220 results about "Systems theory" patented technology

The invention discloses a self-healing control method for operation of an urban distribution network, which is used in an operated urban distribution network. The method adopts an integrative coordination control mode of the urban distribution network based on the self-healing control technology; the process of signals and the generation of control strategies have self adaptability; the method automatically finishes a control process without external intervention, coordinates the action behaviors of a relay protection device, a switch, a safe automatic device and an automatic adjusting device, and carries out coordination control on the relay protection device, the switch, the safe automatic device and various automatic adjusting devices and parameters thereof so as to realize the technical proposal of stable, safe, reliable and economic operation of the urban distribution network; and the method belongs to the application field of cross technology of power system theory, control theory and artificial intelligence.

A method for controlling well bore pressure based on model prediction control theory and systems theory, which belongs to the field of well bore pressure control technique, includes: detecting a well bottom pressure, a stand pipe pressure, a casing pressure, an injection flow rate and an outlet flow rate during construction process, and determining the presence of overflow or leakage; if there is no overflow or leakage, then fine-adjusting the wellhead casing pressure according to the slight fluctuations of the well bottom pressure, the stand pipe pressure or the casing pressure, ensuring that the well bottom pressure, the stand pipe pressure or the casing pressure are at a set value; if there is overflow or leakage, then using a well bore multi-phase flow dynamic model to simulate and calculate the overflow or leakage position and starting time of the overflow or leakage, predicting the variation over a future time period of the well bore pressure in the well drilling process, and utilizing an optimization algorithm to calculate the control parameter under a minimum of an actual well bottom pressure difference during the future period; and repeating the optimization process for the next time period after a first control parameter is selected and set. The present method enables the well bore pressure to be controlled within the allowable fluctuation range of a project, thus achieving precise pressure control.

The invention discloses a bearing-free asynchronous motor control method based on a neural network inverse system theory. A composite controlled object is composed of two sets of Park inverse transformation, two sets of Clark inverse transformation, two sets of current regulating inverters, a flux linkage observer, and a bearing-free asynchronous motor; a fuzzy neural network and integrators form a fuzzy neural network inverse system; and the fuzzy neural network inverse system is in series connection with the composite controlled object; besides, the bearing-free asynchronous motor is decoupled into a pseudo linear system comprising two displacement subsystems, a rotating speed subsystem and a rotor flux linkage subsystem; and the obtained pseudo linear system is introduced into internal model control to form closed-loop control. According to the invention, the control precision is high and there is high robustness on an external disturbance, a parameter change and a modeling error, thereby realizing high-performance control on a bearing-free asynchronous motor.

The invention discloses a cooperative design method of fault detection filter and controller under DoS attack. The method is applied to a USV course control system, and is a cooperative design methodof a fault detection filter and an elastic event trigger controller based on a state observer, and the method comprises the following steps of: establishing a mathematical model based on the state observer USV control system under the influence of an actuator fault, a DoS attack and a network delay; introducing an event trigger mechanism related to the state of the observer, and establishing the model of the USV control system capable of simultaneously describing the time delay of the network transmission and the influence of the event trigger mechanism by using the time-delay system theory, determining an event trigger matrix W of the USV control system model, a state observer gain matrix L1, L2, a fault detection filter gain matrix V1, V2 and a controller gain matrix K; establishing a fault detection filter and an elastic event trigger controller based on a state observer under the DoS attack. The cooperative design method of fault detection filter and controller under DoS attack caneffectively resist the DoS attack and detect the fault in time.

The invention discloses a detection method for geometrical errors of a rotation shaft of a five-axis numerical control machine tool, belongs to the technical field of machine tool precision detection, and relates to a detection and identification method for the geometrical errors of the rotation shaft of the five-axis numerical control machine tool. The detection method comprises the steps that image information of a concentric target are collected by a binocular camera and used for representing the actual movement information of the rotation shaft, the three-dimensional coordinate information of a feature point is acquired finally through camera calibration and image processing, and the movement track represents the space movement track of one point on the rotation shaft; and through combination of a multi-body system theory of the machine tool and a subcoordinate transformation theory of the machine tool, the errors PIGE having no relation to the position of the rotation shaft and the errors PDGE having a relation to the movement position of the rotation shaft are identified and measured. The method effectively achieves detection and identification of the geometrical errors of the rotation shaft of the machine tool, the measurement process is simple and fast, and the measurement efficiency is high. The requirements for the operation track of the machine tool are simple in the measurement process, cooperation with other shafts is not needed, and other shaft linkage errors are avoided.

The invention discloses a holographic dynamic balance method based on empirical modal breakdown flexible rotor, which is characterized by the following: resolving the data of rotor in the whole speed raising course through empirical modal breakdown advantage based on holographic spectrum information integral elementary and system theory; extracting the industrial frequency component; drawing the holographic baud graph; calculating the weight quality and orientation of different rotary speeds, especially near the weight information of critical rotary speed. The invention breaks through the limitation of traditional stable data and reduces the risk, which can reach the better balancing effect.

The invention discloses a voltage reactive real-time control system of a regional power grid and a control method thereof. The system comprises an SCADA (supervisory control ad data acquisition) system, an EMS (enhanced massage service) system, a power grid simulation system and a power grid test system, wherein the SCADA system is connected with a power system; the EMS system is connected with the SCADA system; the power grid simulation system is connected with the SCADA system, and is used for finishing the simulation of voltage reactive real-time control of the power system; and the power grid test system is respectively connected with the power grid simulation system, the EMS system and the SCADA system, and is used for finishing the reactive control optimal scheme of the power system. According to the invention, nonlinearity complex behavior of the simulation power system from the aspect of full grid is performed, the generation of the final control scheme is finished by a test system, and voltage stable operation of the power system is controlled remotely or controlled through remote regulation; and the system and method have great significance in power grid stability, safety operation of power equipment and industrial and agricultural production.

The invention belongs to the field of building energy consumption auditing. A public building energy consumption auditing statistics splitting method can conduct efficient energy consumption statistics on buildings different in area, size and usage situation, is wide in application range and performs flexible and changeable splitting statistics calculation according to specific situation. The monthly electricity bill of a building is divided into air conditioner energy consumption, internal load energy consumption and other energy consumption. The public building energy consumption auditing statistics splitting method comprises the steps that 1 monthly illumination energy consumption and device energy consumption are calculated; 2, surrounding structure load, fresh air load and internal personnel load are calculated; 3, air conditioner load CL of the building is calculated; 4, a rated SCOPe of a system is calculated according to an actual investigating and surveying value; 5, a formula of the SCOP is calculated, wherein a system alpha is unknown; 6, the theoretical EHVAC' of the air conditioner system is calculated; 7, the actual EHVAC of the air conditioner system is calculated, wherein Eother is unknown. The method is mainly applied to an energy consumption auditing occasion.

The invention aims at an intermittent process with uncertainty, and proposes a constrained 2D tracking control method for the uncertainty intermittent process. The constrained 2D tracking control method comprises the steps of: firstly, designing an iterative learning control law for a given system dynamic model; secondly, converting the original system dynamic model into a 2D-FM closed-loop systemmodel expressed in the form of a predictive value according to a 2D system theory and the designed iterative learning control law through introducing state errors and output errors; and finally, giving a sufficient condition expressed in the form of a linear matrix inequality (LMI) for ensuring robust asymptotic stability of a closed-loop system and an expression form of the optimal control law according to a designed infinite time domain performance index and a Lyapunov stability theory. According to the constrained 2D tracking control method, numerical values of tracking errors under the control of the constrained 2D tracking control method are smaller, and the convergence is faster; more importantly, the control input does not drastically fluctuate and only require slight adjustment, thereby being conducive to resource conservation and reducing troubles caused by frequent operations.

The invention relates to an asphalt pavement structure analysis equivalent method based on a pavement material stress and strain dependent model. According to a structural form and a material type ofan asphalt pavement to be analyzed, the thickness of each layer, a Poisson ratio and a pavement material modulus stress (strain) dependent model are determined, the modulus of each layer of an asphaltpavement structure is represented by the pavement material modulus stress (strain) dependent model, a calculation and analysis system is established by combining a calculation load and an interlayercombination condition, the most unfavorable point of the stress of each layer of the asphalt pavement structure is taken as an equivalent calculation point, the final modulus of each structural layeris obtained through iteration calculation, and the stress, strain and displacement of any point in the asphalt pavement structure are calculated according to an elastic layered system theory on the basis of the final modulus. This method considers the influence of material nonlinearity on pavement mechanical calculation, and enables the stress analysis of the asphalt pavement structure to be morereasonable and perfect.

The invention provides an area integrated environment risk evaluation and portioning method, for reflecting the environment risk status of an area. The method comprises the following steps: obtaining area environment risk correlation information, and according to an area integrated environment risk system theory, through combination with the obtained area environment risk correlation information, constructing an area integrated environment risk evaluation index system, wherein the index system comprises a risk source harm index, a risk field intensity index, a risk acceptor vulnerability index and a risk control mechanism validity index; determining an index weight and quantification model of the index system; according to the determined index weight and quantification model of the index system, obtaining an area integrated environment risk index; and according to the area integrated environment risk index, performing risk partitioning on the area so as to obtain an area integrated environment risk partitioning graph. The method provided by the invention is applied to the field of environment science and environment risks.

The invention includes steps: select the reference template for gray correlation analysis and convert the original pictures to pictures of gray correlation by calculating the two-dimensional gray absolute connection; (2) next process the pictures of gray connection with threshold values; (3) then apply the cubic-polynomial-fitting of the two-dimensional gray absolute connection in a small area on the pictures of the gray connection; (4) obtain the fitting parameter by least square method and (5) use the first and second derivatives of the fitting function on the gradient slope to obtain the edge of sub-pixel. This invention for the first time applies the gray system theory for extracting the edge of sub-pixel, effectively suppressing the interferences from white noise and colored noise, enhancing the precision of the edge extraction, reducing the data sizes of the pictures, thus facilitating the operation of the extraction algorithm. This invention can be widely applied in the field of measuring techniques.

The invention discloses a hybrid switching system theory-based Buck circuit modeling method and application thereof. The method comprises the following working steps of: 1, analyzing a Buck circuit, portioning a state space, and determining the number of working states; 2, determining switching conditions among the working states; 3, establishing a sate equation and an output equation of the Buck circuit; 4, determining a state matrix, an input matrix and an output matrix of a system according to circuit parameters; and 5, establishing a model of the Buck circuit based on the hybrid switching system theory. By utilizing the hybrid switching system theory, the modeling of the Buck circuit is accurate, and system stability and control performance are accurately analyzed, particularly complicated characteristics of a converter system caused by switching; and the Buck circuit has the advantages of simple structure, small volume, high conversion efficiency and the like.

The invention relates to a pre-stack non-linear fluid identification method for a fuzzy neural network of a chaotic quantum-behaved particle swarm. Fluid identification is always a key point and difficult point problem in the oil-gas exploration field. By aiming at deficiency in the common fluid identification method at present, a multi-attribute angle gather combination fluid identification factor is built by researching an AVO (amplitude versus offset) response characteristic comprising different fluids; a chaos search mechanism, a quantum-behaved particle swarm and a fuzzy system theory are organically combined to fully perform respective advantages and complementarities of the chaos search mechanism, the quantum-behaved particle swarm and the fuzzy system theory; a novel group intelligent optimization algorithm of a ''chaotic quantum-behaved particle swarm fuzzy system'' is developed and researched, and a mechanism and an optimizing performance of the pre-stack non-linear fluid identification method are researched from two aspects of the theory and practicality; problems of poor global search capability, premature convergence and the like in a traditional optimization algorithm are fundamentally improved; the optimization algorithm is introduced into fluid identification to form the pre-stack non-linear fluid identification method for the fuzzy neural network of the chaotic quantum-behaved particle swarm; the problem existing when a traditional fluid detection means is used for carrying out fluid identification is effectively solved; fluid identification precision is improved; and a new scientific and effect technical method is provided for the fluid identification.

A converter oxygen consumption prediction method based on grey prediction and a neural network combined model belongs to that technical field of oxygen prediction of converter in iron and steel enterprise. The oxygen consumption of a converter is predicted by analyzing the factors that affect oxygen consumption. Based on the nonlinear computational characteristics of Elman feedback neural network,the grey system theory can not only accelerate the convergence rate of artificial neural network prediction model, but also more effectively show the change law of oxygen consumption in converter, and improve the accuracy of prediction. By combining with the combined model of grey prediction and Elman neural network, the combined model has strong global searching ability, and optimizes the network at the same time, and adds appropriate operators, which enhances the ability of searching local optimal solution and global optimal solution, and can effectively improve the prediction accuracy, guide the steelmaking production to use oxygen reasonably, and improve the production efficiency.

The invention relates to a bituminous pavement structural analysis and increment method based on a modulus stress and strain dependence model of pavement materials. The method includes the steps of according to the structural pattern and material type of a bituminous pavement in a simulation analysis, determining the thickness and Poisson's ratio of each layer and the modulus stress and strain dependence model of the pavement materials, adopting the modulus stress and strain dependence model of the pavement materials to represent the modulus of each layer of a bituminous pavement structure, combining calculation load with interlayer combination conditions to create a calculation analysis system, using an increment method as an analysis basis, obtaining a modulus matrix of each point of theinteriors of pavement structural layers through finite element software numerical calculation, and based on the steps above, calculating the stress, strain and displacement of an arbitrary point in the bituminous pavement structure according to an elastic layered system theory. According to the method, influences caused by non-linear problems of materials on pavement mechanical calculation are taken into account to make the force analysis of the bituminous pavement structure more reasonable and complete.

The invention discloses a mixing scheduling method suitable for real-time system periodic tasks. The method comprises the following steps: searching a ready real-time system task set T and sorting the tasks in an ascending order according to deadlines; finding the task with the shortest deadline, wherein the execution time C and the deadline D of the task with the shortest deadline are taken as input data of a fuzzy reasoning system; processing the input data by a CPU (central processing unit), i.e. mapping a threshold value delta output by the fuzzy reasoning system onto a membership function of the threshold value, and determining the property of the threshold value delta according to the membership function. The mixing scheduling method uses a fuzzy system theory to organically combine an RM (rate monotonic) algorithm and an EDF (earliest deadline first) algorithm for scheduling the execution tasks, so the deadlines of the tasks cannot be missed, and system resources are fully utilized.

The invention discloses a dynamic traffic abnormal data detection and recovery method including abnormal data detection and abnormal data recovery. A density-based local abnormal isolated point discovery method is adopted for abnormal data detection, and a grey system theory based recovery method is adopted for abnormal data recovery. By the method, abnormal data in vehicle operating data in dynamic traffic are detected and recovered effectively in real time, data quality is improved, and traffic safety is guaranteed finally accordingly.

The invention relates to a mountain torrent disaster risk evaluation method based on a polymorphic system theory. The method includes the following steps: collecting data; carrying out mountain torrent disaster status survey; grading influence factors; establishing a model; and determining different risk grades. Through collection and arranging of basic information of hydrology and landform with a small basin being a unit, technological means such as GIS, satellite remote sensing and hydrological analytical calculation is fully utilized to extract related data, combined with mountain torrent disaster field survey data, a small-basin rainstorm flood analysis is made, a mountain torrent-threatening residential area mountain torrent disaster status defense capability is evaluated, and village danger zones along a river are scientifically divided, through analysis evaluation, basic characteristics of small-basin rainstorm flood of a mountain torrent disaster danger zone and a personnel and property distribution situation are mastered relatively comprehensively and accurately, a relation among a rainstorm, mountain torrents and a disaster is analyzed, and critical rainfall of villages, market towns and towns along the river that may cause occurrence of a mountain torrent disaster is analyzed, thereby providing support for further improving a mountain torrent disaster prevention and control capability and sustainable development of social economy.

The invention provides a shield driving parameter prediction method based on a grey system model. According to the method, tunneling parameters of continuous tunneling of a set quantity of rings by ashield tunneling machine are selected to serve as sampled data; the sampled data is converted into a generation sequence displaying a certain law, and a tunneling parameter grey prediction model basedon the grey system theory is established based on the generation sequence, wherein the sampled data is input into the tunneling parameter grey prediction model, and the tunneling parameter grey prediction model obtains tunneling parameter prediction values of subsequent tunneling segments through calculation; the tunneling parameter prediction values are fed back to a shield manipulator to guideshield tunneling machine tunneling parameter control; and tunneling parameter samples are updated in real time to realize dynamic circulation of tunneling parameter prediction. Through the method, byweakening the randomness of original data to highlight the inherent law of the original data, only a small amount of original data is needed; and meanwhile, the model is properly corrected through thedifference between a model fitting value and an actual value, prediction precision can be improved, and the prediction result is more approximate to practice.

The invention discloses a modeling based on a piecewise-linear system of a hybrid system theory and a control method, and belongs to the field of automatic control. All segmented models of the piecewise linear system can be integrated in an uniform frame so as to accurately describe the interaction of a model switch event and a continuous dynamic process, thereby being beneficial to eliminating vibration caused by the model switch; and a linetype performance index is adopted to replace traditional quadratic performance index to forecast controller design, and an OPC (organic photoconductor) client end program independently developed by Matlab is utilized to realize the integration of mixed prediction control algorithm and a DCS (data communication system) control system.