Annular line motor speed fluctuation suppression method based on sliding mode iterative learning

Abstract

The invention discloses an annular line motor speed fluctuation suppression method based on sliding mode iterative learning, and belongs to the technical field of motor control. The method comprises the following steps: establishing an annular line motor speed state equation, defining a speed error, designing a sliding mode surface, designing a sliding mode reaching law, obtaining the output of a speed controller during k-th iteration by combining a formula, designing an iterative learning item, and estimating unknown periodic disturbance through iterative learning to accelerate the convergence speed of the iterative learning. And a sliding mode surface is adopted to replace a speed error in iterative learning. According to the invention, iterative learning is adopted to suppress speed fluctuation of the loop motor, and the method is used for speed closed-loop control of the loop motor by using the strong robustness of the sliding mode controller, and can be realized in a standard digital control chip without additional hardware modification. The speed fluctuation caused by various factors such as a driving strategy, stator module splicing and system disturbance is effectively inhibited, and the stability and the anti-disturbance capability of the system are enhanced.

Description

Technical Field

[0001] The invention relates to a method for suppressing speed fluctuation of a toroidal linear motor based on sliding mode iterative learning, and belongs to the technical field of motor control. Background Art

[0002] The ring line motor is composed of key components such as linear stator modules, arc stator modules, movers and position detection modules. Its unique design allows free splicing, thus adapting to the needs of various industrial production lines such as material transportation and liquid filling. However, this splicing structure also leads to the problem that the stator core is easy to break when the stator module is spliced, which directly leads to the fluctuation of the electromagnetic thrust of the mover, and is ultimately reflected in the speed fluctuation of the motor, affecting the stability and accuracy of the system.

[0003] The Chinese invention patent with the application date of July 19, 2023 and the application number of CN202310888383.X, entitled "A Passive Multi-Motor Ring Line Motor Drive Control System and Control Method", discloses that when the drive strategy disclosed is adopted, speed fluctuations will occur during the coil switching process. In addition, factors such as stator slot effect, current measurement error, and external system disturbances can also cause speed fluctuations.

[0004] The existing speed fluctuation suppression methods are mainly divided into two types:

[0005] One is the observer method based on current loop control, which converts the observed thrust or torque fluctuations into current and then compensates in the current loop. However, this method has limitations and can only be used to suppress the thrust or torque fluctuations estimated by the motor electrical system, but cannot estimate the thrust or torque fluctuations caused by the mechanical part (cogging force).

[0006] One is to apply advanced control algorithms to the speed loop and stabilize the speed fluctuation within a certain range through the strong robustness of the controller. Although this method has a wider range of applications and can deal with speed fluctuations generated by both the electrical system and the mechanical part, its effectiveness still needs to be improved when faced with complex and changeable disturbances.

[0007] Iterative learning control, as a control strategy based on the internal model principle, reduces the periodic fluctuation of speed by learning historical errors. It is widely used in speed fluctuation suppression and position tracking of servo systems. Ring line motors are usually used in situations where repetitive tasks are performed. When the entire motion process is regarded as a full cycle of iterative learning, the application of iterative learning can suppress all speed fluctuations in the process. However, the robustness of iterative learning control is an issue that needs to be paid attention to in practical applications. It usually needs to be connected in parallel or series with other controllers to improve the anti-disturbance capability.

[0008] As a robust control algorithm, sliding mode control is favored due to its insensitivity to system parameter changes and load disturbances. It can overcome system uncertainty problems, provide strong robustness, and provide a new idea for speed fluctuation suppression. Summary of the invention

[0009] In order to solve the problems existing in the background technology, the present invention provides a method for suppressing speed fluctuation of a ring line motor based on sliding mode iterative learning.

[0010] To achieve the above purpose, the present invention adopts the following technical solution: a method for suppressing speed fluctuation of a ring line motor based on sliding mode iterative learning, the method is executed in a DSP, an FPGA and an MCU. The method comprises the following steps:

[0011] S1: Establish the speed state equation of the ring line motor:

[0012]

[0013] In formula (1):

[0014] x(t) is the speed, which is the system state variable;

[0015] y(t) Output for the system;

[0016] f(x,t) is an unknown periodic disturbance;

[0017] M is the mass of the mover;

[0018] b is the ratio of the back electromotive force coefficient to the mass;

[0019] u(t) is the total output of the controller;

[0020] B(x,t) is the viscous friction coefficient;

[0021] F d is an external disturbance;

[0022] t is time;

[0023] S2: Define the speed error:

[0024] e(t)=v ref (t)-x(t) (2)

[0025] In formula (2):

[0026] e(t) is the velocity error;

[0027] v ref (t) is the given mover speed;

[0028] S3: Design a sliding mode iterative learning controller to suppress the speed fluctuation of the ring line motor.

[0029] S301: Design of sliding surface:

[0030]

[0031] In formula (3):

[0032] s(t) is the sliding surface;

[0033] c is the integration constant;

[0034] e(τ) is the velocity error at time τ;

[0035] τ is the integrated quantity;

[0036] To integrate the velocity error between time 0 and t;

[0037] S302: Deriving equation (3):

[0038]

[0039] S303: Substituting equation (1) and equation (2) into equation (4), we can obtain:

[0040]

[0041] S304: Design sliding mode reaching law:

[0042]

[0043] In formula (6):

[0044] ζ(t) is the sliding mode reaching law;

[0045] λ>0 is the switching gain;

[0046] η>0 is the convergence coefficient;

[0047] sgn(*) is the sign function, S305: Combine equations (5) and (6) to obtain the speed controller output at the kth iteration:

[0048]

[0049] In formula (7):

[0050] k is the number of iterations;

[0051] is the total output of the controller at the kth iteration;

[0052] is the output of the sliding mode controller;

[0053] Output of controller for iterative learning;

[0054] x k is the system state variable at the kth iteration;

[0055] is the recursive part of the unknown periodic perturbation f(x,t) that needs to be learned in the system;

[0056] Each iteration learns to control the output All are stored in memory.

[0057] S306: Design iterative learning items to estimate unknown periodic disturbances through iterative learning f(x,t) , that is, the unknown periodic disturbance that needs to be learned in the system f(x,t) The recursive part of In order to speed up the convergence of iterative learning, the sliding surface is used to replace the speed error in iterative learning:

[0058]

[0059] In formula (8):

[0060] The unknown periodic disturbance estimated for the kth iteration of learning f(x,t) value;

[0061] The unknown periodic disturbance estimated for the k-1th iteration of learning f(x,t) value;

[0062] γ is the learning gain;

[0063] δ is the sliding mode switching gain in iterative learning;

[0064] σ is the sliding mode approach coefficient in iterative learning.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] The present invention adopts iterative learning to suppress the speed fluctuation of the ring line motor, and utilizes the strong robustness of the sliding mode controller for the speed closed-loop control of the ring line motor. It can be implemented in a standard digital control chip (DSP, single-chip microcomputer, or FPGA, etc.) without additional hardware modification, and effectively suppresses the speed fluctuation caused by various factors such as driving strategy, stator module splicing, system disturbance, etc., enhances the stability and anti-disturbance ability of the system, reduces hardware cost, is easy to implement and maintain, and has extremely high application value in the field of industrial control. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 It is a structural schematic diagram of a ring-shaped wire motor which is the object of the present invention;

[0068] Figure 2 is a flow chart of the present invention;

[0069] Figure 3 It is the flow chart of sliding mode iterative learning controller;

[0070] Figure 4 This is the speed experiment waveform under the action of proportional integral controller;

[0071] Figure 5 This is the experimental waveform of speed error under the action of proportional integral controller;

[0072] Figure 6 It is a speed test waveform diagram under the action of the method of the present invention;

[0073] Figure 7 It is a waveform diagram of the speed error experiment under the action of the method of the present invention. DETAILED DESCRIPTION

[0074] The technical solution of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0075] A method for suppressing speed fluctuation of a toroidal motor based on sliding mode iterative learning, the method comprising the following steps:

[0076] S1: Establish the speed state equation of the ring line motor:

[0077]

[0078] In formula (1):

[0079] x(t) is the velocity, which is the system state variable;

[0080] y(t) is the system output;

[0081] f(x,t) is an unknown periodic disturbance;

[0082] M is the mass of the mover, which is obtained by mass measuring equipment such as a balance or spring scale;

[0083] b is the ratio of the back-EMF coefficient to the mass. The back-EMF coefficient is defined as the back-EMF of the motor at a speed of 1 m / s, which can be obtained through an oscilloscope.

[0084] u(t) is the total output of the controller;

[0085] B(x,t) is the viscous friction coefficient;

[0086] F d is an external disturbance;

[0087] t is time;

[0088] S2: Define the speed error:

[0089] e(t)=v ref (t)-x(t) (2)

[0090] In formula (2):

[0091] e(t) is the velocity error;

[0092] v ref (t) is the given mover speed;

[0093] S3: Designing a sliding mode iterative learning controller to suppress the speed fluctuation of the ring line motor is the core content of this invention. Figure 3 .

[0094] S301: Design of sliding surface:

[0095]

[0096] In formula (3):

[0097] s(t) is the sliding surface;

[0098] c is the integration constant;

[0099] e(τ) is the velocity error at time τ;

[0100] τ is the integrated quantity;

[0101] To integrate the velocity error between time 0 and t;

[0102] S302: Deriving equation (3):

[0103]

[0104] S303: Substituting equation (1) and equation (2) into equation (4), we can obtain:

[0105]

[0106] S304: Design sliding mode reaching law:

[0107]

[0108] In formula (6):

[0109] ζ(t) is the sliding mode reaching law;

[0110] λ>0 is the switching gain;

[0111] η>0 is the convergence coefficient;

[0112] sgn(*) is the sign function,

[0113] S305: Combine equations (5) and (6) to obtain the speed controller output at the kth iteration:

[0114]

[0115] In formula (7):

[0116] k is the number of iterations;

[0117] is the total output of the controller at the kth iteration;

[0118] for Figure 3 The output of the sliding mode controller in ;

[0119] for Figure 3 The iterative learning controller output in ;

[0120] x k is the system state variable at the kth iteration;

[0121] is the recursive part of the unknown periodic perturbation f(x,t) that needs to be learned in the system;

[0122] Each iteration learns to control the output All are stored in the memory, which can be a storage device that does not lose power when the power is off, such as EEPROM and hard disk. This makes it easy to query the program during the next execution and apply the last iteration learning information to the current control.

[0123] S306: Design an iterative learning item to estimate the unknown periodic disturbance f(x, t) through iterative learning, that is, the recursive part of the unknown periodic disturbance f(x, t) that needs to be learned in the system In order to speed up the convergence of iterative learning, the sliding surface is used to replace the speed error in iterative learning:

[0124]

[0125] In formula (8):

[0126] Learn the estimated unknown periodic disturbance f(x,t) value for the kth iteration;

[0127] Learn the estimated unknown periodic disturbance f(x,t) value for the k-1th iteration;

[0128] γ is the learning gain;

[0129] δ is the sliding mode switching gain in iterative learning;

[0130] σ is the sliding mode approach coefficient in iterative learning.

[0131] The method of the present invention is executed in DSP, FPGA and MCU.

[0132] In order to compare the effects of the present invention, Figure 4 and Figure 5 The experimental waveform of the speed controller using proportional integral controller is shown. Figure 4 This is the speed test waveform under the proportional integral controller. Figure 5 This is the experimental waveform of speed error under the action of proportional-integral controller. Figure 6 This is the speed test waveform under the action of the method of the present invention, Figure 7 This is the speed error experimental waveform under the action of the method of the present invention.

[0133] It can be seen from the experimental results that the method proposed in the present invention can stably and effectively suppress the speed fluctuation of the mover and keep the speed fluctuation within a very small range.

[0134] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations within the meaning and range of equivalents of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0135] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A method for suppressing speed fluctuation of a ring line motor based on sliding mode iterative learning, characterized in that: The method comprises the following steps: S1: Establish the speed state equation of the ring line motor: In formula (1): x(t) is the velocity, which is the system state variable; y(t) is the system output; f(x,t) is an unknown periodic disturbance; M is the mass of the mover; b is the ratio of the back electromotive force coefficient to the mass; u(t) is the total output of the controller; B(x,t) is the viscous friction coefficient; F d is an external disturbance; t is time; S2: Define the speed error: e(t)=v ref (t)-x(t) (2) In formula (2): e(t) is the velocity error; v ref (t) is the given mover speed; S3: Design a sliding mode iterative learning controller to suppress the speed fluctuation of the ring line motor.

2. The method for suppressing speed fluctuation of a toroidal linear motor based on sliding mode iterative learning according to claim 1, characterized in that: The S3 comprises the following steps: S301: Design of sliding surface: In formula (3): s ( t ) is the sliding surface; c is the integration constant; e(τ) is the velocity error at time τ; τ is the integrated quantity; is the velocity error from time 0 to t Find the integral between; S302: Deriving equation (3): S303: Substituting equation (1) and equation (2) into equation (4), we can obtain: S304: Design sliding mode reaching law: In formula (6): ζ( t ) is the sliding mode reaching law; λ>0 is the switching gain; η>0 is the convergence coefficient; sgn(*) is the sign function, S305: Combine equations (5) and (6) to obtain the speed controller output at the kth iteration: In formula (7): k is the number of iterations; is the total output of the controller at the kth iteration; is the output of the sliding mode controller; It is the controller output for iterative learning; x k is the system state variable at the kth iteration; is the recursive part of the unknown periodic perturbation f(x,t) that needs to be learned in the system; S306: Design an iterative learning item to estimate the unknown periodic disturbance f(x, t) through iterative learning, that is, the recursive part of the unknown periodic disturbance f(x, t) that needs to be learned in the system In order to speed up the convergence of iterative learning, the sliding surface is used to replace the speed error in iterative learning: In formula (8): Learn the estimated unknown periodic disturbance f(x,t) value for the kth iteration; Learn the estimated unknown periodic disturbance f(x,t) value for the k-1th iteration; γ is the learning gain; δ is the sliding mode switching gain in iterative learning; σ is the sliding mode approach coefficient in iterative learning.

3. The method for suppressing speed fluctuation of a toroidal linear motor based on sliding mode iterative learning according to claim 2 is characterized in that: The method is executed in DSP, FPGA and MCU.

4. The method for suppressing speed fluctuation of a toroidal linear motor based on sliding mode iterative learning according to claim 3 is characterized in that: Each iteration learns to control the output All are stored in memory.

Images