179 results about "Matlab simulation" patented technology

The invention belongs to the technical field of GNSS engineering safety, and relates to an anti-interference normal null widening method for a dynamic GNSS receiver. On the basis of a normal-distribution probability model, a null widening model of the dynamic GNSS receiver is provided. The model is linearized on the situation of small angle changing, and frequency spectrum gains formed before and after widening are compared by means of a Matlab simulation tool. By means of a power insertion algorithm, the relationship of an output SNR and an input INR is analyzed before and after widening, and ultimately engineering realizability of an algorithm is put forward through FPGA and DSP platform verification. As is shown by a result, widening null formed through the widening algorithm can effectively counteract interference sources changing within a certain range, the aim of preventing dynamic interferences is achieved and robustness of a self-adaptation algorithm is improved.

The invention discloses a control method of an alternating voltage sensorless high voltage direct current transmission converter, belonging to the technical field of electrical equipment and comprising the following steps: establishing a stator resistor and an inductor for a virtual motor; building relative position relationships among a current vector, a voltage vector and a flux linkage vector, and analyzing a vectorgram; establishing a converter and flux linkage mathematic model, and calculating a virtual flux linkage vector of a system to obtain a power feedback quantity of the system; acquiring an active control signal and a reactive control signal of the system through a direct power control algorithm, and generating a PWM trigger converter for respectively and independently controlling the active power and reactive power of the system; and utilizing MATLAB simulation software to set up a system model for verifying, and obtaining a systematic selection device when the verification is successful. By utilizing Matlab / Simulink to set up a corresponding simulation model, the designed method is verified to have rapid response speed, the voltage and power after startup can still reach stable values after about 2 power frequency periods and have high steady state precision.

The invention relates to a simulation development platform in the field of aerospace, and aims to provide a simulation platform capable of supporting the verification of a manned / unmanned aerial vehicle cluster formation control algorithm. According to the EEG-based manned / unmanned aerial vehicle cluster formation VR simulation method and system, a real-time simulation Simulink Real Time target machine is configured to execute the real-time simulation function of a Matlab simulation program and is connected with a simulation platform management platform through an Ethernet. The simulation platform management computer downloads the MATLAB program into the target machine. The target machine runs the MATLAB program, and sends a simulation result to the simulation platform management computerin real time, and displays and saves data on the computer. Each Simulink Real Time target machine + embedded controller denotes a UAV. The embedded controller runs an UAV control algorithm to calculate a control signal. The EEG-based manned / unmanned aerial vehicle cluster formation VR simulation method and system are mainly applied to aerospace simulation occasions.

The invention discloses an intelligent parking lot parking space guiding mechanism algorithm based on a best parking space model. The method mainly comprises three portions including the determination of the parking lot best parking space model, the drawing of a road network weighted graph and the design and programming of a parking space guiding mechanism algorithm. At first, according to the driving distance of a vehicle for entering a parking space, the walking distance for the driver of the vehicle to walk out from the parking lot and the personal safety factor, a mathematical model is established through the shortest path method, and thus, the best parking space model is determined; then, according to the best parking space model, a parking lot road network is abstracted into a weighted graph in the graph theory for solving the best parking space problem, so that the best parking space problem is converted into the shortest distance calculation problem on the weighted graph; and finally, the improved floyd algorithm having the advantage of good performance is adopted to complete the best parking space selection and guiding program, and the best parking space selection and guiding program is verified to be successful through Matlab simulation.

The invention discloses an ant colony-based QoS optimization routing method in ultraviolet wireless Mesh network, which comprises the steps of: first, constructing an ultraviolet-based wireless Mesh network topology structure chart on the basis of the research on ultraviolet communication characteristics; second, setting a probability formula of ant colony algorithm according to different QoS constraint conditions; third, providing an ant colony-based QoS optimization routing method in ultraviolet wireless Mesh network in combination with excellent properties such as ultraviolet transmission characteristics, distributed computation of ant colony algorithm, positive feedback, greedy heuristic search, high robustness and the like; at last, performing simulation comparison on new algorithm and classic shortest route Dijkstra algorithm in Matlab simulation software respectively, thereby analyzing the performance and advantage of the new method. The method of the invention solves the shortcoming that the existing QoS routing algorithm cannot be directly applied to the communication based on ultraviolet.

The invention discloses an improved instantaneous symmetrical component method-based current detection method for a distribution static synchronous compensator (DSTATCOM), which comprises the following steps of: 1, determining a symmetrical component method and a method for expressing an instantaneous value in a phasor time domain; 2, determining the instantaneous value; 3, implementing the improved instantaneous symmetrical component method; 4, establishing a model by adopting a MATLAB simulation tool to perform simulation analysis on a conclusion; 5, filtering, converting and processing data; and 6, subtracting obtained three phases of positive fundamental active currents iafp<+>, ibfp<+> and icfp<+> from a load current to obtain required comprehensive compensation command currents iac, ibc and icc comprising harmonic components, negative sequence components and reactive components. The method avoids a complex phase shift circuit, a phase locked loop circuit, and an address generator and a table lookup process of sine and cosine function table, and eliminates errors and faults caused thereby.

The invention relates to a power-reaching-law-based sliding-mode controlled magnetic suspension train system control method. Based on a single magnet structure magnetic suspension system model, and onthe basis of performing linearization on the input and output relation, the power-reaching-law-based sliding-mode controlled magnetic suspension train system control method analyzes the control relation of the application of sliding-mode control of the power reaching law in the single magnet structure magnetic suspension system, and utilizes a Lyapunov stability theory to analyze the stability ofthe method. The Matlab simulation result shows that compared with traditional sliding-mode control, the sliding-mode control of the power reaching law has better control performance, and has the advantages of significantly weakening buffeting, being smaller in the positional signal error, being better in dynamic characteristic, and being higher in robustness.

The invention relates to a global dynamic path planning algorithm for multiple virtual target points based on a dynamic window. A dynamic window method is applied to the global path planning direction, and the defect that traditional global path planning is discontinuous and unsmooth is improved; and as for specific operation, by adding the multiple virtual target points, updating the course angleof an unmanned vehicle on the special position and adding random obstacles, global dynamic path planning of the unmanned vehicle is achieved, and the global dynamic path planning algorithm is appliedto complex environments such as 8-surrounding tracks in 'Formula Student Autonomous China'. The MATLAB simulation result shows that the unmanned vehicle can effectively avoid the obstacles occurringrandomly, and global path planning and tracing are safely and stably completed.

The invention discloses an evaluation method applied to the field of risk analysis of a railway signal system. The method comprises the steps of firstly, formulating the levels of risk of the railway system, expressing a cloud model for evaluating the levels of risk by a forward cloud generator of a MATLAB simulation software, and generating a standard risk grade evaluation set cloud model figure; marking the failure mode of a function by an expert according to the formulated levels of risk to obtain a risk factor set, and converting the risk factor set into a comprehensive evaluation matrix R; utilizing an analytic hierarchy process to obtain risk factor set weight coefficients corresponding to all parameters in the risk factor set by the expert, and calculating a comprehensive evaluation result cloud model figure by fuzzy synthetic operator; comparing the comprehensive evaluation result cloud model figure with the standard risk grade evaluation set cloud model figure to obtain the level of risk of the comprehensive evaluation result. After the method is adopted, the risk evaluation result is more objective and accurate.

The invention discloses an integration platform of a Matlab (matrix laboratory) simulation model based on an HLA (high level architecture), which overcomes the disadvantages that the efficiency is low, the performance is poor and the like in the prior art. The integration platform of the Matlab simulation model based on the HLA disclosed by the invention comprises a simulation model module, a configuration file module, an HLA enabling module and an RTI (real time information) system. The configuration file module is used for filling SOM (simulation object model) information; and the HLA enabling module is used for realizing the interaction between the simulation model and the RTI system. The HLA enabling module comprises a simulation parameter configuration sub-module, an input sub-module, an output sub-module, a data space sub-module, an RTI service function sub-module and a callback service function sub-module. The invention discloses an integration method of the Matlab simulation model based on the HLA. According to the integration platform and the integration method of the Matlab simulation model based on the HLA disclosed by the invention, the integration of the HLA of the Matlab simulation model is realized, and the reusability of the simulation model is improved.

The invention firstly simplifies a human body target motion into a compound motion of a typical motion form, and puts forward a human body walking and running empirical model according to measured biomechanical experiment data. On the basis of an XYZ convention, an Euler rotation matrix is used for establishing and perfecting human body motion animation models under a state of marching on the spotand a walking and running state; then, on the basis of a continuous wave signal, an integral radar echo model of a human body walking and running target and a radar echo model of each position of thetarget are constructed; and a Matlab simulation tool is used for analyzing radar echo characteristics under different human body motion states and generating a corresponding time domain graph throughthe short-time Fourier transform so as to lay a theoretical foundation for the moving human body target characteristic extraction and the walking and running state of the human body. The time domaingraph of the human body motion is divided into a training set, a verification set and a testing set, the improved convolutional neural network is input for training, the network parameter is regulatedto realize model convergence, and the network can correctly classify the human body motion state.

The invention discloses a renewable energy capacity allocation method for promoting consumption, includes the following steps: (1) acquiring a power network topology and modeling according to the power network structure to form a data matrix capable of representing the characteristics of the power network, (2) to test the rationality of power network data and its adaptability to power network planning, (3) Analyzing the boundary conditions of various flexible resources in the power grid, (4) uploading the renewable energy and load power curve in the dispatching center, (5) establishing the renewable energy planning model which includes the planning layer model and the operation layer model, (6) solving the renewable energy planning model based on Matlab simulation platform; The invention comprehensively considers the constraint of source-network-load-storage, and establishes a model aiming at the renewable energy consumption based on the objective functions and constraint conditions ofthe planning layer and the operation layer, so as to obtain the multi-point layout and planning of the renewable energy with the highest renewable energy utilization rate and the largest renewable energy consumption capacity.

The invention discloses the realization of a comprehensive detection algorithm of an electrocardiogram signal at the application layer of an electrocardiogram monitoring internet of thing, belonging to the technical field of the internet of thing. The invention mainly solves the problem of comprehensive detection of each wave shape component in the application layer of the electrocardiogram monitoring internet of thing. The invention builds a series of detection methods, detection standards and threshold parameters based on the wavelet transform technique, provides a detection method based on the wavelet transform, the Hilbert transform and the improved envelope transform to the electrocardiogram signal, and detects and identifies the specific shape and position of the QRS wave group, the P wave and the T wave. The detection algorithm provided in the invention has better robustness, and can preferably restrain or eliminate external factors of baseline drift, high-frequency interference and the like. The electrocardiogram signal comprehensive detection algorithm has the false detection rate of 0.89% through the MATLAB simulation and the MIT-BIH data base mark comparison.

Provided is a general calibration method for common video cameras, panorama video cameras and fisheye three-dimensional video cameras and based on a one-dimensional calibration rod. The method includes four steps of 1 initialization of inner parameters of video cameras; 2 initialization of outer parameters of the video cameras; 3 building of an optimized objective function; 4 non-linear optimization of the inner parameters and the outer parameters of the video cameras. Due to the fact that the existing calibration algorithm can not meet the accuracy and convenience requirements of three-dimensional vision systems of the fisheye lens video cameras, a general three-dimensional vision system calibration method for the common video cameras, the panorama video cameras and the fisheye lens video cameras on the basis of a general video camera model is designed. By means of Matlab simulation and real experiments, the method is proved to be feasible and effective. The method has good practical value and application prospects in the technical field of machine vision.

The invention belongs to the electric driving control field of electric vehicles, in particular to a driving anti-skid control method and a system of a pure electric vehicle. The method comprises: through MATLAB simulation software to calculate the range of motor speed change rate when the automobile transmission is in D gear and R gear, according to the real-time rotational speed of the motor tocalculate the motor rotational speed change rate of the current transmission gear, and judging whether the vehicle is in a slip state by judging whether the motor speed change rate exceeds a value range of the motor speed change rate of the corresponding gear, when the vehicle is judged to be in a slip state, the vehicle is removed from the slip state by correcting the requested torque value of the driver. The invention improves the driving force control performance of the whole vehicle without adding an external sensor and an additional data interface of the whole vehicle, and is easy to be integrated in the existing control system of the whole vehicle, and has good universality.

The invention is a kind of prediction method adaptive for website update time, which is the improved adjacency method. It can predict the next updating time of website according to its history regulation, quickly predict the order of updating frequency in the absence of prior knowledge for the updating frequency of website, and adapt to the sudden change of updating frequency of website rapidly. Through MATLAB simulations, the method can accurately predict the website updating time. Compared with the classic adjacency method, this method can ensure the trendy property of the captured website under the condition of significant reducing system expense. The method adapts to the website grasp system, and its performance is excellent in a real application.

The invention provides a fuzzy PID based automobile cruise control system which comprises an automobile cruise control system module, a fuzzy control module, a traditional PID module, a fuzzy PID controller design module and an MATLAB simulation result module, and the modules are connected via electric signals. According to the invention, overshoot of the automobile cruise control system is correspondingly reduced, reaction speed is increased, the driving speed is effectively kept at the cruise speed, an accurate mathematical model is not relied on, the system is not sensitive to parameter change, and the robustness is very high.

The invention discloses a modulation signal classification method for cuckoo search-improved gray wolf optimizer-least square support vector machine. The method selects a high-order cumulant and a local mean decomposition amount approximate entropy for the characteristic parameter of a modulation signal, and utilizes cuckoo search for the second update of the wolf position to optimize the two keyparameters of a least squares support vector machine model, namely, the penalty coefficient Gamma and the kernel parameter Sigma, so as to obtain the optimal kernel limit learning machine parameter value. The method reduces the influence of noise factor on the signal recognition result, makes up for the defects of under-envelope, over-envelope and boundary effects in the traditional modal empirical decomposition, and effectively improves the defect that the gray wolf optimization global searching ability is poor and is easy to fall into the local optimal solution in processing of high-dimensional data, compared with the original gray wolf optimization result by MATLAB simulation, is it proved that the method can intelligently classify the modulated signal more efficiently and accurately, and has a good application prospect.

The invention discloses a baseline selection method based on a long-short baseline interferometer direction-finding system. A long-short baseline interferometer angle-measurement principle is utilizedto combine MATLAB simulation for long-short baseline unambiguity angle-measurement modeling and simulation, system parameters of interferometer ambiguity resolution ability, measured angles and the like under different baseline size combinations are analyzed through setting different frequencies, an optimal baseline size structure configuration of a long-short baseline angle-measurement model under a known working frequency band is given, that is, the direction-finding system is enabled to have widest baseline phase error tolerance through selecting appropriate size relationships of long-short baselines on the premise of giving a system working frequency range and an angle-measurement range, thus a success rate of angle-measurement unambiguity of the type of interferometer is improved ina case of a larger phase error, and direction-finding performance of a direction-finding system using the long-short baseline interferometer direction-finding system in actual application and influences of the system and an environment is improved.

The invention relates to a six-axis mechanical arm operation method, and particularly relates to a six-axis mechanical arm movement control method based on G code programming, which uses G codes as transit to realize the automatic programming of six-axis mechanical arm movement. The six-axis mechanical arm movement control method based on G code programming comprises the following steps of: (1) constructing a visual model of a six-axis mechanical arm in a 3D (three dimensional) environment; (2) establishing the simulation virtual movement of the six-axis mechanical arm in a matlab simulation control platform; (3) generating G codes according to a path trajectory after drawing with Auto CAD / MasterCAM; (4) planning a movement path by using the generated G codes in combination with the movement characteristics of the six-axis mechanical arm; (5) generating instruction codes according to the movement planning programming of the six-axis mechanical arm, and then carrying out interactive analog simulation movement; (6) overcoming interference problems through interference experiments; and (7) causing the six-axis mechanical arm to complete automatic machining operation in a practical environment. The six-axis mechanical arm movement control method based on G code programming is high in accuracy of machining movement and effectively overcomes or prevents interference problems possibly happening during automatic control.

The invention discloses an improved ant colony algorithm and dynamic window method-based hybrid algorithm applied to intelligent vehicle path planning. The algorithm can realize real-time obstacle avoidance, improve the path planning efficiency and realize automatic feedback control of an intelligent vehicle. According to the algorithm, after the Matlab simulation platform and the ROS-based intelligent vehicle platform are used for specifying a starting point and a target point on the premise that the obstacle is known, global path planning of the intelligent vehicle is completed, meanwhile,unknown obstacles are set on the grid map, local moving target points are planned, the local target points are tracked in real time, and local real-time obstacle avoidance of the intelligent vehicle is completed. According to the intelligent vehicle path planning method based on the improved ant colony algorithm and the dynamic window method, the turning angle of the path is smoothened, the path planning efficiency is improved, real-time obstacle avoidance of the intelligent vehicle is achieved, and good robustness and accuracy are achieved.

The invention relates to an adjoint matrix-based water supply pipe network leakage fault reverse sourcing method. The method is characterized by comprising the following steps of: establishing a pipe network flow field transient equation; constructing a sensitivity function on the basis of pressure wave influences formed on a flow field by pipe network leakage; deriving an intensity of pressure according to the sensitivity function, and carrying out reverse processing in the aspects of space and time on an adjoint equation; and carrying out analog simulation by applying MATLAB, verifying an obtained analytical solution and determining a final reverse sourcing model. According to the method provided by the invention, a judging model for detecting a leakage position is obtained through deriving the intensity of pressure P, a function and a displacement x; a time for detecting the leakage position or a leakage position is set through MATLAB simulation, so that a corresponding leakage position or detection time is found; and finally, the leakage positioning in the aspects of time and space is realized. The method has the advantages of being scientific, reasonable, high in sourcing speed, and high in practical value.

The invention relates to a cross-layer optimization design method based on incomplete channel state information (CSI) and antenna transmit power allocation for a wireless space time coding multiple input and multiple output (MIMO) system. According to a power allocation algorithm, optimization aims to maximize the average spectral efficiency (ASE) of the system. In order to reduce complexity in the solution of an optimization problem, the problem is converted into the minimization of average packet error rate (PER) of the system according to a relationship between the ASE of the system and the average PER. In order to avoid the multiple iterative computation of the conventional optimal power allocation algorithm, a power allocation method based on a maximum compression signal to noise ratio is provided, and closed power allocation can be realized. By the method, the iterative computation is not required, and positive power requirements are met; and moreover, due to high proximity, performance approximate to that of the conventional optimization algorithm can be achieved, and effective compromise between the complexity and the performance is realized. A matlab simulation platform shows that the fed back incomplete CSI can be effectively used for rate and power adaptation and automatic repeat request, and the spectral frequency of the system is greatly improved.

The invention claims protection of a single-ended fault ranging method based on a single-ended traveling wave method and an inherent frequency method. According to the method, inherent-frequency-method-based ranging is carried out and a multiple signal classification (MUSIC) algorithm is introduced to obtain an inherent frequency principal component, so that an initial value of a fault point is obtained; wavelet-transform-based single-ended traveling wave ranging is carried out and no fault point reflected wave, adjacent-line reflected wave and opposite-end bus reflected wave need to be distinguished; times of modulus maximum occurrence are recorded in sequence to obtain a plurality of ranging results; and then screening is carried out based on the initial value to obtain a final result. The MATLAB simulation calculation shows that the method is not affected by the fault distance, transition resistance, fault type and wiring mode and has high ranging accuracy and robustness.

The invention relates to a facial image feature extraction method based on a gray level co-occurrence matrix, facial image features comprise contrast, homogeneity, correlation and energy, and the method comprises the following steps: (1) acquiring a facial image; (2) performing preprocessing operation on the face image, namely converting the face image into a grayscale image; and (3) processing the grayscale image, and obtaining the textural features of the facial image, including contrast, homogeneity, correlation and energy. According to the method, a gray level co-occurrence matrix method is adopted, feature extraction is carried out on the face texture image through MATLAB simulation experiments, the face features are easier to recognize, and therefore the visual effect better than that of an original image is obtained, and the effect on the aspect of classification precision improvement is remarkable.

The invention discloses a brand new orthogonality-training-based clock estimation method of bi-direction relay channel physical layer network coding. In a bi-direction relay channel PNC, two signals arrive at a relay node at different time, and then relative time migration exists. According to the method, firstly, the relative time migration is converted into the difference of two absolute time migrations, secondly, the two absolute time migrations are estimated, and finally, the estimation value of the relative time migration is obtained. According to the estimation of the two absolute time migrations, two estimation algorithms including the optimization sampling point algorithm and the interpolation algorithm based on discrete Fourier transform are put forward. The estimation on any absolute time migration can be achieved through any algorithm. By means of a Matlab simulation platform, the feasibility of the brand new orthogonality-training-based clock estimation method is verified, and the optimal algorithm combination is found. By means of the combination, when the signal to noise ratio is small, the mean square error of the system is very close to the theory lower bound, and meanwhile the calculation amount is small.

The invention relates to a microgrid load prediction method based on an LSSVM neural network, and belongs to the field of microgrid loads. The invention provides a load prediction method based on a least square support vector machine technology in combination with a neural network, and the method is characterized in that firstly, model parameters of a least square support vector regression machineare optimized by using an ant colony algorithm, the regression machine is trained by using an optimized model, the regression machine provides better structure and parameters for an RBF neural network, and finally, a prediction result is obtained through matlab simulation training. According to the invention, the micro-grid coincidence prediction accuracy is improved.

The invention discloses a dynamic simulation method of using differential braking to control an aircraft turning process. The method comprises: by changing a structural parameter of an aircraft, an initial turning state parameter, torque applied by a pilot to braking, an engine thrust control parameter, and by using Matlab simulation software, and in a Simulink environment, calculating a turning angle of each time, a turning angular velocity of each time, a turning radius of each time, a turning linear speed of each time, as well as a lateral force applied by the ground to a front and a main wheel in the aircraft turning process; and checking the lateral force subjected by the wheels by using of a peak friction coefficient between the wheels and a runway according to the condition of the runway. The method provided by the invention can be applied to design the capability of using differential braking to control the aircraft turning process; a simulation tool is used to optimize the design in each step; and a ground maneuvering capability in the condition of using only differential braking to control the aircraft turning is accurately predicted.

The invention discloses a method for simulating takeoff stages of single shot included angle type rocket boosted unmanned aerial vehicles. The method comprises the following steps of: firstly analyzing locomotion mechanisms of three stages such as in-orbit sliding, rocket disengaging and rising to a safety height, and speed flight, so as to determine force and moment, acting on an airplane, of each flight stage; establishing a mathematic model by utilizing a three-state locomotion mechanism equation set; completing digital-analog simulation by utilizing a Matlab simulation environment so as toobtain reliable unmanned aerial vehicle safe launch envelope. According to the method, powerful technical support is provided for safe launch of unmanned aerial vehicles.

The invention discloses an Euler-Bernoulli beam vibration control method based on backstepping iterative learning. The method comprises a step of constructing an Euler-Bernoulli beam system accordingto dynamic characteristics of an Euler-Bernoulli beam, a step of constructing a vibration control method based on the backstepping iterative learning according to the Euler-Bernoulli beam system in combination with a Lyapunov method, wherein virtual control quantity design, backstepping item design and iterative item design are included, a step of verifying the stability of the Euler-Bernoulli beam system under the vibration control method, a step of performing digital simulation on the Euler-Bernoulli beam system by using MATLAB simulation software and verifying whether a control effect meetsexpectation or not, and a step of adjusting gain parameters of a controller according to a simulation result if not such that the controller has a relatively good control effect. According to the vibration control method based on the backstepping iterative learning provided by the invention, the vibration of the Euler-Bernoulli beam system can be effectively suppressed, so that the Euler-Bernoulli beam system works more stably.