142 results about "Fuzzy logic system" patented technology

According to a first aspect of the invention there is provided a method of decision-making comprising: a data input step to input data from a plurality of first data sources into a first data bank, analysing said input data by means of a first adaptive artificial neural network (ANN), the neural network including a plurality of layers having at least an input layer, one or more hidden layers and an output layer, each layer comprising a plurality of interconnected neurons, the number of hidden neurons utilised being adaptive, the ANN determining the most important input data and defining therefrom a second ANN, deriving from the second ANN a plurality of Type-1 fuzzy sets for each first data source representing the data source, combining the Type-1 fuzzy sets to create Footprint of Uncertainty (FOU) for type-2 fuzzy sets, modelling the group decision of the combined first data sources; inputting data from a second data source, and assigning an aggregate score thereto, comparing the assigned aggregate score with a fuzzy set representing the group decision, and producing a decision therefrom. A method employing a developed ANN as defined in Claim 1 and extracting data from said ANN, the data used to learn the parameters of a normal Fuzzy Logic System (FLS).

The invention discloses a robust adaptive underactuated surface ship path tracking control method based on a fuzzy unknown observer. The robust adaptive underactuated surface ship path tracking control method based on the fuzzy unknown observer comprises the following steps that an unmanned ship kinematics and dynamics model is established; a path tracking error dynamic state is built; a line-of-sight guidance law with variable speed is proposed; a fuzzy logic system is established; and a controller based on the fuzzy unknown observer is designed. In a guidance subsystem, the line-of-sight guidance law with the variable speed is proposed, the control flexibility and robustness of a guidance system are improved, and the position error is enabled to be asymptotically stabilized to zero; andin a control subsystem, the fuzzy unknown disturbance observer is designed to estimate the unknown disturbance quickly and accurately, and effective compensation is carried out on the designed speed and a heading controller, so that the tracking error between a guidance signal and actual quantity is asymptotically stabilized back to zero. The involved algorithm framework can enable a whole closed-loop system to be globally asymptotically stabilized, and the control flexibility and tracking accuracy of a path tracking control system are greatly improved.

A system for intelligent market trading implemented with a neural network system (Machine Learning) comprising an input, one or more processors and an output. The input comprises a database of price of a symbol and a pair in a timeframe. The first processor is configured to receive the respective input to generate a technical analysis, a trading signal, and a market report with a probability value. The second processor generates a coefficient for regulating the probability value of the generated trading signals and technical analysis using fuzzy logic systems alongside of a neural network system. The third processor computes the correlation coefficient of symbols under Mesh topology and regulates the resultant probability value of each trading signals and technical analysis. The output comprises a processor to receive and evaluate the individual resultant probability values of the generated trading signals and technical analysis and delivers an output data. The output data is sent via notification to a user for detecting a suitable spot for placing their orders in the financial market.

This invention relates to one automatic exposure method based on multiple cutting and blur logics in digital imaging technique field, which comprises the following steps: dividing digital image area according to human face mode and Gauss mode into six areas and processing sum computation according to image exposure and its grey rectangle distribution by cutting near grey values between 0 and 255; representing its result for each area exposure evaluation and leading blur logic system to integrate each area grey information to get each area of different weight; finally computing to get whole image automatic exposure judge result.

A method and apparatus for the onsite assessment of sensory data during the drilling of a subterranean well to determine when a drilling tool has reached an optimal drilling terminus. One or more sensory data streams are captured and monitored by a terminus decision module, which identifies the appropriate combinations of sensory readings which might indicate that the drilling tool has reached an optimal drilling terminus. The terminus decision module might be either a coded formula-based software component, or might use a fuzzy inference or “fozzy logic” system in the assessment of sensory data. The need for offsite or offline engineering assistance is removed. In addition to the method, both a stand-alone apparatus as well as an add-on instrumentation kit for a PC otherwise in use at the drilling site are disclosed. The system of the present invention could be used in single or multi-axis drilling applications, and could be integrated with the depth or location control system for the drilling tool to automatically adjust the positioning or attributes of the tool.

The invention discloses a control method of a driving system of a permanent magnet synchronous motor of an electrical automobile considering iron loss, and provides a control method of a driving system of a permanent magnetic synchronous motor considering iron loss based on a self-adaptive fuzzy backstepping method, which solves the non-linear problem of the power driving and control system of the motor of the electrical automobile, enables the motor to quickly reach the stable running state and is more suitable for the control objects requiring quick dynamic response, such as the driving system of the electrical automobile. The control rules u[d] and u[q] only adopt one self-adaptive parameter theta, so as to reduce the calculation amount. The method has the advantages that the problem of position tracking and control of the permanent magnet synchronous motor considering the iron loss under the conditions of orienting to the site and having undetermined parameter and load torque disturbance is solved; the fuzzy logic system is used for approximating to the unknown non-linear item, and the self-adaptive fuzzy backstepping method is used for enabling the tracking error to approximate to 0; the more accurate control precision is reached, and the ideal position tracking and control effect is ensured.

The present invention discloses an electric vehicle asynchronous motor fuzzy adaptive dynamic surface control method with the consideration of an iron loss. According to the control method, by using the nonlinear function in a fuzzy logic system approximation system, an adaptive backstepping method is used to design a controller, and the dynamic surface control technology and a fuzzy adaptive method are combined. Through introducing a first-order low-pass filter, a 'computing explosion' problem caused by continuous derivation in traditional backstepping control is successfully overcome. In addition, control signals uqs and uds only exist in an adaptive parameter Theta<^>, and the amount of computation is reduced. Through fuzzy adaptive dynamic surface control method adjustment, motor operation can rapidly reaches a stable state and is more suitable for a control object with the need of rapid dynamic response like an electric vehicle driving system, a simulation result shows that the influence of parameter uncertainty is overcome and an ideal control effect is ensured according to the control method, and the rapid and stable response of rotation speed is realized.

The invention discloses a self-adaption strong tracking unscented kalman filter (UKF) positioning filter algorithm based on fuzzy logic. The self-adaption strong tracking UKF positioning filter algorithm comprises the steps that: (1) a positioning filter model is built; (2) initial parameters of a filter are set; (3) the state quantity is subjected to filtering by adopting the UKF filter algorithm; (4) a fuzzy logic system is used for solving softening factors in the self-adaption tracking algorithm; (5) the self-adaption factors in the strong tracking self-adaption algorithm are solved; and (6) the epoch moment is increased by 1, the next moment observation is read, and the operation returns to the step (4) until the operation is completed. The strong tracking self-adaption algorithm in introduced on the basis of the UKF filter algorithm, in addition, a novel recursive algorithm is adopted in the strong tracking self-adaption algorithm for estimating the information covariance matrix, and the softening factors in the strong tracking algorithm are solved through a fuzzy logic reasoning system and are estimated in real time according to the work state of an epoch moment filter. The estimation is carried out in satellite navigation user receiver position estimation, and the positioning performance and the capability of carriers adapting to the dynamics can be greatly improved.

The invention discloses a reentry vehicle PID (proportion, integration and differentiation) type sliding mode posture control method based on self-adaptive fuzziness, relates to a PID type sliding mode posture control method of reentry vehicles and belongs to the technical field of vehicle control. Aiming at parameter adjusting characteristics of a PID type sliding mode function, PID type sliding mode parameters are enabled to have time-variant characteristics, so that a system is ensured to output tracking instruction information quickly while the problems of system overshoot and control input saturation of the system are avoided. A global sliding mode algorithm is introduced to improve a PID type sliding mode dynamic equation, so that robustness of a conventional PD sliding mode is enhanced. By applying a self-adaptive fuzzy logic system, the system is ensured to output the tracking instruction information quickly, response overshoot and control input saturation of the system are avoided, tracking errors can be reduced, and robustness of the conventional PD sliding mode can be improved.

The invention discloses an input saturation considered asynchronous motor command filter finite time fuzzy control method. Aiming at nonlinear problems of a motor driving and control system, a fuzzy logic system is adopted for approximation to a nonlinear function in the system, a command filter technique is introduced into a traditional backstepping design method, errors generated in filtering are reduced through introduction of a compensation mechanism, the problem of computation explosion caused by continuous derivation in traditional backstepping control is successfully solved, and control precision is improved. Small system stable tracking errors and short dynamic responding time under finite time control are realized, system convergence rate is increased, and interference rejection capability is improved. Under the condition of consideration of input saturation, bounded parameters of a closed-loop system can be guaranteed, and convergence of tracking errors of the system into a sufficiently small origin neighborhood in finite time can be guaranteed as well.

The invention discloses an observer-based adaptive command filter control method for output consistency of a multi-single-arm manipulator. Modeling of dynamic characteristics of a multi-single-arm manipulator is performed; and an adaptive controller is designed by combining a backstep method with a command filtering technique. During the controller design process, an unknown item of the system approximates by using a fuzzy logic system, so that the need of the precise dynamic model of the manipulator is eliminated. A state observer estimates an unmeasurable state in the system. With the command filtering technique, a complicated signal derivation calculation explosion problem is solved. Since the manipulator system output is restricted, an output restriction problem is solved by using an obstacle Lyapunov function. For a mechanical connection part of the manipulator, the driver always has a non-smooth input dead zone problem; and the influence on the system by the input dead zone is compensated by using the slope information of the input dead zone. The manipulator system output can track the reference signal effectively; and all signals are semi-globally bounded ones.

The invention relates to a device for detecting the leakage of an oil-gas pipe network based on type-2 fuzzy logics and a method. The device comprises a data acquisition unit, a signal filtering plate, an A / D (Analog to Digital) conversion unit, an FPGA (Field Programmable Gate Array), a level conversion unit and an upper computer, wherein the data acquisition unit comprises a pressure sensor, a flow sensor, a density sensor, a digital sensor which is used for acquiring the state of a pump and a digital sensor which is used for acquiring the opening degree of a valve; the signal filtering plate comprises a filter, a multi-way switch and a signal amplification circuit; and output terminals of all the sensors and an output terminal of the digital sensor which is used for acquiring the opening degree of the valve are all connected to an input terminal of the filter, an output terminal of the filter is connected with one terminal of the multi-way switch, the other terminal of the multi-way switch is connected with an input terminal of the signal amplification circuit, an output terminal of the signal amplification circuit is connected with the FPGA through the A / D conversion unit, and the FPGA is connected with the upper computer through the level conversion unit. According to the device and the method, the leakage detection on the oil-gas pipe network is carried out by adopting a type-2 fuzzy logic system, the current state of the pipe network is judged, and thus, the accuracy of detection can be improved.

The invention discloses an electric car permanent magnet synchronous motor command filtering fuzzy control method taking iron loss into account. According to the fuzzy control method, a command filtering technology is introduced in a traditional back-stepping design method, error caused by filtering is reduced by introduction of compensation signals, and a problem of 'calculation explosion' caused by continuous derivation in the traditional back-stepping control is overcome successfully. In the control method provided by the invention, a fuzzy logic system is used for approaching a nonlinear function in the system, a command filtering back-stepping technology and a fuzzy self-adaptive method are combined together to form a fuzzy self-adaptive speed controller; after being regulated by the control method provided by the invention, a motor can quickly run in a steady state, and the control method is more suitable for a control object needing fast dynamic response, such as an electric car drive system; simulation result shows that, with the control method provided by the invention, influence caused by inaccuracy of parameters can be overcome, ideal control effect is guaranteed beneficially, and fast and steady response to revolving speed is realized.

The invention discloses an observer-based command filtering error compensation fuzzy control method of an induction motor. Aiming at the problem of non-linearity existing in a driving and control system of the induction motor, a command filtering technology is introduced to a traditional backstepping design method; and meanwhile, by an error compensation mechanism, an error caused by filtering is reduced, so that the control accuracy is improved, and the problem of calculation explosion caused by continuous derivation in traditional backstepping control is successfully solved. According to the method, the rotor angular speed of the induction motor is estimated by a dimension reduction observer; meanwhile, a fuzzy logic system approaches to a non-linear function in the motor driving system, and the command filtering backstepping technology is combined with an adaptive method to construct a controller; after regulation by the method, the motor running can rapidly reach a stable state; and a simulation result shows that by the method, the influence of parameter inaccuracy can be solved, an ideal control effect is favorably ensured, and the rapid and stable response to a rotation speed is achieved.

The invention discloses a command filter limited time fuzzy control method of a permanent magnet synchronous motor. The control method is capable of, in allusion to the existent nonlinear problem in a motor drive and control system, introducing a command filter technology into the traditional backstopping design method, and successfully overcoming the problem of 'computation explosion' in the traditional backstopping control caused by the continuous derivation. A fuzzy logic system is used for approaching the nonlinear function in the system, and the command filter backstopping technology is combined with a fuzzy self-adaption method to construct a fuzzy self-adaptive controller; the limited time method has the anti-interference performance and the robustness to the signals, such as the external load interference; and under the limited time control, the system stability tracking error is small, the dynamic response time is short, and the convergence rate and the interference rejection capability of the system are improved. Compared with the prior art, the control method has the faster response speed, the stronger anti-interference performance and the better tracking effect.

The invention relates to a non-linear self-adaptive flight control method belonging to the technical field of near-space aircraft flight control. According to the invention, with regard to problems of indeterminate parameters in vertical control of near-space aircrafts, and with consideration given to advantages of sliding-mode control over non-linear system control and the feature that interval second-type fuzzy control with nondeterminacy fuzzy sets is especially suitable for solving problems of nondeterminacy, a second-type fuzzy control system is combined with sliding-mode control and self-adaptive control to design a flight controller to enable the flight controller to have better control performance. The stability and robustness of the near-space aircrafts are raised.

The invention discloses a mechanical hand robust tracking control method based on a self-adaptive fuzzy sliding mode. The mechanical hand robust tracking control method adopts sliding mode control torealize mechanical hand trajectory tracking, regulates switching gain of a sliding mode control algorithm through a self-adaptive fuzzy logic system, and reduces sliding mode control buffet; and a robust controller is adopted to compensate for un-modeled dynamics and external disturbances. According to simulation experiment performed by a two-freedom mechanical hand, a sliding mode control input signal is smooth under action of the mechanical hand robust tracking control method based on the self-adaptive fuzzy sliding mode, so that the mechanical hand has higher trajectory tracking precision.

The invention provides a non-model robot multi-peg-in-hole assembly control method capable of using environment forecasting for optimization, and belongs to the robot assembly technology field. The non-model robot multi-peg-in-hole assembly control method capable of using the environment forecasting for the optimization uses a universal operating value function for forecasting environmental related knowledge, designs a fuzzy logic system according to human assembly experience, uses learned knowledge forecast as input, and outputs parameters used for optimizing a non-model control algorithm, and when the number of iterations of a deep reinforcement learning network reaches the upper limit and assembly meets requirements, the deep reinforcement learning network after completing training is output and used for outputting assembly action during the multi-peg-in-hole assembly process. The non-model robot multi-peg-in-hole assembly control method capable of using the environment forecasting for the optimization can achieve optimization for the existing non-model robot control algorithm, and shortens time needed in multi-peg-in-hole assembly of a robot.

The invention discloses an adaptive fuzzy backstepping tracking control method of an active power filter, relates to controllers of the active power filter and particularly provides an adaptive fuzzy backstepping tracking control method, combining adaptive control, fuzzy control and backstepping control and aiming at a three-phase active power filter. For shortcomings of a backstepping control law design, a fuzzy logic system is utilized to approach an unknown nonlinear function, and the fuzzy logic system is adjusted on line according to an adaptive law, so that harmful effects on the system due to parameter uncertainty are avoided. An adaptive fuzzy backstepping controller enables a compensating current to track an instruction current signal in real time, stabilizes the tracking deviation in neighborhoods of 0 and utilizes the Lyapunov method to analyze the stability and the convergence of the system so as to guarantee that all signals in a closed-loop system has global asymptotic stability.

The invention discloses a control method of an MEMS (micro-electromechanical system) micro-gyroscope based on direct self-adaptive fuzzy control. A control system of the MEMS micro-gyroscope based on direct self-adaptive fuzzy control comprises a direct self-adaptive fuzzy controller, and is characterized in that: the direct self-adaptive fuzzy controller comprises a basic fuzzy controller which is built by a fuzzy logic system and is used for approximating an ideal controller of the MEMS micro-gyroscope, and a D (digital) controller which is used for ensuring that the state of a gyroscope system is bounded. In the control system of the MEMS micro-gyroscope based on direct self-adaptive fuzzy control, the direct self-adaptive fuzzy control method is applied to gyroscope control. The knowledge and the experience of experts can be combined with the fuzzy controller, and parameters in the fuzzy system are self-adaptively adjusted by a Lyapunov-based method, thereby the stability of the fuzzy control system is ensured. The fuzzy controller can be widely applied to the MEMS gyroscope control to improve the stability and the reliability of the system, and has great value in use in industry.

The invention discloses a wind profile radar echo spectrum reconfiguration method based on fuzzy logic recognition. The wind profile radar echo spectrum reconfiguration method includes the specific steps: rapidly performing median filtering on wind profile radar echo power spectra; extracting turbulent echo by means of fuzzy logic recognition according to difference among turbulent signals in echo signals and clutter (ground clutter, intermittent clutter and radio frequency interference) signals in terms of spectral continuity, spectral intensity, spectral position and spectral width; fuzzingsubordinate functions of the spectral intensity and the spectral continuity for the echo power spectra, converting the subordinate functions into a spectral intensity fuzzy basis and a spectral continuity fuzzy basis and recognizing a fuzzy logic system by the aid of the fuzzy bases serving as substitute values of actually detected power spectra; and calculating wind profile radar turbulent echo signal moment data including noise level, signal-to-noise ratio, first moment and second moment by means of performing Gaussian least square fitting on turbulent echo spectral peaks recognized by the aid of fuzzy logic. By the aid of the wind profile radar echo spectrum reconfiguration method, turbulent echo signals without clutter interference can be acquired, and the detection height of an atmospheric wind field is effectively increased.

The invention belongs to the soil humidity inversion method and particularly relates to the soil humidity inversion method aiming for the ultra wide band radar echo. The soil humidity inversion method aiming for ultra wide band radar echo comprises steps of obtaining near-real-time echo data by using the characteristics of short pulse, strong penetrability, and anti-interference of the ultra wide band radar, utilizing a fuzzy logic system to study and extract characteristic parameters of a membership function from the echo data, and inverting soil volume water content through performing template matching on the membership function. The method provided by the invention is accurate and fast and low in cost, and can monitor the changing of the soil humidity in unattended operation for long time. The low cost of the invention is applicable to generalization and applicable to the assembled radar sensing network performing real time monitoring on the big area soil humidity, and, as a result, the invention provides a reliable mean to realize the accuracy agriculture.

The invention belongs to the field of wireless sensor network node movement, and discloses a wireless sensor network node combined movement algorithm based on a genetic fuzzy tree. The algorithm comprises the steps of firstly, performing sensor network task allocation: inputting performance indexes of sensors Si, performing comprehensive scoring on the performance indexes by using a fuzzy logic system A, moving the front N sensors Tn having the highest comprehensive scores, and keeping the remaining sensors still; secondly, performing sensor combined route planning: solving the distance between the sensor Tn and a target and the distance between the sensor Tn and the sensor Tj, processing the distance values as an input of a fuzzy logic system B, and outputting the obtained movement distance value of the sensor Tn, wherein the movement direction of the Tn is determined by the Coulomb's law; and finally, optimizing the fuzzy logic system A and the fuzzy logic system B in the fuzzy logic tree by using a genetic algorithm, so that a rule library and a database are adaptively changed, and the combined route planning time is shortest. By adopting the algorithm, the positioning and tracking performance of the network on the target can be effectively improved.

The invention discloses a wireless sensor network routing method based on fuzzy logic. Each turn of data collection process comprises the following steps: (10) cluster initial dividing: each sensor node generates a random numb, if the random number is less than a given threshold, the current node state is translated into a candidate cluster head node, and the normal state node selects the candidate cluster head node nearby to add in the cluster; (20), mobile gateway location information broadcasting: a mobile gateway broadcasts the own location information, the sensor node computes the distance to the mobile gateway node after receiving the mobile gateway location; (3) cluster head selection: selecting a cluster head node of each cluster by adopting a fuzzy logic system model according thea state parameter of each cluster member; and (40), data collection: the data is collected by the sensor node, and is uploaded to a base station by the mobile gateway after being aggregated and fusedat the cluster head node. The routing method disclosed by the invention is balance in energy load, small in energy consumption and long in network life cycle.

The invention discloses a low-background spectrum unscrambling method based on a sodium iodide detector. The method comprises the following steps: (1) a gamma detector after energy calibration actually measures a radionuclide spectrum and a natural background spectrum, and noise reduction is carried out; (2) a deconvolution algorithm is adopted to process a gamma energy spectrum after noise reduction; (3) a peak searching algorithm carries out searching on all potential peak positions of the gamma energy spectrum after noise reduction, and a peak position list is acquired; and (4) the peak position list information and a nuclide library are combined to be together inputted to a fuzzy logic system, the system gives the peak position recognition confidence for any nuclide characteristic peakin the nuclide library, constraints are set to further adjust the peak position recognition confidence, and thus, a nuclide list and the nuclide recognition confidence are acquired. The low-background spectrum unscrambling method based on the sodium iodide detector has the advantages of accurate peak position reduction, remarkable improvement of energy resolution, decomposition of an overlapped peak, low error recognition rate, accurate background nuclide analysis and accurate low activity nuclide analysis, and can be used for nuclide recognition and activity calculation for radiation monitoring equipment such as a gated radiation monitor and a nuclide recognition instrument.

The invention discloses an adaptive event trigger control method for a nonlinear uncertain system, which comprises the steps of firstly, for an input saturation phenomenon, adopting a smooth hyperbolic tangent function to approximate the saturation characteristic of system control input so as to avoid the phenomenon of unsmooth control input and facilitate the subsequent design; secondly, for an uncertain part of the system, improving the traditional Fuzzy Logic Systems (FLSs) to a certain extent, and taking the time-varying approximation error of an approximation system into consideration; finally, providing an event trigger control mechanism of a dynamic threshold for the bandwidth constraint existing in the actual system, wherein the trigger threshold changes along with the change of the control quantity at the last moment, so that more precise and flexible control can be realized, and the system bandwidth resources can be better saved on the basis of ensuring the control effect.

The invention belongs to the technical field of robot control, and specifically discloses a force / position hybrid control method of a multi-mechanical arm system based on command filtering. The methodis based on the Lyapunov function, an anti-step method is used for constructing an intermediate virtual control signal, gradual recurrence is carried out to obtain a control law, and therefore an endeffector of multiple mechanical arms is controlled. A fuzzy logic system is used for processing an unknown nonlinear function in the multi-mechanical arm system, and meanwhile, a command filtering technique is used for solving the problem that a second derivative of the actual position of a desired object does not exist. The method can ensure that a position tracking error and an internal force adjustment error of the object are converged to a sufficiently small neighborhood around an original point. In summary, by means of the force / position hybrid control method of the multi-mechanical armsystem, effectivity under various working conditions is achieved, the object accurately tracks a desired trajectory, and the internal force borne by the object is controlled within a reasonable range.

The invention discloses an asynchronous motor command filtering fuzzy control method based on state constraints. An obstacle Lyapunov function is constructed to ensure that the rotor angular velocity,stator current and other state variables of an asynchronous motor drive system are always within a given state interval. A command filtering technology is introduced to overcome the 'computation explosion' problem which cannot be avoided by the traditional back-stepping method, and a filtering error compensation mechanism is introduced to eliminate the influence of filtering error. A fuzzy logicsystem is adopted to approximate a nonlinear term in the system, and a command filtering fuzzy controller is constructed. In addition, a more accurate model is used in view of the iron loss of the asynchronous motor. The simulation results show that the method not only can achieve an ideal position tracking effect, but also can avoid safety problems caused by the violation of state constraints byconstraining the rotor angular speed, stator current and other state variables within a given constraint interval.

The invention discloses a back-step self-adaptive fuzzy sliding-mode control method of an under-actuated aerial autonomous underwater vehicle (AUV) under composite disturbance. The back-step self-adaptive fuzzy sliding-mode control method comprises the steps of building a kinematics and kinetic model of the AUV, and building a Serret-Frenet coordinate system-based track tracing error model; and respectively designing track tracking back-step sliding-mode controllers of a horizontal plane and a vertical plane under the condition that no interference is considered according to the error model soas to achieve a track tracing function. On the basis, a working state of the system under a combined interference condition is considered, a self-adaptive fuzzy logic system is additionally arrangedat an original controller, the interference-resistance capability of the system is improved, and the track tracing control of the under-actuated AUV under the condition of external composite interference is achieved. By the back-step self-adaptive fuzzy sliding-mode control method, the composite interference of the under-actuated AUV can be identified, and a reference scheme having advantages of adaptability, high robustness and the like is provided for accurate control of track tracing of the AUV.