117results about How to "Reduce the impact of uncertainty" patented technology

The invention discloses a regional energy internet scheduling method based on random planning and model predictive control. The method comprises the steps of (1) analyzing the operation characteristics of all units and interconnection lines in a regional energy internet, and constructing a mathematical model of each unit; (2) analyzing the output of the wind and light renewable energy and the uncertainty of cold, heat and electric loads, and generating prediction scene data which are required for the operation of the optimization scheduling by adopting the scene generation and reduction technology; (3) establishing a day-ahead scheduling random planning model with the lowest total operating cost of the system as a target, and determining the on-off state of each unit; (4) establishing an intra-day scheduling random planning model with the lowest total operating cost of the system as a target, and determining the running power in each unit within a day; (5) establishing an intra-day real-time rolling correction model by adopting the model predictive control technology, and correcting the operation plan of each unit. According to the invention, the accurate tracking of loads and thesmooth unit output are achieved. The high dynamic performance and the strong robustness are also realized.

The invention discloses a price demand response-based intraday economic scheduling model, which comprises the following steps: (1) introducing a price demand factor, building a demand elasticity-based price demand response model, and guiding a user to change a power consumption behavior to respond to a wind power output change through a real-time power price; and (2) by building a target function and constraint conditions of power balance, conventional unit output, spinning reserve, conventional unit ramp rate, network safety and wind power output of a robust-interval economic scheduling model, integrating the price demand response model into the robust-interval economic scheduling model, and building a price demand response-based robust-interval intraday economic scheduling model with large-scale wind power consumption. The price demand response model is introduced into the robust-interval economic scheduling model by considering a wind curtailment factor; the robust-interval intraday economic scheduling model with large-scale wind power consumption by considering a price demand response is built; and a linear programming-based solving method is provided according to the duality principle.

The invention discloses a coordinated scheduling method for an electricity-hydrogen multi-energy complementary DC microgrid, and the method is established based on the electricity-hydrogen multi-energy complementary DC microgrid, and comprises the following steps: initializing each system; performing the day-ahead prediction of the output of a renewable energy power generation system and the localload demand; performing day-ahead economic dispatching based on the predicted power, the electric energy storage system reserve SOC and the hydrogen energy system reserve SOHC; predicting photovoltaic, fan output and local load requirements in real time in an ultra-short period; and carrying out real-time rolling optimization on the day-ahead economic dispatching result according to the ultra-short-term prediction result. According to the invention, through day-ahead and online coordinated scheduling, the normal operation of the electricity-hydrogen multi-energy complementary DC microgrid isensured, the optimal operation of the system is ensured, and the influence caused by uncertainty is reduced; and the economy of the system is improved, and the working efficiency of the microgrid is improved.

The present invention discloses an energy storage prospect distribution control method of smoothing microgrid tie line power. The energy storage prospect distribution control method of smoothing the microgrid tie line power can solve the problem of the microgrid power balance control in the condition having new energy random fluctuation. Specifically, a finite time rapid distribution power control protocol is enforced between energy storage individuals to realize the control target of smoothing the microgrid tie line output power, and the power regulation margin and the cost of energy storage are considered in the enforcement process for a time in the future. The energy storage prospect distribution control method of smoothing the microgrid tie line power considers the rapid fluctuation characteristics of the new energy curve and the energy storage device physics restriction, the regulation power of an energy storage polymer is obtained through solution of the model prediction control (MPC) problems for a time in the future, and the finite time rapid distribution power control protocol is designed based on the sliding-mode control (SMC) method to allow the charging and discharging power of the energy storage in the polymer to rapidly track a target power so as to realize the target of smoothing the microgrid tie line power.

The invention relates to a method for designing an industrial alarm on basis of alarm evidence fusion, which belongs to the technical field of industrial alarm design. The method is based on a fuzzy subjection function to construct a fuzzy threshold, the measured values of a process variable at each moment are compared with the fuzzy threshold to calculate an alarm evidence, and the alarm evidence shows the uncertainty degree that the value of the process variable exceeds or is lower than the fuzzy threshold; a linear weighting evidence is utilized to update rules, the alarm evidence of the current moment is fused with the alarm evidence in the past time, so the whole alarm evidence of the current moment is obtained, the alarm is judged to be sent out or not according to related judgment standards, the fusion process can effectively reduce the influence of uncertainty, so the alarm accuracy is improved; and a test sample is extracted according to the measured data of the process variable. A method for finding out the optimal fuzzy threshold under the lowest false alarm rate and missing report rate standards is provided.

The invention discloses an adaptive UKF (Unscented Kalman Filtering)-based lithium battery SOC (State Of Charge) estimation method which comprises the following steps: performing a quick calibration experiment on a lithium battery, thus obtaining an SOC and OCV (Open Circuit Voltage) relation curve; building a model for the lithium battery to be detected, identifying parameters of a battery model through battery charging and discharging experiments, and building a discrete state space model of a battery system; estimating a battery SOC through an improved UKF algorithm. The method disclosed by the invention solves the problems of reduction of filtering precision and even generation of filtering divergence possibly due to the uncertainty and an unknown noise statistical property of the battery model in the UKF algorithm.

The invention discloses a high-speed switching receiving radio frequency channel group delay consistency method, and aims to provide a group delay consistency method which is universal, stable, reliable and small in distortion. The method is realized through the following technical scheme: in a receiving channel group time delay consistency circuit, customizing a microwave radio frequency switch meeting time and reliability requirements of high-speed switching receiving radio frequency channel group time delay consistency, and controlling switching time errors and switching time of the microwave radio frequency switch to be consistent; when the signal passes through the channel first-stage mixer, setting any one received signal frequency to be converted to a middle filter center frequencypoint through a local oscillator frequency mixing rate; using an MCU to send a multi-channel high-speed switching control command and a second pulse control command to a synchronous signal processingunit through an I/O direct control line; and the time of the channel state switching control command arriving at all control switches being consistent, so that the signal on-off time difference between channels caused by the time difference of the control command is reduced, and the channel delay consistency is improved.

The invention relates to a design method of a frequency converter alarm of a ship electric propulsion system, belonging to the field of ship safe operation and maintenance. At first, the historical data of the effective value of the A-phase input voltage of the frequency convert is converted into an alarm reliability vector by using a relational mapping transformation method, and the alarm reliability vector is then recursively fused at the current time with the alarm reliability vector at the past time by using the alarm reliability fusion rule, the fusion process can effectively reduce the influence of uncertainty and reduce the false alarm rate and missed alarm rate of the alarm device. The global alarm reliability vector at the current time is obtained and the global alarm reliabilityvector is used to determine whether the alarm is issued.

The invention discloses a cruising path planning system and method for an unmanned surface vehicle in a limited area, the cruising path planning system comprises a data preprocessing unit and a targetinformation searching system, the data preprocessing unit and the target information searching system are connected in two ways, and an input end of the data preprocessing unit is connected with output ends of a radar target track generating module and an AIS (Automatic Identification System) target track generating module. The invention relates to the technical field of maritime control. According to the cruising path planning system and method for the unmanned surface vehicle in the limited area, the optimal association effect is achieved through a dynamically regulated value of a track association part, the data association accuracy is improved on a certain degree, meanwhile, the filter techniqueis used to reduce the influence brought about by the indeterminacy of a model when a radaror an AIS acquires information of an obstacle and an unmanned surface vehicle, the robustness of a filtering algorithm is improved, the estimation speed is increased, and the neural network techniqueis used to approach the model in reality to the greatest extent.

The invention discloses a flexible multi-task proactive scheduling optimization method in a cloud manufacturing environment. The flexible multi-task proactive scheduling optimization method in the cloud manufacturing environment is oriented to a service provider and a service user, is used for optimizing task scheduling between the service provider and the service user, and comprises the followingsteps: establishing a fitness function based on time, cost and reliability; according to the fitness function, establishing a multi-task proactive scheduling objective function based on fitness, robustness and stability; and solving the multitask proactive scheduling objective function by adopting a GA algorithm. The service interruption problem is considered, optimization is carried out in combination with multiple targets, premature convergence in the target function optimization process is avoided while population diversity is guaranteed, and therefore a more robust and stable scheduling scheme is obtained.

The invention discloses a time slice-based task scheduling method. The realization method comprises the steps of: when a system detects a newly arrived task or task completion, performing re-initialization on task parameters of all tasks immediately; then splitting each task into sub tasks with reasonable execution time slice lengths; determining an execution sequence of the sub tasks and a processor for executing the sub tasks; and finally, updating a task scheduling list, scheduling task execution according to a new scheduling list, and feeding back task completion information to the abovementioned task parameter initiation part in time so as to promote to generate a new task scheduling list. The time slice-based task scheduling method can be used for an isomorphic multi-processor system.

The invention relates to a task scheduling method and device, and a computer readable storage medium. The task scheduling method comprises the steps of obtaining a plurality of to-be-scheduled tasks;determining service features, technical features and resource features related to each to-be-scheduled task; and performing dynamic task scheduling on the plurality of to-be-scheduled tasks accordingto the service features, the technical features and the resource features related to each to-be-scheduled task.

The invention relates to a servo self-adaptive control system and method for a supersonic wave motor in input saturation conditions. The system comprises a pedestal and a supersonic wave motor fixing rack used for fixing the supersonic wave motor, wherein the supersonic wave motor fixing rack is arranged on the pedestal, an output shaft on one side of the supersonic wave motor is connected with a photoelectric encoder, an output shaft on the other side is connected with a flywheel inertia load, the output shaft of the flywheel inertia load is connected with a force moment sensor via a shaft coupling device, and a signal output end of the photoelectric encoder and a signal output part of the force moment sensor are respectively connected to a control system. The control system consists of a backstepping controller and a motor, a whole controller system is built based on backstepping calculation, and therefore good control effects can be obtained. The servo self-adaptive control system and method for the supersonic wave motor in the input saturation conditions put forward in the invention is high in control accuracy, simple and compact in structure and good in using effects.

The invention relates to a thermal conduction model calibrating method based on double-deck nesting uncertainty propagation. The uncertainty optimization problem that when cognition uncertainty and inherent uncertainty exist in thermal conduction model input parameters at the same time, random variables exist in a target function is solved. The method includes the steps of firstly, obtaining the probability distribution function of an inherent uncertainty parameter A and the section of a cognition uncertainty parameter; secondly, generating a cognition uncertainty parameter sample ep; thirdly, generating an inherent uncertainty parameter sample a={aq/q=1,2,3...,n}; fourthly, generating model output data ysq(x/aq,ep); fifthly, calculating the consistency of the final model output data ys(x,A/ep) and reference data yr; sixthly, outputting the cognition uncertainty parameter ep as the calibration result. The method is applied to the field of thermal conduction models.

The invention aims to provide an economy scheduling model based on price demand response. The model is firstly based on the price elasticity coefficient to analyze the relationship between the price demand response scheduling cost and the interactive response quantity. Then, the interactive response quantity's static algorithm of the price demand response is described and used as one of the desired allocation rules. Based on that, in consideration of the network security constraint and the price demand response and the interactive response satisfaction constraints, the power grid side price demand response scheduling cost is used as the smallest goal, and a real-time optimization scheduling model is created to ensure the safe operation of the power grid in real-time scheduling.

The invention provides a lithium ion battery residual life integrated prediction method considering uncertainty, a data noise quantification method based on model prediction error decomposition is proposed and is applied to residual life prediction based on particle filtering by considering data uncertainty. In consideration the uncertainty of the model, a lithium ion battery residual life prediction method based on model integration is proposed. The method comprises a data acquisition step, an individual model construction step, a model weight acquisition step, an integrated model construction step and a prediction step, the degradation state of the battery capacity is predicted by using an integrated model, and a prediction result of the residual life is obtained according to a failure threshold value of the battery capacity. According to the method, a model integration method based on time varying and degradation weighting is provided, an integration model based on optimal model weighting can be established to reduce the model uncertainty influence caused by model selection, the data uncertainty caused by data noise is reduced, and the prediction accuracy and robustness of the residual life of the lithium ion battery are improved.

The invention relates to an experimental device and method for the measuring depression depth of a composite material after impact, and belongs to the technical fields of experimental mechanics and non-contact optical test of composite materials. According to the method, a grid line projection measuring technology is combined with an optical triangulation technology, a CCD camera is used to shoot photos of digital grid lines projected onto a plate of the composite material before and after impact, deformation and phase change of the digital grid lines at the surface of the composite-material plate before and after impact are measured by utilizing the phase measurement technology, the depth of an impact depression of the composite-material plate after impact is measured in the full field, and the impact resistance of the composite-field plate the full-field depth information of the depression after impact are obtained. The grid line projection measuring technology used in the invention includes non-contact full-field measurement, and compared with point contact measurement methods including a vernier caliper, a height gauge and the like, tedious procedures of measuring the depths of different positions for multiple times are avoided, influence of uncertainty of the maximal depression depth is reduced, and depth measurement for the depression after impact is more convenient, simpler and more accurate.

The invention relates to a fuzzy distribution method for the reliability of a radar system. The method comprises the steps of S1, defining a reliability index; S2, determining a sub-system set; S3, determining an influence factor set; S4, determining an influence factor weight; S5, determining an influence factor membership matrix; S6, fuzzily comprehensively judging the reliability; and S7, distributing the reliability of the radar system, wherein if the reliability index does not meet requirements, the reliability of the radar system is re-distributed, and if the reliability index meets requirements, reliability distribution is continuously performed on the sub-system. According to the method provided by the invention, a interval analytic hierarchy process and a fuzzy distribution methodare combined to form a reliability distribution method, interval numbers are used for describing uncertain information in the radar system, historical reliability data of similar products and valuable experience of experts are comprehensively considered, qualitative information and quantitative information are combined, and thus a distribution result is more accordant with or closer to the actualcondition, and the problem that the reliability index of the radar system is difficult to distribute effectively can be effectively solved.

The invention relates to an output feedback controller-based ultrasonic motor servo control method, comprising the following steps: S1: providing a base and an ultrasonic motor arranged on the base, wherein an output shaft at one side of the ultrasonic motor is connected with a photoelectric encoder, an output shaft at other side of the ultrasonic motor is connected with a flywheel inertia load, the output shaft of the flywheel inertia load is connected with a torque sensor through a coupling, and the signal output end of the photoelectric encoder and the signal output end of the torque sensor are respectively connected to a control system; S2: the control system being established on the basis of output feedback control, and a Lyapunov function being used as a tuning function on the controller are used for obtaining better control performance. The control system consists of a feedback controller and a motor, and the whole controller system is established on the basis of feedback calculation so as to obtain better control performance. The device and the control method thereof provided by the invention have the advantages of high accuracy, simple and compact structure and good service effect.

The invention discloses a permanent magnet synchronous motor L1 adaptive iterative learning control method, which comprises the following steps of: establishing a mathematical model of a PMSM, and on the basis of the mathematical model, designing an L1 adaptive learning controller as a feedback controller to compensate non-repetitive uncertainty of a system in a time domain so as to ensure the performance of the system along a time axis; and compensating system repetition uncertainty in an iteration domain by utilizing ILC, tracking a periodic input signal, and enabling an error to converge along an iteration axis. According to the permanent magnet synchronous motor L1 adaptive iterative learning control method adopting the above structure, L1 adaptive control is combined with ILC, and the problem that it is difficult to achieve ideal performance of a PMSM due to uncertainty of dynamic parameters is solved.

The invention relates to an ultrasonic motor fuzzy neural network control method based on a base function network, comprising a base and an ultrasonic motor arranged on the base. The output shaft at one side of the ultrasonic motor is connected with a photoelectric encoder, and the output shaft at the other side of the ultrasonic motor is connected with a flywheel inertia load. The output shaft of the flywheel inertia load is connected with a torque sensor through a coupling. The signal output ends of the photoelectric encoder and the torque sensor are connected to a control system. The control system is composed of a fuzzy neural network controller based on a recursive radioactive base function network and a motor. The system of the whole controller is established on the basis of the recursive radioactive base function network, a fuzzy neural network is taken as the adjustment function, and therefore, better control performance is achieved. The control accuracy is high, the structure is simple and compact, and the using effect is good.

The invention discloses an intelligent terminal and a demodulation method and device for Gaussian frequency-shift keying signal thereof. The method comprises the steps: carrying out the matching filtering of a receiving signal and all possible signal modes in the time period from nT to (n+3)T according to a phase estimated value (shown in the description) of the receiving signal and I<n-1>, and obtaining the optimal matching waveform of the receiving signal in the time period from nT to (n+3)T; judging I<n> according to the optimal matching waveform of the receiving signal in the time period from nT to (n+3)T; obtaining the maximum correlation value angle delta (theta<n>) of the receiving signal in the time period from nT to (n+3)T according to the receiving signal and the optimal matching waveform of the receiving signal in the time period from nT to (n+3)T; calculating the result of the following formula (shown in the description) according to the phase estimated value (shown in the description) of the receiving signal, I<n> and the maximum correlation value angle delta (theta<n>); carrying out the above steps in a circulating manner according to the result of the formula and I<n>; and obtaining all to-be-modulated data through recursion. The method integrates matching filtering and angle iteration, employs the maximum correlation value angle delta (theta<n>) obtained in matching filtering to participate the angle iteration, carries out frequency loop tracking, and reduces the influence caused by frequency changes.

The invention relates to a limit cycle suppression design method for an ultrasonic motor servo control system based on a gain limiting compensator. An ultrasonic motor is arranged; an output shaft atone side of the ultrasonic motor is connected with a photoelectric encoder and an output shaft at the other side of the ultrasonic motor is connected with a flywheel inertial load; the output shaft ofthe flywheel inertia load is connected to a torque sensor via a coupler; and a signal output terminal of the photoelectric encoder and a signal output terminal of the torque sensor are respectively connected to a control system. The control system is established based on a gain limiting scheme; and with the compensator, the limiting cycle of the servo system is minimized, so that the good servo control performance is obtained.