13 results about "Hyperbolic tangent function" patented technology

This invention provides an improved sliding mode active disturbance rejection control (ADRC) method and system for an automotive shimmy system based on an electromagnetic linear actuator. Addressing the system's strong nonlinear characteristics and unknown external disturbances, a mathematical model of the automotive shimmy system based on the electromagnetic linear actuator is established. A nonlinear tracking differentiator is constructed to process the desired input signal of the wheel shimmy angle, rationally arrange the transient process, and synchronously extract the differential signal of the desired signal. A continuous and smooth Ifal function is constructed based on trigonometric sine and inverse proportional functions, and a novel extended state observer is designed to estimate the system's internal and external disturbances in real time. A super-helical sliding mode control law based on the hyperbolic tangent function is designed to replace the error feedback control law in the traditional ADRC, outputting a control voltage. This invention effectively estimates and compensates for the impact of vehicle state parameter changes, model uncertainties, and external disturbances on system stability, improving dynamic performance and control accuracy, and exhibiting good robustness and anti-interference capabilities.

This invention claims protection for a digital back-end calibration system for pipeline ADCs, comprising a down-conversion unit, an ADC to be calibrated, a low-speed, high-precision ADC, an LMS adaptive filter, and a subtractor; it solves the problem of decreased system accuracy in pipeline ADCs due to inter-stage gain errors. An inverse hyperbolic tangent function is introduced into the original algorithm model to construct a nonlinear functional relationship between the step size and the error signal, jointly constraining the step size value so that the current step size value is related to the square of the ratio of the current error to the previous error, improving the convergence speed of the algorithm. Simultaneously, step size normalization processing is combined to increase the range of step size selection and improve stability. A low-speed, high-precision ADC is used as a reference, connected in parallel with the ADC to be calibrated, and the difference between their digital outputs is sent to the LMS adaptive filter for processing, so that the output of the ADC to be calibrated continuously approaches the output of the low-speed, high-precision ADC, while the conversion process of the original ADC remains unaffected, achieving the purpose of digital calibration.

The present application provides a method and system for segment frequency hopping of UAV measurement and control link based on spectrum entropy potential field gradient, relating to the technical field of unmanned aerial vehicle, wherein the method comprises: constructing a space-time interference potential field model that integrates spectrum entropy weight and terrain coupling factor, and calculating the comprehensive interference potential energy of each space-time point in the task airspace; extracting a multi-scale potential field gradient sequence with enhanced spectrum entropy along the planned flight path of the UAV; using an adaptive threshold to detect gradient mutation points, and dividing the flight path into several continuous segments with similar interference characteristics; based on the mean interference potential energy and spectrum entropy characteristics of each segment, configuring the frequency hopping rate, frequency point number and residence time through a constrained optimization framework; using a hyperbolic tangent function with adaptive width to achieve smooth transition of the segment boundaries; and using a modulated two-dimensional coupled chaotic mapping to generate a frequency hopping sequence. The present application greatly improves spectrum utilization efficiency, reduces system power consumption and enhances the ability to resist intelligent tracking interference while ensuring communication reliability.

This invention discloses a method and system for stabilizing a robotic arm based on fractional-order sliding mode adaptive compensation. The method includes: constructing a unified dynamic model incorporating time-varying delays, nonlinear disturbances, and neural network approximation errors; defining the sliding mode function using Caputo fractional derivatives, establishing an improved trend law based on the improved Fal function and hyperbolic tangent function, and obtaining a control law based on the error-driven dynamic model and the improved approach law; constructing a dynamic adaptive compensator linked to time-delay gradient information to address the residual errors of the radial basis function and the unknown nonlinear terms in the neural network approximation, and dynamically adjusting the compensation gain based on the dynamic adaptive compensator; constructing a Lyapunov functional adapted to the fractional-order system, deriving the exponential stability criterion for the closed-loop system using Young's inequality and Halany's inequality, and determining the quantitative correlation between the fractional-order order and the convergence rate. This invention solves the problems of imbalance between robustness and smoothness and weak time-delay adaptability in existing technologies, significantly improving control accuracy and reliability.

The present application belongs to the technical field of video recognition, and particularly relates to a real-time monitoring method for safety state of workers based on image recognition, comprising: obtaining images of a work site and preprocessing, and extracting a sequence of personnel center coordinate points; constructing a motion fluctuation value model based on direction continuity, and quantifying behavior stability by using displacement vector and direction angle deviation; introducing a hyperbolic tangent function with saturation characteristics, and nonlinearly coupling the motion fluctuation value and the distance of personnel from a dangerous source, and calculating a safety risk index; and dynamically adjusting the monitoring frequency through index mapping according to the risk index, and realizing graded early warning. The present application solves the technical problems of poor robustness and uneven resource allocation of traditional monitoring methods in complex environments, improves the accuracy of safety supervision through deep coupling of motion stability and spatial constraints, and realizes fine configuration of computing resources.

This invention relates to the field of computer-aided design and discloses a computational design method for negative thermal conductivity metamaterials based on topology optimization algorithms. The method includes the following steps: defining the material's relative density field and the active heat source's power density field as dual design variables; performing active-passive collaborative optimization iteration using the adjoint variable method and the moving asymptote method; introducing a hyperbolic tangent function to quantize the continuous power field, extracting the coordinates away from the heat source and applying repulsive constraints; performing cross-scale mechanical-thermal decoupling reconstruction, replacing stress concentration regions with microscopic metalattices; calculating the Jacobian matrix to generate a feedforward compensation network and performing engineering-level derivation. This invention breaks the theoretical limit of thermal conductivity in passive metamaterials, achieves interference-free physical mapping of standard hardware in topological space, eliminates destructive thermal stress through lattice reconstruction, generates a physical system with extremely low computational latency, and realizes a dynamic adaptive negative thermal conductivity representation under complex perturbations.

The application discloses a GaN HEMT high-precision hybrid modeling method, first, the static characteristic data and dynamic capacitance data of a GaN HEMT device are acquired through a semiconductor parameter analyzer, and the dynamic switching characteristic curve of the device is acquired through double-pulse testing; then, the static characteristics of the device are modeled based on ANN; further, based on the dynamic capacitance test data, the input capacitance C iss , output capacitance C oss and reverse transmission capacitance C rss are converted to obtain C gs , C C gd and C ds , and the capacitances which change significantly with voltage C gd and C ds are nonlinearly fitted in the form of hyperbolic tangent function superposition, the dynamic capacitance model is realized in LT-spice by combining the charge control relationship with a behavior type voltage-controlled current source; finally, the static conduction model and the dynamic capacitance model are embedded in the SPICE equivalent model of the GaN HEMT, and high-precision simulation of the forward output characteristics, reverse conduction characteristics and dynamic switching process of the device is realized. The method can improve the simulation precision of the GaN HEMT model under the conditions of a wide voltage range and high-speed switching.

This invention relates to a feature selection-based system and method for assessing the operational status of LED explosion-proof lights. The method includes the following steps: S1, data acquisition and preprocessing; S2, calculating the fuzzy similarity between sensor features based on a Gaussian kernel function, and constructing a fuzzy Tcos equivalence relation; S3, introducing a local fuzzy self-information learning model to quantify the information contribution of each sensor feature to the lighting fixture status assessment; S4, applying a hyperbolic tangent function for nonlinear transformation to enhance the model's ability to represent complex degradation patterns; S5, constructing a feature selection model based on local fuzzy self-information learning to adaptively select a subset of key features; S6, based on the subset of key features, using a machine learning classification algorithm to construct an LED explosion-proof light status assessment model to achieve health status scoring, fault warning, and remaining life prediction for the LED explosion-proof light. This invention enables more accurate, efficient, and adaptive lighting fixture status assessment.

The application provides an online self-adaptive calibration method and system for low power factor error of an electric energy meter, comprising the following steps: measuring initial phase error at multiple preset low power factor calibration points to establish a data set of power factor and error; constructing an initial error function based on the data set; calculating a second derivative sign change point of the function as a boundary point to divide multiple calibration subintervals; adopting a weighted sum model of Legendre polynomial and hyperbolic tangent function to fit a phase error compensation formula in each subinterval; calculating a compensation value according to a real-time power factor position and a corresponding subinterval compensation formula during actual operation of the electric energy meter; and if the power factor is near the boundary point, then smoothing and fusing adjacent interval results through a Gaussian weighting function to realize online correction of the phase error.

This invention discloses a design method for a hyperbolic tangent attraction law in a discrete-time sliding mode controller for a DC motor speed control system. Based on the hyperbolic tangent function, a discrete-time hyperbolic tangent attraction law is constructed. Hyperbolic tangent-type adaptive interference compensation measures are embedded into the discrete-time hyperbolic tangent attraction law to construct a discrete-time hyperbolic tangent attraction law with interference compensation capability, thereby designing a discrete-time sliding mode controller. The output signal is then calculated as the control input signal for the DC motor speed control system, enabling the system to follow the given speed signal. The design method for the hyperbolic tangent attraction law in a discrete-time sliding mode controller provided by this invention features fast convergence and chatter-free characteristics, while also improving the tracking accuracy, anti-interference capability, and effectively reducing output speed fluctuations in the DC motor speed control system.

The present application relates to the technical field of adaptive filtering, and discloses a deviation compensation adaptive filtering method and system based on a logistic hyperbolic tangent function, wherein based on an estimated error signal, a non-impulsive interference error square median is constructed, and then a non-impulsive interference error signal variance estimation value and an adaptive weight vector power estimation value are further constructed to obtain an input noise variance estimation value; based on the input noise variance estimation value, the non-impulsive interference error signal variance estimation value and the adaptive weight vector, a deviation compensation term is constructed; based on the foregoing parameters and a hyperbolic cotangent function, a plurality of parameter values are constructed to update an adaptive weight error power estimation value at a current moment, and obtain an adaptive weight error power estimation value at n+1 moment; based on the plurality of parameter values, an optimal step length is constructed and smoothed to obtain a target step length, and an adaptive weight vector at the current moment is updated to obtain an adaptive weight vector at n+1 moment.

The application provides a grease automatic saponification process parameter optimization method and system and a storage medium, which comprises the following steps: constructing a BP neural network process quality prediction model with a penetration and a dropping point as outputs by using historical production data; using a weighted Euclidean distance between a model prediction value and a target value as fitness, and performing parameter optimization by using an improved sparrow search algorithm; using a Circle chaotic mapping to generate a population of process parameter combinations during initialization, and dividing the population into discoverers, joiners and sentinels; using a convergence factor based on a hyperbolic tangent function to adjust an optimization step length by the discoverers; updating the position of the joiners by calculating the average centroid of a global optimal individual and a discoverer position and combining Cauchy mutation; the sentinels adopt different strategies according to the fitness ranking; iterating until the maximum iteration number or the error accuracy requirement is met, outputting an optimal process parameter combination, and transmitting the optimal process parameter combination to a saponification control system as a set value of a reaction kettle.

This invention discloses a COD detection anti-interference method and system based on a three-optical-path and SE-1DCNN, belonging to the field of water quality detection technology. The method includes: constructing a three-optical-path detection module to simultaneously acquire three transmitted light signals from the water body to be tested, converting them into three sets of raw absorbance data: COD main signal, turbidity reference signal, and chloride ion characteristic signal; preprocessing the three sets of data to extract pure multi-channel optical characteristic signals and construct a multi-dimensional feature dataset; inputting the characteristic signals into an improved SE-1DCNN model to output a preliminarily de-interferenced COD characteristic signal; subsequently, substituting this signal into a second-derivative turbidity correction model to eliminate turbidity scattering interference and baseline drift; and then completing high-chlorine nonlinear compensation through a hyperbolic tangent function chloride ion compensation equation to obtain an interference-free COD absorbance signal. This invention solves the problem of poor COD detection accuracy in existing technologies.