103 results about "Non linear model" patented technology

The invention relates to the technical field of non-electrical variable control, and discloses an industrial water chiller temperature intelligent adjusting system, which comprises a refrigeration circulation loop and a control unit, the control unit calculates a steady state control component based on the water outlet temperature deviation, performs differential processing on the refrigerant pressure to extract the gradient, and outputs the gradient. Generating a transient compensation component when the gradient exceeds a dynamic noise threshold; according to the method, the problem of thermal lag is solved by utilizing the pressure wave transmission speed advantage, aggressive response is prevented from triggering low-pressure shutdown through a safety margin constraint mechanism, the pressure safety margin is calculated in real time, a gain coefficient is determined according to a nonlinear model, and a final driving instruction is generated. And the dynamic balance of the control response speed and the system physical security boundary is realized.

The invention provides an underwater-water surface unmanned system cooperative control method based on NMPC, belongs to the technical field of robot control, and particularly provides an underwater terrain prediction method based on sonar information feedback by using multi-beam sonar data, and obtains underwater terrain coordinate data by fusing a robot state predicted by a non-linear model in NMPC. And according to the predicted underwater terrain information, an underwater terrain following control problem is converted into an optimization problem with constraints by using NMPC, and terrain following control of the underwater robot can be realized by solving the optimization problem. On the basis, a task-triggered underwater-water surface unmanned system cooperative control strategy is constructed, and the tracking of the underwater robot by the water surface unmanned ship is realized. And finally, the cooperative control problem of the underwater-water surface unmanned system for unknown sea area exploration is successfully solved.

The invention is suitable for the technical field of viscosity monitoring and control, and provides a viscosity monitoring and control system for the blockage risk of a cyclized rubber solution conveying pipeline, the viscosity monitoring and control system comprises a tank body for storing a cyclized rubber solution, a hydraulic pump and a conveying pipeline, a liquid inlet of the hydraulic pump is communicated with the tank body, and a liquid outlet of the hydraulic pump is communicated with the conveying pipeline; a stirring device for stirring the cyclized rubber solution is arranged in the tank body, and the flow channel state evaluation module is used for constructing a flow channel state evaluation model according to the cross sectional area of the conveying pipeline, the density of residual solidified colloid on the inner wall of the conveying pipeline and the sealing performance of a connector of the conveying pipeline and outputting a flow channel state coefficient. According to the method, the pipeline blockage risk degree can be dynamically evaluated in real time, the influences of different inducements such as hydraulic pump load abnormity, pipeline structure degradation and solution fluidity reduction are accurately distinguished, and quantitative output of the risk level is achieved through the nonlinear model.

The invention belongs to the field of wind power, and discloses a floating wind turbine generator thrust constraint robust adaptive pitch control method, which comprises the following steps: establishing a floating wind turbine generator nonlinear model considering coupling between rotor rotation dynamics and platform pitching motion; setting a control target based on comprehensive consideration of power adjustment, platform stability and limit load constraint; designing a self-adaptive propeller pitch control method based on a fast self-adaptive law; and designing a thrust envelope protection system based on thrust limit detection and a self-adaptive thrust avoidance strategy, and integrating the thrust envelope protection system into the self-adaptive pitch control method, so that the wind turbine generator can operate within an allowable thrust range. The self-adaptive propeller pitch control method can achieve efficient power adjustment and platform pitching motion suppression at the same time, is superior to a traditional method in the aspects of transient response and robustness, and is particularly suitable for the severe marine environment.

A method includes determining a portion of a flight path of an aerial vehicle. The method also includes determining an attribute value representing an operating condition expected to be experienced by the aerial vehicle at the portion of the flight path. The method additionally includes determining, based on the attribute value and using a non-linear model, a power value representing an amount of power expected to be consumed by the aerial vehicle in connection with the portion of the flight path. The method further includes determining, based on the power value, an energy value representing an amount of energy expected to be consumed by the aerial vehicle in connection with the portion of the flight path. The method yet further includes determining the flight path based on the energy value.

The invention discloses a cross arm and insulator installation robot motor control method based on a T-S fuzzy model, and the method comprises the following steps: building a permanent magnet synchronous motor nonlinear model according to electromagnetism and motor dynamics; based on a sector nonlinear method, establishing a permanent magnet synchronous motor T-S fuzzy model; designing an observer to obtain a load torque estimated value; designing an L-infinity robust controller to ensure that the angular velocity of the motor can track a reference instruction; and an anti-control gain matrix solving criterion is formulated, and it is ensured that the system meets performance indexes. According to the method, the nonlinear control problem of the permanent magnet synchronous motor system is effectively solved, the influence of continuous interference signals on the system can be effectively suppressed, and the robustness of the system is enhanced.

The invention provides an anti-interference control method for the concentration of a main reactant in a continuous stirring reaction kettle process, belongs to the technical field of chemical process control, and solves the problem that in the chemical process of producing cyclopentanol by catalyzing electrophilic water with cyclopentadienoic acid, the concentration of the main reactant is not influenced. The technical problem that the concentration of a main reactant is difficult to track a set value without steady-state errors under the conditions of fluctuation of feeding concentration, uncertainty and external disturbance of the continuous stirring reaction kettle is solved. According to the technical scheme, the method comprises the steps of constructing a model pre-estimation compensator and an anti-interference control structure, designing a four-dimensional decision model, carrying out parameter collaborative optimization by adopting a multi-target genetic optimization algorithm, and carrying out optimal solution selection based on a TOPSIS method. Under the condition of feed concentration fluctuation, the dynamic response speed and the anti-interference capability of the system can be remarkably improved, and faster adjustment time, smaller overshoot and stronger robustness can be realized in linear and nonlinear models.

The application provides a photovoltaic power station photovoltaic power prediction method and system. Among them, a cloud layer movement time sequence library is constructed based on historical cloud charts, and a nonlinear model of cloud speed and output attenuation is established. The light sensor array monitors the cloud layer thickness and aerosol density in real time, combines the model to calculate the shadow area light intensity attenuation gradient, and predicts the remaining time of the cloud group reaching the core area. According to the remaining time, the power prediction confidence interval is divided, the satellite data is input into the multi-scale meteorological fusion architecture, and the meteorological feature extraction path of the attention mechanism is adjusted based on the cloud density. The ground reflectivity correction value calculated by fusing the light sensor scattering data is used to generate a short-term power prediction sequence of the sudden cloud layer scene. The sequence is input into the energy management system, combined with the reactive power compensation parameters of the grid-connected point voltage deviation and the grid rules, and the dual-objective scheduling instructions of active and reactive power are output. The technical scheme provided by the application improves the cooperative scheduling accuracy of the photovoltaic power station under the sudden change of the cloud layer.

The invention discloses a soybean moisture content online detection system and method based on capacitance sensing, and relates to the field of agricultural machinery intelligent detection, and the system comprises a sampling mechanism, a control unit and a detection unit; the sampling mechanism is arranged on the outer side of a grain conveying channel of the soybean combine harvester and used for collecting soybeans in the grain conveying channel; the detection unit is arranged in the sampling mechanism and is used for detecting the weight, temperature and dielectric signals of the soybeans; the control unit is connected with the detection unit and the sampling mechanism, obtains a dielectric signal of the soybean and the temperature of the soybean when the weight of the soybean reaches a preset value, converts the dielectric signal of the soybean into a voltage signal, and controls the temperature of the soybean on the basis of the temperature of the soybean and the voltage signal; and calculating the moisture content of the soybeans by adopting a built-in moisture content-breakage rate nonlinear model. The soybean crushing rate is reduced, and the detection efficiency is improved.

The present application relates to the field of intelligent medical treatment, in particular to a tumor treatment dosing regimen Pareto optimization method based on forward-backward stochastic differential equation. The present application unifies the terminal tumor load, dosing cost and treatment risk into the same stochastic control framework, can establish the Pareto optimality condition corresponding to the nonlinear model, and further converts into the implementable closed-loop state feedback control law in the LQ case. Through the combination with the numerical example and the Pareto frontier analysis, an implementable, interpretable and scalable technical path is provided for the multi-objective individualized treatment regimen design, which can solve the problem that the existing technology is difficult to uniformly process the terminal therapeutic effect, dosing consumption and cumulative risk, and difficult to obtain the implementable closed-loop feedback strategy under the forward-backward stochastic control framework.

A vehicle includes a system and method of modeling and controlling tractive effort of a wheel of the vehicle. The system includes an observer, a predictive controller, and an online solver. The observer receives dynamic model parameters of the wheel and determines an estimate of a wheel speed and an uncertainty of the wheel speed using a nonlinear model of the wheel. The predictive controller determines an average gain and a differential gain from the estimate of the wheel speed and the uncertainty of the wheel speed. The online solver calculates a motor torque and a wheel brake torque for increasing tractive effort of the wheel on a road based on the average gain and the differential gain. The motor torque and the wheel brake torque are applied on the vehicle.

The invention discloses a distributed control method with unknown saturation hysteresis input, and relates to the technical field of distributed control systems, and the method comprises the following steps: S1, training a meta-learning model through a meta-learning algorithm, learning parameters and structures of a dynamic adjustment robust controller, and forming an offline meta-training stage; s2, real-time system feedback data are received, controller parameters are adjusted through the meta learning model, nonlinear characteristics such as hysteresis and saturation are dynamically compensated, and an online adaptation stage is formed. The parameters of the controller are adjusted on line through the meta-learning model, the nonlinear influence caused by unknown saturation hysteresis can be dynamically compensated, and an accurate nonlinear model is not needed. And in combination with Lyapunov stability analysis and a parameter constraint mechanism, the stability of a closed-loop system in transient and steady-state processes is ensured, and system oscillation caused by parameter adjustment is avoided. And the online adaptation stage can quickly adapt to a new nonlinear scene, and the response speed is improved.

A method includes determining a portion of a flight path of an aerial vehicle. The method also includes determining an attribute value representing an operating condition expected to be experienced by the aerial vehicle at the portion of the flight path. The method additionally includes determining, based on the attribute value and using a non-linear model, a power value representing an amount of power expected to be consumed by the aerial vehicle in connection with the portion of the flight path. The method further includes determining, based on the power value, an energy value representing an amount of energy expected to be consumed by the aerial vehicle in connection with the portion of the flight path. The method yet further includes determining the flight path based on the energy value.

The invention relates to the technical field of communication transmission, and provides an equivalent simulation method and device for transmission performance evaluation of an optical fiber communication system, and the method comprises the steps: generating a signal power density spectrum of each span according to a link parameter; calculating a nonlinear noise power density spectrum according to the link parameters and the signal power density spectrum of each span; and taking the signal power density spectrum as an input parameter of the equivalent simulation model, and calculating a nonlinear damage index at the tail end of the optical transmission system to obtain transmission performance evaluation. A simulated signal power density spectrum is used for replacing a tested signal power density spectrum, the nonlinear damage simulation precision is still kept under the condition that model parameter dependence is reduced, and a nonlinear model is more flexibly applied to various scenes. According to the calculation method, the algorithm is optimized and upgraded from the two aspects of operation efficiency and input parameter dependency, the problems that a non-linear noise algorithm is low in operation speed and input parameters are difficult to obtain are solved, and the algorithm implementation complexity is reduced while the algorithm simulation precision is guaranteed.

The invention relates to the technical field of biochemical wastewater treatment and automatic control, in particular to a comprehensive utilization and treatment system for dioscorea zingiberensis saponin wastewater. The data acquisition module comprises a data acquisition module, a prediction module, a quantification module, a risk hedging module and a control execution module; the system estimates key enzyme activity by adopting a non-linear model by collecting a water inlet fingerprint vector and a reactor state; the core of the method is that a system safety distance is determined according to enzyme activity and flora health degree, and control weights of three targets of collapse risk, effluent compliance and resource recovery are dynamically adjusted according to the system safety distance; when the safe distance changes, the system executes compound control through a multi-objective optimization algorithm; according to the method, prospective early warning of the core biochemical state is realized, and the defect of response lag of a traditional method is overcome.

This invention provides a fault detection method, system, device, and storage medium for pneumatic control valves, belonging to the field of industrial process fault detection. The method includes: introducing a nonlinear modeling approach based on Gaussian process regression (GPR) into the fast layer to construct the flow coefficient C. V A high-precision nonlinear model is used, whose residual statistics can sensitively capture transient anomalies in control valve performance that deviate from expectations. In the slow layer, Activity-KSFA, a kernel-based slow feature analysis, is employed to effectively extract slowly varying features during system degradation, and T² statistics are used for slow anomaly detection. Finally, a dual-threshold and continuous decision mechanism is combined to suppress false alarms while maintaining high sensitivity. Simulation results on the DAMADICS platform show that C... V While achieving zero false alarms, the residual maintains a detection rate of over 98% for most typical faults, complementing the T² statistic and significantly enhancing the adaptability of this invention to different fault modes.

The invention provides a camera imaging model calibration method and system. The method comprises the following steps: constructing a nonlinear imaging model of a target camera; collecting a calibration image based on a chessboard target, and extracting a sampling point coordinate on the calibration image; and solving the calibration parameters of the nonlinear imaging model by using a nonlinear minimum mean square optimization algorithm so as to complete calibration of the camera imaging model. Thus, the nonlinear imaging model of the camera is firstly established, the calibration parameters of the nonlinear model are solved through the LM nonlinear minimum mean square optimization algorithm, the calculation precision of the model parameters is remarkably improved, a good practical effect is achieved, and the technical problem that the calibration result error of an existing camera imaging model is large is solved.

This invention discloses a method and system for determining vibration-induced cavitation in micro-gap insulating oil, relating to the field of power equipment condition monitoring technology. First, a micro-gap fluid pressure analysis model under vibration is established. By considering a nonlinear model with multi-field coupling, the fluid pressure in the micro-gap is obtained. Then, to analyze the cavitation pressure threshold of bubble nuclei, a multi-parameter coupled analytical model incorporating dynamic gas-liquid balance correction is established to obtain the cavitation pressure threshold. Finally, a dynamic cavitation determination and critical state early warning model for insulating oil is established to obtain the cavitation risk factor and cavitation determination results. The method proposed in this invention considers the influence of multiple dynamic factors, has good dynamic adaptability, and the introduction of a multi-field coupled nonlinear model improves the accuracy of cavitation determination, providing a new approach for micro-gap cavitation research.

The invention discloses a control system and method for synchronous coupling of a robot motion state and an acousto-optic warning time domain, relates to a man-machine interaction technology, and provides a scheme for solving the problems of motion state and acousto-optic separation and the like in the prior art. When the host receives a moving or grabbing task, the multi-mode synchronous planner generates a mechanical arm joint space trajectory, and meanwhile real-time kinematics feature vectors of the end effector in a Cartesian space are calculated in parallel; converting the physical motion parameters into target warning efficiency parameters according to a preset nonlinear model, and sending the target warning efficiency parameters to the intelligent warning terminal; the intelligent warning terminal directly sends real-time lighting effect data to the PID and aging compensation controller; sending the state switching instruction to a stack type finite-state machine for logic processing; and a hardware feedback signal is combined to form closed-loop control, and finally the LED array and the buzzer are driven to send out an acousto-optic signal which is strictly synchronous with the action of the robot. The device has the advantages that the warning lamp changes along with the speed of the mechanical arm, and the frequency of the buzzer changes suddenly along with acceleration.

The invention discloses a composite network attack train control method, device and equipment, a medium and a product. The method comprises the following steps: acquiring a first running speed and first channel communication data of a train; based on the first channel communication data, judging whether a DoS attack aiming at the transmission of the first set point occurs in the train or not, and if so, compensating the first set point to obtain a second set point; a first traction control instruction is generated based on the second set point and the first running speed, a second running speed of the train at the next moment is obtained through prediction in combination with the discrete nonlinear model, then data reconstruction is conducted on the second running speed to obtain a third running speed, and whether the FD I attack aiming at transmission of the second running speed occurs or not is judged according to the third running speed; if yes, taking the speed as a fourth operation speed after compensation of the FD I attack until a preset iteration termination condition is met, and obtaining a target operation speed; and controlling the train based on the target running speed. The control precision of the train under the composite network attack can be improved.

A new energy automobile EHB system hydraulic pressure control method based on a hybrid optimization algorithm comprises the steps that a nonlinear model of an EHB system is built, and then a permanent magnet synchronous motor model, a transmission mechanism model and a hydraulic cylinder model are built; performing parameter identification on the motor model and the hydraulic cylinder model by adopting a nonlinear hybrid eagle-Harris optimization algorithm to obtain model parameters; constructing an improved strong tracking unscented Kalman filter; an improved multi-strategy sparrow search algorithm is introduced to optimize sampling point distribution state control parameters in the improved strong tracking unscented Kalman filter, and a hydraulic pressure estimated value is obtained; and setting reaching law parameters of the super-spiral sliding mode controller by adopting an improved whale group optimization algorithm so as to obtain an improved super-spiral sliding mode controller, and controlling the hydraulic pressure of the EHB system through the improved super-spiral sliding mode controller. According to the invention, the problems of insufficient control precision, slow response speed, poor robustness and poor working condition adaptability in the prior art can be solved.

The invention discloses a power frequency voltage measuring method and device and a computer program product, and the method comprises the steps: S1, collecting an analog voltage signal of a measured power frequency power line through a non-contact induction module; s2, amplifying the collected analog voltage signal, and converting the analog voltage signal into a digital voltage signal; s3, filtering the digital voltage signal to extract a power frequency fundamental component, and removing signal noise and non-target signal components; and S4, performing nonlinear fitting on the filtered signal through a pre-constructed nonlinear model to complete amplitude correction, and obtaining a power frequency voltage measurement result. Potential safety hazards of traditional contact type measurement can be avoided, hardware cost is reduced, circuit coupling interference is avoided, filtering linear delay is guaranteed to be free of phase distortion, meanwhile, error propagation is avoided through nonlinear correction, measurement precision and self-checking capacity are improved, and the method is adaptive to different measurement systems and is suitable for power utilization inspection, equipment protection and troubleshooting scenes.

The invention relates to the technical field of control systems, and particularly discloses a dredger mud concentration control system based on an adaptive algorithm, comprising: a data acquisition module for acquiring internal working condition data and external dynamic environment data of dredging operation in real time; and the data processing module is in communication connection with the data acquisition module and is used for performing space-time alignment processing on the acquired data and calculating an external environment correction factor based on a nonlinear model. According to the dredger mud concentration control system, dynamic optimization and risk accurate management of dredger mud concentration control are achieved by integrating the data acquisition module, the space-time alignment processing module, the external environment correction factor calculation module and the self-adaptive control module; the system can dynamically adjust a risk threshold and execution parameters according to environmental parameters such as real-time water flow and tide, and the accuracy and timeliness of pipe blockage risk identification are remarkably improved; in addition, the system suppresses measurement abrupt change caused by transverse movement of the ship body through motion decoupling and inertia filtering, and the system stability is enhanced.

The application discloses a method for identifying cancer collaborative driving pathways based on a weighted mutation matrix, and comprises the following steps: 1) setting a nonlinear CMDP model; 2) setting an MPGA: 2.1) chromosome coding and initial population; 2.2) setting a fitness function; 2.3) selecting an operator; 2.4) a mutation operator; and 2.5) an MPGA algorithm specific process. The method can identify more biological information, has strong expansibility and practicability, and can identify genes enriched on multiple important driving pathways.

The invention provides a mode hopping checking and processing method for a wavelength scanning laser for current tuning, and belongs to the technical field of semiconductor laser modulation. According to the method, on the basis that a data set of current and output wavelength is obtained according to a current-wavelength nonlinear model established in an earlier stage, the current change trend of each pin of the laser is in a sawtooth peak shape by controlling the current change gradient of a left reflector, a right reflector and a phase pin of the laser; and further checking the output spectrum by using an optical fiber etalon and a dynamic optical fiber grating array, identifying a current combination in a current data set corresponding to a mode hopping region, removing, changing a spectrum interval, and carrying out calibration and checking again until the mode hopping phenomenon of the output spectrum is completely eliminated. The mode hopping phenomenon of the output spectrum of the current-tuned wavelength scanning laser is eliminated, the working stability and reliability of the laser are improved, and the continuity of the output spectrum of the laser and the system stability are remarkably improved.

The present application relates to intra-predicting a chroma block of a video picture into a bitstream of encoded video picture data. A first predictor of the chroma block is derived according to a first non-linear model based mode. If deriving a chroma predictor according to a linear model based mode is disabled, a second predictor of the chroma block is derived according to a second non-linear model based mode, and a final predictor of the chroma block is determined by blending the first predictor and the second predictor.

An illumination source includes a droplet generator, a laser, a detector, and a controller. The droplet generator produces a stream of droplets of target material directed to an interaction region. The laser irradiates the droplets at the interaction region using a beam of pulses. The irradiated droplets generate output illumination of the illumination source. The detector measures an aspect of an interaction between a pulse from the beam and a droplet from the stream. Controller includes circuitry and determines a pulse timing adjustment that is nonlinearly dependent on the measured aspect. The controller also controls a subsequent laser pulse of the beam based on the pulse timing adjustment.

The embodiment of the present specification provides a kind of control method, device, system, equipment and storage medium of production system, the method is applied to predictive control system, the predictive control system includes linear model and nonlinear model, the method comprises: at each sampling time, the following steps are iteratively executed until the target function value that meets the preset condition is solved: determine input sequence;The first output sequence that the linear model is predicted to the input sequence determined this time and the second output sequence that the nonlinear model is predicted to the input sequence determined this time are fused, and then substituted into the preset target function to obtain the target function value by calculation;Using the input sequence corresponding to the target function value that meets the preset condition solved, control instruction is generated to control the production system.

The invention relates to the technical field of material determination and analysis, in particular to an EVA and POE composite material irradiation quality evaluation method based on near-infrared hyperspectrum. A multi-index comprehensive evaluation system for microscopic chemical characteristics and macroscopic spatial uniformity is constructed aiming at the characteristic that the quality of an irradiation modified material is doubly dominated by a microscopic cross-linking / degradation competition mechanism and macroscopic spatial heterogeneity. The method is characterized in that a spectrum decoupling technology is used for separating competitive reaction signals, and micro chemical evolution is quantitatively analyzed; the spatial heterogeneity is converted into a statistical index, and the technical blank of macroscopic dose distribution quantification is filled up; and deep fusion of'spectrum-space 'two-dimensional features is realized through a nonlinear model. Through cooperative complementation of the multi-dimensional information, multi-dimensional and lossless quantitative evaluation of the quality of the EVA / POE composite material after irradiation is realized, and the problem that a single-dimensional index cannot accurately reflect the real irradiation quality of the material is effectively solved.