitness value are obtained based on the left binary code, the right binary code, and the objective function. Specifically, it includes:

[0084] 501. The updated left antenna code and the updated right antenna code are respectively measured to obtain a left binary code and a right binary code;

[0085] In this embodiment, based on Equation (9) and a preset measurement rule, the updated left antenna code and the updated right antenna code are measured to obtain a left binary code and a right binary code

[0086] 502. The left binary code and the right binary code are respectively converted into a left real number code and a right real number code, and the left real number code and the right real number code are respectively subjected to anti-normalization processing to obtain a left solution and a right solution;

[0087] In this embodiment, let the left real number code be Let the right real number code be Let the left solution be Let the right solution be

[0088] 503. The left solution and the right solution are respectively substituted into the objective function to obtain a left fitness value and a right fitness value;

[0089] In this embodiment, the left solution and the right solution are respectively substituted into the objective function to calculate the left fitness value and the right fitness value

[0090] In this embodiment, according to the updated left antenna code, the updated right antenna code, and the corresponding left fitness value and right fitness value, the initial quantum code is updated by using a preset update rule to obtain an updated quantum code, and an updated fitness value is obtained based on the updated quantum code and the objective function. Specifically, it includes:

[0091] 601. Obtain a preset initial moving distance, and calculate the moving quantum gate rotation angle according to the initial position corresponding to the initial solution and the preset initial moving distance;

[0092] In this embodiment, let the rotation angle of the mobile quantum gate be θ′ ij , and update the current quantum encoding q of the longhorn beetle t , denoted as q t+1 ;

[0093]

[0094] where d t is the moving distance that the longhorn beetle antennae need to move at time t, and sign(·) is the sign function.

[0095] 602. Update the initial quantum encoding based on the calculated rotation angle of the mobile quantum rotation gate, the initial binary encoding, the left fitness value, and the right fitness value according to a preset update rule to obtain an updated quantum encoding;

[0096] 603. Measure the updated quantum encoding to obtain an updated binary encoding;

[0097] In this embodiment, measure the updated quantum encoding q t+1 based on Equation (9) and a preset measurement rule to obtain an updated binary encoding p t+1 .

[0098] 604. Convert the updated binary encoding to an updated real-number encoding, and perform an anti-normalization process on the updated real-number encoding to obtain an updated solution;

[0099] In this embodiment, let the updated real-number encoding be Let the updated solution be x t+1 .

[0100] 605. Substitute the updated solution into the objective function to obtain an updated fitness value;

[0101] In this embodiment, let the updated fitness value be G'(x t+1 ).

[0102] In this embodiment, if the updated fitness value < the preset fitness value, then use the updated fitness value to replace the preset fitness value, and return to execute measuring the initial quantum encoding using the preset measurement rule, which specifically includes:

[0103] 701. If the updated fitness value < the preset fitness value, then use the updated fitness value to replace the preset fitness value, and update the initial search distance and the initial moving distance based on the preset update rule, and then return to execute measuring the initial quantum encoding using the preset measurement rule;

[0104] In this embodiment, when returning to execute the measurement of the initial quantum encoding using a preset measurement rule, a random number is randomly selected again within the preset value selection range to obtain a new measurement result based on the initial quantum encoding, that is, a new initial binary encoding is obtained.

[0105] 702. If the updated fitness value ≥ the preset fitness value, update the initial search distance and the initial movement distance based on the preset update rule, and return to execute the measurement of the initial quantum encoding using the preset measurement rule.

[0106] In this embodiment, the remaining parameters of the improved beetle antennae algorithm are updated according to equations (18)-(20):

[0107]

[0108] In the formula, η δ is the decay rate of the beetle antennae search distance, τ is a constant, K is the maximum number of iterations, and it is related to the beetle antennae search distance δ t+1 and the beetle antennae movement distance d t+1 at the (t + 1)-th iteration to form a fixed ratio between the two.

[0109] In this embodiment, since the improved beetle antennae algorithm can dynamically adjust the fitness value and the search strategy, it can converge to the global optimal solution faster during the search process; this fast convergence characteristic not only improves the solution speed of the algorithm, but also ensures the efficiency and stability of the solution process; further, the present application proposes an improved beetle antennae algorithm based on quantum state encoding, variable normalization, and an adaptive step size mechanism. By introducing qubit phase encoding and quantum rotation gates, the solution space is optimized and searched. This algorithm has stronger global search ability and effectively avoids the defect that the traditional beetle antennae algorithm is prone to falling into local optimality.

[0110] The optimization method of the magnetic levitation positioning platform in the embodiments of the present invention has been described above. Next, the optimization device of the magnetic levitation positioning platform in the embodiments of the present invention will be described. Please refer to Figure 2 One embodiment of the optimization device of the magnetic levitation positioning platform in the embodiments of the present invention includes:

[0111] A construction module 801, configured to construct an objective function based on the coil parameters to be optimized and the array parameters to be optimized, and generate an initial quantum encoding based on the coil parameters to be optimized and the array parameters to be optimized;

[0112] A first measurement module 802, configured to measure the initial quantum encoding using a preset measurement rule to obtain an initial binary encoding, and obtain an initial fitness value based on the initial binary encoding and the objective function;

[0113] The first update module 803 is configured to update the preset left antenna encoding and right antenna encoding according to the initial binary encoding and the initial fitness value by using a preset update rule;

[0114] The second measurement module 804 is configured to measure the updated left antenna encoding and the updated right antenna encoding respectively to obtain a left binary encoding and a right binary encoding, and obtain a left fitness value and a right fitness value based on the left binary encoding, the right binary encoding, and the objective function;

[0115] The second update module 805 is configured to update the initial quantum encoding according to the updated left antenna encoding, the updated right antenna encoding, and the corresponding left fitness value and right fitness value respectively by using a preset update rule to obtain an updated quantum encoding, and obtain an updated fitness value based on the updated quantum encoding and the objective function;

[0116] The judgment module 806 is configured to, if the updated fitness value < the preset fitness value, replace the preset fitness value with the updated fitness value, and return to execute measuring the initial quantum encoding by using the preset measurement rule;

[0117] The output module 807 is configured to obtain the best fitness value and output the optimal solution corresponding to the best fitness value when the preset iteration stop condition is satisfied.

[0118] Based on the same idea as the method in the above embodiment, the device provided in this application can implement the method of the above embodiment.

[0119] Above Figure 2 The optimization device of the maglev positioning platform in the embodiment of the present invention is described in detail from the perspective of modular functional entities. Next, the optimization device of the maglev positioning platform in the embodiment of the present invention will be described in detail from the perspective of hardware processing.

[0120] Figure 3FIG. 0 is a schematic structural diagram of an optimized device for a magnetic levitation positioning platform provided by an embodiment of the present invention. The optimized device 900 for the magnetic levitation positioning platform may vary greatly due to different configurations or performances, and may include one or more processors (central processing units, CPUs) 910 (for example, one or more processors) and a memory 920, and one or more storage media 930 (for example, one or more mass storage devices) storing application programs 933 or data 932. Among them, the memory 920 and the storage media 930 may be transient storage or persistent storage. The program stored in the storage media 930 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the optimized device 900 for the magnetic levitation positioning platform. Further, the processor 910 may be configured to communicate with the storage media 930 and execute a series of instruction operations in the storage media 930 on the optimized device 900 for the magnetic levitation positioning platform to implement the steps of the optimized method for the magnetic levitation positioning platform provided by the above method embodiments.

[0121] The optimized device 900 for the magnetic levitation positioning platform may further include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input / output interfaces 960, and / or one or more operating systems 931, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, and so on. Those skilled in the art can understand that Figure 3 the shown structural diagram of the optimized device for the magnetic levitation positioning platform does not constitute a limitation on the optimized device for the magnetic levitation positioning platform, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0122] The present invention also provides a computer-readable storage medium. The computer-readable storage medium may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions run on a computer, the computer is caused to execute the steps of the optimized method for the magnetic levitation positioning platform.

[0123] Those skilled in the art can clearly understand that for the sake of convenience and brevity of description, the specific working processes of the above-described system or device and unit can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0124] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0125] Finally, it should be noted that the above are only preferred examples of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for optimizing a magnetic levitation positioning platform, characterized in that: include: constructing an objective function based on the coil parameters to be optimized and the array parameters to be optimized, and generating an initial quantum code based on the coil parameters to be optimized and the array parameters to be optimized; The initial quantum code is measured using a preset measurement rule to obtain an initial binary code, and an initial fitness value is obtained based on the initial binary code and the objective function; According to the initial binary code and the initial fitness value, the preset left antenna code and the right antenna code are updated using a preset update rule; The updated left antenna code and the updated right antenna code are measured respectively to obtain a left binary code and a right binary code, and a left fitness value and a right fitness value are obtained based on the left binary code, the right binary code and the objective function; According to the updated left antenna code, the updated right antenna code and the corresponding left fitness value and right fitness value, the initial quantum code is updated using a preset update rule to obtain an updated quantum code, and an updated fitness value is obtained based on the updated quantum code and the objective function; If the updated fitness value is less than the preset fitness value, the preset fitness value is replaced by the updated fitness value, and the method returns to execute the measurement of the initial quantum code by using the preset measurement rule; When the preset iteration stop condition is met, the best fitness value is obtained, and the optimal solution corresponding to the best fitness value is output.

2. The optimization method of the magnetic suspension positioning platform according to claim 1, characterized in that: The objective function is constructed based on the coil parameters to be optimized and the array parameters to be optimized, and the initial quantum code is generated based on the coil parameters to be optimized and the array parameters to be optimized, including: A calculation formula for magnetic flux density and a calculation formula for suspension force output are constructed based on the coil parameters to be optimized and the array parameters to be optimized, and a maximization optimization function is constructed based on the calculation formula for magnetic flux density and the calculation formula for suspension force output; The maximum optimization function is inverted to obtain the objective function; Each coil parameter to be optimized and each array parameter to be optimized are expressed by k qubits, and each qubit expresses a superposition state of two quantum states; Integrate all quantum bits to obtain the initial quantum code.

3. The optimization method of the magnetic suspension positioning platform according to claim 1, characterized in that: The method of measuring the initial quantum code by using a preset measurement rule to obtain an initial binary code, and obtaining an initial fitness value based on the initial binary code and an objective function, includes: Get the preset value range, and randomly select a random number from the preset value range; The initial quantum code is measured based on the selected random number to obtain an initial binary code; Convert the initial binary code into a real number code, and perform a denormalization process on the real number code to obtain an initial solution; Substitute the initial solution into the objective function to obtain an initial fitness value.

4. The optimization method of the magnetic suspension positioning platform according to claim 3, characterized in that: The step of updating the preset left antenna code and the right antenna code according to the initial binary code and the initial fitness value by using a preset updating rule comprises: Obtaining a preset initial search distance, and calculating a search quantum revolving door angle according to an initial position and an initial search distance corresponding to an initial solution; According to the calculated search quantum rotating door angle and the initial binary code, the preset left antenna code and the right antenna code are updated based on the preset update rule.

5. The optimization method of the magnetic suspension positioning platform according to claim 4, characterized in that: The updated left antenna code and the updated right antenna code are measured respectively to obtain the left binary code and the right binary code, and the left fitness value and the right fitness value are obtained based on the left binary code, the right binary code and the objective function, including: The updated left antenna code and the updated right antenna code are measured respectively to obtain a left binary code and a right binary code; The left binary code and the right binary code are converted into the left real code and the right real code respectively, and the left real code and the right real code are denormalized respectively to obtain the left solution and the right solution; Substitute the left solution and the right solution into the objective function respectively to obtain the left fitness value and the right fitness value.

6. The optimization method of the magnetic suspension positioning platform according to claim 5, characterized in that: The method of updating the initial quantum code according to the updated left antenna code, the updated right antenna code and the corresponding left fitness value and right fitness value respectively using a preset update rule to obtain an updated quantum code, and obtaining an updated fitness value based on the updated quantum code and the objective function includes: Obtaining a preset initial moving distance, and calculating a rotation angle of a moving quantum gate according to an initial position corresponding to an initial solution and the preset initial moving distance; According to the calculated moving quantum revolving door angle, the initial binary code, the left fitness value and the right fitness value, the initial quantum code is updated based on a preset update rule to obtain an updated quantum code; The updated quantum code is measured to obtain the updated binary code; Convert the updated binary code into an updated real number code, and perform a denormalization process on the updated real number code to obtain an updated solution; Substitute the updated solution into the objective function to obtain an updated fitness value.

7. The optimization method of the magnetic suspension positioning platform according to claim 6, characterized in that: If the updated fitness value is less than the preset fitness value, the preset fitness value is replaced by the updated fitness value, and the method returns to execute the measurement of the initial quantum code by using the preset measurement rule, including: If the updated fitness value is less than the preset fitness value, the preset fitness value is replaced by the updated fitness value, and the initial search distance and the initial moving distance are updated based on the preset update rule, and then the method returns to execute the measurement of the initial quantum code using the preset measurement rule; If the updated fitness value is greater than or equal to the preset fitness value, the initial search distance and the initial moving distance are updated based on the preset update rule, and the method returns to execute the measurement of the initial quantum code using the preset measurement rule.

8. An optimization device for a magnetic suspension positioning platform, characterized in that: include: A construction module, used to construct an objective function based on the coil parameters to be optimized and the array parameters to be optimized, and to generate an initial quantum code based on the coil parameters to be optimized and the array parameters to be optimized; A first measurement module is used to measure the initial quantum code using a preset measurement rule to obtain an initial binary code, and obtain an initial fitness value based on the initial binary code and an objective function; A first updating module, used for updating the preset left antenna code and the right antenna code according to the initial binary code and the initial fitness value using a preset updating rule; A second measurement module is used to measure the updated left antenna code and the updated right antenna code respectively to obtain a left binary code and a right binary code, and obtain a left fitness value and a right fitness value based on the left binary code, the right binary code and the objective function; A second updating module is used to update the initial quantum code according to the updated left antenna code, the updated right antenna code and the corresponding left fitness value and right fitness value respectively, using a preset updating rule to obtain an updated quantum code, and obtain an updated fitness value based on the updated quantum code and the objective function; A judgment module, configured to replace the preset fitness value with the updated fitness value if the updated fitness value is less than the preset fitness value, and return to execute the measurement of the initial quantum code with the preset measurement rule; The output module is used to obtain the best fitness value when the preset iteration stop condition is met, and output the optimal solution corresponding to the best fitness value.

9. An optimization device for a magnetic levitation positioning platform, characterized in that: The optimization device of the magnetic suspension positioning platform includes: a memory and at least one processor, wherein instructions are stored in the memory; At least one of the processors calls the instructions in the memory to enable the optimization device of the magnetic levitation positioning platform to perform each step of the optimization method of the magnetic levitation positioning platform as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the various steps of the optimization method of the magnetic levitation positioning platform as described in any one of claims 1 to 7 are implemented.

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