44 results about "Criterion function" patented technology

The invention relates to the technical field of equipment calibration, in particular to a multi-channel pressure sensor calibration method and system, and the method comprises the steps: constructing a flexible pressure response platform, carrying out the channel calibration according to the flexible pressure response platform, and carrying out the preliminary deviation modeling; generating a nonlinear response correction factor according to a result output by the preliminary deviation modeling, and performing local regression adjustment on the channel according to the nonlinear response correction factor; in response to completion of local regression adjustment of each channel, performing unified response surface fusion processing; and in response to completion of unified response surface fusion processing, constructing a stability comprehensive criterion function, and generating a calibration result according to the stability comprehensive criterion function. According to the method, the limitation that a traditional method depends on a linear model and static single-point calibration is overcome, and the problem of error accumulation caused by inter-channel interaction interference and delay response is solved.

The invention relates to the technical field of network security, and discloses a program-level code similarity analysis method and device based on semantic slicing, and the method comprises the steps: constructing a program-level target function call graph based on a target source code; matching the target function call graph with a standard function call graph to obtain a plurality of isomorphic sub-graphs; performing semantic slicing on each function node in the first sub-graph and the second sub-graph to obtain a first slicing result of the first sub-graph and a second slicing result of the second sub-graph; and evaluating the slice similarity between each function in the first slice result and each function in the second slice result, and determining the similarity of the target source code according to the slice similarity. According to the method, the user-defined function call graph for eliminating system function interference is constructed, an isomorphic sub-graph matching algorithm is combined, multi-dimensional features are comprehensively considered, the accuracy of similarity calculation is improved, effective support is provided for practical application scenes such as code reconstruction and security audit, and the guarantee of code quality and security is improved.

The invention belongs to the field of aircraft fault diagnosis and maintenance guarantee, and particularly relates to a flight parameter diagnosis rule dynamic compiling method. According to the method, codes required by the criterion, the blank-leaving criterion formula and the associated parameters are designed in advance according to the criterion function, the criterion formula and the associated parameters are filled after the criterion formula is analyzed, the to-be-compiled criterion file is generated, and finally the to-be-compiled file is compiled into the executable program capable of being linked to the main program through the compiling tool chain. And thus, the criterion is dynamically compiled into an executable program. The time for converting the criterion into the executable program is greatly shortened, the software development process is guaranteed to a great extent, and the guarantee efficiency is greatly improved.

The invention discloses a power prediction method for a wind power generation system based on a stacked sparse auto-encoder network Hammerstein model, and aims to solve the problems that only nonlinear mapping is modeled and dynamic characteristics of the system are neglected and parameter coupling of the Hammerstein model leads to complex identification in an existing method, the Hammerstein model is constructed, an ARMAX model is utilized to describe a dynamic linear module, and the dynamic linear module is used to predict the power of the wind power generation system based on the stacked sparse auto-encoder network Hammerstein model. A static nonlinear module is described by stacking the sparse auto-encoder network; designing a zero-mean Gaussian signal input proxy model, realizing series module decoupling based on covariance function characteristics, and eliminating parameter coupling; a self-adaptive multi-strategy grey wolf optimization algorithm is adopted to determine the number of neurons in a network hidden layer, training is performed in combination with a sparse criterion function, and the feature extraction capability is improved. According to the method, synchronous capture of static nonlinear and dynamic linear characteristics is realized, the calculation complexity is reduced, the model identification precision, prediction precision and robustness are improved, and the method is suitable for accurate prediction of the power of a wind power system.

The invention discloses an elastic prediction control method for a converter, and the method comprises the steps: constructing an output current increment prediction model which comprises an inherent dynamic item reflecting the mapping relation between the historical data of a converter system and the output current increment, and an attack item reflecting external abnormality; constructing a criterion function, calculating the gradient of the criterion function about the coefficient matrix, setting the gradient to be zero, and obtaining the estimation of the coefficient matrix at the current moment; taking the error between the reference current of the next period and the actual output current of the current period as the target output of an output current increment prediction model, rewriting the output current increment prediction model, and obtaining the control law of the voltage increment; and based on the control law of the voltage increment, substituting the coefficient matrix estimation at the current moment to obtain a voltage control increment, and selecting the switching state of the converter based on the voltage control increment. According to the method, converter prediction control without parameter dependence can be realized, false data attacks are resisted, the switching frequency is reduced, and the system robustness is improved.

The present invention belongs to the field of aircraft fault diagnosis and maintenance, and specifically relates to a method for dynamically compiling flight parameter diagnostic rules. The present invention pre-designs the code required for the criterion according to the criterion function, leaving blanks for the criterion formula and associated parameters. After the criterion formula is parsed, the criterion formula and associated parameters are filled in, and a criterion file to be compiled is generated. Finally, the criterion file to be compiled is compiled into an executable program that can be linked to the main program through a compilation tool chain, thereby realizing the dynamic compilation of the criterion into an executable program. This greatly shortens the time it takes to convert the criterion into an executable program, greatly speeds up the guarantee software development process, and significantly improves guarantee efficiency.

The invention discloses a four-rotor aircraft data driving control method breaking through bandwidth constraint under hostile attack. The method specifically comprises the following steps: establishing a kinetic model of a four-rotor aircraft; converting the obtained kinetic model into an equivalent dynamic linearization equation by using a dynamic linearization method; designing a criterion function, and designing a data driving control method of the four-rotor aircraft; an event triggering mechanism is introduced, denial of service attack is considered, and then the final four-rotor aircraft safety event triggering data driving control method is obtained through arrangement of the obtained control method. According to the method, model-free adaptive control is applied to attitude control of the four-rotor aircraft, the advantages of PID are combined, malicious denial of service attacks are considered, an event triggering mechanism is introduced, the good flight quality of the aircraft is guaranteed, system bandwidth resources can be saved, and the working time of the aircraft is prolonged.

The embodiment of the invention provides an alternating current servo system control method, system and device based on an internal model principle and a medium, and belongs to the technical field of motor control. The method comprises the following steps: performing mechanism analysis, system identification and model order reduction processing on the alternating current servo system to obtain a four-order model corresponding to the alternating current servo system; on the basis of the fourth-order model, designing the corresponding optimal state feedback of the AC servo system under a linear quadratic regulator; determining a state observer of the inner ring object model, and determining an optimal observer parameter by using a first LQ criterion function according to the state observer; determining a first state space expression corresponding to the AC servo system according to the optimal state feedback and the optimal observer parameter; and determining a target control parameter corresponding to an optimal controller of the AC servo system according to the first state space expression, so that the AC servo system realizes optimal control according to the target control parameter.

The invention relates to the technical field of inverters, and discloses a VSG-based inverter parameter identification method and device, equipment and a storage medium, and the method comprises the steps: generating an initial population through an initial search space and a preset number Q of individuals, the initial search space reflecting the value range of model parameters of a VSG-based inverter model, and the value range of the model parameters of the VSG-based inverter model; the initial population comprises Q initial individuals, and each individual corresponds to a group of candidate model parameters; performing iterative updating on the model parameters through evolution operations such as variation, crossover and out-of-group competition, and finally determining target fitness according to a predetermined real response value of the inverter, an estimated response value of the inverter under the candidate model parameters in the target population and a preset criterion function. According to the method, the optimal individual corresponding to the optimal identification result of the model parameters is evaluated, the parameter identification accuracy is improved, and the problems of modeling and simulation of a high-proportion new energy power system can be solved while the power grid voltage support capability is improved.

The invention relates to the technical field of inverters, and discloses an inverter parameter identification method based on multi-point crossover and a related device, and the method comprises the steps: determining a first population corresponding to a model parameter of an inverter model under a current iteration number G; performing evolution processing on the first population by using a preset multi-point crossover rule to obtain a target population; determining target fitness according to a predetermined real response value of the inverter, an estimated response value of the inverter under the model parameter individuals in the target population and a preset criterion function; if the target fitness does not meet the preset convergence condition, G is made to be equal to G + 1, the step of determining the first population corresponding to the model parameters of the inverter model under the current iteration number is executed again, and G is the current iteration number; and if the target fitness meets a preset convergence condition, taking a model parameter corresponding to the optimal model parameter individual in the target population as an optimal identification result. Parameter identification is carried out through a multi-point crossing rule, so that a parameter identification result is more reliable and accurate.

The present invention discloses a multi-wavelength phase unwrapping method and an object height measurement method and height measurement system. The multi-wavelength phase unwrapping method is used to obtain the optimal phase sequence of the coordinates at the surface of the object to be measured at the optical wavelength based on a multi-wavelength off-axis digital hologram of the object to be measured at the optical wavelength, using a height distribution model based on synthetic wavelength chain guidance and phase sequence search: the height distribution of any coordinate at the surface of the object to be measured at the optical wavelength in the hologram is used as an initial value, and a phase sequence is searched for at a certain interval within a preset range of the initial value. The phase sequences found by the search are used to form a criterion function. When the minimum value of the envelope of the criterion function is taken, the corresponding phase sequence is considered to be the optimal phase sequence. The present invention determines the optimal phase sequence by searching for the minimum value of the envelope of the criterion function, rather than by finding the minimum value of the criterion function. This greatly solves the problem of errors in the optimal phase sequence caused by noise damage to the criterion function.

The application discloses a kind of cylinder linear motor multi-objective optimization method, equipment and storage medium, the average thrust of the cylinder linear motor and thrust fluctuation are optimization target, the design parameter influencing it is analyzed, and the range of its value is determined;Sample library is constructed by optimal Latin hypercube experimental design;Kriging model is established based on the sample library;The expected maximum adding point criterion function and prediction function of model are parallel optimized using NSGA-II algorithm;If the model reaches the set convergence accuracy, the optimal design parameter is obtained by NSGA-II algorithm optimization;Otherwise, the real value is calculated and added to the sample library, and the optimization is repeated.The application combines NSGA-II algorithm and Kriging model, and parallel optimization is carried out on the expected improvement maximum criterion function and prediction function using NSGA-II algorithm, which can quickly improve the model accuracy and improve the optimization efficiency and robustness of the algorithm.

Unlike conventional or otherwise known decomposition methods like standard functional decomposition, time-affecting linear pathway (TALP) decomposition, or output-affecting linear pathways (OALPs) from the decomposition of TALPs, advanced output-affecting linear pathway (A-OALP) decomposition from algorithms separate the output variables of each execution pathway such that there is only one output variable per A-OALP, converting an algorithm into a set of process groups. A-OALPs extend parallelization by combining task-like parallelism with dynamic loop parallelism. The lightweight nature of A-OALPs allows for persistent thread and code management.

The present invention relates to the field of control methods and is directed to solving the problem that existing model-free adaptive control methods cannot effectively improve the dynamic response performance of a controlled system and cannot effectively utilize the dynamic linearization error in the model-free adaptive control process to suppress disturbances. The method of the present invention considers the dynamic linearization error in the control process to establish an extended full-format dynamic linearization data model of the controlled system, compensates the controlled object based on this, estimates the extended pseudo-gradient of the controlled system based on the recursive augmented least squares method, obtains a model-free adaptive controller based on the extended full-format dynamic linearization data model at time k based on an improved criterion function, inputs the compensated controlled object control input signal into the controlled object, calculates the system dynamic linearization error difference, and performs model-free adaptive control.

A variable buffer status report configuration is transmitted from a wireless communication network node to a user equipment. The configuration may include one or more functions to compute a buffer status report indication indicating a metric of the user equipment related to the buffer or to uplink traffic stored in the buffer, or to compute a table used to indicate the metric. The configuration may include a function to determine a precision variable that corresponds to a step size between different criteria or criterion functions used to determine the buffer status report indication. The buffer status report indication may vary in size based on the indicated value. The user equipment may apply different received configurations, or a function thereof, to determine a buffer status report indication based on different parameters, such as traffic type, traffic quality of service, buffer size, or buffered uplink traffic.

The application discloses a kind of aircraft global time-varying aerodynamic parameter identification method, comprising: S1. establishing aircraft rigid body dynamics model, and obtaining time-varying parameter to be identified;S2. the time-varying parameter to be identified is written as polynomial form about time;S3. state sensitivity, covariance sensitivity, gain sensitivity, filter state sensitivity and covariance sensitivity are estimated;S4. according to aerodynamic parameter characteristics or time period, carry out local subarea;S5. in current interval, obtain state estimated value, estimated covariance matrix, Kalman gain, state filter value, covariance matrix by parameter value in combination with Kalman filter;S6. according to the above obtained criterion function, when criterion function is not minimum value, parameter is updated using Newton-Raphson algorithm;S7. using moving average filter to smooth all parameters, obtain a smooth global aerodynamic data curve.The application avoids the problem that fitting is not accurate when parameter variation amplitude is too large.

The invention relates to the technical field of charging piles, and discloses a fan rotating speed control method for a power module, electronic equipment and a storage medium, and the method comprises the steps: constructing a dynamic linearization data model related to the air inlet temperature and the fan rotating speed of the power module; based on the dynamic linearization data model, a pre-built first criterion function is combined, and an estimation function of the air inlet temperature is obtained; and obtaining an estimated value of the pseudo partial derivative, and substituting the estimated value of the pseudo partial derivative into the estimation function of the air inlet temperature for calculation to obtain an output value of the fan rotating speed. According to the method, self-adaptive control over the rotating speed of the draught fan is achieved by combining estimation of the pseudo partial derivative with the estimation function of the air inlet temperature, the rotating speed of the draught fan of the power module can be adjusted in real time, the noise pollution is reduced while the heat dissipation requirement is met, and the model-free self-adaptive control mode is adopted; the rotating speed of the fan can be controlled without establishing a complex process model, external interference factors can be effectively eliminated, and the control precision is improved.

The invention discloses an English syllable u feature wavelet coefficient extraction method based on a spline interpolation wavelet neural network, and the method comprises the steps: firstly carrying out the normalization and threshold preprocessing of an audio signal, and effectively removing the interference of environment noise; secondly, constructing a three-layer neural network feedback matrix based on a six-order spline wavelet function, and generating a feedback matrix through transposition operation and inverse matrix calculation of a global matrix psi; then, inverse discrete Fourier transform is utilized to construct a criterion function containing frequency domain errors; and finally, dynamically adjusting the weight of an output layer through iterative training, and terminating training when the modulus value of the criterion function is smaller than a training error iteration ending condition, so as to obtain a wavelet coefficient set representing the characteristics of the longhairy sound u. According to the method, the frequency domain localization characteristic of the six-order spline wavelet is innovatively combined with the adaptive learning of the neural network, the anti-noise performance is improved while the feature extraction precision is ensured, and the problem of individual pronunciation difference is solved.

The invention discloses a construction layer Q estimation method and system based on a depth consistency criterion function. According to the method, seismic data are divided into a plurality of structural layers according to interpretation horizon, and seismic wave attenuation in each layer is represented by an equivalent quality factor Q value; a scanning Q value is set, and a reflection coefficient and corresponding reconstructed seismic data are obtained through unsteady-state inversion; characterizing the consistency of the reconstructed seismic data in the layer by using a depth consistency criterion function layer by layer, and selecting a Q value corresponding to the highest consistency as the Q value of the layer; and performing layer-by-layer circulation processing to finally obtain a structural layer Q model and corresponding reconstructed Q value compensation seismic data. According to the invention, a stable construction layer Q model estimation technology integrated with construction information can be provided, and the resolution and reliability of seismic data are remarkably improved.

The invention belongs to the technical field of ship motion, and discloses a ship LAAV motion model parameter identification method based on a dynamic immune genetic algorithm, which comprises the following steps of: constructing an identification model fitness criterion function by using ship real sea test data, setting a hyper-parameter adaptive adjustment mechanism, and performing several-generation selection, intersection, variation and immune operation on an initial population to identify ship LAAV motion model parameters. And finally determining model parameters. According to experimental verification, unknown parameters in a ship LAAV motion model are optimized by utilizing a DIGA framework in combination with sea test data, and an optimal solution is substituted into the LAAV model to generate AVP (Attribute, Velocity, Position) data in a simulation manner. The test result shows that the DIGA method has the advantages of high precision and high convergence speed in the LAAV model parameter identification problem, and the similarity between the generated AVP data and the sea test data is more than 90%.

The application discloses a kind of based on model-free adaptive multi-farm machine formation path navigation-tracking control system and control method, belong to agricultural machinery navigation technical field.Main steps are:1, using sensor, real-time acquisition agricultural machinery position information, pre-look lateral deviation and area deviation.2, based on deviation information and control input constructs dynamic linear equation, constructs criterion function, minimizes tracking error in control increment, deduces control law, combines pseudo partial derivative online estimation algorithm, realizes model-free adaptive trajectory tracking.3, based on the position information of leader agricultural machinery of design, real-time control follower motion control operation, realizes agricultural machinery vehicle path tracking precision.4, based on the model-free adaptive control scheme of design pre-look deviation.The application can adapt to complex farmland environment, not dependent on accurate model and have strong adaptive ability, realizes high-precision, strong robustness collaborative operation, provides technical support for modern agricultural intelligent development.

The invention relates to an aircraft product simulation method supporting multi-mode calculation, which comprehensively considers multiple factors such as function universality, compatibility and the like of an aircraft product model extension platform, and adopts echelon packaging and real-time scheduling technologies from the perspective of protecting an aircraft product control model. The first-stage package is a dynamic link library of two standard functions and five interaction components, and the second-stage package is an aircraft product integrated dynamic library containing a unique identification code. The access and replacement of different types of aircraft product component entities / models are supported, the aircraft product model extension calls the core function, calling of each component model can be realized, the requirements of real-time calculation of information such as anti-interference capability simulation motion trails, motion speeds and motion attitudes of different types of aircraft products are met, and the real-time calculation of the anti-interference capability simulation motion trails is realized. And analysis and distribution of open-loop data are supported, multi-mode aircraft product simulation is supported, and aircraft product model debugging time and cost can be effectively reduced.

The invention provides a method, a device and equipment for predicting the compressive strength of medium and high strength concrete based on a GA-BP neural network model, and a storage medium, and relates to the technical field of concrete strength prediction. The method comprises the following steps: acquiring a plurality of groups of concrete test samples containing cement, slag, fly ash, water, a water reducing agent, stone and sand and corresponding compressive strength measured values; a GA-BP neural network model is constructed, the node number M of an input layer of the GA-BP neural network model is consistent with the concrete component parameter type, a quadratic form error criterion function is used as a target function, a weight and threshold optimal solution is obtained through genetic algorithm optimization, and model construction is completed; performing normalization processing on the test sample, and inputting the test sample into the model for training; and normalizing to-be-predicted concrete component parameters, and inputting the normalized to-be-predicted concrete component parameters into the trained model to output a compressive strength predicted value. According to the method, accurate and stable prediction of the strength of the concrete with the complex mix proportion is achieved, and the problem that a traditional grey water ratio empirical formula is large in error is solved.

The present invention discloses a method for extracting characteristic wavelet coefficients of the English long vowel u based on a spline interpolation wavelet neural network. The method first normalizes and thresholds the audio signal to effectively remove environmental noise interference. Secondly, a three-layer neural network feedback matrix based on a sixth-order spline wavelet function is constructed, and the feedback matrix is generated by transposing the global matrix Ψ and calculating the inverse matrix. Then, a criterion function containing frequency domain errors is constructed using an inverse discrete Fourier transform. Finally, the output layer weights are dynamically adjusted through iterative training. When the criterion function modulus is less than the training error iteration end condition, the training is terminated to obtain a set of wavelet coefficients representing the characteristics of the long vowel u. The present invention innovatively combines the frequency domain localization characteristics of the sixth-order spline wavelet with the adaptive learning of the neural network, improving the noise resistance performance while ensuring feature extraction accuracy, and solving the problem of individual pronunciation differences.

The invention relates to the technical field of automation control, and discloses a dual-computer hot standby switching control method and system, and the method comprises the following steps: collecting the operation state parameters of main control equipment, and forming the state vector of the system state; based on the state vector, establishing a state evolution model used for describing the time-varying characteristic of the operation state of the main control equipment; according to the state evolution model, estimating probability distribution of a state in a state space; calculating the state distribution entropy of the operation state of the main control equipment under the geometric information manifold; constructing a joint criterion function, and judging whether the main control equipment is in an unstable state or not according to the function; and when the criterion function satisfies a set switching condition, executing a switching control operation of the hot standby device, and completing control authority transfer of the master control and the standby control. Through the state evolution model and the entropy analysis module, real-time dynamic monitoring and stability evaluation of the operation state of the main control equipment are realized, and the effect of capturing the state change of the equipment in time and performing early warning is obtained.

The invention discloses a data-driven prediction multi-mobile robot inclusion control method and system. The method comprises the following steps: acquiring position information of mobile robots; constructing a dynamic linearization data model, designing a multi-step prediction equation to estimate a future trajectory, minimizing a tracking error and a control increment by using a criterion function, deriving a control law, and combining a pseudo partial derivative matrix online estimation and parameter prediction algorithm to realize model-free adaptive prediction control; constructing a dynamic switching communication network based on the directed topological graph; based on a designed model-free adaptive predictive control model, an inclusion control technology is introduced, so that all followers finally enter and keep moving in a convex hull formed by a leader. The multi-robot system gets rid of dependence on a mathematical model, the controller is designed and analyzed only by using input / output data, all robots can finally enter and keep moving in a convex hull formed by a leader, the cost is effectively reduced, and the applicability of the system is improved.

The present invention relates to a control method and system for maintaining safe driving of high-speed trains under DoS attacks. The method comprises: setting pseudo-partial derivative step size, pseudo-partial derivative weight, control law step size, control law weight, adjustment factor, and control input linearization length; setting the expected trajectory of the leader car, the initial value of the train speed output by the following car, and the initial value of the train traction / braking force input by the following car; updating the predicted value of the pseudo-partial derivative; resetting the predicted value of the pseudo-partial derivative; updating the control input; updating the output based on the mathematical expectation of successful data transmission under DoS attacks; calculating the train speed; judging whether the train's travel time has reached the termination time, and if so, stopping the control; otherwise, repeating the above steps. The present invention proposes an extended model-free control, which introduces a control law update method with an input criterion function of an error adjustment factor, which can effectively shorten the convergence time of high-speed train control to achieve stability and improve the tracking effect of the system.

A variable buffer status report configuration is transmitted from a wireless communication network node to a user equipment. The configuration may comprise one or more functions to calculate a buffer status report indication that indicates, or to calculate a table that is used to indicate, a metric related to a buffer, or related to uplink traffic stored in a buffer, of the user equipment. The configuration may comprise a function to determine a precision variable that corresponds to a step size between different criteria, or criteria functions, that are used to determine a buffer status report indication. Buffer status report indications may vary in size based on a value of the indication. A user equipment may apply different received configurations, or functions thereof, to determine buffer status report indications based on different parameters, such as traffic type, traffic Quality of Service, buffer size, or amount of buffered uplink traffic.

This application discloses a flexible predictive control method for a converter, comprising: constructing an output current increment prediction model, which includes an inherent dynamic term reflecting the mapping relationship between historical data of the converter system and the output current increment, and an attack term reflecting external anomalies; constructing a criterion function, calculating the gradient of the criterion function with respect to the coefficient matrix, and setting the gradient to zero to obtain an estimate of the coefficient matrix at the current time; using the error between the reference current of the next cycle and the actual output current of the current cycle as the target output of the output current increment prediction model, rewriting the output current increment prediction model, and obtaining a control law for the voltage increment; based on the control law for the voltage increment, substituting the coefficient matrix estimate at the current time to obtain the voltage control increment, and selecting the converter switching state based on the voltage control increment. This method can achieve parameter-independent predictive control of the converter, resist spurious data attacks, reduce switching frequency, and improve system robustness.

The invention provides a machine tool control system and method and a storage medium, and belongs to the field of machine tool control, the machine tool control system comprises an input interface control module and an output interface control module, the input interface control module is used for constructing a standard function, and the standard function obtains multiple pieces of precondition information of machine tool operation through an input interface. According to the method, a complex fool-proof mechanism and potential collision logic of underlying hardware do not need to be concerned, the technical threshold is remarkably reduced, the working efficiency is improved, the time cost and the learning cost required by handover are greatly reduced, meanwhile, the problem of system stability caused by disordered program styles and unclear logic is effectively avoided, and the system reliability is improved. And safety risks such as equipment collision or operation faults caused by misreading of a program structure or mismodification of key control logic by maintenance personnel are effectively prevented, and the method has remarkable engineering application value and popularization prospect.