10results about How to "Solve Oscillation Problems" patented technology

The application discloses a data-driven optimal control method for a grid-connected inverter. The method comprises the following steps: constructing a DeePC optimization controller of the grid-connected inverter on the grid side; acquiring a data matrix of the grid-connected inverter in a preset historical period and an initial trajectory after a preset adjacent period, inputting the controller, setting parameters for different control targets and types of the grid-connected inverter, outputting an optimal input data sequence after processing, generating a sinusoidal pulse width modulation wave signal and acting on the grid-connected inverter, and realizing data-driven optimal control. The method can automatically perceive and adapt to the dynamic characteristics of the actual power grid through real-time data-driven predictive control, can present or enhance the control behavior of the grid-constructing or grid-following inverter by modifying the cost parameters, can realize multi-mode flexible, optimal and coordinated control, has excellent dynamic response and steady-state performance, is beneficial to safe and stable operation, and improves the ability to adapt to complex and variable operating conditions and power grid strength.

The invention relates to a distributed intelligent rice transplanter cluster navigation method based on deep reinforcement learning and speed obstacles, which comprises the following steps: acquiring a reciprocal speed obstacle and a speed obstacle vector, inputting the reciprocal speed obstacle and the speed obstacle vector into a BiLTSM network model, and acquiring an environment perception vector; the BiLTSM network model is obtained through training of a training set; and combining the environment perception vector with an ontology perception measurement value to generate an observation space, and setting a reward function for iteratively updating a multi-intelligent-vehicle obstacle avoidance strategy so as to optimize driving control of an individual level in an intelligent vehicle cluster and generate an optimal navigation scheme. The method still faces many challenges in application in the agricultural environment, the defects in the aspects of environment state representation, action mapping and reward design are overcome, and the problem of multi-machine collision avoidance in the complex dynamic environment is effectively solved.

This invention provides a grid-actively supported doubly-fed induction generator (DFIG) wind turbine control system, comprising: a DFIG converter power generation system, a wind turbine primary frequency regulation control module, a wind turbine autonomous inertia response control module, a wind turbine autonomous voltage control module, a rotor-side converter current command generation module, a rotor-side converter current control module, a rotor-side converter signal processing module, a grid-side converter synchronization angle control module, a grid-side converter AC voltage amplitude control module, a grid-side converter current command generation module, a grid-side converter current control module, and a grid-side converter signal processing module. Based on the principle that both the turbine-side and grid-side converters of the DFIG wind turbine employ amplitude and phase control, this invention achieves active support control of the grid frequency and voltage by the DFIG wind turbine unit through active primary frequency regulation, inertia response, and autonomous voltage regulation control strategies, without relying on communication with the power station controller.

The invention discloses a photovoltaic MPPT (Maximum Power Point Tracking) control algorithm, which relates to the technical field of photovoltaic control algorithms, utilizes the characteristics of simple structure, high convergence speed, high global optimization capability, wide applicability and the like of a gradient optimization algorithm, and improves the defects of premature convergence and sensitivity to control parameters of the gradient optimization algorithm. Meanwhile, the photovoltaic output energy efficiency and the stability of the photovoltaic output energy efficiency serve as the evaluation basis, an MPPT algorithm performance evaluation model is constructed through an analytic hierarchy process, photovoltaic MPPT performance is evaluated, and GTO performance is verified and improved.

The invention relates to a data-driven load frequency control method for a power system containing a network-forming converter. The method comprises the following steps: firstly, according to a power system topology, constructing a time-delay nonlinear load frequency control model containing a network construction type converter; taking the model as an environment, simulating operation acquisition data by using a PID controller, and constructing a pre-training data set; then, an agent of an actor-commentator framework is constructed, and offline pre-training is completed through a data set; and finally, accessing the intelligent agent into a system for online interaction, outputting a frequency modulation instruction by an action network, and iteratively updating parameters by combining an award and a loss function to realize self-adaptive control. Compared with the prior art, the method has the advantages of being adaptive to the dynamic characteristics of the GFM, efficient, high in robustness and the like.

The application discloses a method for suppressing speed fluctuation of a direct-current brushless motor, and relates to the technical field of motor control. The method collects three-phase current, bus voltage, rotor position signal and actual speed signal during operation of the direct-current brushless motor, and performs synchronous separation on a speed error signal. A speed fluctuation mapping model is established according to a preset electric angle interval, and corresponding compensation coefficients are configured for different electric angle intervals. A disturbance feedforward compensation amount is generated based on a disturbance component, and a commutation suppression amount is generated based on a periodic fluctuation component. The speed loop control parameters and the current loop control parameters are adjusted according to the current speed fluctuation amplitude and the current ripple level. The disturbance feedforward compensation amount, the commutation suppression amount and the adjusted speed loop control parameters and current loop control parameters are combined into a final control amount, which is output to an inverter driver. The method can take into account load disturbance suppression and commutation ripple suppression, and improve the speed stability and long-term operation disturbance resistance under low-speed heavy-load working conditions.

This invention belongs to the field of high-precision positioning technology. It discloses an inertial navigation positioning calibration method and system based on multi-source error compensation. The method includes acquiring acceleration and angular velocity data output by an inertial measurement unit (IMU), obtaining position, velocity, and attitude information through integration, and constructing navigation state variables under a unified time series. Errors in the navigation state variables are characterized and decomposed into zero-bias error, scaling factor error, dynamic coupling error, and environmental disturbance error, forming a multi-source error superposition relationship and generating an error sequence that evolves over time. Error evolution prediction modeling is performed based on the error sequence, dividing the error sequence into steady-state intervals and transition intervals. An evolution prediction function constrained by motion is constructed within the steady-state interval, and an error-driven enhancement prediction function is constructed within the transition interval. Continuity constraints are applied to adjacent intervals to obtain continuous error prediction results, thereby improving the accuracy and stability of inertial navigation positioning.

This invention discloses a control method for switching a dual-wire energy storage inverter from grid-connected to off-grid operation, comprising the following steps: S1: Detecting abnormal grid conditions and disconnecting the grid-connected relay when an abnormality occurs; S2: Determining whether the absolute value of the filter capacitor voltage exceeds a predetermined threshold and whether the discharge time is less than a predetermined time limit; S3: Selecting a corresponding combination of switching transistors for high-frequency drive based on the polarity of the capacitor voltage to reconstruct the full-bridge circuit into a boost circuit; S4: Calculating the duty cycle of the switching transistors based on the dynamic relationship between the capacitor voltage and the bus voltage, and discharging the capacitor energy to the DC bus through the boost circuit; S5: Resetting the output phase angle of the energy storage inverter to zero and starting off-grid operation. This invention effectively solves the problem of voltage oscillation during off-grid startup of residential dual-wire energy storage inverters under various grid-connected to off-grid operating conditions.

The invention relates to the field of servo control, and provides a method and a device for determining a dead time compensation value of an inverter. The method comprises the following steps: determining a three-phase current instruction in a current control loop of the servo system and an actually measured dead zone characteristic curve corresponding to an inverter in the servo system; determining a dead-zone time compensation value of the inverter based on the three-phase current instruction and the actually measured dead-zone characteristic curve; and determining a dead-zone compensation coefficient, and determining a final dead-zone time compensation value based on the dead-zone compensation coefficient and the dead-zone time compensation value. According to the method and the device, the error compensation phenomenon can be avoided to the greatest extent, and the accuracy of dead time compensation is effectively improved.

The application discloses a space computing cabin active heat management system and method. The system comprises a micro-channel cold plate, a chip, an active pump-driven circulation loop, a heat pump temperature increasing subsystem, a radiation heat dissipation terminal and a pressure cooperative control module. The chip surface is close to the micro-channel cold plate. The micro-channel cold plate is connected with the active pump-driven circulation loop through the pressure cooperative control module. The active pump-driven circulation loop is connected with the heat pump temperature increasing subsystem. The heat pump temperature increasing subsystem is connected with the pressure cooperative control module and the radiation heat dissipation terminal respectively. The application has the advantages of high heat transfer efficiency, small radiation area, high heat flow impact resistance and stable operation, significantly reduces the weight and volume of the radiator, breaks through the high heat flow density dissipation bottleneck of the space computing cabin, and is especially suitable for the heat management of the high power density space data center.