28 results about "Nonlinear observer" patented technology

The invention relates to the technical field of control systems, in particular to a servo driver control system based on multi-modal fusion, and adopts the technical scheme that motor current, rotating speed and load torque signals are acquired in real time through a dynamic parameter identification module, so that the dynamic response speed of the system is increased; an extended state observer (ESO) is adopted to estimate unmodeled dynamics and disturbance through the nonlinear observer module, the observation precision and the real-time performance and adaptability of the system are improved, a hybrid algorithm of fuzzy PID and model predictive control (MPC) is integrated through the adaptive control module, the control precision of the system is improved, and the control precision of the system is improved. The anti-interference compensation module generates a dynamic compensation amount according to the output of the observer, the dynamic compensation amount is injected into a control loop, the anti-interference capability of the system is enhanced, the energy consumption optimization unit adjusts a PWM modulation strategy through an online efficiency optimization algorithm, and the energy efficiency of the system is improved.

The invention discloses a non-electrolytic capacitor permanent magnet motor control method and system based on a non-linear observer, and the method comprises the steps: introducing a gradient search mechanism based on a stator voltage equation of a permanent magnet synchronous motor under a static coordinate system, and constructing a flux linkage observer equation; acquiring a voltage component and a current component of the permanent magnet synchronous motor in a static coordinate system, and observing the flux linkage observer equation to obtain a real component of a flux linkage amplitude error in a rotating coordinate system; and designing an exponential reaching law adaptive law, introducing an exponential reaching law to dynamically adjust the gradient search gain, and combining the real component of the flux linkage amplitude error under the rotating coordinate system as feedback to obtain the rotor position of the permanent magnet synchronous motor. The estimated flux linkage error value is used as the feedback quantity, and the real position of the rotor of the permanent magnet synchronous motor can be quickly and accurately tracked. The non-electrolytic capacitor permanent magnet motor control method and system based on the non-linear observer can be widely applied to the technical field of permanent magnet motor control.

The invention provides a side slip angle estimation method based on an intelligent tire and related equipment, and relates to the field of vehicle motion state estimation.The method comprises the steps that an on-line circulation estimation process is carried out, and the one-time process comprises the steps that the friction coefficient dynamic adjusting amount in the last estimation process is obtained; acquiring a current first friction coefficient output by the intelligent tire system and a corresponding confidence coefficient; outputting a second friction coefficient at the current time according to a second friction coefficient, the friction coefficient dynamic adjusting quantity, the first friction coefficient and the corresponding confidence coefficient which are output by the self-adaptive Kalman filtering last time through the self-adaptive Kalman filtering; and inputting the chassis signal and the second friction coefficient into a nonlinear observer to obtain an estimated value of the side slip angle of the vehicle. A new friction coefficient information source is provided for side slip angle estimation, the side slip angle is estimated through friction coefficients of multiple sources, and decoupling estimation is achieved.

The invention discloses a method for optimizing steering idle speed control of an oil pump motor of a counterbalance forklift truck, relates to the technical field of motor control, and solves the problems that the rotating speed of a motor is obviously lower than a set idle speed and steering is delayed or shaken due to sudden load increase of a hydraulic system at the moment of steering. The steering idle speed control optimization method comprises the steps that the steering feedback idle speed and the steering oil pressure are collected, the steering idle speed falling difference value is calculated according to the preset steering idle speed, and a load dynamic model is established; judging the duration time of the steering idle speed drop difference value, and obtaining the control torque of an oil pump motor by utilizing a composite proportional-integral controller in combination with the steering oil pressure; a torque conversion coefficient is calculated through a third-order nonlinear observer and a temperature compensation coefficient according to steering oil pressure collected by a hydraulic sensor, and then offset torque is obtained; and the control torque and the offset torque of the oil pump motor are calculated according to an idling dynamic weight distribution strategy and then input into the heavy forklift to control the oil pump motor to complete steering idling optimization.

The invention relates to the technical field of active safety control of intelligent automobiles, in particular to a multi-source fusion estimation method and system for a side slip angle and a road adhesion coefficient, and aims to realize step-by-step estimation of the side slip angle and the road adhesion coefficient through a cascade nonlinear observer architecture, solve the problem of joint estimation caused by dynamic coupling of the side slip angle and the road adhesion coefficient, and improve the safety of the side slip angle and the road adhesion coefficient. Based on an estimation result of a cascade nonlinear observer, a joint estimation method for the side slip angle and the road adhesion coefficient based on an exogenous Kalman filtering framework is provided, the problem that stability and optimality / suboptimum are difficult to consider in a traditional method is solved, lane line information is recognized through visual recognition, and a vehicle kinematics model is combined, so that the road adhesion coefficient is estimated. According to the method, a Kalman filter of the vehicle side slip angle is constructed to output expectation and variance, so that the uncertainty of visual estimation of the side slip angle is quantified, meanwhile, after visual-based road surface classification, the expectation and variance of a visual estimation road surface adhesion coefficient are obtained by adopting a Bayesian method, and subsequent multi-source information fusion is facilitated.

The invention discloses a distributed fault-tolerant cooperative control strategy based on a nonlinear observer, belongs to the field of intelligent control, and mainly aims at estimating and compensating actuator faults, unknown nonlinearity and external disturbance in a queue in queue control. And the whole queue is ensured to keep the consistency, stability and passing efficiency of advancing under the condition of a non-zero initial spacing error. The method comprises the following steps: establishing a queue system model with actuator faults, unknown nonlinearity and external disturbance; establishing a queue tracking error; establishing a queue sliding mode error; establishing a queue coupling sliding mode error; establishing a nonlinear observer for external disturbance of the queue; establishing a neural network estimation mechanism for unknown nonlinearity in the queue; establishing a self-adaptive parameter estimation mechanism aiming at the queue actuator fault; and establishing a distributed fault-tolerant queue control strategy based on a nonlinear observer, a neural network estimation mechanism and an adaptive parameter estimation mechanism. The method is used for queue cooperative intelligent control.

According to the fault-tolerant control method for the actuator fault in the urban sewage treatment process, stable control over the dissolved oxygen concentration and the nitrate nitrogen concentration in the urban sewage treatment process under the influence of the actuator fault is achieved. Firstly, a nonlinear observer is designed to accurately estimate an actuator fault; secondly, constructing a radial basis function neural network to accurately characterize the time-varying nonlinear dynamic characteristics of the sewage treatment process; a fault-tolerant controller based on self-adaptive dynamic programming is designed, and the problem that the dissolved oxygen concentration and the nitrate nitrogen concentration deviate from set values due to actuator faults is solved jointly by constructing an evaluation network and an execution network, training a neural network by adopting a strategy iterative algorithm, solving an approximate optimal control law and fusing a prior classical controller. Experimental results show that the method can realize fault-tolerant control of the dissolved oxygen concentration and the nitrate nitrogen concentration, and ensures stable operation of the urban sewage treatment process.

The invention is applicable to the technical field of urban sewage treatment, and provides a robust fault-tolerant control method for dissolved oxygen concentration in an urban sewage treatment process, which comprises the following steps of: constructing a control system kinetic model containing faults and disturbance, establishing a nonlinear observer to estimate the faults and the disturbance, and constructing a fuzzy neural network to estimate an unknown nonlinear function. And designing a robust fault-tolerant controller based on self-adaptive dynamic programming, optimizing a control law through strategy iteration, neural network implementation and an experience playback mechanism, and finally realizing dissolved oxygen concentration control by adjusting the aeration rate. Experimental results show that the method can effectively cope with actuator faults and external disturbance, it is ensured that the dissolved oxygen concentration stably tracks the set value, and the robustness of a sewage treatment system and the effluent quality standard-reaching rate are improved.

The present invention relates to the technical field of electro-hydraulic servo control. Provided is a backstepping sliding mode control method for a heavy-duty forklift pump-controlled lifting system and based on a non-linear observer. In the method, a non-linear robust sliding mode position servo controller with disturbance compensation is designed on the basis of the idea of a backstepping method. Aiming at the problem of the difficulty of controlling the precision of a heavy-duty forklift pump-controlled lifting position, the present invention realizes precise load observation, takes non-linearity and parameter uncertainty into consideration, and uses a sliding mode term to address non-linearity and uncertainty, thereby reducing the effects of abrupt load changes, external disturbance, and unmodeled dynamics on control precision, and achieving a high-precision tracking performance.

The invention discloses a mobile robot formation finite time control method based on visual servo. According to the method, firstly, a relative kinematics model between a navigation robot and a following robot is established under a world coordinate system, the relative kinematics model is converted into a relative vision kinematics model in an image space in combination with a pinhole camera model, and an image error vector is obtained through normalization; for the error model, a non-linear observer is designed to estimate the unknown speed of the piloting robot, a parameter adaptive updating law is provided to process the uncertain feature height, and a finite time controller based on the linear speed and the angular speed is further designed to realize accurate tracking of the piloting robot. The information required by the method can be acquired from the image, the method does not depend on local communication or GPS between the robots, the communication and sensor loads are small, the tracking control precision is good, the system response speed is high, and the method is suitable for efficient cooperative control in the multi-robot formation task.

The application discloses a kind of failure detection method and system of petroleum refining plant sensor, belong to sensor detection technical field;The sensor to be detected of petroleum refining plant is represented using partial differential equation model, and the nonlinear observer of the sensor to be detected is constructed based on the partial differential equation model of the sensor to be detected;Its output is observed by observer, and failure detection is carried out based on the detection residual between observation value and corresponding actual output;The nonlinear observer constructed can cope with the multiple-input multiple-output situation with position interference, and it satisfies that detection residual is ultimately bounded under the condition that the sensor to be detected is healthy, it is easy to determine the preset threshold for failure judgment based on detection residual, and it is also unnecessary to reduce order partial differential equation model to ordinary differential equation for solving, avoid false alarm and miss report situation possibly caused by model reduction, can accurately carry out failure detection to petroleum refining plant sensor.

The present invention discloses a method and system for optical fiber fault detection and separation based on a two-step neural network. The method comprises acquiring optical fiber source data; performing B-spline approximation on the optical fiber source data to obtain a probability density function of light intensity data; performing static modeling on the probability density function and calculating weights at each moment; using a neural network to approximate the weights at each moment and establishing a nonlinear model between the input light intensity data and the weights; constructing a nonlinear filter for fault detection and a nonlinear observer for fault diagnosis based on the nonlinear model; and inputting the optical fiber source data into the nonlinear filter and the nonlinear observer to obtain the fault size. The present application detects fault intrusion through the nonlinear filter of the fault detection method, and then diagnoses different fault information through the nonlinear observer of the fault diagnosis method to obtain the fault size, thereby achieving the purpose of fault separation.

The application discloses a kind of micro electro mechanical system gyroscopes nonlinear bias on-line estimation method, comprising the following steps: S1, using MEMS inertial sensor and external attitude sensor obtains gyroscope angular velocity and non-inertial attitude measurement value, and the static bias correction of gyroscope angular velocity measurement value is carried out, denoising and mapping preprocessing, and the mapping preprocessing of non-inertial attitude measurement value is carried out;S2, construct the nonlinear observer of on-line observation gyroscope bias, with the sensor information obtained in step S1 as input to carry out bias correction with attitude estimation and gyroscope bias estimation.The method is more in line with the actual situation for the assumption of model, and is more widely used, and has higher accuracy, robustness and stability than existing RHO, IEKF method.

The invention relates to a differentiator construction method and device, a nanometer positioning system and computer equipment. Acquiring a virtual controlled system driven by virtual disturbance and a linear Luenberger observer constructed based on the virtual controlled system; performing disturbance state expansion on the virtual controlled system to construct an expansion state observer; performing disturbance estimation on the virtual disturbance based on an extended state observer, and constructing a disturbance compensation item; non-linear processing is carried out on the linear Luenberger observer, and a non-linear observer is constructed; performing disturbance compensation on the nonlinear observer according to the disturbance compensation item to obtain a target differentiator; and collaborative optimization between the estimation precision and the noise suppression capability can be realized based on the target differentiator.

This invention discloses a nonlinear model predictive control method and system for wind turbine generator sets. The method includes the following steps: constructing a nonlinear wind turbine model; wherein the nonlinear wind turbine model includes a nonlinear aerodynamic model, a wind turbine drivetrain model, a wind turbine blade-tower coupling model, and an actuator response model; based on the nonlinear wind turbine model, using wind speed disturbance, rotational speed, pitch angle, tower displacement estimation, and tower velocity estimation as input variables, predicting the state of the wind turbine generator set; wherein the tower displacement estimation and tower velocity estimation are obtained through a nonlinear observer; the input variables of the nonlinear observer are the measured tower acceleration, wind speed disturbance, rotational speed, and pitch angle. This invention can effectively reduce the load on the wind turbine generator set's blade root and tower, which not only helps to reduce the weight of various major components and reduce the cost of the unit, but also improves the stability of the unit's operation and extends its service life.

The invention discloses a passivity-based distributed cooperative control method for a network-building type inverter field station, and belongs to the field of electrical engineering. According to the distributed cooperative control method, a port controlled Hamiltonian method is utilized to design inner ring controllers of network-building type inverters, a nonlinear observer is introduced to ensure the stability of a new energy station, and in addition, a pole assignment method is utilized to determine ideal injection damping parameters of the network-building type inverters in different power grid states. And the dynamic performance of the network-building type inverter station is improved. The method is not only simple to implement, but also solves the problem that the overall dynamic performance of the field station is difficult to consider under the traditional passive control of the inverters in a multi-inverter scene in the network construction type inverter field station, and effectively improves the dynamic performance of the inverter field station under the complex power grid change.

The invention relates to the technical field of motion control, and discloses a motion control method and system for an ambulance boat launching and recovery device and a storage medium, and the method comprises the steps: carrying out the time-space fusion of multi-source perception data, and obtaining environment state estimation and motion state estimation; performing on-line monitoring analysis on the surrounding environment to obtain a real-time sea condition identification result; performing adaptive adjustment on control parameters of the nonlinear observer and the robust controller to obtain optimized control parameters; performing robust control based on the optimal control parameters and a preset task path to obtain a motion control instruction; based on the motion control instruction, executing laying or recovery operation, and feeding back the operation state of the ambulance boat in real time in the laying or recovery operation process; based on the operation state, the motion control instruction is dynamically adjusted, so that the stability of the rescue boat during laying or recovery operation is ensured; according to the invention, the efficiency of the motion control method of the rescue boat launching and recovery device can be improved.

The invention provides a self-adaptive robust control method of an energy-saving forklift pump control steering system, and belongs to the technical field of electro-hydraulic servo control. The self-adaptive robust control method comprises the steps that a mathematical model of the energy-saving forklift pump control steering system is established; based on the mathematical model of the pump control steering system, designing a nonlinear disturbance observer, estimating disturbance of the system and compensating the disturbance; and designing an adaptive robust controller based on the mathematical model of the pump control steering system and the nonlinear observer. Precise observation of steering resistance is realized through a nonlinear disturbance observer, uncertain parameters are dynamically tracked in combination with a parameter projection adaptive law, a composite control strategy of parameter adaptive and robust items is adopted, parameter changes are actively adapted, dependence on strong gain adjustment is not needed, system buffeting is reduced, and control flexibility and practicability are improved.

The application relates to a permanent magnet synchronous motor rotor position estimation method, system and device, which realizes observation of a permanent magnet synchronous motor rotor position based on a cascaded nonlinear PI observer, and comprises the following steps: obtaining currents through current sensors on windings of the permanent magnet synchronous motor; obtaining stator current components through calculation; constructing a first-stage nonlinear PI observer based on the stator current components at a current sampling moment, and obtaining back electromotive force observation values; constructing a position observation error phase detector based on the back electromotive force observation values at the current sampling moment; constructing a second-stage nonlinear PI observer based on rotor electric angle observation errors at the current sampling moment, and obtaining rotor electric angular velocity observation values; and calculating rotor electric angle observation values at the current sampling moment based on the rotor electric angular velocity observation values at the current sampling moment, so as to realize rotor position estimation. Compared with the prior art, the application improves the dynamic performance of rotor position identification and reduces speed fluctuation.

The invention provides a high-speed boat path tracking control method based on an improved nonlinear speed observer, and the method comprises the steps: constructing a kinetic model and a kinematic model of an under-actuated water surface high-speed unmanned boat, designing a thrust saturation limiting function based on an ISRU, and analyzing a path tracking error and a control target; in a feedback function of an original nonlinear speed observer, fusing a hyperbolic tangent feedback mechanism of an error self-adaptive smoothing parameter, replacing a fixed gradient parameter with a parameter dynamically adjusted along with an observation error, substituting the parameter into a new feedback function, and reconstructing a nonlinear observer model; in the self-adaptive dynamic foresight sight guidance law, performing multi-state fusion improvement on a foresight distance, a navigational speed guidance law and a course guidance law; and improving a state estimator and a weight adaptive law of the RBF neural network. A dynamic error gain coefficient is introduced into a state estimator, a dynamic attenuation coefficient is introduced into a weight adaptive law, and the problems of model uncertainty and environmental interference in under-actuated ship trajectory tracking are effectively solved.

The application discloses a kind of based on passive network type inverter station distributed collaborative control method, belong to electrical engineering field.The distributed collaborative control method is designed to the inner loop controller of network type inverter by using port controlled Hamilton method, and the stability of new energy station is guaranteed by introducing nonlinear observer, in addition, the ideal injection damping parameters of each network type inverter under different power grid states are determined by using pole placement method, and the dynamic performance of network type inverter station is improved.The application is not only simple to implement, but also solves the problem that the overall dynamic performance of the station is difficult to be considered under the traditional passive control of the inverters in the network type inverter station scene with multiple inverters, effectively improving the dynamic performance of the inverter station under complex power grid changes.

The purpose of this invention is to provide a device and method for predicting the remaining life of a hybrid fuel cell based on a nonlinear observer, belonging to the field of marine hybrid power. The fuel cell remaining life prediction method of this invention includes the following steps: S1: The marine hybrid power system composed of a fuel cell and a battery adopts a fully active control architecture. The fuel cell and its converter adopt power closed-loop control, and the battery and its converter adopt voltage-current dual closed-loop control; S2: Collect the fuel cell output current and bus voltage; S3: Design a nonlinear observer to estimate the fuel cell degradation factor; S4: Calculate the remaining life based on the relationship between the fuel cell degradation factor and the remaining life; S5: Calculate the maximum output current of the fuel cell based on the fuel cell degradation factor and transmit it as a control constraint to the fuel cell controller. This invention does not require additional sensors, the algorithm is simple to implement and highly versatile, and it is of great significance for the control and monitoring of hybrid power systems.

The invention relates to the technical field of robot intelligent control, in particular to an under-actuated crane all-drive system method based on low gain feedback. A to-be-determined coupling signal containing trolley displacement and a load swing angle is constructed, a second derivative of the signal about time is deduced, an all-wheel-drive system model is further obtained through deduction, a nonlinear observer is introduced into the model, unknown disturbance borne by the under-actuated crane in the complex working condition is estimated and compensated, and therefore the under-actuated crane under the complex working condition is determined. And the anti-interference capability of the whole system is ensured. According to the method, a linear closed-loop system is further constructed, an auxiliary function containing load swing angle information is introduced into the linear closed-loop system to improve the suppression capability on load swing, a system state tracking error is introduced, and then a state-space equation is reconstructed. A low-gain feedback control rate is also designed, so that the actuator is prevented from falling into a working condition of input saturation.

This disclosure provides a method and related equipment for estimating the center of gravity sideslip angle based on intelligent tires, relating to the field of vehicle motion state estimation. The method includes: an online cyclic estimation process, where each step includes: acquiring the dynamic adjustment amount of the friction coefficient from the previous estimation process; acquiring the first friction coefficient and corresponding confidence level output by the intelligent tire system for the current estimation; outputting the second friction coefficient for the current estimation using an adaptive Kalman filter, based on the second friction coefficient, the dynamic adjustment amount of the friction coefficient, the first friction coefficient, and the corresponding confidence level output by the adaptive Kalman filter; and inputting the chassis signal and the second friction coefficient into a nonlinear observer to obtain the estimated value of the vehicle's center of gravity sideslip angle. This provides a new source of friction coefficient information for center of gravity sideslip angle estimation, achieving decoupled estimation by estimating the center of gravity sideslip angle through friction coefficients from multiple sources.

The application provides a fault-tolerant control method for actuator failure of a municipal sewage treatment process, and realizes stable control of dissolved oxygen concentration and nitrate nitrogen concentration of the municipal sewage treatment process under the influence of actuator failure. First, a nonlinear observer is designed to accurately estimate actuator failure. Second, a radial basis function neural network is constructed to accurately characterize the time-varying nonlinear dynamic characteristics of the sewage treatment process. A fault-tolerant controller based on adaptive dynamic programming is designed, an evaluation network and an execution network are constructed, and a policy iteration algorithm is used to train the neural network, so as to solve an approximate optimal control law, and the prior classical controller is fused to jointly solve the problem that the dissolved oxygen concentration and the nitrate nitrogen concentration deviate from the set value caused by the actuator failure. Experimental results show that the method can realize fault-tolerant control of the dissolved oxygen concentration and the nitrate nitrogen concentration, and ensure stable operation of the municipal sewage treatment process.

The invention relates to the technical field of robots, in particular to a puncture robot based on a neural network and a nonlinear observer. The robot comprises a kinetic model construction module, a kinetic model decomposition module, a first robust controller construction module, a puncture error prediction module, a second robust controller construction module and a third robust controller control module. A control model can be divided into a nominal control item, a disturbance control item and an external puncture control item, a control error is divided into a plurality of controllers according to the error generation reason, and error elimination is carried out respectively. Wherein an external puncture control item can change along with the change of a puncture object and a punctured object, so that variables are too many, and the control accuracy during puncture can be remarkably improved by adopting the radial basis function neural network model for prediction.

This invention provides a fast frequency support control method and system for a grid-type converter, comprising: Step S1: establishing a heterogeneous power system model, including a GFM converter model, a synchronous generator (SG) model, and a GFL wind turbine model; Step S2: based on the established GFL wind turbine model, treating the output power and load power of the GFL wind turbine as disturbances, and designing a preset time nonlinear observer to estimate the disturbances; Step S3: designing a preset time sliding mode controller to adjust the output power increment of the GFM converter to adjust the frequency of the heterogeneous power system; Step S4: simulating the suppression of oscillations by adjusting the frequency of the heterogeneous power system, and displaying the simulation results. This invention can demonstrate smaller overshoot and shorter convergence time.

The application discloses a spacecraft formation event-triggered attitude coordination control method considering communication time delay, comprising the following steps: according to the communication topology structure of a spacecraft formation system, an attitude dynamics model of the spacecraft formation is established, which can consider external disturbance, model uncertainty and communication time delay; based on the attitude dynamics model, a nonlinear observer is constructed, which can observe the collective nonlinear term of the spacecraft formation system; based on the nonlinear observer, an event-triggered attitude coordination control law and an event-triggering mechanism are designed; according to the event-triggered attitude coordination control law, the attitude and angular velocity of the formation spacecraft are controlled, and according to the event-triggering mechanism, it is determined whether the corresponding event-triggered attitude coordination control law of the formation spacecraft needs to be updated and whether the state information of the formation spacecraft needs to be sent to the adjacent formation spacecraft. The application can consider the influence of disturbance, uncertainty and communication time delay, save the energy, communication and computing resources of the system while ensuring good control performance.