Speed sensorless motor control method based on sliding mode

Abstract

The invention discloses a speed sensorless motor control method based on a sliding mode, and relates to the field of motors, and the speed sensorless motor control method based on the sliding mode comprises the following steps: 1, designing a superspiral sliding mode controller, and restraining the buffeting problem of a motor system through a discontinuous item in integral sliding mode control; step 2, obtaining position information of a rotor through a phase-locked loop algorithm; the step 1 specifically comprises the step 11 that the super-spiral sliding mode control rate is composed of a discontinuous time derivative and a continuous function of a sliding variable, and the method has the beneficial effects that the method is a speed sensorless motor control method, the hardware cost of a speed sensor is saved, control is carried out based on a super-spiral sliding mode observer, and the control efficiency is improved. And a phase-locked loop technology is introduced to replace an arc tangent algorithm, so that the dynamic response capability and the anti-load interference capability are enhanced, the problems of large rotating speed error, large rotor position error and the like when the motor is just started are well solved, and the chattering phenomenon is effectively inhibited.

Description

Technical Field

[0001] The invention relates to the field of motors, and in particular to a speed sensorless motor control method based on sliding mode. Background Art

[0002] The existing speed sensorless technologies mainly include:

[0003] (1) Rotating high-frequency voltage injection method: Rotating high-frequency voltage injection technology is a method of implementing signal injection in a two-phase stationary coordinate system and thereby accurately obtaining position information. By injecting a rotating high-frequency voltage signal into the stator winding of the motor, the physical properties of the motor itself are used to extract the position information of the rotor. This high-frequency signal injection method is relatively easy to implement, but the extraction and filtering of the response signal are relatively complex, and the application of the filter will affect the position estimation result and reduce the dynamic characteristics of the system (permanent magnet synchronous motor speed sensorless control system).

[0004] (2) Model reference adaptation: Model reference adaptation is to establish a parameter uncertainty model based on the original model. By comparing the performance of the actual motor with the performance of the predetermined reference model, the control parameters are automatically adjusted to make the operation of the actual motor as close as possible to the predetermined reference model. Model reference adaptation is mainly used for back-EMF observation in position sensorless control. It has problems such as strong dependence on system parameters and difficulty in model selection.

[0005] (3) Extended Kalman Filter: The Extended Kalman Filter is a recursive estimation algorithm with strong anti-interference and high robustness. This method predicts the motor state through a mathematical model and uses real-time measurement data to continuously correct these predictions, thereby improving the accuracy of the estimation. Since motor control requires strong real-time performance, the Extended Kalman Filter has high requirements for processor computing power, and engineering applications are somewhat difficult.

[0006] (4) Sliding mode observer: The sliding mode observer applies sliding mode variable structure control to the position estimation algorithm. It uses the mathematical model of the motor and measurable variables such as current and voltage to construct a dynamic sliding mode, and accurately estimates the system state on this mode. Since the sliding mode observer has excellent dynamic response performance and strong anti-disturbance ability, it has been widely used in sensorless control. Due to the hysteresis and inertia of the system, the sliding mode motion will experience jitter. How to suppress or eliminate jitter and improve the position estimation accuracy is a key research direction.

[0007] In summary, the existing motor speed sensorless technology has weak universality and needs to be improved. Summary of the invention

[0008] The object of the present invention is to provide a speed sensorless motor control method based on sliding mode to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] A speed sensorless motor control method based on sliding mode comprises the following steps:

[0011] Step 1, design a super-helical sliding mode controller to suppress the motor system chattering problem by integrating the discontinuous terms in the sliding mode control;

[0012] Step 2, obtaining the rotor position information through a phase-locked loop algorithm;

[0013] Step 1 specifically includes:

[0014] Step 11, the super helical sliding mode control rate is composed of two parts: a discontinuous time derivative and a continuous function of the sliding variable, and the super helical sliding mode control rate expression is obtained;

[0015] Step 12, determining the convergence of the motor system obtained by the super-helical sliding mode control rate;

[0016] Step 13, design a first-order sliding mode observer;

[0017] Step 14: Replace the sign function in the first-order sliding mode observer with the Sigmoid function.

[0018] As a further solution of the present invention: in step 11, the super-helical sliding mode control rate is composed of two parts: a discontinuous time derivative and a continuous function of the sliding variable, and its expression can be expressed as:

[0019]

[0020] Among them, k1 and k2 are super-helical sliding mode gains, and both k1 and k2 are greater than 0.

[0021] As a further solution of the present invention: in step 12, a vector is taken based on the superhelical sliding mode control rate representation:

[0022]

[0023] After derivation and characteristic equation calculation, we have the function V as:

[0024] V=ζ T Pζ (7);

[0025] The time derivative of the function V is:

[0026]

[0027] Since V is a quadratic positive definite function, it can be deduced that:

[0028]

[0029] From formula (9), we can get:

[0030]

[0031] Since Q is also a positive definite matrix, we have:

[0032]

[0033] Finally, we get:

[0034] It can be seen from the Lyapunov stability that the super-helical sliding mode algorithm can ensure that the system is asymptotically stable on the sliding mode surface within a limited time.

[0035] As a further solution of the present invention: In step 11, during the process of derivation and characteristic equation calculation, firstly, the derivative is obtained:

[0036] Right now:

[0037]

[0038] in:

[0039]

[0040] The characteristic equation is:

[0041]

[0042] As a further solution of the present invention: in step 13, a first-order sliding mode observer is designed:

[0043]

[0044] As a further solution of the present invention: in step 14, the sign function in the first-order sliding mode observer is replaced with a Sigmoid function, thereby improving the stability and stability of the system, and its mathematical form is:

[0045]

[0046] By adjusting the coefficient a of the Sigmoid curve, the curve shape of the function can be flexibly shaped, thereby affecting the overall performance of the control system.

[0047] As a further solution of the present invention: in step 2, the motor generates a back electromotive force After filtering, the position information extraction stage is entered, and the rotor position information is obtained through the phase-locked loop algorithm, and the following relationship is obtained:

[0048] e β sinθ=-e α cosθ (16);

[0049] set up Surface Mount PMSM d =L q ,so Combining formula (16), we can get the back electromotive force error Δe:

[0050]

[0051] Under the phase-locked loop transfer number:

[0052]

[0053] Where: ω n Determines the width of the PI regulator.

[0054] Compared with the prior art, the beneficial effects of the present invention are: the present invention is a speed sensorless motor control method, which saves the hardware cost of the speed sensor, performs control based on a super-helical sliding mode observer, and introduces a phase-locked loop technology to replace the inverse tangent algorithm, thereby enhancing the dynamic response capability and the ability to resist load interference, and better solves the problems of large speed error and large rotor position error when the motor is just started, and effectively suppresses the jitter phenomenon, with strong universality. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is the motion trajectory diagram of the super helical sliding mode.

[0056] Figure 2 Schematic diagram of the phase-locked loop structure.

[0057] Figure 3 This is the schematic diagram of the optimized super-helical sliding mode observer.

[0058] Figure 4 This is the simulation model diagram of the super helical sliding mode observer.

[0059] Figure 5 This is the simulation model diagram of the Sigmoid function.

[0060] Figure 6 This is a simulation model diagram of a PLL super-helical sliding mode observer.

[0061] Figure 7 This is the motor speed waveform.

[0062] Figure 8 This is the motor speed error waveform. DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments 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 present invention, rather than all 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.

[0064] A speed sensorless motor control method based on sliding mode comprises the following steps:

[0065] Step 1, design a super-helical sliding mode controller to suppress the motor system chattering problem by integrating the discontinuous terms in the sliding mode control;

[0066] Step 2, obtaining the rotor position information through a phase-locked loop algorithm;

[0067] Step 1 specifically includes:

[0068] Step 11, the super helical sliding mode control rate is composed of two parts: a discontinuous time derivative and a continuous function of the sliding variable, and the super helical sliding mode control rate expression is obtained;

[0069] Step 12, determining the convergence of the motor system obtained by the super-helical sliding mode control rate;

[0070] Step 13, design a first-order sliding mode observer;

[0071] Step 14: Replace the sign function in the first-order sliding mode observer with the Sigmoid function.

[0072] See also Figure 1 The super spiral sliding mode algorithm is an innovative second-order sliding mode observer technology that can effectively suppress the chattering problem. This method suppresses the system chattering problem by integrating the discontinuous terms in the sliding mode control. The dynamic point moves in a spiral around the origin within the designed sliding mode control surface. Its motion trajectory is as follows Figure 1 shown.

[0073] The super-helical sliding mode control rate consists of two parts: the discontinuous time derivative and the continuous function of the sliding variable. Its representation can be expressed as:

[0074]

[0075] Where k1 and k2 are super-helical sliding mode gains, and both k1 and k2 are greater than 0, and sgn is the sign function.

[0076] To prove the convergence of the system, we take the vector ζ for equation (1):

[0077]

[0078] The derivative is:

[0079]

[0080] Right now:

[0081]

[0082] in:

[0083]

[0084] The characteristic equation is:

[0085]

[0086] Because k1 and k2 are greater than 0, the characteristic equation has negative real roots. According to Lyapunov's stability theorem, for any positive definite matrix Q, the equation A T P+PA=-Q has a unique positive definite matrix P, so the function V is:

[0087] V=ζ T Pζ (7);

[0088] The time derivative of the function V is:

[0089]

[0090] Since V is a quadratic positive definite function, it can be deduced that:

[0091]

[0092] in

[0093]

[0094] From formula (9), we can get

[0095]

[0096] Since Q is also a positive definite matrix:

[0097]

[0098] Finally, we get:

[0099]

[0100] Formula (2) to Formula (13) are mathematical calculation proofs, and the letters in them have no actual physical meaning.

[0101] Among them, P, Q, and V are all positive definite matrices, and the derivative of V is negative definite. According to Lyapunov stability, the super-helical sliding mode algorithm can ensure that the system is asymptotically stable on the sliding mode surface in a limited time. The built-in integral link of the algorithm can play a correction role, and the observer is designed as follows:

[0102]

[0103] is the estimated motor back electromotive force, k1 and k2 are the super-helical sliding mode gain coefficients, and both k1 and k2 are greater than 0. α 、i β is the current on the α-β axis.

[0104] In order to better suppress the motor chattering phenomenon, this paper replaces the sign function in the first-order sliding mode observer with the Sigmoid function, which helps to improve the stability and stability of the system. Its mathematical form is:

[0105]

[0106] e is a natural constant and a is a curve coefficient.

[0107] By adjusting the coefficient a of the Sigmoid curve, the curve shape of the function can be flexibly shaped, thereby affecting the overall performance of the control system.

[0108] The motor generates back EMF After filtering, we enter the stage of extracting position information. Ordinary sliding mode observers usually use the inverse tangent algorithm to obtain the position information of the rotor, but the inverse tangent algorithm has a large error. In order to improve the observation accuracy, this paper uses the phase-locked loop algorithm to replace the inverse tangent algorithm. The following relationship is obtained:

[0109] e β sinθ=-e α cosθ (16);

[0110] e β 、e α is the back electromotive force on the α-β axis, and θ is the motor rotor angle.

[0111] set up Surface Mount PMSM d =L q ,so Combining formula (16), we can get the back electromotive force error Δe:

[0112]

[0113] is the estimated motor back EMF, is the estimated motor rotor position, θ is the actual motor rotor angle, and k is the transfer coefficient.

[0114] From formula (17), the schematic diagram of the phase-locked loop algorithm can be obtained as follows: Figure 2 shown.

[0115] Under the phase-locked loop transfer number:

[0116]

[0117] Where: ω n Determines the width of the PI regulator. k is the transfer coefficient K p , K i is the PI adjustment parameter.

[0118] The control principle diagram of super spiral sliding mode observer (ST-SMO) is as follows: Figure 3 As shown:

[0119] Simulation experiments and results:

[0120] In the MATLAB / Simulink environment, a simulation model of PMSM speed sensorless control system with PLL super spiral sliding mode observer is built. The simulation model of ST-SMO observer (super spiral sliding mode observer) is as follows: Figure 4 shown.

[0121] The Sigmoid function is a widely used activation function that can map any real value to a range between 0 and 1. The simulation model of the Sigmoid function is as follows: Figure 5 shown.

[0122] The simulation model of permanent magnet synchronous motor speed sensorless control system based on ST-SMO is as follows Figure 6 shown.

[0123] The simulation runs at a given speed of 800r / min. A load of 3N·m is added at t=0.35s, and the load is released at t=0.65s. The speed waveform is as follows: Figure 7 , the speed error waveform is as follows Figure 8 It can effectively solve the problems of large speed error and large rotor position error when the motor is just started, and effectively suppress the vibration phenomenon.

[0124] It is obvious to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be considered as exemplary and non-restrictive in all respects.

[0125] 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 speed sensorless motor control method based on sliding mode, characterized in that: The sliding mode based speed sensorless motor control method comprises the following steps: Step 1, design a super-helical sliding mode controller to suppress the motor system chattering problem by integrating the discontinuous terms in the sliding mode control; Step 2, obtaining the rotor position information through a phase-locked loop algorithm; Step 1 specifically includes: Step 11, the super helical sliding mode control rate is composed of two parts: a discontinuous time derivative and a continuous function of the sliding variable, and the super helical sliding mode control rate expression is obtained; Step 12, determining the convergence of the motor system obtained by the super-helical sliding mode control rate; Step 13, design a first-order sliding mode observer; Step 14: Replace the sign function in the first-order sliding mode observer with the Sigmoid function.

2. The sliding mode based speed sensorless motor control method according to claim 1, characterized in that: In step 11, the super-helical sliding mode control rate consists of two parts: the discontinuous time derivative and the continuous function of the sliding variable, and its representation can be expressed as: Among them, k1 and k2 are super-helical sliding mode gains, and both k1 and k2 are greater than 0.

3. The sliding mode based speed sensorless motor control method according to claim 1 or 2, characterized in that: In step 12, a vector is taken based on the superhelical sliding mode control rate representation: After derivation and characteristic equation calculation, we have the function V as: V=ζ T Pz (7); The time derivative of the function V is: Since V is a quadratic positive definite function, it can be deduced that: From formula (9), we can get: Since Q is also a positive definite matrix, we have: Finally, we get: It can be seen from the Lyapunov stability that the super-helical sliding mode algorithm can ensure that the system is asymptotically stable on the sliding mode surface within a limited time.

4. The sliding mode based speed sensorless motor control method according to claim 3, characterized in that: In step 11, during the process of derivation and characteristic equation calculation, the first step is to derivate: Right now: in: The characteristic equation is:

5. According to the sliding mode based speed sensorless motor control method of claim 1, in step 13, a first-order sliding mode observer is designed:

6. The sliding mode based speed sensorless motor control method according to claim 1, characterized in that: In step 14, the sign function in the first-order sliding mode observer is replaced with the Sigmoid function to improve the stability and stability of the system. Its mathematical form is: By adjusting the coefficient a of the Sigmoid curve, the curve shape of the function can be flexibly shaped, thereby affecting the overall performance of the control system.

7. The sliding mode based speed sensorless motor control method according to claim 1, characterized in that: In step 2, the motor generates back EMF After filtering, the position information extraction stage is entered, and the rotor position information is obtained through the phase-locked loop algorithm, and the following relationship is obtained: And β sinθ=-e α cosθ (16); set up Surface Mount PMSM d =L q ,so Combining formula (16), we can get the back electromotive force error Δe: Under the phase-locked loop transfer number: Where: ω n Determines the width of the PI regulator.

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