47 results about "Finite control set" patented technology

The invention discloses a low-voltage ride-through control method of a flywheel energy storage system, which is based on a low-voltage ride-through control strategy of model predictive current control (MPCC) so as to improve the low-voltage ride-through capability of the flywheel energy storage system when a power grid fails. A future current value is predicted through system modeling and a prediction algorithm, so that effective control is realized. The MPCC-based machine side-power grid side coordination control strategy can quickly respond to the voltage sag of the power grid, provide reactive power support, stabilize the voltage of the direct current bus, and ensure the safe and reliable operation of the flywheel energy storage system during the voltage sag period of the power grid. A traditional pulse width modulation (PWM) technology is abandoned, the optimal switching state is directly selected through a limited control set, and hardware implementation of a power grid side converter is simplified. A differential control strategy aiming at a power grid symmetric fault (three-phase voltage sudden drop) and an asymmetric fault (single-phase grounding) is provided, the method is suitable for a complex power grid fault scene, and the system universality is improved.

The invention belongs to the technical field of electromechanical control, and particularly relates to a fault-tolerant control method for open-circuit faults of a symmetric six-phase permanent magnet motor. The method comprises the following steps: obtaining actual voltage vectors in alpha beta and xy subspaces under a normal condition; selecting six actual voltage vectors of which the xy subspace size is zero and the alpha beta subspace size is not zero as a finite control set; then dividing an alpha beta subspace into six sectors by using the six actual voltage vectors; then calculating a reference voltage vector by using a dead-beat control principle, and selecting two actual voltage vectors of a sector where the reference voltage vector is located as candidate voltage vectors; and selecting an optimal voltage vector through a cost function, and obtaining a corresponding power device driving signal. The problems that smooth transition from the healthy working condition to the fault working condition of the symmetric six-phase motor needs fault diagnosis and control reconstruction under the healthy working condition and the open-circuit fault working condition, the structure of a driving system is complex, and the transient switching process of the system is unstable are solved.

The invention discloses a finite set model prediction direct power control method for a single-phase three-level rectifier. The method comprises the following steps: carrying out SOGI conversion on alternating current side voltage and current of the single-phase three-level rectifier and output voltage of the rectifier to respectively obtain two-phase orthogonal rotating vectors; calculating to obtain active power and reactive power according to the rotation vector; performing finite control set model prediction control through the calculated active power and reactive power and the rotating vector output by the SOGI, circularly traversing the switching state vector, and predicting the active power and reactive power rate at the next moment and the voltage difference between the upper capacitor and the lower capacitor at the direct current side; and finding out an optimal switching state through cost function calculation to control the three-level rectifier. According to the invention, faster dynamic response can be realized, and the method is especially suitable for a system with transient load disturbance; the FCS-MPC is easy to add system constraints, so that the robustness to power grid fluctuation and load fluctuation is higher; and the influence caused by uncertain factors such as external interference and model errors is reduced.

The invention discloses a flux weakening method of a permanent magnet synchronous motor finite control set model prediction control system based on an expected fundamental wave voltage closed loop, and belongs to the technical field of permanent magnet synchronous motor speed regulation control. According to the method, the problems of voltage saturation and poor robustness of a finite control set model prediction control system in a weak magnetic region are solved. According to the method, one-step delay compensation is carried out on the stator current, the stator current predicted value predicted through delay compensation is substituted into the voltage vector model under current vector dead beat control, and the compensated voltage vector reference value can be calculated. And an expected fundamental wave voltage vector is calculated based on the compensated voltage vector reference value, and finally the expected fundamental wave voltage vector is used as feedback of closed-loop flux-weakening control, so that maximum voltage control can be realized, and voltage saturation of a flux-weakening area is avoided. The method provided by the invention has better current dynamic performance, faster acceleration time and better robustness. The method can be applied to field weakening control of the permanent magnet synchronous motor.

The present disclosure relates to a finite control set model predictive control method of an LLCL battery energy storage converter, wherein the method uses a finite control set model predictive control method to control an energy storage converter based on an LLCL filter, establishes and discretizes a state space mathematical model of the LLCL battery energy storage converter to obtain a discrete model, converts reference values of a current at a grid side into reference values of a current at a converter side and a capacitor voltage based on a phasor method at the same time, defines a cost function, compares an output result of a prediction model with the reference value, selects an optimal voltage vector and selects a most appropriate switching state to work.

The invention relates to the technology of power electronics and electric energy quality control, in particular to an energy storage type UPQC and switch state prediction control method based on improved model prediction control, which comprises a series active filter, a parallel active filter, a direct current bus, an energy storage system and a controller, according to the control method, an energy storage power and charge state dynamic equation is introduced into an MPC prediction model, and a multi-objective cost function is designed. And the controller predicts and evaluates the candidate switching vector in each sampling period based on a finite control set model predictive control strategy, and outputs an optimal switching state through value function optimization, thereby realizing collaborative optimization of electric energy quality management and energy storage energy management. According to the method, the dynamic response capability and compensation precision of the UPQC under the working conditions of voltage sag / sag, imbalance, harmonic waves and load fluctuation are remarkably improved, meanwhile, the energy storage utilization efficiency and the system stability are improved, and the method is suitable for a power distribution network with new energy high permeability and large load fluctuation.

The invention discloses a permanent magnet synchronous motor wide speed range model prediction control method and system based on a mean value reduction optimization algorithm, and belongs to the technical field of motor control. According to the method, a discrete mathematical model of the permanent magnet synchronous motor is established under a d-q rotating coordinate system, a q-axis current reference value is generated by an outer ring through a speed PI regulator, and a d-axis current reference value is calculated in combination with a maximum torque per ampere (MTPA) principle and a weak magnetic region voltage constraint; finite control set model prediction control is adopted in an inner ring, enumeration prediction is conducted on candidate voltage vectors of the three-phase voltage source type inverter, a cost function containing a d-axis current error, a q-axis current error and an electromagnetic torque error is constructed, an optimal voltage vector is selected, and a three-phase PWM signal is generated through space vector pulse width modulation to drive a motor. The system is provided with a mean value reduction optimization module, joint optimization is carried out on speed outer ring PI parameters and cost function weight coefficients in the off-line stage, the parameters are stored in a lookup table, and automatic setting of control parameters is achieved. The permanent magnet synchronous motor can improve the dynamic response performance of the rotating speed and the current in the base speed area and the weak magnetic area, reduce the total harmonic distortion of the stator current, improve the voltage utilization rate and the overall operation efficiency of the permanent magnet synchronous motor, and is suitable for occasions such as electric vehicle driving and high-performance servo systems.

The application provides a motor field weakening control method and system based on limited set model predictive control, can solve the problem that the output voltage of limited control set model predictive control cannot be directly used for closed-loop field weakening control, and comprises the following steps: obtaining operation parameters of a current sampling period of a motor, and predicting dq axis currents of a next sampling period; constructing a reference voltage of the next sampling period, the reference voltage is divided into a sampling voltage component and a transient voltage component, performing boundary judgment on a reference current vector corresponding to the transient voltage component, and determining whether to perform dynamic amplitude limiting processing on the transient voltage component according to a boundary judgment result; adding the sampling voltage component and the processed transient voltage component to obtain a corrected reference voltage, then obtaining a field weakening current component through comparison and closed-loop feedback, superimposing the field weakening current component to obtain a corrected d-axis reference current, and updating the reference current; and obtaining an optimal voltage vector through an evaluation function of limited set model predictive control to perform control.

The application discloses a kind of three-phase unbalanced power grid under pulse width modulation rectifier coordination control method and system, and it is related to power electronics and electric energy conversion control technical field.The method comprises: collecting three-phase voltage and current and DC bus voltage;By positive and negative sequence separation, construct unbalance degree index κ;With outer loop active power reference generated by active disturbance rejection controller, after amplitude limiting and slope limiting processing, it is sent into inner loop limited control set model predictive controller;Introduce κ-saturation flag joint gain scheduling mechanism on-line adjustment observer bandwidth and feedback gain, and set saturation fallback state machine to freeze integral channel;Inner ring uses two-step prediction, DC bus state perception, reactive power weight soft scheduling and reactive power average value offset removal.This application converts power grid unbalance degree into control parameter on-line setting basis, realizes outer ring safety constraint and inner ring prediction scheduling coordination, significantly suppresses DC bus voltage fluctuation and reactive power pulsation, improves system robustness and embedded realizability.

This invention provides a control method and apparatus for a 4L-NNPC inverter based on an improved finite control set model. The method includes: real-time acquisition of the current three-phase grid voltage, current flying capacitor voltage, and current output three-phase current; calculation of the static reference current and a preliminary evaluation function; determination of a candidate switch state set through an output level screening mechanism, combining the preliminary evaluation function and the static reference current; for each candidate switch state, prediction of the corresponding state flying capacitor voltage and state output three-phase current at the next moment based on the current output three-phase current; calculation of the current tracking cost function and the balancing flying capacitor voltage cost function using a multi-objective cost function based on sliding mode control theory, generating an overall cost function; and selection of the candidate switch state that minimizes the overall cost function as the optimal control output for the 4L-NNPC inverter control. This invention significantly reduces computational complexity while improving system dynamic performance and steady-state accuracy.

The present invention belongs to the field of control technology and metal forming technology, and specifically relates to a sensorless full-closed-loop control system and method for a press machine based on a finite control set. The present invention uses the difference between the forming process curve and the actual position of the slider as the control command position input of the whole machine control system, establishes a dynamic model, and calculates the torque as the input of the torque prediction control algorithm. The present invention sets a sensorless control algorithm module and a predicted torque algorithm module of a finite control set in the servo motor driver, calculates the rotational speed and electromagnetic torque prediction values, and finally obtains a value function. The slider position information can be added to the value function to control the slider position without overshooting, and the dynamic performance is significantly improved. The anti-interference performance of the motor servo driver is improved and the reliability is also significantly improved, and the cost of the servo motor is greatly reduced.

This invention discloses a neural network-based active disturbance rejection (ADRR) composite control method and system for permanent magnet synchronous motors (PMSMs). The method includes: constructing a second-order PMSM mathematical model; constructing a second-order nonlinear ADRR controller; generating a first control quantity based on the second-order nonlinear ADRR controller according to position commands and initial position feedback, and inputting the first control quantity into a current loop controller to control the PMSM; adjusting and optimizing the second-order nonlinear ADRR controller using a radial basis function neural network based on current position feedback and position commands; generating a second control quantity based on the adjusted and optimized second-order nonlinear ADRR controller according to position commands and current position feedback; predicting multiple sets of switching state combinations based on a dual-vector finite control set model using the second-order PMSM mathematical model and the second control quantity, and selecting the optimal switching state combination from the multiple sets of switching state combinations; and controlling the PMSM according to the optimal switching state combination. This significantly improves the real-time performance and robustness of the system.

The present invention belongs to the technical field of electromechanical control, and more specifically, relates to a symmetrical six-phase permanent magnet motor open-circuit fault-tolerant control method. The method comprises: obtaining the actual voltage vector in the αβ and xy subspaces under normal conditions; then selecting six actual voltage vectors whose size in the xy subspace is zero and whose size in the αβ subspace is not zero as a finite control set; then using these six actual voltage vectors to divide the αβ subspace into six sectors; then using the deadbeat control principle to calculate the reference voltage vector, and selecting two actual voltage vectors in the sector where the reference voltage vector is located as candidate voltage vectors; selecting the optimal voltage vector through a cost function, and obtaining the corresponding power device drive signal. The present invention solves the problem that the smooth transition from the healthy condition to the fault condition of the symmetrical six-phase motor under the healthy condition and the open-circuit fault condition requires fault diagnosis and control reconstruction, the drive system structure is complex, and the system transient switching process is unstable.

The application provides a motor control method and device, and the method comprises the following steps: obtaining motor parameters and identification parameters of a motor based on a prediction period, wherein at least part of the identification parameters can be updated based on real-time working conditions of the motor, and the update period is an integer multiple of the prediction period, the motor parameters comprise q-axis current, d-axis current and electric angular velocity, and the identification parameters comprise stator resistance, q-axis inductance, d-axis inductance and permanent magnet flux linkage; and control parameters of the motor are determined according to the motor parameters, the identification parameters and a limited control set model predictive control algorithm, so as to control the operation of the motor. Thus, by setting the identification parameters and updating the identification parameters based on the real-time working conditions, the model can be made to be close to the actual operation state of the motor in real time, so that the model mismatch problem caused by parameter drift can be effectively weakened, and the control precision of the limited control set model predictive control algorithm is improved.

The invention discloses a distributed finite control set model prediction control method and a controller, and the method comprises the steps: converting the voltage of a first bridge arm into a voltage series form for expression, and constructing a first bridge arm discrete mathematical model expressed by the voltage series; calculation is carried out based on a first bridge arm voltage discrete mathematical model expressed by voltage levels, selection of switching states is converted into selection of voltage levels, the number of switching states needing to be calculated is reduced, the calculation burden is reduced, and therefore rapid control over the modular multilevel matrix converter is achieved. Moreover, potential categories of false data injection attacks possibly occurring in the control structure are further analyzed, the defects of a conventional detector are explored, and a detector combining a fuzzy logic structure and a neural network is provided to achieve rapid detection of the false data injection attacks and ensure system safety.

The invention provides a 4L-NNPC inverter control method and device based on an improved finite control set model. The method comprises the steps of collecting a current three-phase voltage of a power grid, a current flying capacitor voltage and a current output three-phase current in real time; static reference current and a preliminary evaluation function are obtained through calculation; determining a candidate switch state set through an output level screening mechanism in combination with the preliminary evaluation function and the static reference current; for each candidate switch state, predicting a state flying capacitor voltage and a state output three-phase current corresponding to the current output three-phase current at the next moment according to the current output three-phase current; a multi-target cost function based on a sliding mode control theory is adopted to calculate a current tracking cost function and a balanced flying capacitor voltage cost function, and an overall cost function is generated; and selecting a candidate switch state which enables the total cost function to be minimum as the optimal control output of the 4L-NNPC inverter. According to the method, the dynamic performance and the steady-state precision of the system are improved while the calculation complexity is remarkably reduced.

The embodiment of the invention discloses a modular multilevel converter sub-module fault-tolerant operation method and a modular multilevel converter sub-module fault-tolerant operation system. The method comprises the following steps: identifying and processing a sub-module fault in an MMC system, and adjusting the capacitor voltage of the remaining sub-modules so as to ensure the stability of the direct current side voltage when the sub-module fault occurs; under the condition that the direct current side voltage is stable, alternating current tracking is set to be the highest priority, and an optimal switching sequence is searched in a limited control set by establishing a mathematical model and a design value function; after current tracking is completed, interphase circulating current suppression is selected as a secondary target, and the circulating current influence is minimized by using discretization processing and a voltage compensation technology; and after the secondary target is optimized, a sorting voltage-sharing algorithm is implemented, and the input or bypass state of each sub-module is monitored and dynamically adjusted in real time. By implementing the method provided by the embodiment of the invention, not only can the operation speed be improved, but also an efficient fault-tolerant operation scheme is provided for MMC sub-module faults, and the reliability and the performance of the system are remarkably improved.

The invention relates to the technical field of power system frequency control, in particular to a power system frequency control method and system based on a weight factor-free model, and solves the problems of rapid development of a renewable energy system and reduction of inertia and damping of the power system by adopting an inverter and a voltage source converter on a large scale. A target function is converted into a linear quadratic cost function by adopting weight factor-free model predictive control, so that the calculation amount is reduced; an inner ring of finite control set model predictive control uses an SW factor to control a voltage source inverter without a weight factor; optimal control is realized through optimal switching control of power grid current, balance of voltage of a neutral point clamping capacitor and geometric fast frequency control; by managing the power injection of the inverter, the operation within the frequency limit is ensured, the optimal power flow is realized during the disturbance period, the frequency control of the power system of the voltage source inverter in the low-inertia environment is realized, and the calculation time and the calculation amount are reduced.

The invention discloses a grid-connected inverter fault ride-through method and system considering symmetric and asymmetric faults, and relates to the technical field of electric power, and the method comprises the steps: obtaining power grid voltage measurement data and power grid current measurement data, and carrying out the fault ride-through of a grid-connected inverter based on the power grid voltage measurement data and the power grid current measurement data; generating reference voltage data and reference phase data through droop control; based on the power grid voltage measurement data and the reference voltage data, outputting through a finite control set model prediction control strategy to obtain a switching signal for driving an inverter switch; when the power grid current measurement data exceed a preset current rated value, judging that the current is in a fault state, calculating to obtain a virtual impedance value based on the fault state, and generating a voltage correction value based on the virtual impedance value and the power grid current measurement data to adjust the reference voltage data; and according to the adjusted reference voltage data, a switching signal for driving an inverter switch is updated, and accurate current constraint under symmetric and asymmetric faults is realized.

The embodiment of the application discloses a modular multilevel converter submodule fault tolerance operation method and system. The method comprises the following steps: identifying and processing the submodule fault in the MMC system, adjusting the capacitor voltage of the remaining submodules to ensure the stability of the DC side voltage when the submodule fault occurs; under the condition that the DC side voltage is stable, the AC current tracking is set as the highest priority, the optimal switching sequence is found in the limited control set by establishing a mathematical model and designing a value function; after the current tracking is completed, the interphase circulating current suppression is selected as the secondary target, and the discrete processing and voltage compensation technology are used to minimize the circulating current influence; after the secondary target optimization, the sorting voltage sharing algorithm is implemented, and the input or bypass state of each submodule is monitored and dynamically adjusted in real time. Through the implementation of the method of the embodiment of the application, not only the operation speed is improved, but also an efficient fault tolerance operation scheme is provided for the MMC submodule fault, and the reliability and performance of the system are significantly improved.

The invention belongs to the technical field of renewable energy source grid connection, and provides a grid-connected converter cluster model prediction dual-mode control method and a grid-connected converter cluster model prediction dual-mode control system, which overcome the influence of line impedance difference by introducing a distributed compensation mechanism into a traditional control architecture, realize accurate reactive power equalization among converters in a network construction mode, and improve the reliability of the system. The hidden danger of power oscillation is eliminated; limited control set model prediction control is adopted to replace a traditional PI controller to serve as a unified inner ring, the smoothness and safety of the mode switching process are effectively improved, a complete cluster control framework is constructed by integrating collaborative switching, power coordination and rapid inner ring control, and the operation stability of the system under wide-range power grid impedance changes is comprehensively improved.

The invention belongs to the technical field of bid invitation management, and discloses a swimming pool heat pump SCOP working condition optimal energy efficiency debugging control method based on multi-parameter dynamic optimization, and the method comprises the steps: S1, obtaining state data, and obtaining an adjustment boundary of a control quantity based on the state data; s2, constructing an initial candidate set based on the adjustment boundary, and obtaining a limited control action set based on the initial candidate set; s3, respectively acquiring an input vector corresponding to each group of control combinations in the limited control set, acquiring a predicted COP value based on the input vector, and acquiring an index sequence based on the predicted COP value; and S4, obtaining an alternative set based on the index sequence, respectively calculating a comprehensive score of each group of control combinations in the alternative set, obtaining an optimal control combination based on the comprehensive scores, and updating the control instruction based on the optimal control combination. According to the method, the instantaneous energy efficiency and the final SCOP of the swimming pool heat pump under multiple working conditions are remarkably improved, and the industrial pain points that the energy efficiency is low and the system is prone to oscillation due to traditional unified control logic are solved.

The invention discloses a finite control set model prediction control method and device with high control precision. The method comprises the following steps: obtaining a state-space equation of a control object according to a system optimization target, and obtaining an increment of the optimization target from k to k + 1; according to the xj peak value of the optimization target at the moment k to the moment k + 1 and the error of the optimization target at the moment k + 1, constructing a value function of multi-target optimization of the system at the moment k; the optimal switch action position and the optimal switch state at the current k moment are solved by minimizing the constructed multi-objective optimized value function; and compensating the delay time to construct a compensation-considered value function, and obtaining an optimal switch action position and an optimal switch state at the k + 1 moment by minimizing the compensation-considered value function. According to the invention, the switching position of the switching state can be flexibly changed, the switching time is flexible, variable and online adjustable, the switching precision of the inverter is improved, and the characteristic that switching does not exceed one time in each control period is kept.

The invention relates to the technical field of converter control, and discloses a finite control set model prediction control method, device and equipment for a machine side converter, and the method comprises the steps: inputting the port voltage of the machine side converter at the current moment under a target coordinate and the stator current of a fan at the current moment under the target coordinate into a prediction model, the stator current of at least one future moment under the target coordinate is predicted through the prediction model; on the basis of the stator current of at least one future moment under the target coordinate and the machine side current reference value under the target coordinate, performing traversal calculation to obtain the optimal switching state of each bridge arm of the converter, which minimizes the value of the cost function; and controlling each bridge arm of the converter according to the optimal switching state. According to the method, the on-off state of each bridge arm of the machine side converter can be adaptively changed on line, tedious PI setting is reduced, decoupling is not needed, multiple times of conversion is not needed, and the operand is small.

The invention relates to the technical field of motor driving control, and discloses a three-phase permanent magnet synchronous motor driving system and a control method thereof. Aiming at the problems of output current quality reduction and calculation burden increase when the existing limited control set model prediction control is combined with the switching state PWM to control the inverter, the method comprises the following steps: establishing a leakage current mathematical model, adopting limited switching state dead-beat prediction leakage current control, and combining switching state prediction and a virtual voltage vector. Common-mode voltage and leakage current are reduced, current THD is reduced, calculation amount is reduced, virtual voltage vectors are generated through software, cost is reduced, and an economical and efficient control scheme is provided.

The present invention discloses a brushless DC motor position sensorless control method based on model predictive control. Firstly, the rotor position angle and speed information of the motor are obtained by constructing a brushless DC motor model reference adaptive system, and then the q-axis current reference value i is obtained by using the speed outer loop PI regulator. q ref ; Then, the d-q axis component i of the stator current at time (k+1) is predicted online according to the prediction model d (k+1), i q (k+1); further, a value function is constructed using the reference value and predicted value of the stator current d‑q axis component at time (k+1), and the optimal voltage vector is selected by minimizing the value function, thereby obtaining the optimal switching state of the inverter; the brushless DC motor control method provided by the present invention adopts a finite control set model predictive control strategy, does not need to adjust the current inner loop parameters, can obtain better dynamic and steady-state performance, and realizes position sensorless operation, thereby improving system reliability and reducing hardware costs.

The invention discloses a fractional order finite control set model control method based on a single-phase quasi-Z-source rectifier, and belongs to the field of power electronics. Compared with traditional integer order finite control set model prediction control and fractional order finite set model prediction control without delay compensation, the method has the advantages that the input side alternating current distortion rate is reduced, the fluctuation of the output side direct current voltage is reduced, the dynamic response speed of the output side direct current voltage is increased, and higher control precision is achieved.

The present application discloses a distributed finite control set model predictive control method and a controller. The method expresses the voltage of the first arm in the form of voltage levels, constructs a discrete mathematical model of the first arm expressed in voltage levels, performs calculations based on the discrete mathematical model of the first arm voltage expressed in voltage levels, reduces the number of switching states to be calculated by converting the selection of switching states into the selection of voltage levels, reduces the computational burden, and thus realizes the fast control of the modular multilevel matrix converter. Moreover, the present application further analyzes the potential categories of false data injection attacks that may occur in this control structure, explores the deficiencies of conventional detectors, and proposes a detector combining a fuzzy logic structure and a neural network to achieve the fast detection of false data injection attacks and ensure system security.

The invention provides a network construction type inverter power synchronization control method and system based on model prediction control, and the method comprises the steps: 1, building a power-phase dynamic coupling model, and carrying out the mathematical modeling of a dynamic relation between the output active power of an inverter and the phase difference of power grid voltage; step 2, designing a cost function taking active power synchronization error minimization as a target, and predicting a future phase evolution trajectory in combination with real-time state feedback of a power grid; 3, in each control period, on the basis of a current power grid state measurement value, enumerating all feasible phase adjustment amounts in a limited control set, and solving an optimal phase increment enabling the cost function to be minimum through a rolling optimization mechanism; and 4, superposing the optimal phase increment to the current phase angle, generating a phase instruction of the next control period, and compensating the prediction deviation in real time through a feedback correction mechanism to realize dynamic tracking and synchronous control of the active power.

The present invention discloses a switchable predictive control method for active power filters. This method is applicable to APF control strategies that are difficult to balance dynamic and steady-state performance, and facilitates switchable predictive control of APFs. The method designs a Model Predictive Control + Repetitive Control (MPC+RC) module with an additional predictive function. This module is combined with a Finite Control Set Model Predictive Control (FCS-MPC) module to achieve time-sharing output and real-time switching between two different predictive control strategies, thereby achieving the "fast response - precise control" optimization effect of the APF.