43 results about "Uncertain systems" patented technology

The invention discloses a saturated self-adjusting controller for a time-varying delay uncertain system. The controller comprises three parts, namely a self-adjusting limiter, a conventional PID controller and an anti-integral saturator, wherein the conventional PID controller generates a control command uc(t) according to the offset of the controlled parameter y(t) and a target value r(t) thereof; the self-adjusting limiter calculates a steady-state gain K of a time-varying delay uncertain object under the corresponding working condition under the driving of a working condition variable s(t), dynamically generates a limiting value according to the K and r(t), timely limits the uc(t) and generates a final control function u(t); and the anti-integral saturator limits the integral function in the PID controller according to the offset of the uc(t) and u(t) in order to solve the possible integral saturation problem. By applying the invention, an engineering technician can conveniently apply effective control to a class of time-varying delay uncertain systems widely present in the process industry on an industrial control system (device) or in the mode of combining a hardware circuit with software programming so as to improve the safety and operating level of the production process.

The invention discloses a method for setting a fractional-order PID (proportion, integration and differentiation) controller for a parameter uncertainty system which is a controlled object. The fractional-order PID controller is applied to the parameter uncertainty system which is the controlled object. The method is used for optimally setting to-be-set parameters of the fractional-order PID controller, and includes firstly determining stability regions of parameters of the system; secondly, determining frequency and parameter variation ranges of the stability regions of the parameters of the system; thirdly, optimally setting the parameters of the controller by a genetic algorithm. The method for setting the parameters of the fractional-order PID controller on the basis of the parameter uncertainty system has the advantages that the parameters of the fractional-order controller can be effectively set when the controlled object is the parameter uncertainty system, the dynamic performance of the system can be optimized, and the fractional-order controller can realize a good control effect and is excellent in dynamic performance.

The invention relates to a simulating device and a simulating method for pipeline leakage acoustic emission signals, and belongs to the technical field of acoustic emission inspection. One end of a pipeline is sealed, and the other end of the pipeline is connected with the pressurized air charging device. A leakage hole capable of adjusting air leakage quantity is formed in the surface of the pipeline. A waveguide rod with a sensor is mounted on the surface of the pipeline and is away from the air leakage hole by certain distance. One end of the waveguide rod is connected with an acoustic emitter. Leakage acoustic emission signals detected by the simulating device are decomposed by an HHT and then subjected to BP network training to acquire classification results, so that simulation of the pipeline leakage acoustic emission signals is realized. By the simulation method and the simulation device, organization structure and operation mechanism of human brains are simulated in terms of microstructure and function, so that nonlinear systems and uncertain systems can be described well.

The invention relates to a method of a DC motor networked tracking controller. The method comprises the steps of (1) establishing a DC motor discrete system state equation with the consideration of atime-varying network induced delay, describing the DC motor system as a discrete-time norm bounded uncertain system with a one-time input delay, and using an uncertain system method to process an exponential time-varying problem in a motor state equation, (2) establishing a closed-loop system model of a DC motor networked tracking control system containing uncertainties, wherein the closed-loop system is an uncertain augmented closed-loop system with the one-step input delay, and (3) designing the DC motor networked tracking controller including the steps of firstly carrying out H-infinity performance analysis on the closed-loop system to verify stability and then designing the networked tracking controller, wherein the time delay is divided into a mean part and an uncertainty part in modeling, a networked control system is described as a class of discrete-time norm bounded uncertain system, and a networked H-infinity tracking control strategy is used to design a state feedback controller.

The invention relates to a multiple sectioned Bayesian network-based electronic circuit fault diagnosis method. Common electronic circuit fault diagnosis methods include a fuzzy set fault dictionary method, a neural network approach, a Bayesian network method and the like, and have low fault resolution, interpretability and real-time property. The method comprises the following steps of: setting two adjacent fault diagnosis reasoning credibility threshold parameters, and determining the number of intelligent agents; obtaining Bayesian subnetwork structures, mapping a fault cause source to each Bayesian subnetwork, and learning credibility condition probability parameters among nodes of a Bayesian subnetwork model by using an expectation-maximization (EM) algorithm; using nodes corresponding to overlapped signals as overlapped subareas of the network to form a complete multiple sectioned Bayesian network (MSBN) so as to construct a linked junction forest; and inputting respective k target characteristic signals serving as observation evidence into each Bayesian subnetwork. A spatial multi-source information fusion method is adopted, the fault diagnosis capacity of a system is improved, the method is suitable for complicated and uncertain systems, and the fault diagnosis accuracy and speed are greatly improved.

The invention provides a ship path tracking control method for uncertain systems. External interference, model uncertainty and uncertain system parameter problems are solved at the same time. Startingfrom the description of a mathematical model of the ship and considering the subsistent influence of non-zero drift angles on course angles in the tracking process, a self-adaptation law is introduced to solve the uncertainty and interference problems, and the tracking performance is guaranteed by combining a controller designed based on a backstepping method. According to the control algorithm,suppression control on interference and uncertainty can be effectively realized, so that the tracking error is gradually changed to zero, and high-precision trajectory tracking control is guaranteed.

A vehicle stability control method for a traveling system with uncertainties which Contains the following steps: Collecting vehicle driving state information, according to the two-degree-of-freedom model, expressing The uncertainties of the analytical system of the vehicle model as linear uncertain systems, Taking the deviation between the actual value and the expected value of the state quantityas the input of the robust optimization vehicle stability controller, obtaining the expected value of the control quantity required for vehicle stability by using the suboptimal control method, and distributing the tire force by the pseudo-inverse distribution method, and finally executing the tire force distribution result by the actuator.

The invention provides a rapid active disturbance rejection method for air cavity pressure based on an extended state observer. The method is suitable for intake and exhaust pressure control of a typical engine transition state test task, and mainly comprises the following steps of constructing a control model of an air cavity pressure system based on linear active disturbance rejection control, and estimating total disturbance (the sum of internal disturbance and external disturbance) influencing a controlled quantity in real time through an extended state observer, dynamically transforming an original uncertain system into an ideal integral series system through a special state feedback mechanism, estimating disturbance by utilizing natural advantage predictability and disturbance rejection of a linear active disturbance rejection controller, and updating the convergence rate and the global search capability through an improved whale algorithm, and immediately eliminating disturbanceby using the controlled quantity, so that the purpose of rapid and active disturbance rejection is achieved. Technical support can be provided for follow-up complex control technology research such as aircraft engine transition state test environment simulation multivariable control and dynamic decoupling control.

The invention provides a hybrid state estimation method for a high-dimensional deep coupling uncertain system, which comprises the following steps of: firstly, constructing a state, parameter and measurement model of the high-dimensional deep coupling uncertain system, and designing a corresponding observer model to obtain estimated values of the state and the parameter; secondly, discretizing thesystem to decompose the system into a low-dimensional discretized hybrid model, and further obtaining the low-dimensional discretized hybrid model and a parameter model; and finally, taking the observer output estimation value as an auxiliary signal, performing filtering processing on the state estimation value of the low-dimensional discretization hybrid model by using a volume Kalman filteringalgorithm, and outputting a state value of the low-dimensional discretization hybrid model. According to the method, the system model is corrected through the estimated value output by the observer, the system state estimation precision can be effectively improved on the premise that the system stability is guaranteed, meanwhile, the calculation dimension of the filtering calculation process is reduced through the low-dimensional volume Kalman filtering algorithm, and the method is suitable for high-dimensional, coupled and nonlinear system state estimation with uncertainty.

The invention discloses a finite time remote security state estimation method for a time delay uncertainty system. The method comprises the steps of establishing a controlled system state space model;establishing a state estimator system model and a computing center, and carrying out a state estimation task; establishing an extended state estimation model of the extended state estimation system;providing existence conditions of the finite time remote safety state estimator through an energy function in combination with a bounded judgment auxiliary equation; and designing a state estimator algorithm through the steps of giving system parameters, initializing parameters, solving an inequality group, modifying the initializing parameters and the like, generating a remote security state estimation strategy, and achieving finite time remote safety state estimation of the time delay uncertainty system. According to the invention, the robust finite time security state estimation of the timedelay uncertainty system based on the remote transmission data can be ensured, and the timeliness and reliability of the state estimation under the remote data transmission mode with the network attack are realized.

The invention relates to a prediction method and particularly relates to a Chinese chemical fertilizer price index prediction method based on a BP neural network, belonging to the technical field of time sequence prediction. According to the technical scheme provided by the invention, the Chinese chemical fertilizer price index prediction method based on a BP neural network comprises the following steps: (a) training the BP neural network by use of the historical data of the Chinese chemical fertilizer price to obtain a price index prediction model; and (b) predicting the price index by use of the price index prediction model. The method provided by the invention needs consideration of statistical property calculation and can be theoretically applied to the modeling of any non-linear time sequence; with a unique non-traditional expression way and inherent learning ability, the method has tremendous advantages in controlling highly non-linear and seriously uncertain systems; and the method realizes high accuracy of predicting the Chinese chemical fertilizer price index.

The invention relates to the technical field of agricultural machinery, and specifically relates to an intelligent agricultural machinery fertilization method and device based on the Internet of things. According to the invention, an agricultural information server terminal sends water and fertilizer ratio information and motor speed recommendation information to a main control module through a wireless signal module according to a geographical location information matching result, a water and fertilizer ratio module builds a neuron structure model, the main control module controls the water and fertilizer ratio module, a speed control module and a liquid pump on the basis of the neuron model and controls an agricultural machinery fertilization device to perform a fertilization operation by combining an environment compensation module, an Internet of things monitoring terminal realizes remote operation monitoring through a GPS data terminal switch and a man-machine interaction unit, the water and fertilizer ratio module is controlled to realize different ratios, the motor is controlled to realize different rotating speeds and the liquid pump is controlled to realize different operating conditions according to the recommended operation information, uncertain systems can be learnt and adapted by using the neural network, a method basis is provided for variable rate fertilization, and the scientificity and the reliability of the operation are improved.

The invention discloses a pressure big data intelligent detection system based on the Internet of Things, and the system is characterized in that the system comprises a parameter collection platform and a pressure big data processing subsystem, the system achieves the pressure detection and intelligent prediction, and improves the reliability and accuracy of pressure detection and prediction; according to the invention, the problem that accurate detection and reliable management of multi-point pressure are greatly influenced due to the fact that existing pressure detection is not influenced by an uncertain system which is strong in interference, large in lag and nonlinear according to multi-point pressure detection is effectively solved.

The invention discloses a tension detection and intelligent control system which is characterized in that the control system comprises a parameter acquisition and control platform and an intelligent tension control subsystem, and the control system achieves intelligent control over the winding speed and tension detection of yarn and the tension of the yarn. The reliability and accuracy of yarn winding process measurement and yarn tension control are improved; the method effectively solves the problem that accurate detection and reliable control of the tension detection and control process are greatly influenced due to the fact that an existing tension detection and control process is not influenced by a non-linear uncertain system with large fluctuation, large lag and large fluctuation of the tension in the spinning process.

The invention discloses a material weighing large data detection and packaging intelligent control system which is characterized in that the system comprises a parameter acquisition and control platform and a packaging intelligent control subsystem, and intelligent control over the weight detection and packaging process of packaged materials is achieved. The reliability and accuracy of weighing and packaging in the material packaging control process are improved; the method effectively solves the problem that accurate operation and reliable management of the material weighing and packaging process are greatly affected due to the fact that the existing material weighing and packaging process does not have the influence of a non-linear uncertain system with strong interference and large lag in the material weighing and packaging process on accurate weighing and reliable packaging of the material.