2189 results about "Error signal" patented technology

Disclosed in the present invention are a grid-connect control method and apparatus for a grid-connect inverter. The method comprises: on the basis of a control structure of a grid-connect inverter in a dp domain, passing a deviation signal of a power outer loop through power outer loop controllers, so as to generate reference values of a current inner loop, and comparing the reference values of the current inner loop with an actual output current, so as to obtain error signals, wherein the control structure comprises a PQ power control outer loop and a current control inner loop, and the actual output current is obtained by means of performing phase tracking, on the basis of a synchronous reference frame phase-locked loop, on the voltage of a point of common coupling; and adjusting the error signals by means of a current inner loop controller, so as to generate modulation signals, performing pulse width modulation (PWM) on the modulation signals, so as to generate an on-off signal of an inverter bridge power semiconductor device, and controlling the state of connection and disconnection between the grid-connect inverter and a power grid on the basis of the on-off signal. In the present embodiment, the connection and disconnection between a grid-connect inverter and a power grid are controlled, so as to improve the stability of the grid-connect inverter in weak power grids.

The invention provides an automatic energy-saving control method and device for a ring cooling fan based on load feedback, relates to the field of ring cooling fans, and solves the technical problem of delay of regulation and control in an energy-saving working state. The method comprises the steps that working condition data are input into a preset powder box model, and a feed-forward air volume instruction is obtained through calculation; and inputting the working condition data into a state observer to obtain an optimal estimated temperature value. And the deviation between the optimal estimated temperature value and a preset temperature set value is calculated, and a feedback air volume compensation instruction is obtained through calculation of a feedback controller according to the deviation. And fusing the feed-forward air volume instruction and the feedback air volume compensation instruction to obtain a final air volume control instruction, and issuing the final air volume control instruction to a fan frequency converter for execution. And continuously monitoring the numerical value and the change trend of the feedback air volume compensation instruction, taking the feedback air volume compensation instruction as a prediction error signal of the powder box model, and adaptively adjusting key thermal parameters in the powder box model. The method is used in the control process of the ring cooling fan.

The invention discloses a real-time monitoring and feedback control system for enamel electrostatic powder coating, and relates to the technical field of industrial enamel coating. The system comprises a data acquisition and monitoring module, a feedback control decision module, an execution mechanism control module, a spraying path planning and adjusting module, a parameter optimization and adaptive adjustment module and a multi-target cooperative adjustment strategy module. The system builds a standardized state vector and recognizes abnormity by collecting spraying enamel electrostatic powder state parameters, deposition error signals and environment interference data, and closed-loop control and dynamic adjustment of spray gun electrode voltage, powder supply amount and spray gun path parameters are achieved. Intelligent algorithms such as particle swarm optimization are introduced to optimize a controller and process parameters, the coating uniformity and the deposition efficiency are automatically balanced in combination with a multi-target collaborative strategy, and stable spraying quality is achieved under complex working conditions. The method has the advantages of self-learning, self-adaption and expandability, and the intelligent level and the production performance of the enamel electrostatic powder spraying process are remarkably improved.

An adaptive variable step-size LMS filter based on a hyperbolic tangent function and its filtering method and computer equipment belong to the field of filter technology, and solve the problem that the LMS algorithm improved based on a nonlinear function requires too many manual adjustments of parameters and that the convergence speed and convergence accuracy of the traditional LMS algorithm cannot be satisfied simultaneously. The method of the present invention includes: determining the filter tap length and the number of iterations; initializing the filter parameters; obtaining the filter input signal vector; determining the instantaneous expected signal of the filter; obtaining the instantaneous output signal; obtaining the instantaneous error signal of the filter and the accumulated amount of the error signal based on the instantaneous output signal; obtaining the instantaneous step size using a step-size update formula based on a hyperbolic tangent function; and continuously iterating the filter tap weight coefficient vector to construct an LMS filter using the filter tap weight coefficient vector obtained after the number of iterations. The present invention is suitable for improving the performance of the LMS filter, and the filter of the present invention can be widely used in various signal processing fields.

An underwater acoustic sensor network node positioning error correction method combined with acoustic velocity inversion, which method relates to the technical field of acoustic velocity inversion. The method comprises: deploying an acoustic source point and underwater acoustic sensor nodes which are at fixed positions, the underwater acoustic sensor nodes collecting acoustic velocity data sent by means of the acoustic source point, and by means of acoustic velocity data at different underwater acoustic sensor nodes, using an acoustic velocity field inversion algorithm to construct an acoustic velocity field model; collecting real-time acoustic velocity data at the different underwater acoustic sensor nodes, and obtaining acoustic velocity characteristic information at the different underwater acoustic sensor nodes and water characteristic information at the different underwater acoustic sensor nodes; performing comprehensive analysis on the acoustic velocity characteristic information and the water characteristic information, and evaluating the positioning accuracy of the acoustic velocity field model in respect of the underwater acoustic sensor nodes; and comparing quantized positioning accuracy results for the underwater acoustic sensor nodes with a preset threshold, and when there is a relatively large error in the positioning accuracy, generating an error signal. The method is conducive to improving the precision of underwater acoustic wave propagation and the accuracy of underwater acoustic sensor network node positioning, and evaluating the positioning accuracy of an acoustic velocity field model in respect of underwater acoustic sensor nodes.

The invention relates to the technical field of adaptive filtering, and discloses a deviation compensation constraint adaptive filtering method and system based on error nonlinearity, and the method comprises the steps: constructing an adaptive weight vector and a noise-containing input signal vector according to an adaptive weight and a noise-containing voice signal sampling value when the weight of an adaptive filter is subjected to linear constraint; after the inner product generates an output signal, an estimation error signal is generated, and an error square median is calculated; calculating an error signal variance estimated value and a self-adaptive weight vector power estimated value according to the error square median and the self-adaptive weight vector, and then calculating an input noise variance estimated value; calculating a deviation compensation item according to the adaptive weight vector and the input noise variance estimation value, and updating the adaptive weight vector with the noise-containing input signal vector and the estimation error signal; and calculating the inner product of the updated adaptive weight vector influenced by the low-efficiency input noise and the noise-containing input signal vector to obtain an output signal subjected to input noise deviation compensation.

The invention discloses an aircraft control surface oscillation fault monitoring method based on multi-scale wavelet transformation, and the method comprises the steps: carrying out the calculation through a PID (Proportion Integration Differentiation) control law through an autopilot according to an input flight path command, and obtaining a control surface control instruction deltadepth; a control surface deflection prediction value delta est is generated based on the nonlinear model and the control surface control instruction, the control surface deflection prediction value and an actual deflection value delta mea collected by the sensor module are subtracted to generate a residual signal Rn, and the residual signal is decomposed into a plurality of sub-band signals through wavelet decomposition; wavelet energy calculation is carried out on the sub-bands possibly containing the control surface oscillation fault signals, whether a fault occurs or not is judged according to the magnitude of an energy comparison threshold value, and the judgment threshold value is determined through Monte Carlo simulation. According to the method, instruction signals are separated by generating residual errors, wavelet transform processing is carried out on residual error signals, interference of noise and irrelevant frequency signals on monitoring performance is reduced, meanwhile, small-amplitude oscillation signals can be effectively monitored according to sub-band wavelet energy serving as a fault criterion, and the monitoring coverage rate of oscillation faults is remarkably increased.

The invention relates to a method and a system for detecting the concentration of trace methane by locking the position of an absorption peak, and belongs to the technical field of laser gas detection. Modulated laser output by a laser is divided into two paths, one path enters a reference light path, the other path firstly passes through a gas absorption cell and then enters an actual detection light path, and methane gas with known concentration is sealed in the reference light path; demodulating a modulation signal output by the actual detection light path, and calculating to obtain a trace methane gas concentration value; and demodulating the modulation signal output by the reference light path to obtain a second harmonic signal, comparing the amplitude of the second harmonic signal with the amplitude of a harmonic signal corresponding to a preset methane absorption peak to generate a wavelength shift error signal, and adjusting the driving parameter of the laser through a feedback mechanism to generate a wavelength shift error signal. The output power and wavelength drift of the laser are monitored in real time, and it is ensured that the laser wavelength is always locked within the methane absorption peak range. According to the invention, high-precision and high-stability trace methane concentration detection can be realized.

The invention discloses a high-current wide-capacitance-range LDO (Low Dropout Regulator) based on a frequency compensation circuit. The LDO comprises a first-stage operational amplifier, a second-stage operational amplifier and a third-stage operational amplifier The secondary operational amplifier is used for carrying out secondary amplification on the amplified error signal; the driving circuit is used for enhancing the driving capability of the error signal subjected to secondary amplification; the current output circuit is used for adjusting the output current of the output demand according to the secondary amplified error signal with the enhanced driving capability and the input voltage; the feedback circuit is used for generating new feedback voltage according to the output current; the first-stage operational amplifier is also used for amplifying a new error signal; and the frequency compensation circuit is used for adjusting the positions of a plurality of zero poles in the new error signal according to the output current by utilizing the multi-zero pole dynamic compensation branch and the current buffer compensation branch so as to offset a secondary pole and widen the whole unit gain bandwidth at the same time to obtain an adjusted error signal. According to the invention, a large bandwidth can still be obtained in a large current output range and a large load capacitance range.

The invention relates to an active noise reduction method and system, a storage medium, electronic equipment and a vehicle. The method comprises the steps that operation parameters of an air conditioning device on the vehicle and a first error signal collected through a preset sensor are obtained; reading noise signals corresponding to the operation parameters of the air conditioning device from a preset database as reference signals; determining a filter coefficient based on the reference signal and the first error signal; and processing the reference signal based on the filtering coefficient to obtain a control signal and playing the control signal so as to perform noise reduction on the reference signal. According to the method, by establishing the corresponding relation between the operation condition of the air conditioning device and the noise signal and combining the virtual microphone technology, noise reduction can be conducted under the condition that a reference microphone and a microphone at the target position are not installed, the cost is effectively reduced, and equipment installation is simplified.

The invention relates to an intelligent customer service self-learning method and system, and the method comprises the steps: collecting the interaction data of a user and an intelligent customer service, and forming a multi-dimensional data set; based on a PID (Proportion Integration Differentiation) controller, processing the performance indexes in the multi-dimensional data set, calculating a current error signal, and generating a corresponding control instruction according to the current error signal so as to adjust the response behavior of the intelligent customer service system in real time; evaluating the system performance data adjusted by the control instruction to obtain evaluation feedback; and according to the evaluation feedback, dynamically adjusting the parameters of the PID controller through a self-adaptive control strategy, and feeding back the adjusted parameters to the PID controller in the step S2. According to the invention, by introducing a closed-loop feedback mechanism based on the PID controller and a parameter adaptive optimization strategy, real-time regulation and control of the response behavior of the intelligent customer service system are realized, and the stability, the response speed and the user satisfaction of the system are remarkably improved.

A digital controller for a switching converter configured to receive an input voltage and to generate an output voltage, the switching converter comprising one or more power switches and an energy storage element, the digital controller comprising a ripple cancellation signal generator configured to generate a ripple cancellation signal, the digital controller being configured to receive a digitized current signal, the digitized current signal being a digital representation of a current flow through the energy storage element, generate a filtered digital current error signal using the digitized current signal and the ripple cancellation signal, the ripple cancellation signal being arranged to reduce ripple from the digitized current signal in the generation of the filtered digital current error signal, and control the switching converter, the control of the switching converter being dependent on the filtered digital current error signal, wherein the ripple cancellation signal, within each signal period, comprises a rising slope comprising a first non-linear portion, and / or a falling slope comprising a second non-linear portion.

The invention discloses a grid-connected inverter control method based on second-order linear active disturbance rejection, and particularly relates to the field of grid-connected inverter control. Voltage and frequency error signals between the output side of the inverter and the power grid are obtained, a pre-synchronization control model is constructed, and voltage amplitude and frequency synchronization is achieved; a second-order linear active-disturbance-rejection controller is introduced in the frequency synchronization control process, an extended state observer is adopted to estimate the output frequency, the frequency change rate and a disturbance term, and a state error feedback control law is combined to generate a frequency regulation control quantity, so that accurate frequency control is realized; after grid connection, a dual-channel LADRC power regulation controller is constructed, and decoupling tracking control is carried out on active power and reactive power; meanwhile, on the basis of fast Fourier transform processing as a stable grid-connected state criterion, the method has the advantages of being high in control precision, high in anti-interference capability, good in current waveform quality, high in adaptability and the like, and is suitable for various grid-connected application scenes.

In at least one embodiment, an active noise cancellation (ANC) system is provided. An audio signal source provides an audio signal. At least one loudspeaker projects anti-noise sound within a cabin. At least one microphone provides a first error signal indicative of the noise, the audio signal, and the anti-noise sound and a second error signal indicative of an estimated anti-noise signal. At least one controller is programmed to receive the first error signal and the second error signal and to provide an estimated impulse response based at least on the first error signal and the second error signal. The at least one controller is further programmed to compare the estimated impulse response to one or more pre-stored impulse responses; and to select a first pre-stored impulse response that matches the estimated impulse response to filter one or more reference signals at an adaptive filter to generate the anti-noise signal.

A charge pump, a phase-locked loop, a radar sensor, and an electronic device. The charge pump is applicable to the phase-locked loop. The charge pump comprises a discharging circuit and a charging circuit, both of which are connected to an output end of the charge pump. The discharging circuit reduces a current of the output terminal under control of a first control signal, the charging circuit increases it under control of a second control signal, the first control signal and the second control signal being corresponding to error signals between the two clock signals. The charge pump further comprises a voltage control circuit connected to a first node in the discharging circuit and / or a second node in the charging circuit to maintain the locked state of the phase-locked loop by controlling voltages of corresponding nodes, the first node and the second node being both connected to the output end.

The invention relates to the technical field of wireless communication, and discloses a communication equipment command and dispatch system based on artificial intelligence, the system maps the state of communication equipment into a standardized carrier phase disturbance mode, and after the disturbance mode is adaptively adjusted in combination with channel noise perception and conflict arbitration logic, the communication equipment is commanded and dispatched. Controlling the radio frequency front end to carry out injection; the adjacent communication equipment directly detects the disturbance mode to trigger the cooperative scheduling action by monitoring the physical error signal of the carrier synchronization loop of the adjacent communication equipment, and the implicit cooperative mode based on the physical layer beacon is constructed, so that the complex high-level signaling interaction required by the traditional scheduling is avoided, and the scheduling efficiency is improved. According to the method, the millisecond level, determined by a software protocol, of the collaborative response time between the devices is substituted into the microsecond level determined by the hardware physical layer response entscheid, the system can still maintain reliable transmission of scheduling instructions when facing high-density concurrent conflicts and strong channel noise, and a technical implementation path is provided for ultra-low-delay and high-reliability communication.

The invention relates to the technical field of adaptive filters, and discloses a wide linear adaptive filter, which comprises the following steps of: performing tensor integral solution on a system weight vector at the moment of the wide linear adaptive filter to obtain two adaptive weight vectors; constructing an input matrix based on the sampling value of the input signal, and calculating an estimation signal of the moment based on the product of the input matrix of the moment and the two adaptive weight vectors; and calculating the difference value between the expected signal and the estimation signal at the moment, obtaining an estimation error signal, and updating the gain vector at the obtaining moment and the estimation error signal by using a minimum error mode criterion, updating the two adaptive weight vectors at the obtaining moment, and reconstructing the system weight vector at the moment of the wide linear adaptive filter. According to the invention, the recursive adaptive filtering algorithm resistant to impulse noise interference is realized with low calculation complexity by using weight decomposition and selection of a robust cost function.

The invention provides a vibration active control method based on a secondary channel online identification FxLMS algorithm, a vibration active control system comprises a sensor, a vibration signal conditioner, an actuator, a piezoelectric power amplifier, a real-time control simulation system and a computer, and a built SPMFxLMS algorithm physical model is embedded in a computer controller. The SPMFxLMS algorithm physical model comprises a vibration response error signal calculation module, a control channel adaptive filter, an identification channel adaptive filter and an unknown secondary channel model, and the unknown secondary channel model is constructed according to the identification channel adaptive filter and updated in real time. The algorithm physical model constructed by the invention adopts an improved power scheduling strategy and an identification adaptive filter to update and calculate the vibration response time domain data of the controlled object, so that the obtained control voltage signal is reliable, the residual vibration quantity caused by identification noise is avoided, the vibration suppression effect is excellent, and the method has excellent noise immunity and applicability.

The invention belongs to the technical field of electronic circuits, and provides a low-dropout linear voltage stabilizing circuit, a low-dropout linear voltage regulator and electronic equipment. The low-dropout linear voltage stabilizing circuit comprises an error amplification module, a buffer module, a power module, a feedback module and a transient enhancement module, the buffer module is connected with the error amplification module, the power module and the transient enhancement module, the power module is connected with the transient enhancement module, the feedback module and a load, and the feedback module is connected with the error amplification module. When the current on the load changes, the transient enhancement module provides the first current for the power module according to the target voltage, so that the power module quickly adjusts the target voltage according to the first current and quickly responds to the change of the load; the feedback module outputs feedback voltage according to the target voltage; the error amplification module outputs an error signal according to the feedback voltage and the reference voltage; the buffer module outputs a driving signal to the power module according to the error signal, so that the power module maintains the target voltage stable according to the driving signal.

The invention relates to an accurate collision-free automatic docking control method which is characterized by comprising the following steps: S1, remote guidance: triggering an automatic docking signal, establishing a three-dimensional semantic map, completing autonomous positioning, planning a docking path, performing real-time obstacle avoidance navigation, and executing safe and stable movement to reach a pre-docking position; s2, posture adjustment: when reaching the pre-docking position, determining the target posture of the target docking object and the posture of the object to be docked, and adjusting the posture of the object to be docked to the pre-docking posture; and S3, short-range docking: based on motion compensation, detecting a motion error, generating a motion correction instruction according to error signal feedback, and realizing collision-free accurate docking. The movement function and the body position changing function of the intelligent wheelchair are achieved through the intelligent wheelchair, smooth and stable switching can be achieved in the changing process of the intelligent wheelchair, and meanwhile the intelligent wheelchair is an indoor power assisting system, has the obstacle avoiding walking function and can be in collision-free automatic butt joint with a bed body and a closestool.

The invention provides an aluminum material shearing machine pressure self-adjusting feeding system based on synchronous rollers, relates to the technical field of aluminum material shearing machines, and adopts three synchronous rollers to be mounted in a mounting groove in the surface of a turntable through a movable block, a pneumatic telescopic rod and a pressure sensor in a combined manner to form multi-point support and tension control on an aluminum material. The console collects an extrusion force signal output by the pressure sensor in real time, calculates an actual pressure value in the horizontal direction through a pressure decomposition algorithm in combination with a turntable angle output by the angle sensor, compares the actual pressure value with a preset tension threshold value to generate an error signal, and drives the pneumatic telescopic rod to dynamically adjust the position of the synchronous roller; and when the error exceeds a set range, the servo motor can be controlled to adjust the angle of the turntable, and the wrapping angle of the synchronous roller is changed to realize tension compensation. The conveying tension of the aluminum material under the complex working condition is kept stable, the conditions of loosening, wrinkling, deviation and too tight snapping are avoided, and therefore the stability of the aluminum material in the conveying process and the follow-up shearing precision are improved.

The invention discloses a miniature sawtooth generation method based on an artificial intelligence optimization algorithm, and the method comprises the following steps: S1, initializing a generation parameter, and mapping the generation parameter to a high-dimensional complex field; s2, selecting and configuring an algorithm, and optimizing parameters by constructing a target function in a high-dimensional complex field; s3, constructing a neural morphology calculation system, processing the optimized parameters through a neural network and a complex modulation activation function, and generating a preliminary miniature sawtooth waveform; s4, error evaluation is carried out, an error signal is converted from a time domain to a frequency domain for weighted analysis and optimization, and key frequency band parameters are identified and adjusted; s5, adaptively adjusting the issuing frequency and synaptic weight of the neural network, generating parameters through continuous optimization, and circularly adjusting the waveform; and S6, outputting the optimized micro sawtooth waveform. According to the invention, high-precision and high-stability micro sawtooth waveform generation is realized, and the method is suitable for signal processing and application in a complex environment.

The invention relates to the technical field of noise reduction seats, in particular to a subway cab active noise reduction system and method based on a multi-channel feedback algorithm. The device comprises a headrest shell, the headrest shell is installed at the top of a seat of a metro cab through a headrest support, a loudspeaker, an error sensor and a master controller are arranged in the headrest shell, and the headrest shell is sequentially provided with a front shell, a rear shell and a long-strip-shaped check block; the headrest supports are correspondingly installed in the long-strip-shaped check blocks on the two sides of the headrest shell respectively and move up and down along the long-strip-shaped check blocks, and the height of the headrest shell is adjusted. The loudspeakers are tightly attached to the ears of a driver at certain intervals; the error sensor forms a rhombic array covering a vertical range of 10cm; and the main controller is fixed on the front shell through the notch of the rear shell. According to the invention, the parameters of the main acquisition filter and the auxiliary acquisition filter of the main controller are adjusted according to the error signal to continuously adapt to the complex and changeable noise environment in the subway cab, so that stable and efficient active noise reduction is realized.

A row driver assembly includes a row driver unit. The row driver unit includes a buffer circuit that drives a control signal to a pixel circuit. The buffer circuit is electrically connected to a high buffer supply voltage and to a low buffer supply voltage. A voltage converter circuit supplies the low buffer supply voltage to the buffer circuit. An error detection circuit outputs an active error signal when the low buffer supply voltage is outside a target voltage window.

A control device for a switching voltage regulator includes: a first detector of a first measurement signal indicative of a current flowing in a first side of the regulator, and providing a first comparison signal as a function of a first threshold; a second detector of a second measurement signal indicative of a current flowing in a second side of the regulator, and providing a second comparison signal as a function of a second threshold; a driving-signal generation circuit which generates a switching control signal from the first comparison signal to drive the switching circuit; a calibration circuit which receives an alert signal indicative of the first threshold, compares the alert signal and the second comparison signal, and provides a calibration signal in response; and a feedback circuit which provides a control signal as a function of an error signal and of the calibration signal.

The invention relates to a robot polishing online flutter suppression method based on reinforcement learning, and relates to the technical field of robot vibration control and regulation, and the method comprises the following steps: starting from a vibration signal and a force error signal in a robot polishing process, performing discrete wavelet transform, energy entropy calculation and statistical feature extraction to obtain a vibration signal and a force error signal; the method comprises the following steps: constructing a multi-source feature vector with high identification degree, normalizing the multi-source feature vector, performing feature fusion and dimensionality reduction by adopting a convolutional neural network and a multi-head attention module to obtain low-dimensional feature representation, constructing a time sequence enhanced strategy model through a DDPG framework embedded with LSTM, and outputting impedance parameters based on a time sequence state by an Actor network in the strategy model to obtain a time sequence enhanced strategy model; and the Critic network realizes stable updating of a strategy by minimizing a loss function and combining entropy regularization so as to regulate and control an end effector of the robot, real-time suppression and efficient control of a complex flutter mechanism in the process of polishing the thin-walled workpiece by the robot are realized, and the self-adaptability and the control precision of the system are remarkably improved.

The invention relates to the technical field of active noise reduction, in particular to an in-vehicle noise control method and system, a medium, electronic equipment and a vehicle, and the method comprises the steps: determining a filtering coefficient according to a reference signal collected by a target sensor and an error signal collected by a preset sound collection module on the vehicle; and processing the reference signal according to the filter coefficient to obtain a control signal of the reference signal for noise reduction. According to the method, acceleration sensors at different positions are started or paused according to the driving state of the vehicle, reference signals which contribute to noise greatly are reserved, the noise reduction amount is increased, and input of unnecessary reference signals is reduced.

The invention discloses an LDO (Low Dropout Regulator) linear voltage stabilizing circuit, and relates to the technical field of LDO linear voltage stabilization, and the LDO linear voltage stabilizing circuit comprises a comparison output module which is used for comparing a received reference voltage with a feedback voltage so as to generate and output an error signal; the buffer driving module receives the error signal and carries out amplification and buffer processing so as to generate and output a driving signal. The first compensation module generates a first compensation signal according to the load current and the sampling current so as to dynamically adjust the amplitude and / or phase of the driving signal; the power switch module controls the on-off of a switch according to the received driving signal, and further adjusts the magnitude of voltage output to a load; the feedback module detects the voltage of the load and outputs the voltage to the comparison output module. Therefore, the first compensation module generates the first compensation signal according to the dynamic change of the feedback load current and the load capacitance, so as to dynamically adjust the amplitude and / or phase of the driving signal output to the power switch module, and ensure the stability of a circuit loop.

The invention discloses a laser frequency stabilization system based on Faraday anomalous dispersion atomic filtering, which is used for carrying out frequency stabilization on phase modulation multi-sideband laser, and comprises a frequency doubling laser unit which is configured to comprise a fundamental frequency seed light source, an electro-optical modulator, a fundamental frequency amplifier and a frequency doubling crystal; the light splitting module unit is configured to split the frequency doubling light into a main output light path and a monitoring light path; the atomic optical rotation filter is located on the monitoring light path and is configured to maintain the purity of the frequency-stabilized laser spectrum through purification treatment under the control of the axial magnetic field and the temperature; the frequency stabilization unit is configured to be a frequency stabilization light path and a servo system, and the frequency stabilization light path is used for obtaining laser frequency information and generating an error signal; the servo system is used for controlling the frequency of the fundamental frequency seed light source according to the error signal feedback. According to the laser frequency stabilization system provided by the invention, the spectrum purification and frequency stabilization precision can be improved, so that high-frequency stability locking is realized.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle accurate attitude control method fusing multiple sensors and a flight controller thereof. The method comprises the following steps: acquiring the position and attribute characteristic data of an unmanned aerial vehicle through multiple sensors; determining the offset degree of the statistical period and the offset direction of the unmanned aerial vehicle according to the position difference between the unmanned aerial vehicle position and the planned route in the previous statistical period, the unmanned aerial vehicle direction and the planned route angle; attitude angles are obtained through attitude calculation, the attitude angles form a fluctuation curve, the fluctuation degree is analyzed, and the attitude stability degree of the unmanned aerial vehicle is obtained; the deviation of the unmanned aerial vehicle relative to the initial position is obtained according to the fluctuation curve slope of the yaw angle; comparing the direction with the offset direction to determine a correction angle; and calculating a three-axis error signal through the correction angle, and inputting the three-axis error signal into a PID (Proportion Integration Differentiation) controller for control. A more accurate attitude angle is obtained, so that the control precision is improved.