Improved active-disturbance-rejection motor sensorless control algorithm

Abstract

The invention belongs to the technical field of motor sensorless control, and particularly relates to an improved active-disturbance-rejection motor sensorless control algorithm, which comprises the following steps of: 1, taking output isqr of a speed loop as command value input of a q-axis current loop, and taking isdr = 0 as command value input of a d-axis current loop, the dq axis calculates and outputs voltage commands Vsq and Vsd of the dq axis through two double-ESO extended state observer modules, and then the voltage commands of the dq axis are subjected to reverse park conversion and SVPWM algorithm to obtain an abc three-phase command to be input into the inverter; 2, designing a double-ESO expansion state observer module, wherein the double-ESO expansion state observer module comprises a first expansion state observer module and a second expansion state observer module; the first expansion state observer module is used for estimating back electromotive force # imgabs0 # and # imgabs1 #; the second expansion state observer module is mainly used for estimating disturbance of internal parameter change; 3, an estimator performs feedback input, and the back electromotive force # imgabs2 # and # imgabs3 # obtained in the step 2 are used as input to estimate the rotor angle and angular speed through the back electromotive force; and 4, parameter design is carried out, and motor control is completed. The control performance of the motor sensorless control system can be effectively improved.

Description

Technical Field

[0001] The invention belongs to the technical field of motor sensorless control, and in particular relates to an improved motor sensorless control algorithm with self-anti-disturbance. Background Art

[0002] PMSM permanent magnet synchronous motors are widely used in the industrial field due to their high reliability, high efficiency and high power density. In vector control systems, rotor position sensors (such as Hall effect sensors, optical encoders or resolvers) are usually used to achieve closed-loop current control. However, these sensors increase the cost and reduce the reliability of the system. Therefore, sensorless control technology has been widely studied in the past few decades.

[0003] Sensorless control technology can be divided into three main categories: one is based on back electromotive force (EMF) estimation, the other is based on high-frequency (HF) signal injection, and the other is based on nonlinear flux observer. When stationary and low-speed operation, the method based on HF signal injection is usually used to observe the rotor position, because the back electromotive force is too small to be accurately estimated. When running at medium and high speeds, the method based on back electromotive force estimation and flux estimation is mainly used to obtain the rotor position. Due to the limitation of the control bandwidth, the HF signal injection method is not applicable in this case. In order to achieve sensorless FOC in the full speed range, these two methods need to be combined.

[0004] Most of the existing sensorless control schemes use a solution based on a synovial observer combined with high-frequency injection. High-frequency injection is used when the back electromotive force is relatively small at low speeds, and the synovial observer is started at medium and high speeds for closed loop. Therefore, the main disadvantages of the existing technology are:

[0005] 1. Under low speed or stationary conditions, the method based on back-EMF estimation is difficult to accurately estimate the rotor position because the back-EMF is too small, resulting in the method based on HF signal injection being more commonly used under these conditions.

[0006] 2. The traditional sliding mode observer (SMO) has chatter and phase delay problems, which affect the dynamic performance and accuracy of the system.

[0007] 3. Existing sensorless FOC methods, especially those based on sliding mode observer (SMO) and nonlinear flux linkage, are sensitive to changes in motor parameters, resulting in severe performance degradation when parameters change. Summary of the invention

[0008] The purpose of the present invention is to provide an improved sensorless motor control algorithm with self-anti-disturbance control, which can effectively improve the control performance of the sensorless motor control system.

[0009] The technical solution adopted by the present invention is as follows:

[0010] An improved motor sensorless control algorithm with self-disturbance rejection is characterized by comprising the following steps:

[0011] Step 1: Set the output of the speed loop sqr As the command value input of the q-axis current loop, let i sdr =0 as the command value input of the d-axis current loop, and the dq axis respectively calculates and outputs the dq axis voltage command V through two dual ESO extended state observer modules sq and V sd , then the dq axis voltage command is subjected to inverse Park transformation and space voltage vector switching algorithm to obtain the abc three-phase command input to the inverter;

[0012] Preferably, the step 1 includes the following steps:

[0013] Step 101: Design the speed loop PI parameters by using the bandwidth method, give the motor speed command Wref as input to the speed loop PI controller, use the estimated speed value of the estimator in step 3 as the feedback command, and use the load torque estimated value Perform self-disturbance rejection closed loop and finally output torque current command i sqr ;

[0014] Step 102: The instruction i finally outputted in step 101 sqr As the input of the q-axis dual ESO extended state observer module, i sdr =0 as the input of the d-axis dual ESO extended state observer module, and finally the dq-axis dual ESO extended state observer module will output the dq-axis voltage command and the dq-axis back electromotive force estimation value and

[0015] Step 103: Use the dq axis command output from step 102 as the input of the inverse Park transform in formula 1. The inverse Park transform outputs V sα and V sβ The voltage command is used as the input of the inverse Clarke transformation in formula 2 and outputs Ta, Tb, Tc: the switching time of the three-phase inverter. Finally, according to formulas 3-6, the space voltage vector switching algorithm is used to convert Ta, Tb, Tc into instructions that the embedded system can receive. The specific process is as follows:

[0016]

[0017] In formula (1), V ɑ 、V β 、V d 、V qThey represent the ɑβ axis voltage command and the dq axis voltage command respectively, and θ is the electrical angle;

[0018]

[0019] Offset is a calibration value used as an intermediate variable, which is used to calculate PWM1, PWM2, and PWM3 in the following formula;

[0020] PWM1=((-(T a +offset) / U dc )+0.5)×TIM1_ARR (4)

[0021] PWM2=((-(T b +offset) / U dc )+0.5)×TIM1_ARR (5)

[0022] PWM3=((-(T c +offset) / U dc )+0.5)×TIM1_ARR (6)

[0023] Where θ in Formula 1 is the electrical angle, TIM1_ARR in Formula 4-Formula 6 is the reload value of the embedded system timer, and U dc is the bus voltage, PWM1, PWM2, and PWM3 are the comparison values ​​of the three timer channels respectively;

[0024] Assigning values ​​to the capture compare registers of the corresponding channels in the processor can generate three corresponding rectangular wave signals to control the switching of the MOS tube, thereby generating the desired voltage, current and torque.

[0025] Step 2: Design a dual ESO extended state observer module: The dual ESO extended state observer module includes a first extended state observer module and a second extended state observer module, wherein the first extended state observer module is used to estimate the back electromotive force. and The second extended state observer module is mainly used to estimate the disturbance of internal parameter changes;

[0026] Preferably, step 2 comprises the following specific steps:

[0027] Design the first extended state observer module and the second extended state observer module estimator and establish equations. The specific equations are as follows:

[0028]

[0029] in, is the current error of the corresponding axis, Lx1 With L x2 (x=d,q) is the ESO gain parameter of the corresponding axis, is the estimated back EMF of the corresponding axis, V sx (x=d,q) is the voltage command of the corresponding axis, Ld and Lq are the dq axis inductances.

[0030] Step 3: Estimator feedback input, the back EMF obtained in step 2 and Back EMF is used as input to estimate the rotor angle and angular velocity;

[0031] Preferably, step 3 includes the following specific steps:

[0032] Step 301: Exploitation and Calculate the estimated angle error Δθ rm , the formula is as follows:

[0033]

[0034] (where P is the number of motor pole pairs, Δθ rm is the electrical angle error value)

[0035] Step 302: Input the estimated error value into the Luenberger phase-locked loop, as shown in Formula 9, to obtain an estimated angle value. and the angular velocity estimate and load torque estimate The angular velocity estimate is used as the speed loop feedback to form a closed loop, and the load torque estimate is subtracted from the output of the speed loop to form an anti-disturbance loop to resist external disturbance torque.

[0036]

[0037] in, is the motor viscous friction coefficient, is the motor moment of inertia, g1, g2, g3 are the observer feedforward gains, Te is the torque command, is the estimated electrical angle, It can be calculated by using formula 8.

[0038] Step 4: Perform parameter design and complete motor control.

[0039] Preferably, in step 4, e is the tracking error, and the state equation of the tracking error is: in The bandwidth of the extended state observer module is designed according to the bandwidth method, L x2 and Lx1 is the design parameter, After calculation, we get Where w0 is the bandwidth, which is designed to be 5-10 times the current loop bandwidth, and the motor control is completed according to the design parameters.

[0040] The technical effects achieved by the present invention are:

[0041] The present invention proposes a DADRC module, which can provide a wider speed observation range and stably output back electromotive force; compared with traditional non-sensing algorithms, such as SMO, this method will not cause high-frequency jitter to the system. The DADRC module of the present invention cleverly designs the gain as the bandwidth Wo, which is convenient for design and shortens the parameter adjustment time. The DADRC module of the present invention adopts the idea of ​​self-anti-disturbance, can estimate internal disturbances while not relying on the estimation of magnetic flux, can compensate for disturbances caused by parameter errors, reduces the accuracy dependence of the model, and improves the robustness of the system. The Luenberger estimator used in the present invention is different from the traditional PI controller phase-locked loop PLL. Since the former introduces torque command information, the former has a greater bandwidth than the latter and a higher response speed. The present invention performs external load torque The anti-disturbance algorithm can observe the load torque in real time and compensate for it, thereby improving the system robustness and external anti-disturbance capability. The sensorless observer algorithm of the present invention does not introduce a filter, and has a higher response speed, bandwidth and lower delay compared to SMO. The present invention does not need to observe the flux and is insensitive to the flux parameters. The present invention has a small amount of calculation, occupies less resources, and has a faster computing speed. The present invention does not require sensors, saves costs, and reduces the design space of the motor body. Compared with the inductive closed loop, this solution is more reliable and less prone to failure.

[0042] The purpose of the present invention is to propose an improved self-disturbance rejection and senseless control algorithm in view of the above-mentioned shortcomings of the prior art, so as to effectively improve the control performance of the system. The present invention can achieve a wider senseless speed control range and adopt IF control at extremely low speeds. By using two LESOs to estimate and compensate for external and internal disturbances, no filter is introduced like the traditional SMO sliding film observer, thereby greatly improving the dynamic performance of the system and reducing vibration and phase delay. The internal anti-disturbance strategy of ADRC improves the robustness of the system to changes in motor parameters, ensuring that high-performance control can be maintained in the event of parameter changes or inaccurate models. The present invention also performs external disturbance torque rejection, and can detect and compensate for disturbance torque in time when the motor is stalled or obstructed. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic block diagram of the overall process of the solution of the present invention;

[0044] Figure 2is a schematic flow chart of step 201 of the present invention;

[0045] Figure 3 It is a schematic flow chart of step 3 of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose and advantages of the present invention more clearly understood, the present invention is specifically described below in conjunction with embodiments. It should be understood that the following text is only used to describe one or several specific embodiments of the present invention, and does not strictly limit the scope of protection of the specific claims of the present invention.

[0047] like Figure 1-Figure 3 As shown, an improved motor sensorless control algorithm with self-disturbance rejection includes the following steps:

[0048] Step 1: Set the output of the speed loop sqr As the command value input of the q-axis current loop, let i sdr =0 as the command value input of the d-axis current loop, and the dq axis respectively calculates and outputs the dq axis voltage command V through two dual ESO extended state observer modules sq and V sd ,ESO refers to the extended state observer, which is an important part of the active disturbance rejection control. Then the dq axis voltage command is subjected to inverse Park transformation and space voltage vector switching algorithm to obtain the abc three-phase command input to the inverter;

[0049] Step 1 includes the following steps:

[0050] Step 101: Design the speed loop PI parameters by using the bandwidth method, give the motor speed command Wref as input to the speed loop PI controller, use the speed estimation value of the estimator in step 3 as the feedback command, and use the load torque estimation value Perform self-disturbance rejection closed loop and finally output torque current command i sqr ;

[0051] Step 102: The instruction i finally outputted in step 101 sqr As the input of the q-axis dual ESO extended state observer module, i sdr =0 as the input of the d-axis dual ESO extended state observer module, where the specific implementation process of the dual ESO extended state observer module is shown in step 2. Finally, the dq-axis dual ESO extended state observer module will output the dq-axis voltage command and the dq-axis back electromotive force estimation value and

[0052] Step 103: Use the dq axis command output from step 102 as the input of the inverse Park transform in formula 1. The inverse Park transform outputs V sα and Vsβ The voltage command is used as the input of the inverse Clarke transform in formula 2 and outputs Ta, Tb, and Tc. Finally, according to formulas 3 to 6, the space voltage vector switching algorithm is used to convert Ta, Tb, and Tc into instructions that can be received by the embedded system. The specific process is as follows:

[0053]

[0054] In formula (1), V ɑ 、V β 、V d 、V q They represent the ɑβ axis voltage command and the dq axis voltage command respectively, and θ is the electrical angle;

[0055]

[0056] Offset is a calibration value used as an intermediate variable, which is used to calculate PWM1, PWM2, and PWM3 in the following formula;

[0057] PWM1=((-(T a +offset) / U dc )+0.5)×TIM1_ARR (4)

[0058] PWM2=((-(T b +offset) / U dc )+0.5)×TIM1_ARR (5)

[0059] PWM3=((-(T c +offset) / U dc )+0.5)×TIM1_ARR (6)

[0060] Where θ in Formula 1 is the electrical angle, TIM1_ARR in Formula 4-Formula 6 is the reload value of the embedded system timer, and U dc is the bus voltage, PWM1, PWM2, and PWM3 are the comparison values ​​of the three timer channels respectively;

[0061] In the processor, the capture comparison registers of the corresponding channels are assigned values ​​to generate the corresponding three PWM waveforms, control the switching of the MOS tube, and then generate the desired voltage, current and torque.

[0062] Step 2: Design a dual ESO extended state observer module: The dual ESO extended state observer module includes a first extended state observer module and a second extended state observer module. The first extended state observer module is used to estimate the back electromotive force. and The second extended state observer module is mainly used to estimate the disturbance of internal parameter changes;

[0063] Step 2 includes the following specific steps:

[0064] Design the first extended state observer module and the second extended state observer module estimator and establish equations. The specific equations are as follows:

[0065]

[0066] in, is the current error of the corresponding axis, L x1 With L x2 (x=d,q) is the ESO gain parameter of the corresponding axis, is the estimated back EMF of the corresponding axis, V sx (x=d,q) is the voltage command of the corresponding axis, Ld and Lq are the dq axis inductances.

[0067] The formula of step 101 is designed to obtain Figure 2 Block diagram of , where w0 is the bandwidth.

[0068] Step 3: Estimator feedback input, the back EMF obtained in step 2 and Back EMF is used as input to estimate the rotor angle and angular velocity;

[0069] Step 301: Exploitation and Calculate the estimated angle error Δθ rm ,like Figure 3 As shown, where Te is the torque command value, Te = q-axis current iq × torque constant Kt, the formula is as follows:

[0070] Δθ rm =-tan -1 (f ed / f eq ) (8)

[0071] Step 302: Input the estimated error value into the Luenberger phase-locked loop, as shown in Formula 9, to obtain an estimated angle value. and the angular velocity estimate and load torque estimate The angular velocity estimate is used as the speed loop feedback to form a closed loop, and the load torque estimate is subtracted from the output of the speed loop to form an anti-disturbance loop to resist external disturbance torque.

[0072]

[0073] in, is the motor viscous friction coefficient, is the motor moment of inertia, g1, g2, g3 are the observer feedforward gains, Te is the torque command, is the estimated electrical angle, It can be calculated by using formula 8.

[0074] Step 4: Perform parameter design and complete motor control.

[0075] In step 4, let e is the tracking error, and the state equation of the tracking error is: in The bandwidth of LESO can be designed according to the bandwidth method. x2 and L x1 is the design parameter, After calculation, we get Where w0 is the bandwidth, which is designed to be 5-10 times the current loop bandwidth, and the motor control is completed according to the design parameters.

[0076] The present invention proposes a DADRC module, which can provide a wider speed observation range and stably output back electromotive force; compared with traditional non-sensing algorithms, such as SMO, this method will not cause high-frequency jitter to the system. The DADRC module of the present invention cleverly designs the gain as the bandwidth Wo, which is convenient for design and shortens the parameter adjustment time. The DADRC module of the present invention adopts the idea of ​​self-anti-disturbance, can estimate internal disturbances while not relying on the estimation of magnetic flux, can compensate for disturbances caused by parameter errors, reduces the accuracy dependence of the model, and improves the robustness of the system. The Luenberger estimator used in the present invention is different from the traditional PI controller phase-locked loop PLL. Since the former introduces torque command information, the former has a greater bandwidth than the latter and a higher response speed. The present invention performs external load torque The anti-disturbance algorithm can observe the load torque in real time and compensate for it, thereby improving the system robustness and external anti-disturbance capability. The sensorless observer algorithm of the present invention does not introduce a filter, and has a higher response speed, bandwidth and lower delay compared to SMO. The present invention does not need to observe the flux and is insensitive to the flux parameters. The present invention has a small amount of calculation, occupies less resources, and has a faster computing speed. The present invention does not require sensors, saves costs, and reduces the design space of the motor body. Compared with the inductive closed loop, this solution is more reliable and less prone to failure.

[0077] The purpose of the present invention is to propose an improved self-disturbance rejection and senseless control algorithm in view of the above-mentioned shortcomings of the prior art, so as to effectively improve the control performance of the system. The present invention can achieve a wider senseless speed control range and adopt IF control at extremely low speeds. By using two LESOs to estimate and compensate for external and internal disturbances, no filter is introduced like the traditional SMO sliding film observer, thereby greatly improving the dynamic performance of the system and reducing vibration and phase delay. The internal anti-disturbance strategy of ADRC improves the robustness of the system to changes in motor parameters, ensuring that high-performance control can be maintained in the event of parameter changes or inaccurate models. The present invention also performs external disturbance torque rejection, and can detect and compensate for disturbance torque in time when the motor is stalled or obstructed.

[0078] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. An improved sensorless motor control algorithm with anti-disturbance function, characterized in that: The following steps are involved: Step 1: Set the output of the speed loop sqr As the command value input of the q-axis current loop, let i sdr =0 as the command value input of the d-axis current loop, and the dq axis respectively calculates and outputs the dq axis voltage command V through two dual ESO extended state observer modules sq and V sd , then the dq axis voltage command is subjected to inverse Park transformation and space voltage vector switching algorithm to obtain the abc three-phase command input to the inverter; Step 2: Design a dual ESO extended state observer module: The dual ESO extended state observer module includes a first extended state observer module and a second extended state observer module, wherein the first extended state observer module is used to estimate the back electromotive force. and The second extended state observer module is mainly used to estimate the disturbance of internal parameter changes; Step 3: Estimator feedback input, the back EMF obtained in step 2 and Back EMF is used as input to estimate the rotor angle and angular velocity; Step 4: Perform parameter design and complete motor control.

2. The improved motor sensorless control algorithm of claim 1 is characterized by: The step 1 includes the following steps: Step 101: Design the speed loop PI parameters by using the bandwidth method, give the motor speed command Wref as input to the speed loop PI controller, use the speed estimation value of the estimator in step 3 as the feedback command, and use the load torque estimation value Perform self-disturbance rejection closed loop and finally output torque current command i sqr ; Step 102: The instruction i finally outputted in step 101 sqr As the input of the q-axis dual ESO extended state observer module, i sdr =0 as the input of the d-axis dual ESO extended state observer module, and finally the dq-axis dual ESO extended state observer module will output the dq-axis voltage command and the dq-axis back electromotive force estimation value and Step 103: Use the dq axis command output from step 102 as the input of the inverse Park transform in formula 1. The inverse Park transform outputs V sα and V sβ The voltage command is used as the input of the inverse Clarke transformation in formula 2 and outputs Ta, Tb, Tc: the switching time of the three-phase inverter. Finally, according to formulas 3-6, the space voltage vector switching algorithm is used to convert Ta, Tb, Tc into instructions that the embedded system can receive. The specific process is as follows: In formula (1), V ɑ 、V β 、V d 、V q They represent the ɑβ axis voltage command and the dq axis voltage command respectively, and θ is the electrical angle; Offset is a calibration value used as an intermediate variable, which is used to calculate PWM1, PWM2, and PWM3 in the following formula; PWM1=((-(T a +offset) / U dc )+0.5)×TIM1_ARR (4) PWM2=((-(T b +offset) / U dc )+0.5)×TIM1_ARR (5) PWM3=((-(T c +offset) / U dc )+0.5)×TIM1_ARR (6) Where θ in Formula 1 is the electrical angle, TIM1_ARR in Formula 4-Formula 6 is the reload value of the embedded system timer, and U dc is the bus voltage, PWM1, PWM2, and PWM3 are the comparison values ​​of the three timer channels respectively; Assigning values ​​to the capture compare registers of the corresponding channels in the processor can generate three corresponding rectangular wave signals to control the switching of the MOS tube, thereby generating the desired voltage, current and torque.

3. The improved motor sensorless control algorithm with auto-disturbance rejection according to claim 1 is characterized in that: The step 2 comprises the following specific steps: Design the first extended state observer module and the second extended state observer module estimator and establish equations. The specific equations are as follows: in, is the current error of the corresponding axis, L x1 With L x2 (x=d,q) is the ESO gain parameter of the corresponding axis, is the estimated back EMF of the corresponding axis, V sx (x=d,q) is the voltage command of the corresponding axis, Ld and Lq are the dq axis inductances.

4. The improved motor sensorless control algorithm with auto-disturbance rejection according to claim 1 is characterized in that: The step 3 includes the following specific steps: Step 301: Exploitation and Calculate the estimated angle error Δθ rm , the formula is as follows: (where P is the number of motor pole pairs, Δθ rm is the electrical angle error value) Step 302: Input the estimated error value into the Luenberger phase-locked loop, as shown in Formula 9, to obtain an estimated angle value. and the angular velocity estimate and load torque estimate The angular velocity estimate is used as the speed loop feedback to form a closed loop, and the load torque estimate is subtracted from the output of the speed loop to form an anti-disturbance loop to resist external disturbance torque. in, is the motor viscous friction coefficient, is the motor moment of inertia, g1, g2, g3 are the observer feedforward gains, Te is the torque command, is the estimated electrical angle, It can be calculated by using formula 8.

5. The improved motor sensorless control algorithm with auto-disturbance rejection according to claim 1 is characterized in that: In step 4, e is the tracking error, and the state equation of the tracking error is: in The bandwidth of the extended state observer module is designed according to the bandwidth method, L x2 and L x1 is the design parameter, After calculation, we get Where w0 is the bandwidth, which is designed to be 5-10 times the current loop bandwidth, and the motor control is completed according to the design parameters.

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