22 results about "Nonlinear perturbations" patented technology

The invention discloses a control system for intelligently detecting the lifting process of a tower crane. The control system comprises a data acquisition module, a self-adaptive frequency spectrum filtering module, an impact retention module, a motion time sequence feature construction module, a linear drift monitoring module, a nonlinear disturbance separation module, a threshold statistical decision module and a lifting process control module. The invention belongs to the field of intelligent control, and particularly relates to a control system for intelligently detecting the lifting process of a tower crane, which adopts a self-adaptive sampling method based on gradient triggering to improve the accuracy of fault detection. The control accuracy of the jacking process is improved by applying an optimized wavelet threshold function; extracting linear dynamic characteristics of a load current linear relation through a linear drift monitoring module; residual difference is constructed in the residual subspace, nonlinear energy indexes and errors are calculated, the method is extremely sensitive to nonlinear disturbance and non-Gaussian noise, and a blind area of linear analysis is reinforced; and the control effect of the tower crane lifting process is improved.

According to the invisible watermark embedding method based on the wavelet domain statistical characteristics, the high-frequency sub-band in the wavelet domain is selected as the embedding area, and the robustness of the watermark to conventional attacks such as compression and noise is improved while invisibility is guaranteed. Based on a self-adaptive embedding weight mechanism of a covariance matrix eigenvalue, the embedding strength of different texture regions can be dynamically adjusted, the robustness is enhanced by a smooth region, and distortion is suppressed by an edge region. Nonlinear disturbance is generated by adopting a deep neural network and chaotic encryption preprocessing is combined, so that the predictability of a linear statistical rule is broken, and the method has a relatively good application prospect.

The invention discloses a method, a device, equipment and a medium for enhancing transient stability of networking type energy storage, and relates to the field of power electronic stability, and the method comprises the steps: carrying out the improvement of an active power control structure of initial networking type energy storage based on power deviation feedback and angular frequency deviation feedback, so as to obtain an improved control structure; determining a feedback compensation coefficient in the improved control structure according to the rated angular frequency of the power grid and the steady-state power angle of the network-building type energy storage before fault ride-through; and determining the transient power angle deviation of the network construction type energy storage during the fault ride-through period based on a nonlinear perturbation theory, and controlling the transient power angle deviation to be zero by using the feedback compensation coefficient and a preset constraint condition so as to enhance the transient stability of the network construction type energy storage. Therefore, the power angle fluctuation and the frequency fluctuation of the network construction type energy storage during the fault ride-through period can be greatly reduced, and the transient stability and the frequency stability of the network construction type energy storage are improved.

The present application belongs to the technical field of power system, and particularly relates to a time-delay power system stability analysis method and system. The method firstly establishes a load frequency control system model including time delay and nonlinear load disturbance, wherein the nonlinear load disturbance is a nonlinear disturbance taking unknown exogenous load disturbance as current and delayed state variable; then an augmented Lyapunov-Krasovskii functional is constructed, and an analysis method based on time-delay dependent matrix free matrix integral inequality and anti-convex combination inequality is adopted to analyze the stability of the load frequency control system, so as to obtain the stability criterion of the load frequency control system. The present application plays an important role in improving the calculation accuracy and time delay upper limit, and is helpful to expand the stable operation area of the power system.

The present invention belongs to the field of control technology, and relates to an event-triggered robust nonlinear model predictive control method for agricultural machinery trajectory tracking. The method comprises: establishing a transverse and longitudinal dynamics model of agricultural machinery and its state space equations, and tracking the operation trajectory of agricultural machinery; constructing an improved nonlinear model predictive control system, the improved nonlinear model predictive control system comprises a nonlinear controller of the agricultural machinery nominal system with a pseudo-Huberl function improved cost function, and solving the control input of the agricultural machinery nominal system; optimizing the solver, and using the reinforcement learning actor-critic algorithm to approximate the uncertainty compensation of the agricultural machinery model; using an adaptive parameter nonlinear disturbance observer to estimate and compensate for the external disturbances suffered by the agricultural machinery; through an event triggering mechanism, judging whether to trigger the optimization solver to optimize the solution according to the error between the real value and the predicted value of the agricultural machinery trajectory tracking, and obtaining the input of the agricultural machinery trajectory tracking controller. The present invention enhances the robustness of the control system and reduces the calculation frequency.

The present invention belongs to the field of medical image processing technology, specifically a semi-supervised medical image segmentation method with attention-guided nonlinear perturbation consistency. The present invention uses a small amount of labeled data and unlabeled data to train a model for medical image segmentation, adopts nonlinear transformation for data enhancement, and constrains it through consistency of output level and feature level; nonlinear transformation realizes contrast change by randomly generating Bezier curves for grayscale mapping; consistency constraint of output level encourages generation of similar prediction labels under different enhancements through cross-pseudo-label supervision; consistency constraint of feature level encourages network learning of robust representation that is invariant to nonlinear changes through multi-scale attention-aware feature alignment. The present invention effectively utilizes unlabeled data, improves generalization through data enhancement, and improves the accuracy of medical image segmentation through information mining of unlabeled data. The present invention is applicable to all grayscale-based medical image segmentation tasks.

According to the dual compensation method for the current measurement error of the permanent magnet synchronous motor and the non-linear error of the inverter, the non-linear disturbance observer and the low-pass filter are organically combined, and the current measurement error can be accurately estimated and compensated; meanwhile, on the basis of integral comparison of the voltage actually acting on the motor and the reference voltage, the invention provides an effective compensation means suitable for voltage errors caused by nonlinearity of the inverter. According to the method, motor rotating speed information and A / B / C three-phase current symbol judgment are not needed in implementation, current periodic fluctuation and insufficient torque output caused by two errors can be simply and efficiently eliminated, accurate following and accurate control of the current and the torque are achieved, the method has the advantages of being simple in algorithm, short in execution time and the like, and the method is suitable for popularization and application. And the stability and the reliability of the motor control system are effectively guaranteed, so that the motor control system can be widely applied to engineering practice.

The invention relates to the technical field of automatic control and the like, and provides a frequency converter under-actuated system input constraint dynamic output feedback control method, which comprises the following steps of: establishing a non-linear dynamic model containing a driving state and an under-actuated state, setting a non-linear disturbance and speed combined observer, and estimating unknown disturbance and speed in real time by depending on position measurement. On this basis, a first coupling signal free of an integral term and a second coupling signal for strengthening swing feedback are provided, a bounded function is utilized to carry out saturation processing on an intermediate control quantity, and an adjustable gain dynamic output feedback law is synthesized by combining an observation result and the coupling signals, so that external disturbance and parameter perturbation can be resisted at the same time; the input constraint is strictly met, a speed sensor is not needed, and the driving positioning precision, the load anti-swing performance and the global asymptotic stability of the system are guaranteed.

This invention discloses a smart parcel locker location selection method based on IF-WSP. It utilizes interval fuzzy numbers to establish a fuzzy evaluation matrix, defines random floating parameters, and uses these parameters to weight and integrate expert opinions. An improved chaotic mapping function based on nonlinear perturbation is employed. The method calculates cumulative and summative location selection schemes based on evaluation standard weights, generates a chaotic threshold using the nonlinear perturbation chaotic mapping function, and uses this threshold to perform multiple synthesis of the cumulative and summative location selection schemes. The average location score is then used for defuzzification to determine the final location result. Compared with existing technologies, this invention uses fuzzy logic to transform expert opinions into mathematical expressions and combines them with weighted aggregation and multiplication, fully considering the satisfaction of different customers. This results in parcel locker locations that are closer to customer needs, improving the performance of the parcel lockers and demonstrating significant social value and market application prospects.

The application proposes a wavelet domain statistical feature-based invisible watermark embedding method, which selects the high-frequency subband in the wavelet domain as the embedding area, ensures invisibility, and improves the robustness of the watermark to conventional attacks such as compression and noise. An adaptive embedding weight mechanism based on the eigenvalues of the covariance matrix can dynamically adjust the embedding strength of different texture regions, enhance the robustness of smooth regions, and suppress distortion in edge regions. A deep neural network is used to generate nonlinear perturbations and combined with chaotic encryption preprocessing to break the predictability of linear statistical rules, which has good application prospects.

An ultrasonic ranging calibration method and apparatus based on a multi-parameter coupled compensation sensing network is disclosed. The method includes: first, constructing an ultrasonic ranging system to accurately acquire and transmit basic time parameters and multi-dimensional perturbation parameters; second, constructing a multi-parameter coupled compensation sensing network for distance calibration, fusing multiple parameters through a nonlinear perturbation injection function to construct an input vector, and using a hierarchical coupling compensation method to achieve step-by-step error correction, outputting a compensation amount or compensation factor based on the basic ranging result to complete distance correction; subsequently, collecting sample data under multiple perturbation parameter combinations and multiple reflection conditions, preprocessing the data, dividing it into training and test sets, and using an error constraint strategy based on the predicted deviation distribution for closed-loop training optimization to improve the model's generalization ability; finally, deploying the trained model to the main control processing unit to achieve real-time dynamic compensation ranging. This invention effectively overcomes the accuracy limitations of traditional ultrasonic ranging technology in complex environmental perturbations and multi-reflection characteristic adaptation scenarios, significantly improving ranging accuracy and scenario adaptability, and promoting the application expansion of ultrasonic ranging technology in complex scenarios such as industry, intelligent robots, and autonomous driving.

The invention discloses a high-precision identification method for dynamic parameters of a long cantilever of a drill jumbo based on layered identification and nonlinear coupling modeling, and belongs to the technical field of engineering machinery and control. The method is based on a multi-body dynamic modeling theory, and is combined with a dynamic parameter identification method, a least square optimization algorithm and a model online identification algorithm to realize high-precision identification of inertial parameters, friction coefficients and nonlinear coupling terms of all joints of the mechanical arm. By establishing a kinetic model containing nonlinear disturbance and proposing a layered identification strategy to cope with different stages of no-load operation, drilling impact and the like, nonlinear identification of impact-deformation coupling is realized, and the robustness and the real-time performance of kinetic parameter identification are improved. The method is suitable for optimization and fault diagnosis of the rock drilling operation control system under complex working conditions.

The present invention discloses a model predictive control method and device for suppressing various nonlinear disturbances. First, a state-space model of the servo system is established, and the constraint conditions of the model and the nonlinear disturbance constraint conditions are analyzed; secondly, through the optimization and improvement of the system model, various nonlinear disturbances can be directly incorporated into the novel predictive control strategy designed in this paper; in order to better handle various nonlinear disturbances of the servo system dynamic model, the constraint conditions are adjusted and transformed into a new cost function, which is more in line with the actual servo system dynamic model compared with the traditional constraint conditions and cost functions; then the control law is designed and the stability is analyzed. The model predictive control (MPC) control method proposed by the present invention has high-precision speed tracking ability and anti-interference ability, has a good compensation effect on the coupling effect of various nonlinear disturbances, and has the characteristics of high precision, fast speed and strong robustness.

The application discloses a multi-source data bias detection and optimization method based on digital twinning, relates to the technical field of digital twinning, and comprises the following steps: constructing a real and twinned space-time matrix, using a vector splicing method to construct a coupling bias vector, screening high-bias physical quantities, regarding the space points corresponding to the high-bias physical quantities as grid nodes, constructing a space grid graph, using a path planning algorithm to define a heuristic function, generating an optimized sensor path, using a linear interpolation method to update non-path points, obtaining an updated real space-time matrix, using a gradient descent method to optimize digital twinning model parameters, and generating updated twinned data. The application simulates multi-scale perturbations by means of a sinusoidal wave superposition method and screens main frequencies by means of an elbow rule, thereby enhancing the sensitivity to nonlinear perturbation responses, and through nonlinear fusion and path optimization, the efficiency of sensor deployment and the accuracy of model parameter optimization are improved.

This invention relates to a precipitation time-downscaling forecasting method based on the smoothed weighted allocation method, belonging to the field of meteorological precipitation forecasting technology. This invention addresses the key issue of refined quantitative precipitation forecasting in meteorological services and disaster prevention and mitigation decision-making. It achieves time-downscaling of precipitation at the hourly scale by sequentially averaging, smoothing, and weighting the model's 3-hour cumulative precipitation forecast using the ASW (Averaged-Smoothen-Weighted) method. During this process, a weighted allocation coefficient for time-downscaling is constructed and applied to the hourly precipitation sequence calculation. This adds a nonlinear perturbation term to the temporal variation of precipitation, making the downscaling process closer to the actual physical changes, while ensuring that the model's 3-hour cumulative precipitation remains unchanged before and after downscaling. This method can achieve hourly precipitation forecasts over 120 hours, improving the time resolution of model precipitation forecasts and is suitable for regional or single-station refined precipitation forecasting.

The invention provides a Gaussian splash model reversible watermark generation method and device, and relates to the technical field of watermark algorithms, and the method comprises the steps: selecting a target seal model; selecting a reference Gaussian primitive from the Gaussian splash model to be protected, and determining a reference position based on the covariance of the reference Gaussian primitive; selecting a plurality of nearest neighbor Gaussian primitives in a neighborhood by taking the reference position as a center to construct a local primitive set; performing feature decoupling on the local primitive set to obtain a plurality of geometric appearance features, and adding nonlinear perturbation to the plurality of geometric appearance features to obtain perturbation geometric appearance features; and performing transformation processing on the target seal model by using the disturbance geometric appearance features, and embedding the transformed target seal model into the to-be-protected Gaussian splash model to obtain a Gaussian splash model carrying the dominant watermark seal. By adopting the reversible watermark generation method and device of the Gaussian splash model, the problems that the precision of the 3DGS model cannot be recovered after the watermark is removed and the watermark generation complexity is high are solved.

The invention provides a parallel rotating mirror interferometer system control method and system, and the method comprises the steps: analyzing the relation between the angular speed of a voice coil motor and the optical path difference speed, and building a mathematical model of a parallel rotating mirror interferometer according to the relation; and a CMAC-PID composite control strategy is adopted to control the parallel rotating mirror interferometer so as to suppress nonlinear factor disturbance of the mathematical model. The technical problems that the spectral signal-to-noise ratio obtained through inversion is influenced by the stability of the OPD speed, and the control precision is low and the control performance is poor due to time-varying interference are solved.

The invention discloses a logarithmic terminal sliding mode control method, device and equipment of a nonlinear system, and relates to the technical field of sliding mode control. Aiming at the control problem of the non-linear second-order system, the logarithmic terminal sliding mode surface is provided by combining the terminal sliding mode surface and a natural logarithmic function, and the logarithmic terminal sliding mode surface accelerates the convergence rate of the state of the non-linear second-order system when the state is far away from an equilibrium point on the basis of the terminal sliding mode surface. Meanwhile, in consideration of unknown matching nonlinear disturbance which is often contained in a nonlinear second-order system and can influence the stability and the control precision of the system, the sliding mode disturbance observer is designed based on the proposed logarithmic terminal sliding mode surface, rapid convergence of disturbance estimation errors is achieved, and design of a follow-up controller is facilitated. And finally, a stable first-order logarithmic terminal sliding mode controller is designed based on the Lyapunov stability theory, the nonlinear second-order system state is globally and rapidly converged to a balance point, and the convergence rate and the control precision are improved.

The invention provides an incomplete information constraint uncertain game strategy optimization method and system, and the method comprises the steps: building a nonlinear uncertain differential game process model according to the incomplete information characteristics of a nonlinear uncertain game dynamic process in a strong confrontation scene, and enabling the strategy amplitudes and game states of two parties to be constrained; taking an opponent game strategy and an unknown uncertain item as a disturbance item, introducing a non-quadratic form energy function, a control barrier function and a disturbance function upper bound on the basis of describing a nonlinear disturbance system of a nonlinear uncertain game dynamic process, and constructing a performance index function; converting a safety robust game problem of a nonlinear uncertain dynamic game process into a nonlinear nominal system constraint robust optimization problem; and introducing an event-triggered security robust reinforcement learning technology, and completing approximate solution of an HJB equation by evaluating an online approximation optimal performance index function of a neural network to obtain an own optimal game strategy. According to the method, the uncertain game strategy can be optimized.

The present invention discloses an intelligent detection tower crane lifting process control system, comprising a data acquisition module, an adaptive spectrum filtering module, an impact retention module, a motion timing feature construction module, a linear drift monitoring module, a nonlinear disturbance separation module, a threshold statistical decision module, and a lifting process control module. The present invention belongs to the field of intelligent control, and specifically refers to an intelligent detection tower crane lifting process control system. This solution adopts an adaptive sampling method based on gradient triggering to improve the accuracy of fault detection; applies an optimized wavelet threshold function to improve the accuracy of lifting process control; extracts the linear dynamic characteristics of the linear relationship of load current through a linear drift monitoring module; constructs residual differences in the residual subspace, calculates nonlinear energy indicators and errors, is extremely sensitive to nonlinear disturbances and non-Gaussian noise, and strengthens the blind spots of linear analysis; thereby improving the control effect of the tower crane lifting process.

The invention discloses a model-free predictive power control method and system for a three-phase grid-connected inverter, which belongs to the field of power electronic control. Firstly, a super-local model is constructed to replace the original inverter model, so as to reduce the dependence on the system model. Secondly, a quadratic linear extended state observer is designed, and a quadratic expansion estimation is performed on the nonlinear disturbance residual through an integral negative feedback link, so as to estimate the lumped disturbance of the super-local model, thereby improving the anti-disturbance capability of the observer. Meanwhile, a Kalman filter is introduced into the integral negative feedback link, and the filter factor is automatically adjusted according to the dynamic characteristics of the system, so as to avoid the problems of current distortion and response delay caused by excessive filtering, so as to make it more effective in processing complex nonlinear disturbances. Finally, a deadbeat cost function is designed to ensure the high dynamics of the system, so as to solve the problem that it is difficult to establish an accurate physical model due to the nonlinear disturbance caused by parameter mismatch of the three-phase grid-connected inverter in actual working condition operation.

The invention discloses a double-link coding event triggered nonlinear multi-agent system control method and system, and belongs to the crossing field of automatic control and network security. According to the method, a double-link coding event triggering module is designed, a self-adaptive threshold triggering mechanism and short code word compression are adopted, 16-bit signals are compressed into 3-bit signals, and sensitive information is hidden; the performance boundary is dynamically adjusted through the self-adaptive preset performance strategy module, and the limitation of a traditional method on an initial error is broken through; and in combination with an estimation compensation module, unknown disturbance and virtual control input discontinuity are processed by using a nonlinear disturbance observer and a high-order filter. According to the method and the system, the communication efficiency and the safety can be improved under limited communication resources, the steady-state precision and the global stability of the system under any initial condition and external interference are ensured, and the method and the system are suitable for unmanned vehicle formation, unmanned aerial vehicle cooperation and other scenes.