Device and method for inhibiting uncertainty disturbance and improving conveying performance of euphausia superba conveying suction pump

Abstract

The invention belongs to the technical field of numerical control, and discloses a device and method for inhibiting uncertainty disturbance and improving the conveying performance of an euphausia superba conveying suction pump. The lumped disturbance of the system is estimated by using a disturbance observer, and the constraint of the disturbance upper bound on the conservative property of the control design is avoided; then, a novel sliding mode device is adopted to suppress system lumped disturbance, and the robustness of the system is improved; the novel sliding mode controller adds an exponential function item and a power function item in the reaching law to enable the system state to converge rapidly. A sigmoid function is used for replacing a switching function, continuous control input is achieved, high-frequency buffeting is weakened, and stability and continuity of control signals are guaranteed. Therefore, the positioning precision is improved, a stable control signal can be generated, the control performance of the system is obviously improved, the tracking error is reduced, high-frequency oscillation is avoided, and the control precision of the euphausia superba conveying suction pump servo system is further improved.

Description

Technical Field

[0001] This invention belongs to the field of numerical control technology and relates to a device and method for suppressing uncertainty disturbances and improving the conveying performance of an Antarctic krill conveying pump. Background Technology

[0002] With increased efforts in Antarctic krill resource development and the seafood processing industry's transformation towards "high quality and large scale," efficient transport of Antarctic krill has become a key link affecting the efficiency of the processing chain and product value, with the suction pump system playing the role of the "core of fluid transport." Stable transport of Antarctic krill results in 18% higher subsequent sorting efficiency, 12% lower krill kernel breakage rate, and a 20% increase in the qualified rate of frozen products compared to fluctuating transport. However, the unique characteristics of Antarctic krill transport are gradually limiting the performance of the suction pump system: the mixture of Antarctic krill and water is not a homogeneous medium; its concentration fluctuates with the catch batch, such as differences in krill density in different sea areas. The water-krill mixing ratio is dynamically adjusted due to changes in flow rate during the washing process. Furthermore, ice blocks of varying sizes or shrimp shell impurities are often mixed in during transport. These factors directly lead to "violent and irregular" fluctuations in the suction pump load torque, with fluctuation frequencies exceeding 5 Hz, posing extreme challenges to the motor-driven suction pump control system.

[0003] Most mainstream Antarctic krill conveying pumps currently use "traditional proportional-integral-derivative (PID) control" or "simple closed-loop control" schemes. Their shortcomings are particularly prominent under complex load conditions: First, the response speed is lagging. When faced with sudden load changes, such as the sudden intake of a large amount of ice or other impurities, the response delay of traditional control systems exceeds 0.1 seconds, which can easily cause pump blockage or motor overheating, leading to shutdown. Each time this happens, the pump body needs to be disassembled to clean the impurities and the motor needs to be inspected, which is time-consuming, interrupts production continuity, and shortens the life of the motor bearings. Second, the anti-disturbance capability is weak. It cannot compensate for deviations caused by load fluctuations in real time, resulting in excessive fluctuations in pump outlet pressure. This can not only cause pipeline leakage due to sudden pressure rises, but also exacerbate the breakage of Antarctic krill due to fluid impact, directly reducing the economic value of the product.

[0004] More importantly, the hardware and algorithm design of traditional control systems are ill-suited to the dynamic operating conditions of Antarctic krill transport: the ordinary encoders they use have low resolution and cannot accurately capture minute changes in motor speed; the control algorithms do not consider the randomness of load changes and rely solely on PID regulation with fixed parameters, which cannot respond to fluctuations in fluid characteristics in real time. As the industry demands "high stability (1500 hours of continuous operation without failure), high responsiveness (load change response time ≤0.05 s), and high accuracy (speed fluctuation ≤1%)" for suction pump systems, "rapid response-disturbance suppression" has become the core breakthrough point. If independent control of these two aspects cannot be achieved, load fluctuations will either lead to insufficient transport volume due to speed instability or damage to the equipment due to torque overload; if the control response is delayed, the freshness of Antarctic krill may decrease due to prolonged residence time in the pump, with freshness indicators decreasing for every minute of delay. Therefore, it is urgent to adopt advanced intelligent control algorithms to break through the bottleneck of rapid response in Antarctic krill suction pump systems, realize real-time observation and dynamic compensation of load fluctuations, ensure the stable and efficient operation of suction pump systems under complex fluid conditions, and help the Antarctic krill processing industry overcome current technical constraints. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to address the shortcomings of the prior art by providing a device and method for suppressing uncertainty disturbances and improving the conveying performance of an Antarctic krill conveying pump, so as to enable the Antarctic krill conveying pump to resist random disturbances and accurately locate the target.

[0006] The technical solution of the present invention:

[0007] A device for suppressing uncertainty disturbances and improving the conveying performance of an Antarctic krill conveying pump includes a power supply section, a detection circuit, a DSP processor section, an IPM isolation protection drive circuit, a host computer, and a permanent magnet synchronous motor.

[0008] The power supply section includes a rectifier circuit and an IPM inverter circuit;

[0009] The rectifier circuit is connected to a three-phase AC power supply to convert AC power into DC power.

[0010] The IPM inverter circuit converts the DC power output from the rectifier circuit into AC power, and connects the output of the IPM inverter circuit to the permanent magnet synchronous motor on the Antarctic krill conveying pump to supply power to the permanent magnet synchronous motor.

[0011] The detection circuit includes a current detection circuit, a Hall sensor, a position and speed detection circuit, and an incremental encoder;

[0012] The input of the current detection circuit is connected to the output of the IPM inverter circuit through a Hall sensor. The output of the current detection circuit is connected to one signal input of the DSP processor. This is used to collect the rotor current of the permanent magnet synchronous motor through the Hall sensor and convert the collected analog current into a digital quantity that the DSP processor can recognize.

[0013] The input of the position and speed detection circuit is connected to the output of the permanent magnet synchronous motor through an incremental encoder. The output of the position and speed detection circuit is connected to another signal input of the DSP processor, which is used to acquire the position and speed signals of the permanent magnet synchronous motor rotor through the incremental encoder and convert them into digital quantities that the DSP processor can recognize.

[0014] The DSP processor section includes the DSP processor and its peripheral circuits. It calculates the difference between the reference speed signal and the speed signal of the permanent magnet synchronous motor detected by the incremental encoder to obtain the tracking error of the Antarctic krill conveying pump servo system. This error serves as the input to the novel sliding mode controller. A disturbance observer estimates the lumped disturbance of the novel sliding mode controller suppression system in real time. Then, the lumped disturbance of the novel sliding mode controller suppression system is applied to improve its robustness. The output signal of the novel sliding mode controller suppression system ensures its continuity and stability. Finally, the control signal of the permanent magnet synchronous motor is calculated, generating a PWM signal to servo drive the permanent magnet synchronous motor of the Antarctic krill conveying pump servo system. The PWM port of the DSP processor is connected to another input of the IPM inverter circuit via an IPM isolation protection drive circuit.

[0015] The IPM isolation protection drive circuit is used for opto-isolation and to drive the six IGBTs in the IPM inverter circuit.

[0016] The host computer stores the control program. The control program first processes the data collected by the detection circuit, and then calculates the tracking error by subtracting the processed data from the reference speed signal. This error is used as the input variable of the new sliding mode controller. The new sliding mode control algorithm is executed, and the actual current and actual speed of the permanent magnet synchronous motor are collected by the input disturbance observer. The lumped disturbance of the new sliding mode controller suppression system is estimated. Finally, the program of the new sliding mode control algorithm is downloaded to the DSP processor through the SCI serial port bus and connected to the SCI serial port pin of the DSP processor for execution, driving the permanent magnet synchronous motor servo system.

[0017] The DSP processor uses a TMS320F28379D chip. The peripheral circuitry of the DSP processor includes a level conversion circuit, a fault signal acquisition circuit, a DSP crystal oscillator circuit, a JTAG circuit, and a DSP reset circuit. The level conversion circuit converts the 5V power supply voltage to the 3.3V operating voltage for the DSP processor. The fault signal acquisition circuit is connected to the external interrupt pin of the DSP processor, and the DSP processor's interrupt program handles the fault. The DSP crystal oscillator circuit provides a 30MHz operating frequency for the DSP processor, and pins 1 and 4 of the DSP crystal oscillator circuit are connected to the X1 and X2 interfaces of the DSP processor, respectively. The JTAG circuit is used to test the electrical characteristics of the DSP processor and detect any problems. Pins 1, 2, 3, 7, 9, 11, 13, and 14 of the JTAG circuit are connected to pins 79, 78, 76, 77, 87, 87, 85, and 86 of the DSP processor, respectively. The reset circuit is used to restore the DSP processor's circuitry to its initial state; pin 1 of the DSP reset circuit is connected to pin 80 of the DSP processor.

[0018] A method for suppressing uncertainty disturbances and improving the conveying performance of an Antarctic krill conveying pump includes the following steps:

[0019] Step 1: Input the given rotation speed signal, and the permanent magnet synchronous motor in the Antarctic krill conveying pump servo system will receive the rotation speed signal and start moving;

[0020] Step 2: Determine the actual rotational speed and current of the permanent magnet synchronous motor rotor;

[0021] After the permanent magnet synchronous motor of the Antarctic krill conveying pump servo system starts moving, the detection circuit starts working. The incremental encoder outputs two-phase quadrature square wave pulse signals and a zero-position pulse signal through the position and speed detection circuit, for a total of three pulse signals. All three pulse signals are sent to the quadrature encoder pulse input unit EQEP built into the DSP processor. The resolution of the permanent magnet synchronous motor encoder is improved by quadruple frequency multiplication. At the same time, the general-purpose timer built into the DSP processor is set to directional increment / decrement counting mode. The position offset of the permanent magnet synchronous motor rotor is obtained from the number of pulses of the two-phase quadrature square wave pulse signals, and the direction of rotation of the permanent magnet synchronous motor rotor is obtained from the lead relationship of the two-phase quadrature square wave pulse signals, thus obtaining the position and speed of the permanent magnet synchronous motor rotor. The current of the permanent magnet synchronous motor rotor is collected by the Hall sensor.

[0022] Step 3: Using the position and velocity information of the electronic rotor acquired in Step 2, the tracking error is first calculated in the DSP processor. The lumped disturbance of the novel sliding mode controller suppression system is estimated in real time using a disturbance observer. Then, the lumped disturbance of the novel sliding mode controller suppression system is applied to improve its robustness. The output signal of the novel sliding mode controller ensures the continuity and stability of the suppression system. Finally, the control signal of the permanent magnet synchronous motor, i.e., the control current of the permanent magnet synchronous motor, is calculated. The specific steps are as follows:

[0023] Step 3.1: Establish the electromagnetic torque equation and mechanical motion equation of the permanent magnet synchronous motor;

[0024] Establishing the dq axis model: For permanent magnet synchronous motors, field-oriented control is adopted. The axis of the permanent magnet pole is taken as the d axis, and the q axis is taken as 90° ahead of the d axis in the direction of rotor rotation of permanent magnet synchronous motor. In this way, a dq coordinate system that rotates synchronously with the rotor of permanent magnet synchronous motor is established.

[0025] Let the d-axis current component of the inner current loop be i d If the ratio = 0, making the stator current vector and the permanent magnet magnetic field orthogonal in space, then the electromagnetic torque equation of the permanent magnet synchronous motor is:

[0026] (1)

[0027] In the formula, Electromagnetic torque; It is the extreme logarithm; The nominal flux linkage of a permanent magnet; i d i q L d L q These represent the current and inductance along the d-axis and q-axis, respectively; using i d =0 control, rotor current and stator current are spatially orthogonal, motor type is surface-mounted permanent magnet synchronous motor. , For the stator inductance, the electromagnetic torque equation simplifies to:

[0028] (2)

[0029] The mechanical motion equations of a permanent magnet synchronous motor are:

[0030] (3)

[0031] In the formula, ω m T is the mechanical angular velocity of the motor. L Where J0 is the load torque, J0 is the nominal moment of inertia of the rotor, and B0 is the nominal viscous friction coefficient of the motor.

[0032] The mechanical motion equations of a permanent magnet synchronous motor considering variations in motor parameters and load torque are as follows:

[0033] (4)

[0034] In the formula, , , , For the actual rotor nominal moment of inertia, nominal viscous friction coefficient, and nominal flux linkage of the permanent magnet synchronous motor;

[0035] Rearranging equation (4), we get:

[0036] (5)

[0037] In the formula, , , The lumped disturbance of the novel sliding mode controller suppression system is expressed as:

[0038] (6)

[0039] Step 3.2: Based on the actual position detected in Step 2, define the tracking error as:

[0040] (7)

[0041] In the formula, For speed tracking, This is the reference speed of the permanent magnet synchronous motor rotor. To determine the actual rotational speed of the permanent magnet synchronous motor rotor, the sliding surface is designed as follows:

[0042] (8)

[0043] In the formula, Here, is the gain parameter, satisfying the Hurwitz condition, and s is the sliding surface. To track the error derivative, a reaching law method is used to ensure that the system state reaches and remains on the sliding surface within a finite time. A novel sliding surface reaching law is designed as follows:

[0044] (9)

[0045] In the formula, Let be the coefficient of the reaching law. To switch the gain, , This is an estimate of the lumped disturbance in the novel sliding mode controller's suppression system; when the system state deviates far from the sliding surface, the value in the novel sliding mode reaching law... and Together, they exert an accelerating effect, with the approach rate exceeding the exponential approach law, thus accelerating the rate at which the system state reaches the sliding surface; as the system state approaches the sliding surface, Rapid decay, It plays a dominant role, preventing premature decrease in the reaching rate that could lead to convergence stagnation; the novel sliding mode reaching law changes with the system state and the distance between the sliding surfaces, enhancing the adaptability of the reaching rate; and it introduces... This can improve the robustness of the system; replacing the switching function with the sigmoid function, its flexible gain characteristics and gentle function gradient are both beneficial for reducing high-frequency chattering in sliding mode control, expressed as:

[0046] (10)

[0047] In the formula, Indicates the steepness of the function curve;

[0048] Differentiating equation (8) and substituting it into equation (5), we get:

[0049] (11)

[0050] According to equations (11) and (9), we get:

[0051] (12)

[0052] The control law for the novel sliding mode control, derived from equation (12), is as follows:

[0053] (13)

[0054] Step 3.3: Design the disturbance observer;

[0055] A novel perturbation observation method for perturbation feedforward compensation is designed as follows:

[0056] (14)

[0057] In the formula, , and For perturbation observer gain, This is the upper bound of the rate of change of the disturbance. For symbolic functions, and These are the estimated values ​​of the actual speed of the permanent magnet synchronous motor and the estimated values ​​of the lumped disturbance of the novel sliding mode controller suppression system, respectively. This disturbance observer can accurately estimate the lumped disturbance of the novel sliding mode controller suppression system, and through the second-order sliding mode characteristics, it hides the sign function that causes chattering in the integral action, thereby suppressing system chattering in essence and avoiding the introduction of additional noise by disturbance estimation.

[0058] Step 4: The DSP processor generates six corresponding PWM pulse signals to drive the permanent magnet synchronous motors respectively;

[0059] The PWM signal output by the DSP processor is converted into a drive signal by the IPM isolation protection drive circuit. The fixed 220V three-phase AC power is rectified into stable DC power and sent to the IPM inverter circuit. The IPM inverter circuit controls the conduction and cutoff of the six IGBTs in the IPM inverter circuit according to the six PWM pulse signals generated by the DSP processor, so as to obtain the required three-phase AC power to drive the permanent magnet synchronous motor, realize the high-precision control of the Antarctic krill conveying pump servo system, and thus improve the conveying performance of the Antarctic krill conveying pump.

[0060] The beneficial effects of adopting the above technical solution are as follows: The device and method provided by this invention for suppressing uncertainty disturbances and improving the conveying performance of Antarctic krill conveying pumps utilize a disturbance observer to estimate the lumped disturbance of the system, avoiding the constraint of the upper bound of the disturbance on the conservatism of the control design; then, a novel sliding mode controller is used to suppress the lumped disturbance of the system, improving the robustness of the system; the novel sliding mode controller adds exponential and power function terms to the reaching law, enabling the system state to converge rapidly. When the system state approaches the sliding surface, the exponential term in the reaching law decays rapidly, and the improved power function term plays a dominant role, avoiding premature decrease in the reaching rate that leads to convergence stagnation, enhancing the adaptability of the reaching rate, and reducing the arrival time. Replacing the switching function with a sigmoid function achieves continuous control input, weakens high-frequency chattering, and ensures the stability and continuity of the control signal. This not only improves positioning accuracy but also generates a stable control signal, significantly improving the control performance of the system, reducing tracking errors, avoiding high-frequency oscillations, and thus improving the control accuracy of the Antarctic krill conveying pump servo system. In addition, the use of high-performance Hall sensors and incremental encoders improves the accuracy of the acquired signals, and the use of the TMS320F28379D chip as the core processor enhances the data processing capability of the servo system and improves the conveying efficiency of the Antarctic krill conveying pump. Attached Figure Description

[0061] Figure 1 A structural diagram of a device for a servo control system for an Antarctic krill conveying pump provided in an embodiment of the present invention;

[0062] Figure 2This is a schematic diagram of the main circuit of the permanent magnet synchronous motor in the Antarctic krill conveying and suction pump servo control system provided in an embodiment of the present invention.

[0063] Figure 3 The circuit diagram of the current detection circuit provided in the embodiment of the present invention;

[0064] Figure 4 A circuit diagram of the position and velocity detection circuit provided in an embodiment of the present invention;

[0065] Figure 5 This is a schematic diagram of the peripheral circuit connection of the DSP processor provided in an embodiment of the present invention;

[0066] Figure 6 A circuit schematic diagram of a DSP power supply level conversion circuit provided in an embodiment of the present invention;

[0067] Figure 7 A circuit schematic diagram of the Fault signal acquisition circuit provided in an embodiment of the present invention;

[0068] Figure 8 The circuit schematic diagram of the DSP crystal oscillator circuit provided in the embodiment of the present invention;

[0069] Figure 9 The circuit schematic diagram of the JTAG circuit provided in the embodiments of the present invention;

[0070] Figure 10 The circuit schematic diagram of the DSP reset circuit provided in the embodiment of the present invention;

[0071] Figure 11 The circuit schematic diagram of the IPM protection isolation drive circuit provided in the embodiment of the present invention;

[0072] Figure 12 A flowchart illustrating the method for suppressing uncertainty disturbances and improving the conveying performance of an Antarctic krill conveying pump according to an embodiment of the present invention;

[0073] Figure 13 A schematic diagram of the algorithm principle for suppressing uncertainty disturbances and improving the conveying performance of Antarctic krill conveying pumps, provided in an embodiment of the present invention;

[0074] Figure 14 A comparison of tracking error curves of the Antarctic krill conveying pump servo system based on traditional PID control and novel sliding mode control under sinusoidal disturbance conditions, provided for embodiments of the present invention.

[0075] Figure 15 A comparison of tracking error curves of the Antarctic krill conveying pump servo system based on traditional PID control and novel sliding mode control under sudden load disturbance, provided for embodiments of the present invention; Detailed Implementation

[0076] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings and technical solutions.

[0077] A device for suppressing uncertainty disturbances and improving the conveying efficiency of an Antarctic krill conveying pump, the structure of which is as follows: Figure 1 As shown, it includes a power supply section, a detection circuit, a DSP processor section, an IPM isolation protection drive circuit, a host computer, and a permanent magnet synchronous motor.

[0078] The schematic diagram of the main circuit of the permanent magnet synchronous motor is as follows: Figure 2 As shown.

[0079] The power supply section includes a rectifier circuit and an IPM inverter circuit;

[0080] The rectifier circuit, serving as the input to the entire control device, receives the signal indicating the final operating speed of the permanent magnet synchronous motor, as given by the user. The input of the rectifier circuit is connected to a three-phase AC power supply, converting the changing AC power into stable DC power. Its output is connected to the IPM inverter circuit. The IPM inverter circuit converts the DC power output from the rectifier circuit back into AC power, and its output is connected to the permanent magnet synchronous motor to supply power to it.

[0081] In the rectifier circuit, the anode of the rectifier bridge is connected to the N terminal of the IPM inverter circuit, and its cathode is connected to the P terminal of the IPM inverter circuit. The three-phase current output by the IPM inverter circuit is connected to the permanent magnet synchronous motor through the output terminals U, V, and W. P and N are the input terminals of the IPM inverter circuit after rectification, smoothing, and filtering by the frequency converter; P is the positive terminal, and N is the negative terminal. The rectifier unit adopts a bridge uncontrolled rectification method with large capacitor filtering, which can obtain a constant voltage suitable for IPM operation.

[0082] In this embodiment, the motor's start and stop are controlled by normally open contact switch A and normally closed contact switch B, respectively. During circuit operation, the three-phase AC power is converted from 220V to a three-phase AC power with an effective value approximately equal to the input voltage of the IPM inverter circuit via a transformer. This is then passed through a rectifier bridge transistor circuit to obtain a pulsating DC voltage. Next, the DC voltage is smoothed by capacitor filtering, and a stable voltage is applied across the PN terminals of the IPM inverter circuit. The converted DC power is then inverted into frequency-converted three-phase AC power by the IPM inverter circuit, thereby driving the permanent magnet synchronous motor. The IGBTs in the IPM inverter circuit are controlled by a PWM pulse sequence output from the control circuit to achieve the required amplitude and phase of the three-phase AC power.

[0083] The detection circuit includes a current detection circuit, a Hall sensor, a position and speed detection circuit, and an incremental encoder.

[0084] The input of the current detection circuit is connected to the output of the IPM inverter circuit via a Hall sensor. The output of the current detection circuit is connected to the ADC port of the DSP processor. This circuit is used to acquire the rotor current of the permanent magnet synchronous motor via the Hall sensor and convert the acquired analog current into a digital quantity that the DSP processor can recognize. The current detection circuit is as follows: Figure 3 As shown, the current detection circuit converts the three-phase rotor current of the permanent magnet synchronous motor into digital form via a sensor and then into a series of transformations by the DSP processor. Since the system in this embodiment is a three-phase balanced system, meaning the vector sum of the three-phase currents is zero, only two phase currents need to be detected to obtain the three-phase current. This embodiment uses an LTS25-NP type sensor to detect the current.

[0085] The input of the position and speed detection circuit is connected to the output of the permanent magnet synchronous motor via an incremental encoder. The output of the position and speed detection circuit is connected to the EQEP port of the DSP processor. This circuit is used to acquire the position and speed signals of the permanent magnet synchronous motor rotor via the incremental encoder and convert them into digital quantities that the DSP processor can recognize. The position and speed detection circuit is as follows: Figure 4 As shown, two orthogonal square wave pulse signals A and B are sent to two capture units EQEP1 (pin 90) and EQEP2 (pin 91) of the DSP processor via a high-speed optocoupler LTV-341W. The capture units inside the DSP processor can be defined by software as orthogonal encoded pulse input units, and then the pulses can be counted. Based on the pulse sequence, the direction, position, and speed of the permanent magnet synchronous motor can be determined.

[0086] During motor operation, an incremental encoder detects the motor's actual speed and position, while a Hall sensor detects the actual current. These three measured values—speed, position, and current—are fed into a DSP processor via a detection circuit.

[0087] The DSP processor receives output signals from the current detection circuit and the position and speed detection circuit. After processing these two signals, the DSP processor outputs the resulting signal to the IPM inverter circuit via the IPM protection and isolation drive circuit. The DSP processor section includes the DSP processor and its peripheral circuits. It calculates the difference between the reference speed signal and the permanent magnet synchronous motor speed signal detected by the incremental encoder to obtain the tracking error of the Antarctic krill conveying pump servo system. This error is used as the input of the novel sliding mode controller. The system lumped disturbance is estimated in real time by the disturbance observer. Then, the novel sliding mode control is used to suppress the system lumped disturbance and improve the system robustness. The output signal of the novel sliding mode controller ensures the continuity and stability of the system. Finally, the control signal of the motor is calculated, generating a PWM signal to servo drive the permanent magnet synchronous motor of the Antarctic krill conveying pump servo system. The PWM port of the DSP processor is connected to another input of the IPM inverter circuit via the IPM isolation and protection drive circuit. In this embodiment, the DSP processor model is TMS320F28379D, and its peripheral circuit connection structure schematic diagram is shown below. Figure 5 As shown. The peripheral circuitry of the DSP processor includes a level conversion circuit, a fault signal acquisition circuit, a DSP crystal oscillator circuit, a JTAG circuit, and a DSP reset circuit, as shown below. Figures 6-10 As shown, the level conversion circuit converts the 5V power supply voltage to the 3.3V operating voltage supplied to the DSP processor. The fault signal acquisition circuit is connected to the external interrupt pin of the DSP processor, and the fault is handled by the DSP processor's interrupt program. The DSP crystal oscillator circuit provides the DSP processor with a 30MHz operating frequency. Pins 1 and 4 of the DSP crystal oscillator circuit are connected to the X1 (pin 104) interface and X2 (pin 102) interface of the DSP processor, respectively. The JTAG circuit is used to test the electrical characteristics of the chip and detect whether there is a problem with the chip. Pins 1, 2, 3, 7, 9, 11, 13, and 14 of the JTAG interface circuit are connected to pins 79, 78, 76, 77, 87, 87, 85, and 86 of the DSP processor, respectively. The DSP reset circuit is used to restore the entire circuit to its initial state. Pin 1 of the DSP reset circuit is connected to pin 80 of the DSP processor.

[0088] The IPM isolation protection drive circuit is used for opto-isolation and to drive the six IGBTs in the IPM inverter circuit. The IPM isolation protection drive circuit, such as... Figure 11 As shown, an IPM (Insulation Power Module) protection drive circuit is used instead of a power device as the power supply device. After being processed by the IPM, the current is supplied to the permanent magnet synchronous motor, enabling the motor to move.

[0089] The control program, written in C language, was written using Code Composer Studio 12.2.0 software and stored on the host computer. The control program first processes the data collected by the detection circuit, then calculates the tracking error by subtracting the collected data from the reference command signal, which is used as the input variable of the new sliding mode controller. The new sliding mode control algorithm is executed, and the actual current and actual speed of the motor are collected by the input disturbance observer to estimate the lumped disturbance of the system. Finally, the C language program with the new sliding mode control algorithm as its core is downloaded to the DSP processor via the SCI serial port bus and run to drive the Antarctic krill conveying and suction pump servo system.

[0090] This embodiment also provides a method for suppressing uncertainty disturbances and improving the conveying efficiency of Antarctic krill transport pumps, which is implemented using the aforementioned algorithm based on novel sliding mode control combined with a disturbance observer. Figure 13 As shown, the specific steps include:

[0091] Step 1: Input a reference speed signal, and the permanent magnet synchronous motor will start moving upon receiving the speed signal;

[0092] Step 2: Determine the actual speed, position, and current of the permanent magnet synchronous motor rotor;

[0093] After the permanent magnet synchronous motor of the Antarctic krill conveying pump starts moving, the detection circuit starts working. The incremental encoder outputs orthogonal square wave pulse signals and zero-position pulse signals through the position and speed detection circuit, for a total of three pulse signals. All pulse signals are sent to the orthogonal encoder pulse input unit EQEP of the DSP processor. The encoder resolution is improved by quadrupling the frequency. At the same time, the general-purpose timer is set to directional increment / decrement counting mode. The rotor position offset is obtained from the number of pulses of the two-phase orthogonal square wave pulse signals, and the rotor direction is obtained from the lead relationship of the two-phase pulses, thus obtaining the rotor speed. The rotor current is collected by the Hall sensor.

[0094] Step 3: Using the data collected in Step 2, the tracking error is first calculated in the DSP processor. The lumped disturbance of the system is estimated in real time through a disturbance observer. Then, a new sliding mode controller is used to suppress the lumped disturbance of the system and improve the robustness of the system. The output signal of the new sliding mode controller ensures the continuity and stability of the system. Finally, the control signal of the motor, i.e., the control current of the permanent magnet synchronous motor, is calculated. The specific steps are as follows:

[0095] Step 3.1: Establish the electromagnetic torque equation and mechanical motion equation of the permanent magnet synchronous motor;

[0096] Establishing the dq axis model: For permanent magnet synchronous motors, field-oriented control is adopted. The axis of the permanent magnet pole is taken as the d axis, and the rotor rotation direction is advanced by 90° electrical angles ahead of the d axis as the q axis. In this way, a dq coordinate system that rotates synchronously with the rotor is established.

[0097] Let the d-axis current component of the inner current loop be i d If the ratio = 0, making the stator current vector and the permanent magnet magnetic field orthogonal in space, then the electromagnetic torque equation of the permanent magnet synchronous motor is:

[0098] (1)

[0099] In the formula, Electromagnetic torque; It is the extreme logarithm; The nominal flux linkage of a permanent magnet; i d i q L d L q These represent the current and inductance along the d and q axes, respectively; using i d =0 control, rotor current and stator current are spatially orthogonal, motor type is surface-mounted permanent magnet synchronous motor. , For the stator inductance, the electromagnetic torque equation simplifies to:

[0100] (2)

[0101] The mechanical motion equation of a permanent magnet synchronous motor is:

[0102] (3)

[0103] In the formula, ω m T is the mechanical angular velocity of the motor. L J0 is the load torque, J0 is the nominal moment of inertia of the rotor, and B0 is the nominal viscous friction coefficient of the motor.

[0104] Because the mixture of Antarctic krill and water is not a homogeneous medium, its concentration fluctuates with each harvest batch, such as differences in krill density across different sea areas. Ice or krill shell impurities are often introduced during transport. These factors directly cause the load on the Antarctic krill transport pump to exhibit "violent and irregular" fluctuations. Furthermore, under actual operating conditions, the motor itself is inevitably affected by various disturbances due to the complex interaction of the internal magnetic field and the dynamic changes in the external load, leading to a decrease in the control accuracy of the Antarctic krill transport pump. Therefore, the motion equation of the permanent magnet synchronous motor considering changes in motor parameters and load torque is as follows:

[0105] (4)

[0106] In the formula, , , , These are the actual parameter values ​​of the motor.

[0107] Rearranging equation (4), we get

[0108] (5)

[0109] In the formula, , , For the lumped disturbance of the system, it is represented as

[0110] (6)

[0111] Step 3.2: Based on the actual rotational speed detected in Step 2, define the tracking error of the Antarctic krill conveying pump servo system as:

[0112] (7)

[0113] In the formula, This is the reference speed for the motor rotor. The sliding surface is designed to be the actual rotational speed of the motor rotor.

[0114] (8)

[0115] In the formula, Satisfying the Hurwitz condition, the sliding surface convergence law method can be used to ensure that the system state reaches and remains on the sliding surface in a finite time. A novel sliding surface convergence law is designed as follows:

[0116] (9)

[0117] In the formula, Let be the coefficient of the reaching law. To switch the gain, , This is an estimate of the lumped disturbance. When the system state deviates far from the sliding surface, the approach law... and Together, they exert an accelerating effect, resulting in a reaching rate greater than the general exponential reaching law, thus accelerating the rate at which the system state reaches the sliding surface. As the system state approaches the sliding surface, Rapid decay, It plays a dominant role, preventing premature decrease in the reaching rate that could lead to convergence stagnation. The novel sliding mode reaching law can vary with the system state and the distance between the sliding surfaces, enhancing the adaptability of the reaching rate. This is achieved by introducing [a specific mechanism / introduction] into the reaching law. This can improve the robustness of the system. Replacing the switching function with the sigmoid function, its flexible gain characteristics and gentle function gradient are beneficial for reducing high-frequency chattering in sliding mode control, expressed as:

[0118] (10)

[0119] In the formula, This indicates the steepness of the function curve.

[0120] Differentiating equation (8) and substituting it into equation (5), we get

[0121] (11)

[0122] According to equations (9) and (11), we get

[0123] (12)

[0124] The control law of the novel sliding mode control is obtained from equation (12) as follows:

[0125] (13)

[0126] Step 3.4: Design the disturbance observer

[0127] Because the mixture of Antarctic krill and water is not a homogeneous medium, its concentration fluctuates with each catch batch, such as differences in krill density across different sea areas. Ice or krill shell impurities are often introduced during transport, directly causing "violent and irregular" load fluctuations in the Antarctic krill transport pump. Furthermore, under actual operating conditions, the motor itself is inevitably affected by various disturbances due to the complex interaction of the internal magnetic field and dynamic changes in the external load, leading to a decrease in the control accuracy of the Antarctic krill transport pump. Therefore, a novel disturbance observation and feedforward compensation method was designed.

[0128] (14)

[0129] In the formula, , and For perturbation observer gain, This is the upper bound of the rate of change of the disturbance. For symbolic functions, and These are the estimated values ​​of the actual motor speed and the lumped disturbance, respectively. This observer can accurately estimate the lumped disturbance and, through second-order sliding mode properties, hides the sign function that causes chattering in the integral action, thereby essentially suppressing system chattering and avoiding the introduction of additional noise in the disturbance estimation.

[0130] The observation error of lumped disturbance is defined as

[0131] (15)

[0132] Taking the derivative of the velocity estimation error, we get

[0133] (16)

[0134] Taking the derivative of the disturbance estimation error, we get

[0135] (17)

[0136] In actual operation, the rate of change of the disturbance is bounded: z is a positive number.

[0137] Define Lyapunov functions as

[0138] (18)

[0139] Differentiating equation (18), we get

[0140] (16)

[0141] because and The signs are consistent, therefore and All are positive terms, therefore The first two terms are negative, and only the third term contains the estimated disturbance value. .therefore, Related negative items for

[0142] (17)

[0143] because It is a negative quadratic term. It is a negative higher-order term, and only the third term contains the perturbation estimation error. .therefore, Related negative items for

[0144] (18)

[0145] because ,so It is a bounded term. Therefore, the bounded disturbance related term... for

[0146] (19)

[0147] Substituting equations (17), (18), and (19) into equation (16), we get

[0148]

[0149] in, and Both of these are always negative, and Since it is a bounded term, it can be adjusted The size of the bounded terms Constant negative item and Dominance, thereby ensuring Therefore, the designed disturbance suppression control system is stable, and the speed error... Speed ​​estimation error and disturbance estimation error It will approach zero, ensuring stable operation of the system in the presence of disturbances.

[0150] Step 4: The DSP processor generates six corresponding PWM pulse signals to drive the two permanent magnet synchronous motors respectively;

[0151] The PWM signal output by the DSP processor is converted into a drive signal by the IPM isolation protection drive circuit. The fixed 220V three-phase AC power is rectified into stable DC power and sent to the IPM inverter circuit. The IPM inverter circuit controls the conduction and cutoff of the six IGBTs in the IPM inverter circuit according to the six PWM pulse signals generated by the DSP processor, so as to obtain the required three-phase AC power to drive the permanent magnet synchronous motor, realize the high-precision control of the Antarctic krill conveying pump servo system, and thus improve the conveying performance of the Antarctic krill conveying pump.

[0152] To verify the effectiveness of the algorithm, the following parameters were selected for the permanent magnet synchronous motor: permanent magnet flux linkage. Rotor moment of inertia Viscous friction coefficient polar number Simulation was performed using MATLAB. Based on the provided motor parameters and the novel sliding mode controller designed in this embodiment, the optimal effect was achieved through repeated debugging using MATLAB. The parameter selections are as follows: , , , , , , A reference speed of 1000 r / min was input to the servo control system of the Antarctic krill transfer pump. To verify the performance of the designed transfer pump under "severe and irregular" fluctuating load torque conditions, a sinusoidal load disturbance with an amplitude of 2 N·m and a frequency of 10 Hz was input to the system. A comparison of the speed tracking error curves of the Antarctic krill transfer pump based on a traditional PID controller and a novel sliding mode controller under sinusoidal load disturbance conditions is shown below. Figure 14 As shown. To verify the performance of the designed transfer pump under sudden load changes such as the sudden intake of a large amount of ice, a 2 N·m load was suddenly applied to the Antarctic krill transfer pump after 3 seconds of stable operation. The speed tracking error curves of the Antarctic krill transfer pump based on a traditional PID controller and the Antarctic krill transfer pump based on a novel sliding mode controller under the sudden load change are compared as follows: Figure 15 As shown in the simulation diagram, traditional PID control performs poorly under sinusoidal load disturbances or abrupt load changes, exhibiting large tracking errors. Under sinusoidal load disturbances, the stable error exceeds 10 r / min, and under abrupt load changes, the instantaneous speed error reaches 15 r / min, with a convergence time of approximately 0.12 s. In contrast, the novel sliding mode controller performs better under sinusoidal load disturbances or abrupt load changes, with a stable error of only about 4 r / min under sinusoidal load disturbances and about 5 r / min under abrupt load changes, with a convergence time of approximately 0.02 s. This indicates that the novel sliding mode controller produces better control performance, with smaller tracking errors and faster response speeds. Therefore, the novel sliding mode control has significant advantages over traditional PID control, generating a more stable and continuous control signal, thereby reducing the system's tracking error, improving the performance of the Antarctic krill transport pump, and verifying the effectiveness of this control method.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A device for suppressing uncertainty disturbances and improving the conveying performance of an Antarctic krill conveying pump, characterized in that, The device for suppressing uncertainty disturbances and improving the conveying performance of the Antarctic krill conveying pump includes a power supply section, a detection circuit, a DSP processor section, an IPM isolation protection drive circuit, a host computer, and a permanent magnet synchronous motor. The power supply section includes a rectifier circuit and an IPM inverter circuit; The rectifier circuit is connected to a three-phase AC power supply to convert AC power into DC power. The IPM inverter circuit converts the DC power output from the rectifier circuit into AC power, and connects the output of the IPM inverter circuit to the permanent magnet synchronous motor on the Antarctic krill conveying pump to supply power to the permanent magnet synchronous motor. The detection circuit includes a current detection circuit, a Hall sensor, a position and speed detection circuit, and an incremental encoder; The input of the current detection circuit is connected to the output of the IPM inverter circuit through a Hall sensor. The output of the current detection circuit is connected to one signal input of the DSP processor. This is used to collect the rotor current of the permanent magnet synchronous motor through the Hall sensor and convert the collected analog current into a digital quantity that the DSP processor can recognize. The input of the position and speed detection circuit is connected to the output of the permanent magnet synchronous motor through an incremental encoder. The output of the position and speed detection circuit is connected to another signal input of the DSP processor, which is used to acquire the position and speed signals of the permanent magnet synchronous motor rotor through the incremental encoder and convert them into digital quantities that the DSP processor can recognize. The DSP processor section includes the DSP processor and its peripheral circuits. It calculates the difference between the reference speed signal and the speed signal of the permanent magnet synchronous motor detected by the incremental encoder to obtain the tracking error of the Antarctic krill conveying pump servo system. This error serves as the input to the novel sliding mode controller. A disturbance observer estimates the lumped disturbance of the novel sliding mode controller suppression system in real time. Then, the lumped disturbance of the novel sliding mode controller suppression system is applied to improve its robustness. The output signal of the novel sliding mode controller suppression system ensures its continuity and stability. Finally, the control signal of the permanent magnet synchronous motor is calculated, generating a PWM signal to servo drive the permanent magnet synchronous motor of the Antarctic krill conveying pump servo system. The PWM port of the DSP processor is connected to another input of the IPM inverter circuit via an IPM isolation protection drive circuit. The IPM isolation protection drive circuit is used for opto-isolation and to drive the six IGBTs in the IPM inverter circuit. The host computer stores the control program. The control program first processes the data collected by the detection circuit, and then calculates the tracking error by subtracting the processed data from the reference speed signal. This error is used as the input variable of the new sliding mode controller. The new sliding mode control algorithm is executed, and the actual current and actual speed of the permanent magnet synchronous motor are collected by the input disturbance observer. The lumped disturbance of the new sliding mode controller suppression system is estimated. Finally, the program of the new sliding mode control algorithm is downloaded to the DSP processor through the SCI serial port bus and connected to the SCI serial port pin of the DSP processor for execution, driving the permanent magnet synchronous motor servo system.

2. The device for suppressing uncertainty disturbances and improving the conveying performance of Antarctic krill conveying pumps according to claim 1, characterized in that, The DSP processor uses a TMS320F28379D chip. The peripheral circuitry of the DSP processor includes a level conversion circuit, a fault signal acquisition circuit, a DSP crystal oscillator circuit, a JTAG circuit, and a DSP reset circuit. The level conversion circuit converts the 5V power supply voltage to the 3.3V operating voltage for the DSP processor. The fault signal acquisition circuit is connected to the external interrupt pin of the DSP processor, and the DSP processor's interrupt program handles the fault. The DSP crystal oscillator circuit provides a 30MHz operating frequency for the DSP processor, and pins 1 and 4 of the DSP crystal oscillator circuit are connected to the X1 and X2 interfaces of the DSP processor, respectively. The JTAG circuit is used to test the electrical characteristics of the DSP processor and detect any problems. Pins 1, 2, 3, 7, 9, 11, 13, and 14 of the JTAG circuit are connected to pins 79, 78, 76, 77, 87, 87, 85, and 86 of the DSP processor, respectively. The reset circuit is used to restore the DSP processor's circuitry to its initial state; pin 1 of the DSP reset circuit is connected to pin 80 of the DSP processor.

3. A method using the apparatus for suppressing uncertainty disturbances and improving the conveying performance of an Antarctic krill conveying pump as described in claim 1 or 2, comprising the following steps: Step 1: Input the given rotation speed signal, and the permanent magnet synchronous motor in the Antarctic krill conveying pump servo system will receive the rotation speed signal and start moving; Step 2: Determine the actual rotational speed and current of the permanent magnet synchronous motor rotor; After the permanent magnet synchronous motor of the Antarctic krill conveying pump servo system starts moving, the detection circuit starts working. The incremental encoder outputs two-phase quadrature square wave pulse signals and a zero-position pulse signal through the position and speed detection circuit, for a total of three pulse signals. All three pulse signals are sent to the quadrature encoder pulse input unit EQEP built into the DSP processor. The resolution of the permanent magnet synchronous motor encoder is improved by quadruple frequency multiplication. At the same time, the general-purpose timer built into the DSP processor is set to directional increment / decrement counting mode. The position offset of the permanent magnet synchronous motor rotor is obtained from the number of pulses of the two-phase quadrature square wave pulse signals, and the direction of rotation of the permanent magnet synchronous motor rotor is obtained from the lead relationship of the two-phase quadrature square wave pulse signals, thus obtaining the position and speed of the permanent magnet synchronous motor rotor. The current of the permanent magnet synchronous motor rotor is collected by the Hall sensor. Step 3: Using the position and velocity information of the electronic rotor acquired in Step 2, the tracking error is first calculated in the DSP processor. The lumped disturbance of the novel sliding mode controller suppression system is estimated in real time using a disturbance observer. Then, the lumped disturbance of the novel sliding mode controller suppression system is applied to improve its robustness. The output signal of the novel sliding mode controller ensures the continuity and stability of the suppression system. Finally, the control signal of the permanent magnet synchronous motor, i.e., the control current of the permanent magnet synchronous motor, is calculated. The specific steps are as follows: Step 3.1: Establish the electromagnetic torque equation and mechanical motion equation of the permanent magnet synchronous motor; Establishing the dq axis model: For permanent magnet synchronous motors, field-oriented control is adopted. The axis of the permanent magnet pole is taken as the d axis, and the q axis is taken as 90° ahead of the d axis in the direction of rotor rotation of permanent magnet synchronous motor. In this way, a dq coordinate system that rotates synchronously with the rotor of permanent magnet synchronous motor is established. Let the d-axis current component of the inner current loop be i d If the ratio = 0, making the stator current vector and the permanent magnet magnetic field orthogonal in space, then the electromagnetic torque equation of the permanent magnet synchronous motor is: (1) ； In the formula, Electromagnetic torque; It is the extreme logarithm; The nominal flux linkage of a permanent magnet; i d i q L d L q These represent the current and inductance along the d-axis and q-axis, respectively; using i d =0 control, rotor current and stator current are spatially orthogonal, motor type is surface-mounted permanent magnet synchronous motor. , For the stator inductance, the electromagnetic torque equation simplifies to: (2) ； The mechanical motion equations of a permanent magnet synchronous motor are: (3) ； In the formula, ω m T is the mechanical angular velocity of the motor. L Where J0 is the load torque, J0 is the nominal moment of inertia of the rotor, and B0 is the nominal viscous friction coefficient of the motor. The mechanical motion equations of a permanent magnet synchronous motor considering variations in motor parameters and load torque are as follows: (4) ； In the formula, , , , For the actual rotor nominal moment of inertia, nominal viscous friction coefficient, and nominal flux linkage of the permanent magnet synchronous motor; Rearranging equation (4), we get: (5) ； In the formula, , , The lumped disturbance of the novel sliding mode controller suppression system is expressed as: (6) ； Step 3.2: Based on the actual position detected in Step 2, define the tracking error as: (7) ； In the formula, For speed tracking, This is the reference speed of the permanent magnet synchronous motor rotor. To determine the actual rotational speed of the permanent magnet synchronous motor rotor, the sliding surface is designed as follows: (8) ； In the formula, Here, is the gain parameter, satisfying the Hurwitz condition, and s is the sliding surface. To track the error derivative, a reaching law method is used to ensure that the system state reaches and remains on the sliding surface within a finite time. A novel sliding surface reaching law is designed as follows: (9) ； In the formula, Let be the coefficient of the reaching law. To switch the gain, , This is an estimate of the lumped disturbance in the novel sliding mode controller's suppression system; when the system state deviates far from the sliding surface, the value in the novel sliding mode reaching law... and Together, they exert an accelerating effect, with the approach rate exceeding the exponential approach law, thus accelerating the rate at which the system state reaches the sliding surface; as the system state approaches the sliding surface, Rapid decay, It plays a leading role in preventing the convergence rate from decreasing too early and causing convergence stagnation; The novel sliding mode reaching law changes with the system state and the distance between the sliding surfaces, enhancing the adaptability of the reaching rate; the novel sliding mode reaching law introduces... This can improve the robustness of the system; replacing the switching function with the sigmoid function, its flexible gain characteristics and gentle function gradient are both beneficial for reducing high-frequency chattering in sliding mode control, expressed as: (10) ； In the formula, Indicates the steepness of the function curve; Differentiating equation (8) and substituting it into equation (5), we get: (11) ； According to equations (11) and (9), we get: (12) ； The control law for the novel sliding mode control, derived from equation (12), is as follows: (13) ； Step 3.3: Design the disturbance observer; A novel perturbation observation method for perturbation feedforward compensation is designed as follows: (14) ； In the formula, , and For perturbation observer gain, This is the upper bound of the rate of change of the disturbance. For symbolic functions, and These are the estimated values ​​of the actual speed of the permanent magnet synchronous motor and the estimated values ​​of the lumped disturbance of the novel sliding mode controller suppression system, respectively. This disturbance observer can accurately estimate the lumped disturbance of the novel sliding mode controller suppression system, and through the second-order sliding mode characteristics, it hides the sign function that causes chattering in the integral action, thereby suppressing system chattering in essence and avoiding the introduction of additional noise by disturbance estimation. Step 4: The DSP processor generates six corresponding PWM pulse signals to drive the permanent magnet synchronous motors respectively; The PWM signal output by the DSP processor is converted into a drive signal by the IPM isolation protection drive circuit. The fixed 220V three-phase AC power is rectified into stable DC power and sent to the IPM inverter circuit. The IPM inverter circuit controls the conduction and cutoff of the six IGBTs in the IPM inverter circuit according to the six PWM pulse signals generated by the DSP processor, so as to obtain the required three-phase AC power to drive the permanent magnet synchronous motor and realize the high-precision control of the Antarctic krill conveying suction pump servo system.

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