Explosion-proof holder stepping motor sensorless control method

Abstract

The invention discloses an explosion-proof holder stepping motor sensorless control method, which adopts an EKF (Extended Kalman Filter) sensorless control algorithm based on Kalman filtering to carry out state estimation when a holder runs in a high-speed domain, and can accurately control the rotating speed and the angle position of a motor without depending on a position sensor. The problem that the space of the explosion-proof holder is limited and a sensor is difficult to install is solved, and the reliability of the system is improved. The weak magnetic control of the stepping motor solves the problem that an EKF position sensorless control algorithm cannot drive a high-load holder to rotate at a high speed due to insufficient voltage at the two ends of the stepping motor, and the function of increasing the running speed range of the explosion-proof holder motor is achieved by weakening a rotor magnetic field, reducing the counter electromotive force output of the motor and reducing voltage occupancy. Fuzzy PI control is introduced into a speed current double-closed-loop dq decoupling control strategy, so that the phenomenon of high-frequency out-of-step of the hybrid stepping motor is reduced to a certain extent.

Description

Technical Field

[0001] The invention relates to a position sensor-free control method for an explosion-proof pan / tilt stepper motor. Background Art

[0002] Explosion-proof pan / tilts often use stepper motors to control rotation. Stepper motors are actuators that convert electrical pulses into mechanical angular displacements. Their angular displacement is proportional to the number of input pulses and is synchronized with the input pulses in time. They can achieve high positioning accuracy in a closed-loop mode and can output large torque at low speeds, so they are widely used in motion control.

[0003] However, the driving system of the stepper motor has problems such as nonlinearity, time variation, and interference. Traditional PID control cannot achieve a good control effect. Under high load conditions, the motor is prone to lose steps, resulting in cumulative errors, which leads to unstable operation of the pan-tilt. The use scenarios of explosion-proof pan-tilt stepper motors generally require fast low-speed torque response, but the traditional three-ring FOC control has a very slow low-speed torque response. When the load suddenly increases, the speed closed loop has a significant delay. Servo motors generally use reducers to solve the low-speed problem, but stepper motors generally do not use reducers, and some special control methods are also required. For this reason, the present invention provides a position sensorless control method for explosion-proof pan-tilt stepper motors. Summary of the invention

[0004] The present invention provides a position sensorless control method for an explosion-proof pan / tilt stepper motor in order to solve the problems existing in the above-mentioned prior art.

[0005] The technical solutions adopted in the present invention are:

[0006] A method for controlling an explosion-proof pan / tilt stepper motor without a position sensor, comprising:

[0007] When the explosion-proof PTZ needs to move at a low speed: the stepper motor is controlled by an open-loop S-type acceleration and deceleration algorithm;

[0008] When the explosion-proof gimbal needs to move at medium or high speed, the steps are as follows:

[0009] S1: The MCU written with the dual closed-loop speed regulation algorithm receives the control command to start the explosion-proof PTZ and initializes the program. Then it starts the corresponding sensor and drive circuit, collects the current and voltage data of the stepper motor through the current sensor and voltage sensor, and transmits them to the MCU.

[0010] S2: After the MCU processes the collected data, it obtains the current and voltage signals of the stepper motor and calculates the motor torque and speed based on the motor model and the data of the two sensors;

[0011] S3: The weak magnetic field control module adaptively calculates the weak magnetic field gain according to the weak magnetic field control small signal model to obtain the dq axis current control signal;

[0012] S4: Speed ​​and current dual closed-loop dq decoupling control is realized through a dual closed-loop speed control algorithm, in which the speed outer loop compares the target speed with the actual speed, calculates the speed error, calculates the speed control signal through the fuzzy PI regulator, and converts the speed control signal into a dq axis control signal;

[0013] The torque inner loop compares the target torque with the actual torque, calculates the torque error, calculates the torque control signal through the PI regulator, and converts the torque control signal into a dq axis control signal;

[0014] S5: The dq axis control signal is transformed into the voltage control signal of the αβ axis through inverse park transformation;

[0015] S6: The driving circuit receives the voltage control signal of the αβ axis and uses the space vector modulation SVPWM module to drive the motor coil current and control the rotation of the stepper motor;

[0016] S7: The voltage and current signals collected in step S2 are transformed by Clark and Park to obtain the current signals of the dq axes, and the current signals are used as the actual torque of the speed outer loop in step S4 to perform closed-loop control on the motor torque;

[0017] S8: The voltage and current signals collected in step S2 are transformed by Clark to obtain the voltage and current signals of the αβ axis, and then the actual motor speed is estimated using the motor model through the EKF algorithm, and the actual speed of the speed outer loop in step S4 is used to perform closed-loop control of the motor speed. The MCU repeats S1 to S6 to achieve closed-loop control so that the motor speed and angle reach the target values.

[0018] Furthermore, the motor model is:

[0019] For any winding abc, the voltage equation of winding a is:

[0020]

[0021] Where: V a is the voltage of phase a, Ψ 总 is the total magnetic flux of the winding, e a is the back electromotive force of phase a winding;

[0022]

[0023] Where: J is the moment of inertia of the stepper motor rotor; B is the viscous friction coefficient; K e is the torque constant of the stepper motor; L is the inductance of the stator winding; ω zis the mechanical angular velocity of the rotor; θ is the electrical angular velocity of the rotor;

[0024] Winding b and winding c are the same as winding a.

[0025] Further, in S3, the weak magnetic field control of the weak magnetic field control module includes:

[0026] The explosion-proof gimbal enters the medium and high speed operation state, and adopts the armature reaction magnetic flux in the d-axis that is opposite to the rotor magnetic flux to realize the weakening of the synthetic magnetic field of the stepper motor air gap, and realize the expansion of the motor speed operation range, thereby increasing the operating speed of the motor; the weak magnetic gain of the voltage outer loop method is adaptively calculated according to the weak magnetic control small signal model, and the judgment conditions for entering and exiting the weak magnetic area are set to prevent the vehicle from mistakenly entering the weak magnetic control area under low speed, heavy load and rapid acceleration conditions.

[0027] Further, in S3, the small signal model is:

[0028] Select an operating point in the weak magnetic control area. This operating point is the equilibrium state of the current speed and load conditions, which provides the basis for weak magnetic control. Assume that the voltage, current and flux parameters of the stepper motor fluctuate slightly. Assume that the disturbances of current and angle are Δi a ,Δi b ,Δi c ,Δθ, substitute the nonlinear stepper motor mathematical model equation into the small signal variable, and perform Taylor expansion on each variable at the working point, retain the first-order term, and ignore the high-order small quantity, so as to obtain the linearized equation:

[0029]

[0030]

[0031] θ0 is the angular position of the stable operating point, i.e. the reference angle of the motor;

[0032] Convert the above linearized equations into state space form, define the state vector x = [Δia, Δib, Δic, Δθ], and the input vector u = [ΔVa, ΔVb, ΔVc, Δω] T

[0033] Equation of state:

[0034]

[0035] Among them, A is the system matrix, which describes the linear relationship between state variables, and B is the input matrix, which describes the influence of input variables on state variables.

[0036] Further, in S4, the fuzzy PI regulator makes the error e and the error change rate e cAs the input quantity, it is fuzzified, and the output fuzzy quantity is obtained by using fuzzy rules and reasoning, and then the precise PI control parameters are obtained by defuzzification.

[0037] Furthermore, the control of the SVPWM module includes:

[0038] 1) Space partition:

[0039] In the α-β plane, the voltage vector space is divided into six sectors corresponding to different combinations of switch states, and each sector corresponds to a different motor phase voltage, generating a three-phase voltage waveform;

[0040] 2) Target vector decomposition:

[0041] Through U α and U β Defined target voltage vector U ref , determine the angular position of the vector in the current sector. Then decompose the target voltage vector into two adjacent basic vectors.

[0042] 3) Switching time calculation:

[0043] According to the amplitude and angle of the target voltage vector, the action time of the adjacent basic vector and the action time of the zero vector are calculated. The action time of each switching state is determined by the following relationship:

[0044] T1+T2+T0=T S

[0045] Where T S is the control period of SVPWM;

[0046] 4) Switch sequence generation:

[0047] The corresponding switching sequence is generated according to the action time. SVPWM switches the switches in a specific sequence within each control cycle to modulate the three-phase coils of the motor and generate a three-phase voltage signal.

[0048] In SVPWM control, each phase voltage is represented as a modulation signal and output to the three-phase inverter of the stepper motor to generate the actual three-phase current that drives the stepper motor;

[0049] 5) After driving the motor coil current, the d-axis and q-axis currents of the motor control the flux and torque respectively.

[0050] Furthermore, in S8, the EKF algorithm steps include:

[0051] initialization:

[0052] According to the state estimation value x at the previous moment and the input vector, the state variable of m at the next moment m+1 is predicted, and the estimation equation is:

[0053]

[0054] Error covariance matrix:

[0055]

[0056] Update phase:

[0057] Calculate the Kalman gain to update the state estimate and state error covariance matrix; update the current state estimate and the state error covariance matrix based on the voltage and current sensor data and the predicted state;

[0058] Kalman gain:

[0059]

[0060] Revised estimates:

[0061]

[0062] The coequation matrix at the next moment:

[0063]

[0064] Output the current state estimate, including the motor rotor electrical angle and mechanical speed;

[0065] is the transfer matrix of the stepper motor EKF system, P m+1 is the error covariance matrix of the prior estimate, K m+1 is the Kalman gain, L is the measurement matrix, Q is the covariance matrix of the system noise, R is the covariance matrix of the measurement error, and Y k+1 is the measured value.

[0066] Furthermore, during the low-speed movement, the speed of the stepping motor is 0 to 30% of the rated speed;

[0067] When moving at medium and high speeds, the speed of the stepper motor is above 30% of the rated speed.

[0068] The present invention has the following beneficial effects:

[0069] 1) The present invention uses the EKF algorithm for state estimation, and can accurately control the speed and angle of the motor without relying on the position sensor, which not only reduces the system cost, but also improves the reliability and environmental adaptability of the system. According to the model in the two-phase stationary coordinate system, the simplified two-phase bipolar hybrid stepper motor model includes a permanent magnet rotor and two stator windings 90° apart. Ignoring load disturbances, the rotor position of the two-phase hybrid stepper motor is detected based on Kalman filtering. The speed and current dual closed-loop dq decoupling control strategy ensures the dual closed-loop control of current and speed of the motor when it runs at high speed. The present invention enables the motor to provide stable and responsive rotational power in high-precision applications such as explosion-proof pan-tilt heads.

[0070] 2) The sensorless design reduces potential failure points and improves system safety and maintenance convenience. In special environments such as explosion-proof, the application of this control system not only ensures the safety of operators, but also ensures the stable operation of equipment under extreme conditions, improving production efficiency while also ensuring safety during the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 It is a system structure diagram corresponding to the method of the present invention;

[0072] Figure 2 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0073] The present invention will be further described below in conjunction with the accompanying drawings.

[0074] like Figure 1 and Figure 2 The present invention provides a method for controlling an explosion-proof pan / tilt stepper motor without a position sensor, comprising:

[0075] When the explosion-proof PTZ needs to move at a low speed (the speed of the stepper motor is 0-30% of the rated speed): the stepper motor is controlled by an open-loop S-type acceleration and deceleration algorithm;

[0076] The explosion-proof gimbal motion instructions (including: direction, rotation angle, rotation time) are input to the S-type acceleration and deceleration generator inside the MCU. The S-type acceleration and deceleration generator calculates and generates the stepper motor motion curve data based on the original hardware data of the stepper motor (including: step angle, crystal oscillator frequency, motor beats, timer digits) and the input explosion-proof gimbal motion instructions, including the number of stepper motor steps at each moment in the acceleration, deceleration, and uniform speed stages.

[0077] When the explosion-proof PTZ needs to move at medium to high speed (the speed of the stepper motor is above 30% of the rated speed), the steps are as follows:

[0078] S1: The MCU written with the dual closed-loop speed regulation algorithm receives the control command to start the explosion-proof PTZ and initializes the program. Then it starts the corresponding sensor and drive circuit, collects the current and voltage data of the stepper motor through the current sensor and voltage sensor, and transmits it to the MCU.

[0079] S2: After processing the collected data, the MCU obtains the current and voltage signals of the stepper motor and calculates the motor torque and speed based on the motor model and the data from the two sensors.

[0080] The specific motor model is as follows: the core magnetic resistance and leakage flux are ignored, the air gap magnetic permeability only considers the average component and the fundamental component, and the motor model of the three-phase hybrid stepper motor is constructed assuming that the motor is completely symmetrical inside.

[0081] Taking winding a as an example, for any winding abc, the voltage equation is:

[0082]

[0083] Where V a is the voltage of phase a, Ψ 总 is the total magnetic flux of the winding, e a is the back electromotive force of phase a winding.

[0084]

[0085] Where, J is the moment of inertia of the stepper motor rotor; B is the viscous friction coefficient; K e is the torque constant of the stepper motor; L is the inductance of the stator winding; ω z is the mechanical angular velocity of the rotor; θ is the electrical angular velocity of the rotor.

[0086] Winding b and winding c are the same as winding a.

[0087] S3: The magnetic field weakening control module adaptively calculates the magnetic field weakening gain according to the magnetic field weakening control small signal model to obtain the dq axis current control signal.

[0088] The specific steps are: using the small signal model to dynamically adjust the weak magnetic gain, the gain value is adjusted in real time based on the weak magnetic control small signal model to adapt to the needs of the motor under different operating conditions.

[0089] The weak magnetic control module is equipped with judgment conditions for entering and exiting the weak magnetic area:

[0090] Low speed area: When the motor speed is lower than the set threshold, it is prohibited to enter the weak magnetic control to avoid affecting the torque output at low speed.

[0091] Heavy load condition: According to the change of load torque, it is judged in real time whether it can enter the weak magnetic field area. When the load is too large, avoid entering the weak magnetic field control area to prevent insufficient torque.

[0092] Rapid acceleration state: When the system detects that the motor needs to accelerate rapidly (for example, the speed change rate reaches a certain threshold), it should temporarily exit the weakening magnetic control to prevent the misuse of weakening magnetic control when the torque demand is high, which may lead to a decrease in acceleration performance.

[0093] The small signal model is:

[0094] Select an operating point in the weak magnetic control area. This operating point is the equilibrium state of the current speed and load conditions, which provides the basis for weak magnetic control. Assume that the voltage, current and flux parameters of the stepper motor fluctuate slightly. Assume that the disturbances of current and angle are Δi a ,Δi b ,Δi c ,Δθ, substitute the nonlinear stepper motor mathematical model equation into the small signal variable, and perform Taylor expansion on each variable at the working point, retain the first-order term, and ignore the high-order small quantity, so as to obtain the linearized equation:

[0095]

[0096]

[0097] θ0 is the angular position of the stable operating point, i.e. the reference angle of the motor;

[0098] Convert the above linearized equations into state space form, define the state vector x = [Δia, Δib, Δic, Δθ], and the input vector u = [ΔVa, ΔVb, ΔVc, Δω] T

[0099] Equation of state:

[0100]

[0101] Among them, A is the system matrix, which describes the linear relationship between state variables, and B is the input matrix, which describes the influence of input variables on state variables.

[0102] S4: Speed ​​and current dual closed-loop dq decoupling control is realized through a dual closed-loop speed control algorithm, in which the speed outer loop compares the target speed with the actual speed, calculates the speed error, calculates the speed control signal through the fuzzy PI regulator, and converts the speed control signal into a dq axis control signal;

[0103] The torque inner loop compares the target torque with the actual torque, calculates the torque error, calculates the torque control signal through the PI regulator, and converts the torque control signal into a dq-axis control signal.

[0104] S5: The dq axis control signal is transformed into the voltage control signal of the αβ axis through inverse park transformation.

[0105] S6: The drive circuit receives the voltage control signal of the αβ axis and uses the space vector modulation SVPWM module to drive the motor coil current and control the rotation of the stepper motor.

[0106] The specific implementation process of SVPWM is as follows:

[0107] 1) Spatial partitioning: On the α-β plane, the voltage vector space is divided into six sectors (one sector every 60°), corresponding to different switching state combinations. These sectors correspond to different motor phase voltages, generating three-phase voltage waveforms.

[0108] 2) Target vector decomposition: through U α and U β Defined target voltage vector U ref , determine the angular position of the vector in the current sector. Then decompose the target voltage vector into two adjacent basic vectors.

[0109] 3) Switching time calculation: According to the amplitude and angle of the target voltage vector, the action time of the adjacent basic vectors and the action time of the zero vector are calculated. The action time of each switching state is determined by the following relationship:

[0110] T1+T2+T0=T S

[0111] Where T s is the control period of SVPWM.

[0112] 4) Switch sequence generation: Generate the corresponding switch sequence according to the action time. SVPWM will switch the switch in a specific sequence in each control cycle to modulate the three-phase coil of the motor and generate a three-phase voltage signal. In SVPWM control, each phase voltage can be represented as a modulation signal and output to the three-phase inverter of the stepper motor to generate the actual three-phase current to drive the stepper motor.

[0113] 5) After the motor coil current is driven, the motor’s d-axis and q-axis currents control the flux and torque respectively. Under this control strategy, by adjusting the target voltage vector U ref The direction and amplitude of the stepper motor can be precisely controlled, including speed, torque and positioning control.

[0114] S7: The voltage and current signals collected in step S2 are transformed by Clark and Park to obtain the current signals of the dq axes, and used as the actual torque of the speed outer loop in step S4 to perform closed-loop control on the motor torque.

[0115] S8: The voltage and current signals collected in step S2 are transformed by Clark to obtain the voltage and current signals of the αβ axis, and then the actual motor speed is estimated using the motor model through the EKF algorithm, and the actual speed of the speed outer loop in step S4 is used to perform closed-loop control of the motor speed. The MCU repeats S1 to S6 to achieve closed-loop control so that the motor speed and angle reach the target values.

[0116] The specific steps of the EKF algorithm are:

[0117] Initialization: Predict the state variables of m at the next moment m+1 based on the state estimate x at the previous moment and the input vector; set the initial state estimate and the initial error covariance matrix.

[0118] Estimated equation:

[0119]

[0120] Error covariance matrix:

[0121]

[0122] Update phase: calculate the Kalman gain to update the state estimate and state error covariance matrix; update the current state estimate based on sensor data and predicted state; update the state error covariance matrix;

[0123] Kalman gain:

[0124] K m+1 =P m+1 L T (LP m+1 L T +R) -1

[0125] Revised estimates:

[0126]

[0127] The coequation matrix at the next moment:

[0128]

[0129] Output the current state estimate, including the motor rotor electrical angle and mechanical speed.

[0130] is the transfer matrix of the stepper motor EKF system, P m+1 is the error covariance matrix of the prior estimate, K m+1 is the Kalman gain, L is the measurement matrix, Q is the covariance matrix of the system noise, T is the covariance matrix of the measurement error, and Y k+1 is the measured value.

[0131] The above description is only a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements without departing from the principle of the present invention, and these improvements should also be regarded as within the protection scope of the present invention.

Claims

1. A method for controlling an explosion-proof pan / tilt stepper motor without a position sensor, characterized in that: include: When the explosion-proof PTZ needs to move at a low speed: the stepper motor is controlled by an open-loop S-type acceleration and deceleration algorithm; When the explosion-proof gimbal needs to move at medium or high speed, the steps are as follows: S1: The MCU written with the dual closed-loop speed regulation algorithm receives the control command to start the explosion-proof PTZ and initializes the program. Then it starts the corresponding sensor and drive circuit, collects the current and voltage data of the stepper motor through the current sensor and voltage sensor, and transmits them to the MCU. S2: After the MCU processes the collected data, it obtains the current and voltage signals of the stepper motor and calculates the motor torque and speed based on the motor model and the data of the two sensors; S3: The weak magnetic field control module adaptively calculates the weak magnetic field gain according to the weak magnetic field control small signal model to obtain the dq axis current control signal; S4: Speed ​​and current dual closed-loop dq decoupling control is realized through a dual closed-loop speed control algorithm, in which the speed outer loop compares the target speed with the actual speed, calculates the speed error, calculates the speed control signal through the fuzzy PI regulator, and converts the speed control signal into a dq axis control signal; The torque inner loop compares the target torque with the actual torque, calculates the torque error, calculates the torque control signal through the PI regulator, and converts the torque control signal into a dq axis control signal; S5: The dq axis control signal is transformed into the voltage control signal of the αβ axis through inverse park transformation; S6: The driving circuit receives the voltage control signal of the αβ axis and uses the space vector modulation SVPWM module to drive the motor coil current and control the rotation of the stepper motor; S7: The voltage and current signals collected in step S2 are transformed by Clark and Park to obtain the current signals of the dq axes, and the current signals are used as the actual torque of the speed outer loop in step S4 to perform closed-loop control on the motor torque; S8: The voltage and current signals collected in step S2 are transformed by Clark to obtain the voltage and current signals of the αβ axis, and then the actual motor speed is estimated using the motor model through the EKF algorithm, and the actual speed of the speed outer loop in step S4 is used to perform closed-loop control of the motor speed. The MCU repeats S1 to S6 to achieve closed-loop control so that the motor speed and angle reach the target values.

2. The method for controlling an explosion-proof pan / tilt stepper motor without position sensor according to claim 1, characterized in that: The motor model is: For any winding abc, the voltage equation of winding a is: Where: V a is the voltage of phase a, ψ 总 is the total magnetic flux of the winding, e a is the back electromotive force of phase a winding; Where: J is the moment of inertia of the stepper motor rotor; B is the viscous friction coefficient; K e is the torque constant of the stepper motor; L is the inductance of the stator winding; ω z is the mechanical angular velocity of the rotor; θ is the electrical angular velocity of the rotor; Winding b and winding c are the same as winding a.

3. The method for controlling an explosion-proof pan / tilt stepper motor without position sensor according to claim 1, characterized in that: In S3, the weakening magnetic field control of the weakening magnetic field control module includes: The explosion-proof gimbal enters the medium and high speed operation state, and adopts the armature reaction magnetic flux in the d-axis that is opposite to the rotor magnetic flux to realize the weakening of the synthetic magnetic field of the stepper motor air gap, and realize the expansion of the motor speed operation range, thereby increasing the operating speed of the motor; the weak magnetic gain of the voltage outer loop method is adaptively calculated according to the weak magnetic control small signal model, and the judgment conditions for entering and exiting the weak magnetic area are set to prevent the vehicle from mistakenly entering the weak magnetic control area under low speed, heavy load and rapid acceleration conditions.

4. The method for controlling an explosion-proof pan / tilt stepper motor without position sensor as claimed in claim 3, characterized in that: In S3, the small signal model is: Select an operating point in the weak magnetic control area. This operating point is the equilibrium state of the current speed and load conditions, which provides the basis for weak magnetic control. Assume that the voltage, current and flux parameters of the stepper motor fluctuate slightly. Assume that the disturbances of current and angle are Δi a ,Δi b ,Δθi c ,Δθ, substitute the nonlinear stepper motor mathematical model equation into the small signal variable, and perform Taylor expansion on each variable at the working point, retain the first-order term, and ignore the high-order small quantity, so as to obtain the linearized equation: θ0 is the angular position of the stable operating point, i.e. the reference angle of the motor; Convert the above linearized equations into state space form, define the state vector x = [Δia, Δib, Δic, Δθ], and the input vector u = [ΔVa, ΔVb, ΔVc, Δω] T Equation of state: Among them, A is the system matrix, which describes the linear relationship between state variables, and B is the input matrix, which describes the influence of input variables on state variables.

5. The method for controlling an explosion-proof pan / tilt stepper motor without position sensor according to claim 1, characterized in that: In S4, the fuzzy PI regulator makes the error e and the error change rate e c As the input quantity, it is fuzzified, and the output fuzzy quantity is obtained by using fuzzy rules and reasoning, and then the precise PI control parameters are obtained by defuzzification.

6. The method for controlling an explosion-proof pan / tilt stepper motor without position sensor as claimed in claim 1, characterized in that: The control of the SVPWM module includes: 1) Space partition: In the α-β plane, the voltage vector space is divided into six sectors corresponding to different combinations of switch states, and each sector corresponds to a different motor phase voltage, generating a three-phase voltage waveform; 2) Target vector decomposition: Through U α and U β The target voltage vector U is defined as ref , determine the angular position of the vector in the current sector. Then decompose the target voltage vector into two adjacent basic vectors; 3) Switching time calculation: According to the amplitude and angle of the target voltage vector, the action time of the adjacent basic vector and the action time of the zero vector are calculated. The action time of each switching state is determined by the following relationship: T1+T2+T0=T S Where T S is the control period of SVPWM; 4) Switch sequence generation: The corresponding switching sequence is generated according to the action time. SVPWM switches the switches in a specific sequence within each control cycle to modulate the three-phase coils of the motor and generate a three-phase voltage signal. In SVPWM control, each phase voltage is represented as a modulation signal and output to the three-phase inverter of the stepper motor to generate the actual three-phase current that drives the stepper motor; 5) After driving the motor coil current, the motor's d-axis and q-axis currents control the flux and torque respectively.

7. The method for controlling an explosion-proof pan / tilt stepper motor without position sensor as claimed in claim 1, characterized in that: In S8, the EKF algorithm steps include: initialization: According to the state estimation value x at the previous moment and the input vector, the state variable of m at the next moment m+1 is predicted, and the estimation equation is: Error covariance matrix: Update phase: Calculate the Kalman gain to update the state estimate and state error covariance matrix; update the current state estimate and the state error covariance matrix based on the voltage and current sensor data and the predicted state; Kalman gain: <h2 style=";text-align:left;direction:ltr">K<h2 style=";text-align:left;direction:ltr"> m+1 <h2 style=";text-align:left;direction:ltr"> =P<h2 style=";text-align:left;direction:ltr"> m+1 <h2 style=";text-align:left;direction:ltr"> L<h2 style=";text-align:left;direction:ltr"> T <h2 style=";text-align:left;direction:ltr"> (LP<h2 style=";text-align:left;direction:ltr"> m+1 <h2 style=";text-align:left;direction:ltr"> L<h2 style=";text-align:left;direction:ltr"> T <h2 style=";text-align:left;direction:ltr"> +R)<h2 style=";text-align:left;direction:ltr"> -1 Revised estimates: The coequation matrix at the next moment: Output the current state estimate, including the motor rotor electrical angle and mechanical speed; is the transfer matrix of the stepper motor EKF system, P m+1 is the error covariance matrix of the prior estimate, K m+1 is the Kalman gain, L is the measurement matrix, Q is the covariance matrix of the system noise, R is the covariance matrix of the measurement error, and Y k+1 is the measured value.

8. The method for controlling an explosion-proof pan / tilt stepper motor without position sensor as claimed in claim 1, characterized in that: During the low-speed movement, the speed of the stepper motor is 0 to 30% of the rated speed; When moving at medium and high speeds, the speed of the stepper motor is above 30% of the rated speed.

Images