1005 results about "Negative feedback" patented technology

The invention relates to the technical field of temperature control, and discloses a temperature error compensation method and system for a multi-heating-section coffee maker, and the method comprises the steps: synchronously collecting the real-time temperature value of each heating section, and calculating a temperature error index; constructing a thermal coupling interference model based on the physical distance between adjacent sections and the heat conduction characteristic of the medium; generating a dynamic decoupling compensation parameter according to the model and the error index (including constructing a symmetric interference matrix, calculating a coupling interference component, applying negative feedback and identifying a main interference component); a decoupling parameter is converted into a power adjustment instruction through a multivariable control algorithm (superposition of basic compensation and decoupling compensation, amplitude limiting and phase compensation); and heating output is updated according to the power instruction, and iterative execution is performed based on the error index change trend until the temperatures of all sections reach steady-state balance. The method can effectively model and compensate thermal coupling interference between sections, improves the efficiency of temperature error compensation, and achieves the quick and stable cooperative temperature control of multiple sections.

The invention discloses a fault ride-through hierarchical control method for a network-constructed converter, and the method comprises the steps: introducing a virtual resistor formed by fault current negative feedback into the voltage and current inner loop control of the network-constructed converter based on VSG control through a current inner loop dynamic amplitude limiting control layer after the converter enters a fault ride-through state, the size of the virtual resistor is adjusted in real time along with the amplitude of the fault current so as to carry out dynamic current limiting control on the virtual resistor; and the power outer loop dynamic compensation control layer dynamically adjusts an active power instruction value and a reactive power instruction value of the network construction type converter based on VSG control during the fault ride-through period according to the voltage drop degree of the power grid after the converter enters the fault ride-through state. And respectively performing active-frequency control and reactive-voltage control based on the active power instruction value and the reactive power instruction value. In addition, the method also comprises a state coupling and parameter self-adaption module. According to the method, the GFM converter can have better dynamic performance in the fault recovery stage.

The invention relates to the technical field of robot control, and discloses a mechanical arm trajectory planning control method and system based on a BAFARNN model. The method comprises the steps that a mechanical arm kinematics model is established, and a trajectory tracking problem is converted into a time-varying equation; designing a bounded adaptive function to activate a recurrent neural network model, defining an error function and constructing a dynamic equation; designing a piecewise adaptive coefficient function, and dynamically adjusting the gain according to an error norm and time; setting a Lissajous curve as an expected trajectory, and initializing a simulation environment; the joint speed is solved in real time through an ODE numerical method, and the mechanical arm is driven to move; actual motion data is collected and compared with an instruction, and closed-loop feedback control is triggered when the actual motion data exceed a threshold value. According to the method, rapid convergence is achieved through the piecewise adaptive coefficient function, the bounded activation function and the negative feedback mechanism are adopted to suppress noise, and high-precision and real-time trajectory tracking of the mechanical arm in the dynamic environment is achieved.

The invention provides an outbound routing method and system based on multi-dimensional index coupling and large model decision, and the method comprises the steps: carrying out the preprocessing of the historical data of each line provider, predicting the future performance index through an LSTM neural network, and optimizing the prediction result through a Kalman filter, and eliminating the noise. In the route decision-making link, the system calculates the Q value of each line provider based on the deep Q learning network, comprehensively considers the call completing rate, average cost, negative feedback rate and other factors of each line provider, and intelligently selects the optimal line provider in combination with the user portrait, scene recognition and real-time load state. The system also constructs a complete feedback closed loop, continuously optimizes the model by collecting call result data, and automatically adjusts decision parameters. The call completing rate and the service quality of the outbound service are improved, and the communication cost is reduced.

The invention discloses a fast transient response Buck converter based on AOT control, which is compatible with the advantages of current mode control and AOT control, and is characterized in that an error amplifier is added in a negative feedback control loop, so that the precision of output voltage is improved, a current loop is stable, and the series resistance value of an output capacitor is not specifically limited; the change rate of the switching frequency in heavy load is reduced by using the improved self-adaptive turn-on time module, and the change of the switching frequency under different load current conditions is ensured to be small. The transient enhancement module is used for judging the output voltage, it is ensured that when the load current suddenly changes, the output voltage is fast and stable, overshoot and undershoot are reduced, and therefore the overall stability and reliability are improved. The sleep detection module Sleep is used for detecting a switching tube driving signal VCOMP so as to control the Buck converter to enter a dormant state, and therefore the purposes of reducing power consumption and improving efficiency are achieved.

The invention relates to a product recommendation optimization method based on user portrait dynamic updating, which comprises the following steps: acquiring user behavior sequence data, and analyzing based on behavior consistency indexes including time interval, intention change rate and interest inversion degree; when it is detected that the behavior path has a fault, frequent switching or reverse direction, revoking the update of the path to the user portrait and marking the path as a low credible behavior segment; before user portrait updating is triggered, the portrait mutation risk is judged according to the feature distribution difference between the current behavior and the historical portrait, the behavior uniqueness and the conversion closed loop condition, and when mutation is found, portrait updating is frozen and recorded to a to-be-verified sequence; based on self-consistent state recognition of a historical behavior track, local increment updating is carried out on a staged portrait dimension consistent with a current behavior; and before the recommendation result is generated, performing consistency evaluation on the recommendation target and the user portrait intention, if the alignment degree is lower than a preset threshold value, adjusting or reconstructing the recommendation content, and correcting the deviation label according to continuous negative feedback.

The invention relates to the technical field of industrial valve control, in particular to a floater control-based remote control and monitoring system for a quick-switching blind plate valve, which comprises a data acquisition unit, a cross-dimension data analysis unit and an instruction generation and feedback unit, and is characterized in that the data acquisition unit constructs a three-dimensional motion matrix through a floater trajectory tracking algorithm; an effective pressure fluctuation period is extracted in combination with a pressure-temperature coupling denoising algorithm, a cross-dimension data analysis unit extracts time-frequency fusion features by using a residual convolutional neural network, and dual verification of a fluid phase state is realized through a support vector machine and a dynamic time warping algorithm; and the instruction generation and feedback unit triggers a standard control strategy or a self-learning compensation mechanism according to the confidence coefficient, and corrects control deviation through a negative feedback optimization coefficient matrix, so that the problems of insufficient multi-source data fusion and poor complex working condition adaptability in the traditional technology are solved, accurate remote control and intelligent monitoring of the quick-switching blind plate valve are realized, and the working efficiency of the quick-switching blind plate valve is improved. And the leakage early warning success rate and the valve action reliability are improved.

The invention relates to the field of curriculum personalized adjustment, in particular to a curriculum learning personalized adjustment method and system of an enabling system, and the method comprises the steps: obtaining user information and historical learning data of a user when a learning instruction of the user is received, and recognizing target curriculum data of the user according to the user information and the historical learning data; acquiring historical behavior data of the user, identifying a concentration attenuation trend of the user according to the historical behavior data, and segmenting the target course data into a plurality of course segments according to the concentration attenuation trend; when the user learns the curriculum segment, behavior data of the user is acquired in real time; judging the concentration feedback state of the user according to the behavior data; when the concentration feedback state of the user is positive feedback, generating a learning efficiency enhancement strategy and a composite excitation strategy; and when the concentration feedback state of the user is negative feedback, generating a cognitive load regulation strategy and a pressure balance strategy. The learning state of the user is judged according to the behavior data, and the system can flexibly adjust the learning strategy.

The invention provides spiral feeder and metering scale integrated equipment for improving feeding precision, and relates to the technical field of metering and feeding of powdery and granular materials. According to the integrated equipment, a frequency converter is additionally arranged on a spiral scale, so that a constant-speed spiral metering scale is changed into a speed-regulating spiral metering scale, a signal separator is introduced to divide a PID negative feedback signal output by an instrument into two paths, the two paths respectively control a frequency converter of a steady-flow spiral feeder and a frequency converter of a metering screw, and meanwhile, a speed measuring sensor is additionally arranged on the spiral scale; and synchronous double-closed-loop control is realized. The spiral scale solves the problems that when an existing spiral scale is used for metering powder, flow is unstable, and arching, jet flow, blocking and the like are prone to occurring, the dynamic deviation can be controlled within 0.5%, the feeding precision and stability are remarkably improved, and the spiral scale is suitable for metering and feeding of powdery and granular materials in the industries of cement, chemical engineering, metallurgy, ceramics, grain, transportation and the like.

The invention discloses a microwave cold noise source fusing TEC temperature control and noise temperature compensation technologies, and belongs to the technical field of microwave radiometer calibration. The device comprises a cold source module, a noise compensation module and a constant-temperature control module, wherein the cold source module generates a low-temperature noise signal through a field-effect tube and a terminal resistor; the noise compensation module detects environment temperature change in real time based on a thermistor and a Wheatstone bridge, drives a noise diode to generate a compensation signal, couples the compensation signal with a cold source noise signal after attenuation, and counteracts noise temperature deviation caused by the environment temperature. The constant temperature control module adopts a platinum resistance sensor and a PID algorithm to control a Peltier element in a closed-loop mode, and accurate adjustment (+ / -0.1 DEG C) is achieved. According to the invention, noise compensation and TEC negative feedback temperature control technologies are combined, so that the noise temperature of the system is stabilized in a range of + / -0.1 K for a long time, the measurement precision and reliability of the microwave radiometer in an outdoor complex environment are remarkably improved, and the method is suitable for scenes of remote sensing detection, unmanned aerial vehicle monitoring and the like.

The invention discloses an ultrahigh-precision low-noise band-gap reference circuit, and relates to the technical field of integrated circuit design, the ultrahigh-precision low-noise band-gap reference circuit comprises a starting turn-off circuit, a reference core circuit, a high-order temperature compensation circuit and a digital trimming circuit, the starting turn-off circuit is connected with the reference core circuit, and the high-order temperature compensation circuit is connected with the digital trimming circuit through a Brokaw type band-gap reference topological structure. Accurate compensation of the voltage is achieved through deep negative feedback of the operational amplifier and a high-order temperature compensation circuit, and the temperature drift of the reference voltage is as low as 0.5-2 ppm / DEG C (-40 DEG C to 130 DEG C) and is increased by 5-10 times compared with a traditional band-gap reference (5-10 ppm / DEG C). The power consumption of the system can be saved by turning off the circuit when the circuit is not used, meanwhile, the digital trimming module is added to replace laser trimming in traditional engineering, the upper limit of the trimming range is improved, high-order temperature compensation and the digital trimming circuit are introduced, the precision of output voltage is improved, different devices are replaced, and the noise of the circuit is reduced. The problems that a traditional high-voltage band-gap reference temperature coefficient is high and noise is large are solved.

The invention relates to the technical field of pulse electric field measurement, and discloses a time drift compensation method of a pulse electric field measurement system based on model parameterization. According to the method, a parameterized model is constructed in simulation software, and the parameterized model is additionally provided with two servo zeroing compensation circuits on the basis of an original measurement system, and the two servo zeroing compensation circuits are connected to the output ends of two in-phase operational amplification circuits respectively to form a negative feedback loop used for dynamically suppressing low-frequency baseline drift; acquiring electric field time domain waveform data of the output end of the third in-phase operational amplifier circuit; calculating a transfer function of a pulsed electric field measurement system in the parameterized model, converting the transfer function from a frequency domain state to a time domain state through inverse Fourier transform, and then performing deconvolution on the transfer function of the time domain state and electric field time domain waveform data to obtain real electric field intensity; according to the invention, time drift caused by operational amplifier input imbalance, power supply fluctuation and temperature change is automatically compensated in real time, and the stability and precision of system measurement are improved.

The invention discloses an industrial printer ink-jet control system based on negative feedback control, and relates to the technical field of industrial printers. The ink-jet control system for the industrial printer based on negative feedback control comprises a data input processing module which is responsible for receiving printing data input by a user, converting the printing data into a format which can be identified by the printer, and carrying out preliminary optimization and arrangement on the data at the same time; the data input processing module is connected with a high-speed data transmission module, and the high-speed data transmission module is connected with a sensor monitoring module, a feedback signal processing module, an optimization algorithm control module and a distributed local control module. The calculated amount can be reduced and the time required by deviation calculation can be shortened by simplifying the deviation calculation algorithm, and the deviation can be predicted and adjusted in advance by the predictive control algorithm, so that the system can quickly cope with the change of the ink jet state, and the printing efficiency and quality are improved.

The present invention discloses a Hadoop cluster task scheduling method based on a positive and negative feedback load scheduling algorithm, which is applied to a Hadoop resource allocation center. The cluster task scheduling method comprises: an idle computing node applies to a management node for a task execution request; the management node receives the task request and queries whether there is a historical record of running the task request; the historical records are compared and analyzed, and if the task configuration meets the resource requirements, the task is calculated in this computing node; otherwise, the computing node is re-matched with a new task request; and computing tasks can be dynamically allocated in cluster task scheduling according to the resource usage of different servers and the differences in server performance, thereby achieving efficient completion of computing tasks and improving CPU and resource utilization efficiency.

Front end systems and related devices, integrated circuits, modules, and methods are disclosed. One such front end system includes a low noise amplifier in a receive path and a multi-mode power amplifier circuit in a transmit path. The low noise amplifier includes a first inductor, an amplification circuit, and a second inductor magnetically coupled to the first inductor to provide negative feedback to linearize the low noise amplifier. The multi-mode power amplifier circuit includes a stacked output stage including a transistor stack of two or more transistors. The multi-mode power amplifier circuit also includes a bias circuit configured to control a bias of at least one transistor of the transistor stack based on a mode of the multi-mode power amplifier circuit. Other embodiments of front end systems are disclosed, along with related devices, integrated circuits, modules, methods, and components thereof.

The invention discloses a multi-modal data dynamic reasoning system and method based on a cognitive map, and relates to the technical field of map data management.The method comprises the steps that text, voice and image data input by a user are extracted, user data are analyzed, and a structured interaction record is generated in combination with a user identifier and a timestamp; analyzing historical interaction records, detecting continuous query events of the same user for similar questions, gathering negative feedback signals, analyzing repetition frequencies of repeated events in the used user, and analyzing feedback intensity coefficients of output repeated behaviors; positioning corresponding nodes in the cognitive map according to the repeated behavior characteristics, analyzing attenuation coefficients, activating associated alternative reasoning paths, and outputting a to-be-updated node set and candidate paths; and adjusting the node weight based on the attenuation coefficient, updating the weight according to the semantic relevancy of the candidate path, updating the atlas connection relationship, and outputting the optimized cognitive atlas. Abnormal conditions are identified, the knowledge graph node weight is adjusted, and the analysis accuracy is improved.

The invention belongs to the technical field of fluid machinery, and particularly relates to a novel tank type molten salt reactor main pump structure. Comprising a driving device, a sealing section, an air cavity section and a working section which are sequentially connected from top to bottom. The driving device is connected with the working section through a rotating rod; the rotating rod is rotatably connected with the sealing section and the air cavity section; the air cavity section comprises a third outer shell, an air outlet pipe and an air inlet pipe penetrate through the side wall of the third outer shell, an air outlet control unit is arranged at the end, close to the third outer shell, of the air outlet pipe, an air inlet control unit is arranged at the end, close to the third outer shell, of the air inlet pipe, and the air outlet control unit and the air inlet control unit are connected with the working section. The gas outlet control unit and the gas inlet control unit perform negative feedback regulation on the molten salt liquid level of the third outer shell, so that the molten salt liquid level is prevented from being in direct contact with the sealing section; the working section comprises an impeller, a guide vane, a fused salt inlet and a fused salt outlet, fused salt enters the third outer shell from the fused salt inlet, then flows into the impeller and the guide vane section through the pump inlet to be pressurized and stabilized, and finally flows out through the fused salt outlet.

The invention relates to the field of shared control, and discloses an intelligent shared control method and system of a plasma waterless washing machine, which are used for solving the core pain points of the traditional shared washing machine in the dimensions of prediction, energy consumption, maintenance and control. According to the method, through fusion of multi-model cooperative calculation and interdisciplinary theory, full-link optimization control is combined with an evolutionary game theory incentive mechanism and a Lyapunov energy function optimization algorithm, an equipment start-stop strategy and a user integral rule are dynamically generated, and energy consumption and service quality are balanced; and constructing a thermodynamic entropy increase optimization model to dynamically update an environment coupling coefficient and a weight parameter, and integrating meteorological and power grid data to form a self-adaptive negative feedback control ring. According to the invention, the limitation of traditional single-point optimization is broken through, the cleaning uniformity error is improved, the fault early warning response speed is accelerated, and the energy efficiency and reliability of the shared washing machine are remarkably improved.

The invention relates to the technical field of integrated circuits, in particular to a band-gap reference voltage source circuit with high-order compensation, which comprises a PTAT (proportional to absolute temperature) generation circuit, a high-order compensation circuit and a pre-voltage-stabilizing circuit, wherein the PTAT generation circuit generates PTAT current, and the high-order compensation circuit performs second-order compensation on the PTAT current; the pre-voltage-stabilizing circuit is used for driving the PTAT generation circuit and the high-order compensation circuit and comprises a starting circuit, a positive feedback loop and a negative feedback loop; the gain of the positive feedback loop is lower than that of the negative feedback loop; according to the band-gap reference voltage source circuit, the temperature coefficient and the power supply rejection ratio of the circuit are remarkably optimized by integrating high-order temperature compensation, a pre-adjusting power supply and a high-gain feedback loop, and the designed band-gap reference voltage source circuit has the advantages of being extremely low in temperature drift and high in precision.

The invention discloses an ultra-wideband high-linearity power amplifier with a negative feedback structure. The ultra-wideband high-linearity power amplifier comprises an input matching network, a driving-stage amplifying circuit, an inter-stage matching network, a power-stage amplifying circuit, an output matching network, a negative feedback RLC (Radio Link Control) network and a self-adaptive biasing circuit, an input radio-frequency signal is transmitted to the driving-stage amplification circuit through the input matching network for primary amplification, transmitted to the power-stage amplification circuit through the inter-stage matching network for secondary amplification and output through the output matching network, and the driving-stage amplification circuit comprises a first transistor and a second transistor. The power level amplification circuit comprises a third transistor and a fourth transistor; the self-adaptive bias circuit is used for providing self-adaptive bias voltage for the first transistor and the third transistor; the negative feedback RLC network is used for controlling the gain and bandwidth of the amplifier and comprises a driving-stage negative feedback network and a power-stage negative feedback network. The working bandwidth of the power amplifier can be widened, and the gain, the output power and the linearity of the amplifier can be improved.

The invention discloses a manned aircraft / unmanned aerial vehicle pursuit deep learning control method simulating a pigeon positive and negative feedback mechanism. The method comprises the following steps: step 1, giving mathematical models of a manned aircraft and an unmanned aerial vehicle and performing environment initialization; step 2, building a quaternion PID controller of the unmanned aerial vehicle; 3, a manned aerial vehicle / unmanned aerial vehicle hierarchical decision-making architecture is established; step 4, mathematical modeling of a pigeon positive and negative feedback mechanism; 5, designing a manned aerial vehicle / unmanned aerial vehicle cluster reward function simulating positive and negative feedback of the pigeon flock; 6, planning and designing an escape unmanned aerial vehicle path; step 7, predicting an escape unmanned aerial vehicle path; and 8, generating a manned aerial vehicle / unmanned aerial vehicle cluster pursuit learning strategy based on the actor-commentator network. According to the invention, an efficient, flexible and extensible bionic intelligent pursuit control framework is constructed, and the pursuit task execution efficiency and cooperative combat capability of the manned aerial vehicle / unmanned aerial vehicle heterogeneous cluster in a complex dynamic environment are improved.

The invention discloses a radio frequency power supply dynamic power stabilization system and method based on PID regulation and control, and in a radio frequency ion source, the beam size and the radio frequency power are strongly correlated. In order to ensure beam stability and optimize radio frequency power output, a PID regulation and control module is designed, and radio frequency power is dynamically regulated in a negative feedback regulation and control mode so as to compensate power fluctuation caused by factors such as heating of parts such as a grid mesh or a coil, plasma load change and current drift, and fine regulation of the radio frequency power is realized. The invention relates to the technical field of radio frequency power supplies. According to the radio frequency power supply dynamic power stabilization system based on PID regulation and control and the method thereof, the design ensures that the radio frequency power supply can maintain stable power output under different working conditions and fault conditions, the system has fault self-diagnosis and protection functions, and the reliability and the safety of the system are improved.

The invention discloses an oscillation detection and optimization method and system for strongly connected components of a combinational logic circuit, and the method comprises the steps: building an oscillation detection module according to an external input signal in the strongly connected components and a signal value of the signal, and building an equivalent transformation module in combination with a multiplexer; and inserting the equivalent transformation module into the nested logic ring containing the negative feedback ring to share the output end of the logic gate, and outputting the transformed netlist. According to the invention, the oscillation can be successfully detected and interrupted under the condition that the circuit oscillates, the logic function of the original circuit is not influenced under the condition that the circuit does not oscillate, and the simulation efficiency and stability of the combinational circuit are improved.

The invention relates to the technical field of e-commerce logistics and supply chain management, and discloses a multi-channel e-commerce platform order processing optimization system and method, and the method comprises the steps: correcting physical inventory data through a Lagrange dual variable fed back in a previous period, calculating a virtual inventory, and receiving a discrete order flow; constructing a space-time hypergraph model of the to-be-processed order according to the commodity homogeneous attribute and the spatial neighborhood attribute; performing constraint optimization solution on the hypergraph model based on a Lagrangian relaxation algorithm, and generating an optimal order allocation matrix meeting productivity constraints and a Lagrangian dual variable of a current period; and analyzing the distribution matrix to generate an operation instruction, issuing the operation instruction to the physical warehouse, and feeding back the dual variables to the inventory calculation module. According to the method, collaborative operation benefits are mined through the space-time hypergraph, and a negative feedback closed loop with physical capacity pointing to front-end sales is constructed by using dual variables, so that performance cost optimization and flow adaptive control are realized.

The invention relates to a computing power network service request balanced distribution method and system, and the method comprises the steps: collecting the global information in a current preset period, including the request flow information of each access node, and the computing power information, network state information and historical load information of each service node, and carrying out the centralized convex optimization. Generating a global distribution strategy based on the global information; issuing the global distribution strategy to each access node, dynamically adjusting the distribution strategy through a negative feedback mechanism within a preset time sequence interval according to a local real-time request processing condition after the access node receives the global distribution strategy, and forwarding the distribution strategy to the service node according to the adjusted distribution strategy; and feedback information from the service node and the access node is received in real time, a global distribution strategy is updated based on the feedback information, and the distribution precision and the load balancing effect are improved in the next period. According to the invention, a global optimal strategy is realized through convex optimization, and the distribution probability is adjusted in real time in combination with a negative feedback mechanism.

The invention relates to a voltage output method and system based on a high-voltage power supply widening controller, and belongs to the technical field of high-voltage power supplies. The method comprises the following steps: acquiring a wide-range voltage parameter, and dividing a frequency control region and a pulse width modulation control region of a high-voltage power supply through an arbitration control algorithm to obtain switching judgment information of a power supply working region; constructing a working area switching logic according to the resistance-capacitance network, executing the working area switching logic through a frequency pulse correlation algorithm, coordinating the pulse width and the working frequency, and generating a double-modulation execution signal; a closed-loop negative feedback mechanism is established, and a wide-range overvoltage-free voltage regulation and control instruction is obtained by combining a proportional-integral compensation circuit with a resistance measurement full-right control working frequency and a pulse width; and broadening the output voltage range and inhibiting the overshoot voltage through power supply power driving, coordinating the working frequency and the pulse width in combination with the wide-range overvoltage-free voltage regulation and control instruction, and outputting the wide-range voltage of the high-voltage power supply.

The invention discloses an aircraft cluster cooperative control method based on MADRL, and the method comprises the following steps: obtaining an aircraft cluster cooperative task, considering an aircraft simulation environment containing sudden change interference, and constructing an aircraft kinematics and dynamics model according to the task; modeling the aircraft cluster task into a multi-agent Markov decision process to replace a control process based on negative feedback; performing deep reinforcement learning training on the multi-agent cluster system, and generating an accelerator and three-axis rudder deflection control instruction for controlling the aircraft from the current aircraft environment state value; and designing a deep reinforcement learning algorithm based on selective experience playback, and storing an aircraft environment state value and a corresponding accelerator and three-axis rudder deflection control instruction into a playback buffer pool. According to the method, autonomous intelligent decision making in flight of a multi-agent aircraft cluster system in a complex battlefield environment is realized, and robustness, rapidity and universality of aircraft cluster cooperative control are improved by designing a reward function and a joint strategy.

The invention relates to the technical field of data processing, and discloses a signal intra-pulse modulation pattern recognition method and system, and the method comprises the steps: receiving a radar pulse signal; performing short-time Fourier transform on the radar pulse signal; in the time-frequency matrix, calculating an energy distribution gradient of each time point along a frequency axis; according to the energy distribution gradient of each time point, identifying gradient abrupt change points; determining a filtering bandwidth boundary based on the gradient catastrophe point by adopting a negative feedback regulation mechanism of bandwidth and signal-to-noise ratio; based on the filtering bandwidth boundary, performing bandwidth filtering on the radar pulse signal; calculating an instantaneous frequency, a first-order differential frequency and a second-order differential frequency of the filtered signal through Hilbert transform, and forming a feature vector; predicting a cluster number range through a long and short term memory neural network according to the feature vectors; according to the feature vector, through a K-Means clustering algorithm, carrying out clustering analysis in a clustering number range; and outputting a modulation style label according to a clustering analysis result.

A crane simulation model optimization method based on HIL data optimization comprises the steps that after virtual extreme working condition data is generated according to collected crane conventional working condition sensor data through a multi-mode dynamic model, a double-generator is used for confronting a generated data enhancement module to conduct data optimization; and inputting the optimized data into a crane simulation model for simulation and obtaining a dynamic deviation between simulation output and actually measured extreme working condition data, and optimizing parameters of the double-generator adversarial generation data enhancement module and the crane simulation model through GRPO reinforcement learning so as to realize closed-loop negative feedback regulation. According to the method, the generalization ability and robustness of the crane simulation model can be obviously enhanced, the continuity of the generated data in the time dimension is ensured, and the accuracy of the crane simulation model is obviously improved.

The invention provides a photovoltaic inverter common-mode resonance suppression method and device and a storage medium. The method comprises the steps of obtaining resonance current data of a common-mode loop; determining a differential negative feedback control strategy of a common-mode loop based on the resonance current data and preset common-mode current data; determining a harmonic control strategy of the system according to the first voltage data of the DC unit and the second voltage data of the power grid; determining a pulse width modulation strategy of the system based on a differential negative feedback control strategy and / or a harmonic control strategy so as to suppress common-mode resonance generated during voltage fluctuation; according to the method, the problems of current oscillation and inverter damage caused by common-mode resonance are effectively solved by obtaining the common-mode loop resonance current data and adopting the differential negative feedback control strategy to suppress resonance frequency point oscillation, combining the harmonic control strategy to eliminate the alternating current component, and finally dynamically adjusting the pulse width modulation strategy; the method has the advantage of improving the stability and safety of the system.