30 results about "Fuzzy observer" patented technology

The invention discloses an electromotor dynamic / stable stage parameter identification method based on a stator resistance observer. For the parameter identification at a dynamic stage of an electromotor, a stator resistance T-S (Takagi-Sugeno) fuzzy observer is introduced to obtain an actually-measured value of stator resistance on the basis that the existing MRAS (Model Reference Adaptive System) method is still adopted, and dynamic correction is carried out on a rotating speed reference model and a resistance reference model according to the actually-measured value of the stator resistance; and for the parameter identification at a stable stage, the identification method for the rotating speed of a rotor is achieved by adopting the MRAS method and the stator resistance T-S fuzzy observer which are the same as those adopted in the parameter identification at the dynamic stage, and the identification method for the resistance of the rotor is achieved by adopting simple conversion. The electromotor dynamic / stable stage parameter identification method based on the stator resistance observer has the beneficial technical effects that the problem of inaccurate reference models is solved, the low-speed operating performance of the electromotor can be improved, the adoption of a current injection method is avoided, the current injection equipment is saved, the complexity of a system is lowered, the introduction of torque ripple is avoided, and the like.

The invention relates to a UUV control method and discloses a UUV control method based on T-S fuzzy observer compensation to solve the problem that the UUV track is inaccurate under ocean current interference.The method comprises the steps that the expected track of a UUV in the next step is acquired; an attitude controller conducts error tracking according to the expected track and works out the rudder angle information of vertical rudder and diving rudder in the next step; a T-S fuzzy observer observes the UUV according to ocean current interference, the current state information of the UUV and track position error, and estimates the state information of the UUV in the next step; the thrust of a thruster in the next step is acquired with the state information of the UUV in the next step as an input signal of a speed controller; the UUV is controlled according to the rudder angle information of vertical rudder and diving rudder and the thrust, the motion state of the UUV is acquired, and then the track of the UUV is determined and whether the track coincides with the expected track is judged.The method is used for UUV tracking of underwater cables or pipelines, underwater search and rescue, deep-sea resource detection and terrain detection.

The invention discloses an adaptive fuzzy fault-tolerant control method for a nonlinear system. According to the method, a nonlinear system state space model with an executor fault and external interference is established; a comprehensive fuzzy observer comprises a fuzzy state observer, a fault failure factor observer and a disturbance observer; and an adaptive sliding mode controller uses observation information to compensate influences of fault and interference on the system. In addition, a double-channel event triggering mechanism comprises an event triggering condition from a sensor to thecontroller and an event triggering condition from the controller to an executor. The event triggering based fault tolerant controller combines a triggering mechanism from the controller to the executor, and output is acted on the nonlinear system. Thus, effective fault tolerance control and trajectory tracking control can be realized for such type of nonlinear system under the condition with an executor fault and outside disturbance.

The invention relates to a nonlinear system fuzzy and repetitive output controller and a control method thereof. The nonlinear system fuzzy and repetitive output controller comprises an improved repetitive control module, a state feedback gain module and a fuzzy system module. The improved repetitive control module receives an output variable of a nonlinear system and carries out filtering and time delay processing, and sends an output variable thereof to the state feedback gain module; the state feedback gain module adjusts the output of the repetitive control module and carries out compensation thereon, and an output variable of the state feedback gain module is sent to the fuzzy system module; and the repetitive control module and the fuzzy system module are combined to form the fuzzy and repetitive output controller of the nonlinear system. The fuzzy model is applied to the problem of periodic tracking control of the nonlinear system for the first time, and T-S fuzzy control and repetitive control are combined to form a new high-performance control method; and for the design of a repetitive controller based on a fuzzy observer, with the problem of fuzzy premise variable non-measurableness in an actual system being taken into consideration, the design is more comprehensive.

The invention discloses a vehicle side slip angle estimating method based on a novel fuzzy observer. The method comprises the following steps: at first, utilizing a sensor to detect the vehicle state: specifically, using a yaw velocity sensor to detect the yaw velocity (gamma) during the travelling process of a vehicle and using a speed sensor to detect the vertical wheel speed (vx) during the travelling process of the vehicle; then utilizing a T-S fuzzy modeling method to establish a kinetic model of the vehicle system, wherein the front wheel rotation angle ([delta]f) during the travelling process of the vehicle is taken as external disturbance input of the system; then designing a novel fuzzy observer aiming at the vehicle kinetic model; finally, transmitting the measured state information of the vehicle to the designed fuzzy observer, and calculating the estimated side slip angle. The designed novel fuzzy observer can effectively solve the problem of mismatched parameters caused by T-S fuzzy modeling, and the results of simulation experiments also testify the effectiveness of the novel fuzzy observer.

The invention discloses a thermal load control method for a combined heat and power supply system of a micro gas turbine based on robust fuzzy prediction control, which comprises the steps of acquiring input fuel quantity and hot water temperature data of the combined heat and power supply system of the micro gas turbine, and establishing a T-S fuzzy affine model of the thermal load control process; establishing a global amplification state T-S fuzzy model of the thermal load control process; establishing an off-line fuzzy observer based on the global amplification state T-S fuzzy model; and establishing a robust fuzzy prediction controller based on the global amplification state T-S fuzzy model and the off-line fuzzy observer. According to the method, the influence of system nonlinearityon the controller is weakened by using the T-S fuzzy model, the problem that the state cannot be measured is solved by using the observer, steady-state errors are overcome by using state amplification, the degree of freedom of the controller is enhanced, and the method is a high-quality stable model prediction control method suitable for an actual complex industrial process.

The invention relates to an estimation and compensation finite time control method of a communication delay of a power network. The method comprises the following steps: step S1: constructing a fuzzymodel of a multi-node network of a power system according to a T-S fuzzy model method; step S2: constructing a finite time fuzzy observer, and calculating an error margin of a delay signal within a finite time; and step S3: designing a fuzzy compensation controller according to the obtained error margin, so that the fuzzy model is bounded stable within the finite time. By adoption of the estimation and compensation finite time control method provided by the invention, the bounded stability of the power system within the finite time can be achieved in the presence of network delay, and the safeoperation of the power system is ensured.

The invention discloses a dynamic positioning ship control method based on a T-S fuzzy system. The method comprises the steps that (1) dynamic positioning system modeling of T-S fuzzy form is carriedout, wherein a dynamic positioning ship mathematical model comprises ship kinematics and dynamics models; (2) a T-S fuzzy observer is designed to estimate the state quantity and unknown disturbance ofa system; and (3) an observer-based controller is designed, and a state feedback controller is designed based on the estimated state quantity of the observer. According to the invention, the application scope of the separation principle of the T-S fuzzy observer-controller is extended; a new separation principle condition is studied; and the system stability is ensured.

The invention provides a fuzzy control method based on a chaotic system. According to the method, a piecewise Lyapunov function method is adopted for design first, namely a Lyapunov function is selected for each subsystem, and an aggregate Lyapunov function of a system is a weighted sum of the functions of all the subsystems. Difficulty in solving a common positive definite matrix in a parallel distribution compensation (PDC) method is avoided, conservatism of the design is further reduced, and the range of the solution is widened. The design of a fuzzy observer solves the problem that the state of the system can not be measured directly. Through simulation of the chaotic system, effectiveness of the method is testified. The scheme is also suitable for nonlinear system control of other types, can be used for reference and has practical application value.

The invention relates to an energy Internet energy storage system lithium battery SOC state estimation method. The method comprises the following steps of firstly, constructing a physical model of anenergy Internet energy storage system lithium battery, combining a T-S fuzzy model method and a singular system method to express a dynamic state of a nonlinear system; then, for the energy Internet lithium battery system, designing a fuzzy observer to estimate a state of charge (SOC) of the lithium battery; and then, based on that, further designing a fuzzy controller based on the observer to ensure stability of a closed-loop control system. In the method, a real work condition is considered, and because of the designed fuzzy observer and the fuzzy controller, a system can be operated stably.

The invention provides a maximum power point fuzzy tracking control method with an uncertain photovoltaic system. According to the maximum power point fuzzy tracking control method with an uncertain photovoltaic system, the bias problem of DC / DC converter can be solved by proposing an extended PDC based on integral fuzzy observer, and the system can be driven directly to reach a maximum power point; the proposed controller and observer of fuzzy tracking control method can fuse more system information because of more complex construction forms, a control design feasible solution with significantly reduced conservatism can be obtained by using a developed relaxed LMI design method through the gain of the controller and the observer, thus facilitating the online implementation of a fuzzy tracking control scheme; the photovoltaic power generation system to which the method is directed can have any type of parameter uncertainty, which can solve the technical problem that the prior maximum power point tracking method lacks a strict convergence analysis and provides only approximate maximum power.

A maximum power point fuzzy prediction control method for an uncertain photovoltaic system comprises the following steps: firstly, introducing MPV and DMP fuzzy control configurations with PV voltageand power slope as control outputs; secondly, using a T-S fuzzy model representation method to represent the two fuzzy MPPT control configurations as output adjustment problems in a unified form; then, for the deviation of a DC / DC converter, proposing a predictive PDC control law based on an integral fuzzy observer to directly drive the system to reach the maximum power point. The proposed fuzzy prediction controller can ensure that the photovoltaic system reaches the maximum power point within a limited time. The maximum power point fuzzy prediction control method for an uncertain photovoltaic system can solve the controller and the observer gain online by the newly developed LMI type control algorithm with no need to perform coordinate transformation and calculation on the maximum powerpoint of the converter, and compared to the conventional MPPT method, allows for strict stability analysis and online control design of the system in the event of rapid atmospheric changes.

The invention provides a strip steel hot continuous rolling production billet reheating fuzzy PID temperature adjusting method and belongs to the field of strip steel hot continuous rolling production. The method comprises the following steps of performing T-S fuzzy partial differential equation modeling on a nonlinear billet internal temperature evolution dynamic model with spatial and temporal distribution characteristics to obtain a T-S fuzzy partial differential equation model of nonlinear billet internal temperature evolution dynamic; constructing a T-S fuzzy observer according to the T-S fuzzy partial differential equation model by adopting an observer-based feedback control technology; constructing a fuzzy PID temperature measurement tracking regulator based on a T-S fuzzy observer by applying a PID control strategy; and determining control parameters of the fuzzy PID temperature measurement tracking regulator, applying the fuzzy PID temperature measurement tracking regulator to the nonlinear billet internal temperature evolution dynamic model, and driving the billet lower surface temperature to be regulated to an expected temperature value. According to the method, non-intrusive steel billet temperature surface measurement and adjustment can be realized, so the lower surface temperature of the steel billet reaches an expected temperature value.

The invention relates to a control surface tiny fault tolerance control method for a random attitude hypersonic flight vehicle, belongs to the technical field of flight control, and solves the problems of high fault repair cost, poor fault tolerance control adaptability and reliability for the random attitude hypersonic flight vehicle, difficulty in evaluating the fault tolerance control effect and the like in the prior art. Through carrying out a random attitude hypersonic flight test, tiny faults and interferences are applied to a control system model of the random attitude hypersonic aircraft, and an actual PDF of a random attitude angle is obtained; a fuzzy observer is adopted to carry out fault observation on the control surface after the tiny fault and interference are applied so as to obtain a fault estimation value; obtaining an expected PDF of the random attitude angle; and based on the fault estimation value and a fault-tolerant control algorithm, obtaining a self-adaptive fault-tolerant controller by using the actual PDF and the expected PDF of the random attitude angle, and performing fault-tolerant control repair on the control surface fault. The fault-tolerant control of the early tiny fault of the random attitude hypersonic flight vehicle is realized.

The invention discloses an adaptive optimal output feedback controller structure for two interconnected synchronous generator systems and a realizing method thereof. The controller structure is used for controlling a generator system I and a generator system II. The structure firstly aims at a condition of state observing incapability in practical application. A fuzzy observer is designed for estimating the power angles and the power angle speeds of the two interconnected synchronous generator systems and the mechanical frequencies of the generators, thereby reducing the control cost of the two interconnected synchronous generators, and overcoming defects in traditional state feedback control. Afterwards, a traditional adaptive back-stepping method is used for designing an adaptive back-stepping controller, and a performance index function of the two interconnected synchronous generator systems is estimated through neural network technology, and furthermore an optimal controller of thesystem is designed. Through cooperation of the adaptive back-stepping controller and an approximate optimal controller, the control method can ensure stable operation of the two interconnected generator systems and furthermore can reduce the performance index of the system.

The invention discloses a heat load control method of a micro gas turbine combined heat and power system based on robust fuzzy predictive control, comprising the following steps: collecting input fuel quantity and hot water temperature data of the micro gas turbine combined heat and power system, and establishing a heat load control process The T‑S fuzzy affine model of the heat load control process is established; the global amplification state T‑S fuzzy model is established; the offline fuzzy observer is established based on the global amplification state T‑S fuzzy model; the global amplification state T‑S fuzzy model is established Model and Offline Fuzzy Observer to Build a Robust Fuzzy Predictive Controller. The method of the present invention utilizes the T-S fuzzy model to weaken the influence of the nonlinearity of the system on the controller, adopts the observer to overcome the problem of unmeasurable state, uses the state amplification to overcome the steady-state error, and strengthens the degree of freedom of the controller. A high-quality stable model predictive control method for practical complex industrial processes.

The present invention provides a method for designing an event-triggered observer based on online asynchronous antecedent reconstruction, including: modeling the actual complex nonlinear system as a T-S fuzzy model, and selecting the system output as an antecedent variable; designing a new Fuzzy observer, in which the observer gain is switched at different triggering moments according to the designed online asynchronous premise reconstruction method; a non-continuous Lyapunov function is established to prove that the proposed observer can guarantee the stability and expected performance of the system . The invention provides a scheme for effectively dealing with the mismatch of antecedent variables caused by the introduction of the event trigger mechanism, thereby effectively solving the problem of difficult design of the fuzzy observer. The proposed method is simulated, and the results verify the effectiveness of the method of the present invention.

The invention discloses a non-linear control system fault detection method based on a T-S fuzzy model. The method comprises two stages of construction image characterization and fault detection. The method comprises the following steps: firstly, designing a controller based on a T-S fuzzy observer by considering that a T-S fuzzy model has a good approximate nonlinear system; the stability of a nonlinear system can be ensured while the controller is introduced, a foundation is laid for constructing image characterization of the system and a nominal system, and finally an image characterization model of the system and the nominal system is established. On the basis of image representation, an evaluation function is set by generating input and output errors, threshold setting is completed by solving a series of linear matrix inequalities, and fault detection of a nonlinear control system is achieved through decision logic based on input and output stability. According to the method, the evaluation function can be designed by effectively utilizing the input-output error generated by the image representation model, false report and missing report in process monitoring can be effectively reduced, and the fault detection accuracy is relatively high.

The invention provides an event trigger observer design method based on online asynchronous antecedent reconstruction, which comprises the following steps of modeling an actual complex nonlinear system into a T-S fuzzy model, and selecting system output as a antecedent variable, designing a new fuzzy observer, wherein the gain of the observer is switched at different triggering moments according to the designed online asynchronous premise reconstruction method, and establishing a discontinuous Lyapunov function to prove that the provided observer can ensure the stability and expected performance of the system. A scheme for effectively processing the mismatching of the antecedent variables caused by the introduction of the event triggering mechanism is given, so that the problem of difficulty in designing the fuzzy observer is effectively solved. The method is simulated, and the result verifies the effectiveness of the method.

The invention discloses an electromotor dynamic / stable stage parameter identification method based on a stator resistance observer. For the parameter identification at a dynamic stage of an electromotor, a stator resistance T-S (Takagi-Sugeno) fuzzy observer is introduced to obtain an actually-measured value of stator resistance on the basis that the existing MRAS (Model Reference Adaptive System) method is still adopted, and dynamic correction is carried out on a rotating speed reference model and a resistance reference model according to the actually-measured value of the stator resistance; and for the parameter identification at a stable stage, the identification method for the rotating speed of a rotor is achieved by adopting the MRAS method and the stator resistance T-S fuzzy observer which are the same as those adopted in the parameter identification at the dynamic stage, and the identification method for the resistance of the rotor is achieved by adopting simple conversion. The electromotor dynamic / stable stage parameter identification method based on the stator resistance observer has the beneficial technical effects that the problem of inaccurate reference models is solved, the low-speed operating performance of the electromotor can be improved, the adoption of a current injection method is avoided, the current injection equipment is saved, the complexity of a system is lowered, the introduction of torque ripple is avoided, and the like.

The invention discloses an under-actuated surface vehicle trajectory tracking control system based on a self-adaptive fuzzy observer. A sensor module collects position and course information y of a surface vehicle and outputs the position and course information y to the self-adaptive fuzzy observer; the self-adaptive fuzzy observer receives output of a controller, obtains position and heading estimation, speed estimation, slow varying disturbance force estimation and unknown nonlinear term estimation (please see the expressions in the specification) and respectively transmits the position and heading estimation, the speed estimation, the slow varying disturbance force estimation and the unknown nonlinear term estimation to a trajectory tracking error generator and the controller; a guide system obtains expected speed and accelerated speed information in a hull coordinate system through calculation and respectively transmits the expected speed and accelerated speed information to the trajectory tracking error generator and the controller; the trajectory tracking error generator obtains error information of all states of trajectory tracking and transmits the error information to the controller; the controller calculates a longitudinal thrust and course changing torque control instruction of the current moment and transmits the control instruction to a thrust system, and the thrust system executes the control instruction. The under-actuated surface vehicle trajectory tracking control system can perform fast tracking under the conditions that only the position and the heading angle are measurable and a model has indeterminacy.

The invention discloses a flexible joint robot system event trigger control method based on a fuzzy observer. The method comprises the following steps: establishing a dynamic equation of a flexible joint robot system; designing an adaptive fuzzy observer according to the output information; designing a virtual control rate based on the fuzzy observer; designing an event triggering mechanism and an output feedback controller; the controller is applied to the flexible joint robot system, and a closed-loop robot system is obtained; and updating self-adaptive parameters in the observer through output data so as to update the controller. According to the method, under the condition that only output information exists, tracking control of the flexible joint robot system within a certain error can be achieved, the method is suitable for a system with an unknown model, communication resources can be effectively saved, and data redundancy is prevented.

The invention relates to an estimation and compensation finite time control method of a communication delay of a power network. The method comprises the following steps: step S1: constructing a fuzzymodel of a multi-node network of a power system according to a T-S fuzzy model method; step S2: constructing a finite time fuzzy observer, and calculating an error margin of a delay signal within a finite time; and step S3: designing a fuzzy compensation controller according to the obtained error margin, so that the fuzzy model is bounded stable within the finite time. By adoption of the estimation and compensation finite time control method provided by the invention, the bounded stability of the power system within the finite time can be achieved in the presence of network delay, and the safeoperation of the power system is ensured.

The invention provides a state estimation method for a reactive power compensation device applied to a utility tunnel. The method comprises the steps of establishing a discrete time fuzzy state equation of the reactive power compensation device; designing a fuzzy observer for state estimation; calculating a parameter matrix of the fuzzy observer for state estimation offline; carrying out state estimation on the reactive power compensation device online by use of the fuzzy observer; considering that the state estimation effect reaches an allowed range and sending a state estimation result x< ^ >(k) to a reactive power compensation control unit for follow-up reactive power compensation control when the absolute value of y(k)-y< ^ >(k) is less than epsilon, wherein the epsilon is a preset threshold value for judging whether to put the fuzzy observer into follow-up use or not. According to the method, the technical problem of nonlinear term processing in the physical system of the reactive power compensation device can be solved effectively.

The invention relates to a method for estimating the SOC state of a lithium battery in an energy Internet energy storage system. First, build the physical model of the lithium battery of the Energy Internet energy storage system, and combine the T-S fuzzy model method and the singular system method to express the dynamics of the nonlinear system; then, for the Energy Internet lithium battery system, design a fuzzy observer to charge the lithium battery The state of state (SOC) is estimated; on this basis, a fuzzy controller based on an observer is further designed to ensure the stability of the closed-loop control system. The method of the invention considers real working conditions, and the designed fuzzy observer and fuzzy controller make the system run stably.

The invention relates to a fuzzy repetitive output controller of a nonlinear system and a control method thereof, which includes an improved repetitive control module, a state feedback gain module and a fuzzy system module, wherein the improved repetitive control module receives output variables of the nonlinear system for filtering and Delay processing, the output variable is sent to the state feedback gain module; the state feedback gain module adjusts the output of the repetitive control module and compensates it, the output variable of the state feedback gain module is sent to the fuzzy system module, and the repetitive control module and fuzzy system The modules are combined to form a fuzzy repetitive output controller for nonlinear systems. This invention applies the fuzzy model to the periodic tracking control problem of nonlinear systems for the first time, and combines T-S fuzzy control and repetitive control to form a new high-performance control method. In the repetitive controller based on the fuzzy observer, In terms of design, the problem of unmeasurable fuzzy premise variables in actual systems is taken into consideration to make the design more comprehensive.

The invention discloses an adaptive optimal output feedback controller structure of an interconnected double synchronous generator system and a realization method thereof. The controller structure is used to control generator system I and generator system II. In this structure, the fuzzy observer is designed to estimate the power angle, power angular velocity and mechanical frequency of the interconnected dual synchronous generator system for the situation that the state is unobservable in practical applications, thereby reducing the control cost of the interconnected dual synchronous generator and overcoming The shortcomings of traditional state feedback control; then, use the traditional adaptive backstepping method to design an adaptive backstepping controller and estimate the performance index function of the interconnected double synchronous generator system through neural network technology and design the optimal controller of the system . Under the joint action of adaptive backstepping controller and approximate optimal controller, this control method can not only ensure the stable operation of two interconnected generator systems, but also reduce the performance index of the system.