100 results about "Hyperbolic tangent function" patented technology

The invention relates to the technical field of intelligent control, in particular to an internet-of-things-based old-age care robot intelligent control system, which comprises a multi-mode sensing layer, a safety decision center, an execution driving module, a voice interaction optimization module and an internet-of-things communication module. According to the method, force sense data such as contact force of the mechanical arm, voice data such as voices of old people and view data such as obstacles are collected in real time through a multi-mode sensing layer, a displacement force coupling risk value is calculated through a hyperbolic tangent function coupling model of a safety decision center, and a deviation angle risk value is analyzed and calculated through an improved Lyapunov index spectrum; a total risk value is generated through fusion and is scheduled according to hierarchical intervals, mechanical operation, old people behaviors and environmental risks can be dynamically avoided, and the use safety is remarkably improved; through sub-ambiguity quantitative analysis, comprehensive ambiguity evaluation and intention correction of the voice interaction optimization module, instruction intention is optimized in combination with multi-modal data, the problem of fuzzy voice recognition of old people is effectively solved, and interaction accuracy and response efficiency are greatly improved.

The invention provides a hot rolled steel strip surface defect detection method based on target detection, and aims to solve the problems of difficulty in multi-scale small target recognition, insufficient feature fusion and complex background interference in hot rolled steel strip surface defect detection. Extracting multi-scale defect features by using wavelet convolution through decomposition, convolution and reconstruction processes; multi-scale features are adaptively fused based on channels and space attention through a dynamic feature fusion module (DFF); a dynamic hyperbolic tangent function (DyT) is used to replace a normalization layer to dynamically adjust the input range and compress extreme values to reduce the amount of calculation. The method has the effects of high detection average precision (mAP), low missing report rate and remarkably reduced calculation complexity, effectively improves the efficiency and reliability of identifying the surface defects of the hot rolled steel strip in a complex industrial environment, and is suitable for intelligent steel manufacturing quality control.

The invention discloses a mechanical arm self-adaptive sliding mode control method based on a disturbance observer, and relates to the technical field of mechanical arm control, and the mechanical arm self-adaptive sliding mode control method comprises the following steps: constructing an initial dynamic model based on a Lagrange equation; constructing a simplified two-degree-of-freedom rigid mechanical arm dynamic model based on the initial dynamic model; designing a novel reaching law fusing the advantages of an exponential reaching law and a power reaching law, and combining a hyperbolic tangent function to replace a sign function to construct a sliding mode surface; designing a nonlinear disturbance observer, estimating the total disturbance of the system in real time, carrying out feed-forward compensation, and bringing the composite disturbance influence into a control law; designing a control law and an adaptive law of the mechanical arm through a Lyapun function; the stability of the system is analyzed through a Lyapunov function, tracking errors are proved to be asymptotically converged, and the method is used for ensuring the reliability and stability of the control system. According to the method, the disturbance observer and the self-adaptive sliding mode control strategy are combined, and the control precision and robustness of the mechanical arm when external disturbance and model uncertainty exist are effectively improved.

The invention provides a multi-unmanned aerial vehicle optimal game limited accelerated reinforcement learning control method and device, and relates to the technical field of accelerated reinforcement learning. The method comprises the following steps: constructing an evaluation neural network, and approaching a performance index function of a hyperbolic tangent function and a game neighbor item, the optimal limited control input of the unmanned aerial vehicle and the limited control input of the unmanned aerial vehicle under the worst condition; based on the input parameters, constructing a Hamilton-Jacobian error equation; through an error equation, constructing a summation square error which contains current information and past information and is provided with adjusting parameters; designing a weight updating law for evaluating the neural network; calculating the weight of the next iteration according to a weight updating law; and solving an error between two adjacent iteration weights, comparing the error with a preset threshold value, if the error is smaller than the preset threshold value, stopping iteration, and outputting a solution approaching the optimal game consistency control problem of the distributed unmanned aerial vehicle system. According to the invention, the cooperation efficiency between the unmanned aerial vehicles can be improved.

The invention provides a cooperative anti-swing control method and system for double marine cranes based on preset performance, and relates to the technical field of crane control. Comprising the following steps: establishing a marine crane dynamical model considering double-ship rolling disturbance by using a Lagrange method; determining a drivable variable, and establishing a tracking error of the drivable variable; introducing an exponential preset performance function, constraining the convergence rate, overshoot and steady-state value of the tracking error, and converting the constrained tracking error into an unconstrained variable by using a hyperbolic tangent function; a performance index function considering tracking errors and energy consumption is constructed, a Hamiltonian equation minimization performance index function is constructed, the Hamiltonian equation is solved through a reinforcement learning algorithm, and the optimal control rate is obtained. According to the invention, the convergence speed of the error of the system variable is limited in a preset interval, the steady-state and transient-state performance of error convergence is improved, and accurate control and anti-swing of the load are realized.

The invention provides a design and application method of a sliding-mode deadbeat reaching law, and relates to the technical field of electrical engineering, and the method comprises the steps: designing a sliding-mode deadbeat reaching law SMDRL, designing a control strategy through a deadbeat control principle, defining a state change law on a sliding-mode surface through a sign function, and achieving the design of the sliding-mode deadbeat reaching law SMDRL. It is ensured that the system state converges to the sliding mode surface at the fastest speed in a control period; an improved sliding mode deadbeat reaching law ISMDRL is designed, a traditional sign function is replaced with a hyperbolic tangent function, and parameters of the hyperbolic tangent function are adjusted according to the system state; the SMDRL and the ISMDRL are applied to a speed driving system of a permanent magnet synchronous motor (PMSM), and the speed driving system comprises a PMSM mathematical model, a sliding mode speed controller with a speed disturbance observer and model prediction current control. The SMDRL is introduced from the traditional sliding mode reaching law for the first time through theoretical derivation, the convergence time of the SMDRL is the shortest, and the SMDRL is applied to a permanent magnet synchronous motor speed driving system.

The invention discloses a mathematical modeling AI prediction system in financial risk assessment, which relates to the field of financial data processing and comprises a feature principal component extraction module, a compensation alignment execution module, a momentum regulation and control decision module, a gradient direction optimization module and a risk assessment output module. According to the method, principal components are extracted through covariance matrix decomposition of the qualification-debt ratio and the cash flow fluctuation ratio, feature redundancy is eliminated, the core risk characterization efficiency is improved, a cross-market compensation matrix of transaction frequency and price fluctuation is constructed in combination with SVD and cosine similarity, and the model environment adaptability is enhanced. And analyzing momentum attenuation by adopting a dynamic sliding window of a second derivative matrix eigenvalue ratio, and establishing a regulation and control mechanism to suppress gradient oscillation. Orthogonal interference of historical momentum vectors is eliminated through Schmidt orthogonalization projection, and the accuracy of the gradient optimization direction is guaranteed. And converting abstract numerical values into interpretable risk level classification by using a hyperbolic tangent function in combination with credit rating interval mapping.

The application discloses an infrared image segmentation method based on a local region self-organizing mapping algorithm, which comprises the following steps: firstly, a local region self-organizing mapping algorithm is designed, a plurality of feature bias fields are extracted by moving a local sliding window before iterative evolution of a level set, and a plurality of feature local data driving terms are constructed under a multiplicative bias field model framework; secondly, a plurality of feature global data driving terms are calculated, and a plurality of feature hybrid data driving terms are constructed through an adaptive weight function; then, an adaptive regularization function is used to regularize an energy value range of the plurality of feature hybrid data driving terms, and an initial level set is driven to perform iterative evolution; then, in the iterative process of the level set, a hyperbolic tangent function is used to keep the level set in the iterative evolution, and a symbol rule feature of positive outside and negative inside and a distance rule feature with a modulus value of 1 are kept; meanwhile, a mean filter template is used to continuously smooth the level set and eliminate redundant non-boundary contour lines; finally, a gradient descent method is used to continuously iteratively solve a minimum value of an energy function until a convergence criterion of the level set is reached or a maximum iteration number is reached, and then the method is stopped, at this time, a position of a zero level set is output, and image segmentation is completed. The local region self-organizing mapping algorithm can accurately mine a foreground contour from an infrared image, and has good segmentation speed and precision.

The present invention discloses a single-bit image restoration method, device, terminal, and medium, relating to the field of image processing. The method employs a non-zero quantization threshold to single-bit quantize an image to be restored, determining an initial image quantization model; employs a smooth hyperbolic tangent function to replace the sign function in the initial image quantization model, and performs low-rank matrix decomposition on the image to be restored, determining a target image quantization model; determines an initial optimization model based on a truncated least squares function and the target image quantization model; employs a semi-quadratic minimization method to transform the initial optimization model and determine a target optimization model; employs a proximal block coordinate descent algorithm to solve the target optimization model to obtain low-dimensional submatrices and a noise matrix; and utilizes the low-dimensional submatrices to determine a reconstructed image. This method effectively addresses the problem that prior art cannot effectively suppress quantization noise, thereby affecting image restoration accuracy.

The application provides a training method and device of a current density distribution identification model, the method comprising: inputting a plurality of sampling source points into the current density distribution identification model, and obtaining a loss function in the current density distribution identification model, which is constructed based on a current density distribution function and an electric field integral equation; wherein the loss function comprises a hyperbolic tangent function, a derivative of the hyperbolic tangent function and a product of the Green function; performing series expansion on the hyperbolic tangent function in the loss function, and extracting singular terms from the electric field integral equation in the series expanded loss function to obtain a plurality of singular integrals; performing inner integral calculation and outer integral calculation on each high-order singular integral in the singular integrals to determine the current density distribution function corresponding to the minimum value of the loss function on all sampling source points. The application can quickly solve the singular integrals comprising the hyperbolic tangent function, the derivative of the hyperbolic tangent function and the product of the Green function to obtain the current density distribution function.

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.

The invention discloses an actuator capability and control rate explicitly coupled satellite attitude adjustment method, and belongs to the technical field of satellite attitude adjustment and control. The method comprises the following steps: firstly, establishing a satellite attitude kinematics and dynamics system, modeling an actuator dynamics system by adopting a hyperbolic tangent function, and widening an attitude control system with limited actuator capability into a three-order attitude control system; then designing an attitude anti-saturation regulation controller, taking the maximum control capability of an actuator as a parameter selection reference, and ensuring the asymptotic stability of the system through the Lyapunov theory; and finally, solving an inequality differential equation of the energy function, and establishing an explicit mathematical relationship between the actuator capability and the control rate. According to the method, the relevance between the actuator capacity and the control rate is revealed through an accurate mathematical equation, a theoretical basis is provided for satellite actuator type selection, and meanwhile, the attitude adjustment stability under the condition that the actuator capacity is limited is ensured.

This invention relates to the field of semiconductor device measurement technology, and proposes a method for measuring the nonlinear output junction capacitance of semiconductors based on fitting iteration. This method first constructs a junction capacitance extraction circuit, and then acquires the turn-off transient waveform of the device under test through a test platform. Finally, it uses Fast Fourier Transform to extract the oscillation frequency f. exp Based on the relationship between the oscillation frequency, junction capacitance, and parasitic parameters, the initial junction capacitance C is deduced. oss Subsequently, a hyperbolic tangent function was used for fitting, and the fitting parameters were optimized using the least squares method to obtain the preliminary junction capacitance C under different voltage levels. oss - Test voltage u dc Based on the relationship curve, a simulation circuit for the oscillation frequency was further constructed to obtain the simulation frequency f. m and f m with f exp The fitting curve is compared, and if a deviation exists, the fitting curve is adjusted and iteratively optimized until the error between two adjacent fitting results is lower than the set error threshold, thus obtaining the final accurate junction capacitance C. oss - Test voltage u dc Relationship curve.

The invention belongs to the technical field of attitude monitoring, and particularly relates to a power transmission line tower attitude monitoring method and system based on multi-dimensional sensing, and the method comprises the steps: collecting original inclination angle time sequence data and synchronous environment state data of a power transmission tower, and constructing a time-varying environment turbulence energy index through a sliding window mechanism; based on the index, utilizing a hyperbolic tangent function to construct nonlinear adaptive observation impedance; constructing a quasi-static equilibrium evolution model containing adaptive observation impedance, and iteratively updating a truth value settlement vector of the tower in combination with a direction consistency factor; and calculating the comprehensive gradient based on the truth value settlement vector and triggering a multi-stage early warning mechanism. According to the method, elastic deformation interference caused by wind vibration and thermal drift is effectively eliminated through noise quantification of a physical level and a nonlinear intelligent gating mechanism, and accurate extraction and zero false alarm monitoring of the micro plastic settlement trend of the tower under the complex meteorological condition of the goaf are achieved.

The invention discloses an intelligent teaching quality evaluation system based on multi-modal information fusion, and belongs to the technical field of education evaluation. The system comprises a data acquisition module for acquiring environment state, teacher behavior, student behavior and interactive behavior data; the environment analysis module outputs an environment state coefficient through a Sigmoid-index coupling model; the teacher behavior analysis module adopts a Lorentz function to quantify the optimal interval of the speech speed, and generates a teacher coefficient in combination with the questioning gain; the student behavior analysis module utilizes a hyperbolic tangent function to strengthen behavior cooperation and outputs a student coefficient; the interaction behavior analysis module generates an interaction coefficient based on a logarithm-S type function; the teaching quality evaluation module obtains a teacher-student behavior matching degree; the teaching example optimization module dynamically adjusts the number of examples according to the teacher-student behavior matching degree. According to the method, the problems of high subjectivity, single dimension and poor real-time performance of a traditional evaluation method are solved, and objective quantification and dynamic optimization of teaching quality are realized.

The present application relates to the technical field of industrial edge scheduling optimization, and more particularly to an industrial edge collaborative scheduling optimization method and system based on federated digital twinning. The method comprises extracting and compressing a feature vector by using local convolution and principal component analysis; mapping the feature vector into a digital twinning model of an edge node; calculating a scheduling weight score of each edge node based on the digital twinning model; constructing a global model based on a neural network, wherein the global model parameters and the learning rate are initialized based on the scheduling weight score; combining the hyperbolic tangent function and the collaborative trust score to aggregate the updated parameter gradient of each edge node and calculate a task migration score; and performing migration scheduling according to the task migration score.

The embodiment of the invention provides a creep life extrapolation method, equipment and a medium, and the method comprises the steps: obtaining the fracture time of a to-be-tested material at a preset temperature under different stresses, the to-be-tested material being 9-12% Cr martensitic steel; fitting the fracture time of the to-be-tested material at a preset temperature and under different stresses to obtain a fitting relational expression between the fracture time and the stress of the to-be-tested material at the preset temperature, the fitting relational expression being a hyperbolic tangent function; and predicting the fracture time of the to-be-tested material under the preset temperature and the target stress according to the fitting relational expression. The fitting relational expression adopts a hyperbolic tangent function to describe the characteristic that the degradation rate of the strengthening mechanism of the to-be-tested material in the service process is accelerated first and then slowed down, the inherent defect of linear extrapolation in a long-life interval is overcome, and the life prediction deviation is reduced.

This invention provides a method and related apparatus for establishing a nonlinear mathematical model of a hybrid DC transmission system considering discontinuous characteristics. The method includes: representing the dynamic processes of discontinuous components in the main and control loops of the hybrid DC transmission system using a step function; approximating the step function as a continuous function using a linear combination of hyperbolic tangent functions to obtain a continuous expression; obtaining modular nonlinear differential equations for the rectifier, inverter, and AC / DC networks, and replacing the discontinuous dynamic parts involved in the equations with the continuous expression; and interconnecting the modules according to their input-output relationships to obtain a complete nonlinear mathematical model of the hybrid DC transmission system. This invention establishes a nonlinear mathematical model of a hybrid DC transmission system that accurately reflects discontinuous dynamic characteristics by employing the continuous approximation method using step functions and hyperbolic tangent functions, thereby improving the accuracy and practicality of system modeling.

The invention discloses an oil and gas pipeline multiphase flow electromagnetic heating temperature field cooperative control method and system, and relates to the technical field of electromagnetic heating and temperature field control. Comprising the following steps: dividing a pipeline system into a master control heating section and a slave heating section, and dynamically calculating a basic regulation interval, an approaching minimum value at a high risk and an approaching maximum value at a low risk on the basis of a slave section temperature detection result. Calculating a first correction coefficient through a main control section heat conduction influence model, optimizing a heat conduction intensity factor and a distance attenuation index in combination with a genetic algorithm, and balancing precision, energy consumption and stability; and calculating a second correction coefficient based on the temperature gradient of the adjacent high-temperature section, the normalized distance and the fluid phase state. And mapping the correction coefficient to an interval through a hyperbolic tangent function, and generating a dynamic regulation interval in combination with a basic time interval. And through multi-objective optimization and nonlinear response design, the temperature field control precision is improved, the adaptive capacity to complex working conditions such as multiphase flow medium phase change and flow velocity fluctuation is enhanced, and safe and stable operation of the pipeline is guaranteed.

The present application relates to a kind of variable parameter variable step size pseudo-random injection's Pipeline-SAR ADC calibration method, belong to analog integrated circuit field.This method can calibrate the error caused by non-ideal factors such as capacitor mismatch, operational amplifier gain mismatch, comparator mismatch of Pipeline-SAR ADC, by injecting pseudo-random sequence to extract the error caused by non-ideal factors of ADC, then introduce variable parameter inverse hyperbolic tangent function to change the iteration step of calibration, so that the estimated gain value gradually approaches the actual gain value, to achieve the effect of calibration.Compared with the traditional pseudo-random injection calibration technology, the calibration convergence speed is faster, the accuracy is higher, and the consumption of hardware resources is reduced.The calibration timing and ADC conversion are independent of each other, and the conversion process of ADC is not affected during the calibration process, ensuring that the digital and analog systems operate independently, and enhancing the tracking ability of the calibration system.

The invention relates to the technical field of image data generation, in particular to an interactive art painting content generation method and system, and the method comprises the following steps: inputting a random sequence into a generative neural network, extracting a high-dimensional feature vector, constructing a covariance matrix, screening an orthogonal basis vector, detecting handwriting pen data, and calculating a physical speed value. And calculating a stability coefficient and a disturbance coefficient by using a nonlinear mapping model, weighting an orthogonal basis vector based on the coefficient to construct a synthetic feature vector, driving a neural network to generate an RGB pixel matrix, and updating canvas layer data. According to the method, a nonlinear mapping mechanism from a physical pen wielding speed to a potential spatial feature weight is established, and a hyperbolic tangent function model is utilized to dynamically adjust the synthesis proportion of texture complexity and edge sharpness according to the pen wielding speed, so that smooth semantic evolution, which conforms to physical intuition, of a pen touch visual style along with a physical motion state is realized; and the artistic expressive force and the dynamic reality sense of the digital painting content are obviously improved.

The present invention discloses a video encoding method based on multi-domain perceptual feature fusion, which belongs to the field of image communication technology. The method comprises the following steps: extracting perceptual features in the spatial domain, time domain, and frequency domain from an input video frame sequence; normalizing the multi-domain perceptual features, and generating a perceptual importance factor for each coding unit through a dynamic fusion weight mechanism; constructing a perceptual distortion evaluation based on the perceptual importance factor, replacing the traditional rate-distortion objective function, and guiding the coding unit bit rate allocation; based on the perceptual importance factor, performing nonlinear mapping using a hyperbolic tangent function, calculating the coding unit-level quantization parameter adjustment amount, and combining the basic quantization parameter to obtain the final quantization parameter, thereby achieving adaptive rate-distortion optimization. This method can accurately identify visually sensitive areas and significantly reduce the bit rate while ensuring subjective visual quality.

The present application belongs to the technical field of power system operation, and relates to a double-sided random power grid scheduling method. By analyzing historical data of wind power output, Gaussian mixture distribution fitting is carried out by using software. For determined power system parameters, a double-sided chance constraint random scheduling model is established. Then, the hyperbolic tangent function is used to analytically approximate the cumulative distribution function of random variables in the reserve demand constraint and the line flow constraint, so as to convert the double-sided chance constraint into a deterministic constraint, and convert the original problem into a convex optimization problem which is easy to solve. Finally, the scheduling model is solved to obtain the scheduling strategy. The present application has the advantage that the double-sided chance constraint containing the risk level and the random variable is converted into a solvable deterministic convex constraint by using the hyperbolic tangent function, which effectively improves the solving efficiency of the model and provides a more reasonable scheduling basis for decision makers. The present application can be applied to active power scheduling of a power system containing large-scale renewable energy grid-connected.

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 application relates to the technical field of natural language processing, and relates to a text feature extraction method based on an NGU language model. The patent is optimized and improved based on a GRU model of a recurrent neural network, a new text feature extraction model, namely an NGU language model, is proposed, a gating unit of the GRU is introduced into a normalization mechanism, a hyperbolic tangent function with a saturation zone is replaced by a layer normalization operation, and a feedforward layer neural network of a Transformer is integrated into an iteration unit to improve semantic expression capability of the model, namely data fitting capability of the model.

The invention provides a buffeting-free sliding mode control method and device with pulse random disturbance, electronic equipment and a readable storage medium. The method comprises the following steps: firstly, establishing a dynamic model of a pulse random time delay system with bounded state time delay and uncertainty; a sliding mode surface is designed for the dynamic model, so that the system meets the expected stability once reaching the sliding mode surface; determining a sliding mode dynamic equation based on a sliding mode surface in combination with the dynamic model; based on the sliding mode equation, obtaining a judgment condition and a sliding mode surface parameter matrix for ensuring the index stability under the dynamic mean square significance of the sliding mode; and introducing a hyperbolic tangent function as continuous smooth approximation of a switching function, and constructing a buffeting-free sliding mode controller by using a sliding mode surface parameter matrix to realize control of a pulse random time delay system. By using the sliding mode control method, the problem that the sliding mode control precision is low due to the fact that an existing sliding mode control method cannot process pulses, environmental noise, time lag and uncertainty at the same time and the influence of external disturbance on the controlled output of the system is large can be solved.

The invention relates to the technical field of motor fault detection, discloses a motor turn-to-turn fault feature observation method based on an improved sliding-mode observer, and aims to solve the technical problem that the fault feature estimation precision is reduced due to the buffeting problem of a traditional sliding-mode observer (SMO). An improved fault characteristic observer is designed by taking a back electromotive force residual error under a two-phase static coordinate system as a fault characteristic quantity, the observer is optimized by adopting a linear superhelix algorithm (STA) and a hyperbolic tangent function (tanh), high-frequency buffeting is effectively inhibited, and the convergence of the observer is proved through a Lyapunov stability theory. According to the method, the counter electromotive force estimation precision can be remarkably improved, reliable input is provided for motor fault detection, and the method is suitable for online monitoring and diagnosis of PMSM stator turn-to-turn short circuit faults.

The invention discloses an under-actuated ship trajectory tracking control method. The method comprises the following steps: constructing a ship model into an under-actuated ship three-degree-of-freedom mathematical model containing specific environment interference; designing a nonlinear state observer by combining an acceleration measurement technology based on the constructed ship model; obtaining a relationship between a position error and a speed by a nonlinear state observer, designing a virtual speed control law, and obtaining a speed error between an expected speed and an actual speed; designing a hyperbolic tangent function-based speed error terminal sliding mode surface and an adaptive technology-based external interference estimated value; calculating a terminal sliding mode output control quantity based on a speed error terminal sliding mode surface and an adaptive interference estimation value in combination with a backstepping method; and a final control resultant force and a control resultant force moment are designed for a terminal sliding mode output control quantity by using feedforward compensation of an acceleration estimated value, so that ship trajectory tracking is realized. According to the invention, efficient and accurate tracking of the under-actuated ship trajectory can be realized.

The invention discloses a construction and implementation method of a hyperbolic tangent fractional order memristor chaotic system. The method comprises the following steps: firstly, designing a fractional order magnetic control memristor model containing a hyperbolic tangent function, and constructing a fractional order memristor chaotic system based on the model; through high-resolution order parameter scanning and in combination with Lyapunov exponent spectrum, bifurcation diagram, phase diagram and complexity analysis, rich dynamic behaviors and high sensitivity of the system under order change are revealed; a difference equation model of the system is obtained through a frequency domain approximation and discretization method, digital modeling is completed on a DSP Builder platform, and hardware description language codes executable by an FPGA are automatically generated; finally, the real-time iterative operation of the system is realized on the FPGA development board, and the physical realizability of the chaotic attractor is verified through the oscilloscope. The invention provides a high-precision and low-power-consumption hardware implementation scheme for the fractional order memristor chaotic system, and is suitable for the information security fields of secret communication, image encryption and the like.

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.