279 results about "Error feedback" patented technology

The invention discloses an unmanned aerial vehicle-mechanical arm system cooperative control method for precise spraying. According to the method, through a depth camera and a point cloud reconstruction algorithm, three-dimensional modeling of a target surface and semantic recognition of a spraying area are achieved, and a spraying path and spraying posture data are generated. Based on spraying task requirements, a spraying film thickness experience estimation model is established, and path point-level spraying parameters are obtained. Load mass change, mechanical arm mass center change and spraying reaction force of each path point are calculated, and a coupling dynamic model is constructed in combination with the system state. And dynamic compensation control input is generated by using an adaptive sliding mode control algorithm. After spraying is completed, the actual spraying effect is collected through image and point cloud detection, color, film thickness and texture features are extracted and compared with task requirements, error feedback is generated, and control parameters are adjusted online. According to the method, the problems of dynamic change and error compensation in the spraying process are effectively solved, and the method is suitable for a high-precision spraying task in a complex environment.

The invention relates to the technical field of steam turbine testing, in particular to a testing system for mismatch correction of a wide-load-interval thermal power generating unit speed regulation model, which comprises a thermodynamic system component, a speed regulation system device, a dynamic signal acquisition device and a control device, a dynamic signal processing module analyzes the relevance between main steam pressure sudden change and control valve opening oscillation in real time, a dynamic response database including a time sequence is constructed, and a control valve opening feed-forward compensation instruction and a combustor fuel distribution gradient adjustment signal are generated according to correction parameters. Power over-modulation wave crests caused by sudden load change are suppressed, and primary frequency modulation action delay is reduced; and the simulation verification module compares measured data with model output through an error feedback mechanism, dynamically adjusts high-pressure cylinder flow characteristic curve calibration parameters, optimizes a control strategy in combination with a network-related safety margin evaluation result, and realizes improvement of dynamic response precision in a full peak regulation interval and enhancement of power grid frequency stability.

The invention relates to the technical field of model construction, in particular to a method and a system for constructing a sheet metal working three-dimensional process model. The method comprises the following steps: acquiring equipment specification data and material characteristic data; the method comprises the following steps: acquiring geometric parameters and motion parameters of sheet metal processing equipment by using a three-dimensional scanner, and integrating equipment specification data and material characteristic data to construct a sheet metal three-dimensional initial process model; analyzing a material plastic deformation characteristic of the material characteristic data and setting a processing parameter threshold range; the machining parameter threshold range is input into the three-dimensional initial process model for stage machining process simulation, the flange area strain rate, the dangerous section thinning rate and the rebound angle variable quantity are output, and stage machining process simulation comprises plate inflow stage simulation, forming stage simulation and shaping stage simulation. According to the method, three-dimensional scanning, comprehensive machining process simulation, topological optimization and a real-time error feedback mechanism are introduced, so that the construction accuracy of the sheet metal machining process model is improved.

The invention relates to a data access prediction scheduling method and system based on a dynamic threshold value, and belongs to the technical field of data processing. The method comprises the following steps of: dynamically adjusting an abnormal detection threshold in an access behavior by utilizing reinforcement learning and an error feedback mechanism, realizing preposition identification of potential high-frequency access data by combining abnormal point classification processing and access trend prediction, and generating a scheduling request to drive cache preheating or interface priority scheduling of the data. According to the method, access behavior modeling, anomaly recognition, trend prediction and strategy feedback mechanisms are combined, interface access optimization requirements in a mass data storage system are met, and the key problems that access behaviors are unpredictable, scheduling response lags and the like are solved.

The invention discloses a grid-connected inverter control method based on second-order linear active disturbance rejection, and particularly relates to the field of grid-connected inverter control. Voltage and frequency error signals between the output side of the inverter and the power grid are obtained, a pre-synchronization control model is constructed, and voltage amplitude and frequency synchronization is achieved; a second-order linear active-disturbance-rejection controller is introduced in the frequency synchronization control process, an extended state observer is adopted to estimate the output frequency, the frequency change rate and a disturbance term, and a state error feedback control law is combined to generate a frequency regulation control quantity, so that accurate frequency control is realized; after grid connection, a dual-channel LADRC power regulation controller is constructed, and decoupling tracking control is carried out on active power and reactive power; meanwhile, on the basis of fast Fourier transform processing as a stable grid-connected state criterion, the method has the advantages of being high in control precision, high in anti-interference capability, good in current waveform quality, high in adaptability and the like, and is suitable for various grid-connected application scenes.

The invention relates to the technical field of spraying control, in particular to an anti-corrosion steel pipe inner spraying track self-adaptive control system based on multi-sensor fusion. The feed-forward prediction module generates a feed-forward correction signal through a model compensator and a self-adaptive compensator and predicts and compensates system errors, the feedback control module comprises a track generator and a disturbance observer, a feedback control instruction is generated by comparing a correction track with an original track, an execution mechanism is dynamically adjusted, and the system error is predicted and compensated. The signal driving module adopts a frequency domain decoupling fusion technology, combines a feedforward correction signal and a feedback control instruction, generates a composite control instruction, and ensures the accuracy of trajectory tracking control. According to the invention, through a double-loop control architecture combining feedforward prediction and feedback disturbance suppression, high-precision and strong-robustness self-adaptive control of a spraying track under a complex working condition is realized.

The invention relates to the technical field of road maintenance, and discloses a laser leveling automatic control system for the paving thickness of a cold-recycled mixture, and the system comprises a state obtaining module which is used for obtaining state information in real time; the prediction module is used for generating a final forming thickness prediction value based on the dynamic compaction settlement model; the control decision module is used for determining the deviation between the final forming thickness predicted value and the preset target forming thickness and outputting a target control instruction based on the deviation; the execution module takes the target control instruction as input and sends the target control instruction to the paving device; and the model correction module is used for adjusting parameters of the dynamic compaction settlement model. The state information in the state acquisition module is received through the prediction module, a final forming thickness prediction value is generated, and error feedback adjustment is performed based on the final forming thickness prediction value, so that advanced modeling and compaction ratio prediction and auxiliary paving elevation regulation are realized, and the problems of large system hysteresis and slow response to nonlinear settlement are solved.

The invention discloses an IADRC and torque compensation fused PMSM speed regulation control method. The method comprises the steps of establishing a mathematical model of a surface-mounted permanent magnet synchronous motor in a rotating coordinate system; an improved Luenberger load torque observer is designed; designing an active disturbance rejection controller; designing an improved super-spiral sliding mode algorithm; and designing an improved speed loop active disturbance rejection controller. The improved Luenberger observer identifies the load torque of the system in real time, and parameters obtained through identification are compensated to the improved active-disturbance-rejection controller, so that system oscillation caused by load change is avoided; a traditional non-linear state error feedback control rate in active disturbance rejection control is combined with a super-spiral sliding mode algorithm, and a new piecewise function is designed and applied to a sliding mode reaching law. According to the method, the response speed and the working efficiency of the system are effectively improved, meanwhile, the anti-interference performance of the system is enhanced, and the robustness of the system is improved.

The invention discloses a tunnel or mine water gushing space-time prediction method and system coupled with a hydrodynamic numerical model, and the method comprises the steps: outputting multi-source data based on an identified and verified underground water numerical model, complementing the missing of measured data, quantifying the difference between the permeability characteristics of a fault and a normal stratum, and coupling the difference to a data system, and tunnel or mine excavation space data are merged. And constructing an LSTM-isolated forest-K neighbor regression coupling model, and configuring a multifunctional module to realize multi-scene data co-training. The preprocessed multivariate time series data is divided into a training set and a test set, hidden features are extracted through a coupling model, anomaly detection results are fused, a residual error correction model is synchronously trained, and hyper-parameters and weights are adaptively optimized according to multi-engineering prediction error feedback. And based on the trained coupling model, carrying out synchronous water gushing space-time prediction by adopting a window rolling strategy, and outputting prediction data meeting engineering precision in combination with residual correction. And reliable technical support is provided for safety prevention and control of engineering construction.

The invention discloses an intelligent building fault prediction method based on an adaptive algorithm, and the method comprises the steps: obtaining operation state data collected by a plurality of sensor nodes, carrying out the normalization preprocessing, inputting an improved adaptive prediction model, and obtaining the implicit state representation; an initial fuzzy rule set is generated through fuzzy rule induction, a real-time evolution strategy is introduced, fuzzy rules and neural connection weights are dynamically adjusted according to error feedback, and a self-adaptive prediction model updated through evolution is formed; and then performing multi-step prediction on the key operation parameter time sequence by using the updated model, comparing a prediction result with a dynamic fault threshold value to generate a candidate fault indication, and determining the position and category of a fault to be pre-warned in the building system through time sequence stability verification and space consistency analysis. The method can significantly improve the accuracy and real-time performance of intelligent building fault prediction, and has a good application prospect.

The invention relates to the technical field of mechanical vibration and fluid excitation coupling effect analysis, in particular to a runner crown modification pressure pulsation amplitude measurement method, which comprises the following steps of: extracting pressure gradient distribution and cavitation phase change characteristic parameters of a runner surface through fluid dynamics simulation; targeted arrangement of a high-frequency pressure sensor array in a vortex core area, a boundary layer separation critical position and a modification structure mutation area is guided, and the signal acquisition precision is improved by adopting an annular encryption and axial equal-interval arrangement strategy. And establishing a dynamic error feedback mechanism of actual measurement and simulation. And verifying an abnormal frequency band proportion through frequency domain kurtosis and analyzing envelope spectrum harmonic waves, and screening a modification parameter combination with the pressure pulsation amplitude decreasing to reach the standard and stable frequency band distribution. According to the method, the problem of measurement errors caused by multi-source high-frequency noise and effective signal frequency domain aliasing is solved, a high-precision quantification basis is provided for runner modification optimization, and the method is suitable for the field of mechanical system dynamic characteristic testing.

The invention discloses a VSG-DFIG subsynchronous oscillation adaptive suppression method based on a Hamiltonian model, and belongs to the technical field of subsynchronous oscillation suppression of a power system. The method aims at solving the problem that an existing method for suppressing subsynchronous oscillation existing in grid-connected operation of the doubly-fed induction generator is poor in suppression effect. Comprising the following steps: constructing a port controlled Hamiltonian dissipation model; constructing a closed-loop system dynamic equation based on interconnection and damping distribution under strict passivity; an expected energy function in a unit closed-loop form is constructed, a DFIG unit feedback control law based on a Hamiltonian model is obtained, and further deformation is carried out to obtain a deformed DFIG unit feedback control law; the port controlled Hamiltonian dissipation model is corrected, and a corrected port controlled Hamiltonian dissipation model is obtained; constructing a dynamic equation of the anti-interference adaptive observer, and establishing an error dynamic equation; and constructing a Lyapunov function, and designing an estimation error feedback control law according to the stability condition of the Lyapunov function. The subsynchronous oscillation suppression circuit is used for suppressing subsynchronous oscillation.

The invention discloses an SPMSM robust speed control method based on an adaptive high-order expansion sliding-mode observer, and the method comprises the following steps: designing and building a third-order LESO system according to a motor mathematical model, and the third-order LESO system is used for outputting an estimated rotating speed actual value, an estimated acceleration and estimated total disturbance; combining a non-singular fast terminal sliding mode algorithm with a disturbance observer, and designing a non-singular fast terminal sliding mode disturbance observer which is used for observing an acceleration state variable of the motor; the acceleration state variable is input into the third-order LESO system and replaces the estimated acceleration, and a high-order expansion sliding mode observer is generated; and constructing an active-disturbance-rejection controller by using the high-order expansion sliding-mode observer, linear state error feedback and total disturbance compensation, and performing speed control on the motor by using the active-disturbance-rejection controller. According to the method, high-precision observation of disturbance can be realized under the conditions that only less interference information exists and the method is not sensitive to interference frequency change.

The invention relates to the technical field of power grid stability analysis, in particular to a mechanical vibration micro-grid electromechanical coupling system stability analysis method, which comprises the following steps of: detecting a tooth surface contact radius, a relative speed and a Young modulus to generate a contact stiffness initial value, correcting nonlinear stiffness by interval difference, and calculating the stability of a micro-grid electromechanical coupling system. The method comprises the following steps: calculating a coupling response vector by combining rotor displacement and bearing clearance, inputting a Lyapunov exponent method to solve an exponent vector, constructing a model length ratio to detect derivative characteristics, extracting a multidimensional state vector in a positive value period and the coupling response vector to generate a compensation action, and constructing an FPGA simulation path injection disturbance execution error feedback back-transmission fuzzy control algorithm. According to the method, a contact stiffness dynamic correction and nonlinear difference method is introduced, six-degree-of-freedom displacement and bearing clearance parameters are combined, an electromechanical coupling model is established, a stability boundary is recognized through Lyapunov regression, a critical state is detected through derivative features, and multi-dimensional state vector fuzzy control compensation is fused. And the response and the immunity are optimized by combining FPGA simulation and a disturbance mechanism.

Integrated circuit transceivers having digital timing recovery loops with phase interpolation may incorporate dynamic loop gains to compensate for nonlinearities of the phase interpolation. An illustrative receiver circuit includes: a phase interpolator, a sampling element, a timing error estimator, and a feedback circuit. The phase interpolator provides a sampling signal by applying a phase shift to a clock signal in response to a phase control signal. The sampling element produces a digital receive signal by sampling an analog receive signal in accordance with the sampling signal. The timing error estimator produces a timing error signal indicating an estimated timing error of the sampling signal relative to the analog receive signal. The feedback circuit derives the phase control signal from the timing error signal using a scaling element configured to scale the estimated timing error by a scale factor that depends on the phase control signal.

The invention belongs to the technical field of aero-engine control, and discloses an electric fuel pump active-disturbance-rejection control method based on a radial basis function neural network. According to the method, an intelligent control system is constructed through a radial basis function neural network, an active-disturbance-rejection controller with a nonlinear state error feedback control law as a core is designed, a control strategy is adjusted in real time according to the current state of the system, the complexity of controller parameter setting is reduced, and the stability and response speed of the system are improved. Through verification, the electric fuel pump control system obtained through the design can achieve the stable and rapid control effect under all working conditions, and is high in practicability, good in system robustness and high in anti-interference capacity.

The invention belongs to the technical field of robot error compensation, and particularly relates to a positioning error iterative nonparametric compensation method based on WGA-FDBN-DC and pose dependence, and the method comprises the steps: analyzing a robot positioning error source; constructing a three-in-one positioning error compensation model; based on WOA, performing wide area search to position an error extremal region generated by asymmetric hysteresis; training samples are created, an adaptive threshold value is constructed to dynamically remove abnormal samples, and filtering parameters are updated online in combination with the stochastic approximation theory to screen the training samples; a non-linear mapping relation between joint poses and static errors is constructed through a main network of cascade closed-loop suppression, static error prediction is carried out, a compensation network analyzes dynamic coupling errors of environmental disturbance and mechanical deformation in real time, and the main network and the compensation network form closed-loop control through error feedback. The method achieves the building of a mapping model from the joint motion amount to the joint compensation amount considering the pose dependence of the absolute positioning error, and achieves the direct iteration compensation of the error generated by the joint motion.

The invention provides an automatic vulnerability detection rule generation method based on LLM and static code analysis, and relates to the technical field of network security and software engineering. The method comprises the following steps of: constructing unified structured representation of project code semantics and vulnerability features, classifying taint'source 'and'sink' based on a heuristic rule and LLM (Logical Language Model), and constructing a taint propagation path assisted by a large language model and performing risk assessment; automatically generating a rule based on a'generation-verification-repair 'closed loop mechanism; according to the method, uniform structured representation of code side information and vulnerability side information is constructed, accurate identification of specific project taint sources and sinks and effective paths in multiple environments is achieved, a path risk sorting mechanism is introduced to achieve priority detection of high-risk paths, an automatic rule of error feedback circulation aiming at correction is established, and the accuracy of detection is improved. And the correctness and the performability of the rule grammar are greatly improved, and logic vulnerabilities are reduced, so that the manual debugging and maintenance cost is reduced.

The invention relates to an intelligent design method of a radiation shielding material based on cross-scale error feedback lock step, which comprises the following steps: determining a material component set and acquiring an atomic-scale graph structure of the material component set, and extracting intrinsic performance parameters such as heat conductivity and attenuation coefficient through an atomic-scale prediction module; and then, constructing a design variable vector in combination with a multi-physical field condition, calculating equivalent performance parameters of the composite material, establishing a cross-scale lock step mechanism, and triggering a molecular dynamics and Monte Carlo recalculation module to carry out correction when the deviation between a predicted value and a mesoscopic recalculation result exceeds a limit. Based on the correction parameters, a candidate material scheme is generated by using a multi-objective optimization algorithm; and performing gamma-ray and neutron shielding performance simulation on the candidate schemes through a Monte Carlo radiation transfer model accelerated by a deep neural network, and comparing with an experimental result to realize self-adaptive material design driven by cross-scale errors. According to the method, the design precision and efficiency of the radiation shielding material are remarkably improved.

The invention belongs to the technical field of civil engineering technical construction, and particularly relates to a quantitative prediction method for engineering slurry and muck recycling output, which comprises the following steps: S1, synchronizing a construction scene in real time through BIM / GIS and Internet of Things data, and generating a virtual mirror image of a slurry / muck generation process; s2, correcting a theoretical model error according to real-time monitoring data; s3, predicting the mud / muck yield and the resource rate by adopting a time sequence analysis method and combining with a machine learning algorithm, and quantifying uncertainty; s4, dynamically optimizing model parameters through error feedback, and realizing a prediction-monitoring-correction closed loop; through cooperation of the structures, exclusive correction rules are formulated for different construction types, theoretical model errors can be corrected in time according to stratum changes and construction disturbance, and the adaptability of the model under different working conditions and the reliability of prediction results are improved.

The invention relates to a permanent magnet synchronous motor improved fractional order sliding mode active-disturbance-rejection control method based on an improved fractional order super-spiral sliding mode observer, and the method specifically comprises the steps: firstly, building a mathematical model of a PMSM in an alpha-beta and d-q coordinate system, designing an improved fractional order super-spiral sliding mode disturbance observer, and estimating the unknown disturbance in a system in real time; and finally, optimizing a steepest function and designing a fractional order tracking differentiator in combination with a fractional order calculus principle. A nonlinear state error feedback law is constructed, nonlinear calculation is carried out on the proportion, differential and integral of an error signal, and the anti-interference capability, the response speed and the control precision of the controller are improved; and combining a fractional order tracking differentiator, a fractional order state observer and a nonlinear feedback control law, and designing a fractional order sliding mode active-disturbance-rejection controller. According to the method, system buffeting is effectively weakened while the convergence speed is increased, and the robustness of the controller under load disturbance is effectively improved.

The invention discloses a ground-effect-oriented active-disturbance-rejection-based low-altitude rotor aircraft control method, and the method comprises the steps: constructing a multi-channel cooperative control architecture for a control system of a three-rotor aircraft with a control surface, and enabling the multi-channel cooperative control architecture to comprise a height maintenance channel, a yaw stabilization channel, a pitch attitude channel and a rolling attitude channel; wherein the height channel, the pitching channel and the rolling channel adopt an auto-disturbance rejection control model based on an extended state observer, and disturbance suppression is realized through nonlinear state error feedback; a yaw channel adopts a PID controller with parameter setting optimization, and the control precision is improved by utilizing the periodic disturbance suppression characteristic of the PID controller. According to the invention, the method of fusing ADRC and PID control in a three-duct configuration controller is considered, the coupling interference amount caused by inaccurate model establishment is effectively estimated and compensated, the purpose is to realize the accurate control of the attitude, height and other states of the aircraft, and the flight stability is ensured.

The invention discloses a complex curved surface slow tool servo turning trajectory optimization method based on curvature gradient clustering and trajectory error constraint, and belongs to the technical field of ultra-precision cutting machining and numerical control trajectory optimization, the method comprises the following steps: step 1, trajectory parameterization and initial equal-angle sampling; step 2, calculating a track curvature and a curvature gradient; step 3, performing automatic region classification based on curvature gradient density; step 4, performing target error constraint-based point deletion in the gentle region; 5, carrying out global error verification and out-of-tolerance feedback local encryption; and step 6, outputting a final optimized track point set. According to the method, the target curved surface can be automatically and robustly divided into a'complex area 'and a'smooth area' on the premise of not exceeding the maximum vector height error allowed by the track, an error-driven local point deleting strategy is adopted in the smooth area, and minimum local encryption is performed in an out-of-tolerance area, so that the target curved surface can be quickly and accurately encrypted. The number of final numerical control track points and the program size are obviously reduced, and the track preparation time is shortened.

The invention relates to the technical field of wireless communication, in particular to a low-altitude unmanned aerial vehicle communication system wireless space-frequency sensing method based on error feedback iteration, which comprises the following steps: a multi-antenna base station synchronizes the initial state of a target low-altitude unmanned aerial vehicle through a control signaling channel; the unmanned aerial vehicle sends a synchronization symbol block and a communication symbol block to the multi-antenna base station according to a frame structure; the multi-antenna base station receives the synchronization symbol block and forms normalized complex amplitude error feedback; the transmitting end and the receiving end synchronously utilize wireless space-frequency channel estimation to realize position sensing of surrounding environment reflection points; the method has the beneficial effects that the space-frequency channel sensing results of the receiving and transmitting ends are synchronized only by iterating initial synchronization state control information at the receiving and transmitting ends in the iteration process and only by normalizing complex amplitude error feedback in the iteration process, so that the multi-antenna configuration of the unmanned aerial vehicle is not required, and the space-frequency channel sensing results of the receiving and transmitting ends are synchronized. And the situation that the wireless base station frequently transmits high-complexity and high-link-overhead space-frequency channel estimation information to the unmanned aerial vehicle is avoided, and the real-time performance is high.

The invention discloses an intelligent stereoscopic warehouse inventory data synchronization method and device and a computer program product, and the method comprises the steps: collecting multi-source data of an intelligent stereoscopic warehouse, and constructing a multivariate data set; embedding the multivariate data set into a nonlinear mapping space, and constructing an embedded state vector for expressing inventory behaviors; a scheduling weight evaluation function is constructed based on the embedded state vector and historical error feedback, the scheduling weight of the inventory operation is calculated through the scheduling weight evaluation function, a decision is made on the synchronization mode of the inventory operation according to the scheduling weight, and the synchronization mode comprises instant synchronization, delay synchronization or merging synchronization; and based on the scheduling weight and historical error feedback, dynamically correcting the response tension coefficient of each dimension in the embedded state vector, and applying the corrected response tension coefficient to subsequent embedded state vector construction to form a feedback closed loop. According to the invention, a powerful guarantee is provided for efficient, accurate and stable operation of the intelligent warehousing system.

The invention discloses an attitude control method and system for a reentry flight process of a hypersonic aircraft and a medium, and belongs to the field of aircraft control, and the method comprises the steps: S1, building an aircraft attitude dynamic model; s2, based on the aircraft attitude dynamic model constructed in S1, decoupling the aircraft attitude dynamic model through a feedback linearization method to obtain an aircraft three-channel attitude control model; s3, designing a nonlinear active-disturbance-rejection controller based on the aircraft three-channel attitude control model obtained in S2, and determining to-be-set parameters in a nonlinear extended state observer and a nonlinear state error feedback control law in the nonlinear active-disturbance-rejection controller; and S4, on the basis of the aircraft three-channel attitude control model obtained in the S2 and the nonlinear active-disturbance-rejection controller obtained in the S3, optimizing to-be-set parameters in the nonlinear active-disturbance-rejection controller by adopting a double-delay depth deterministic strategy gradient algorithm, and finally realizing adaptive adjustment control.

The invention relates to the technical field of laser terminal pointing control, and discloses a laser terminal installation error on-orbit calibration method which comprises the following steps: S1, defining multiple coordinate systems including an ideal installation coordinate system of a laser terminal during ground calibration and an actual installation coordinate system caused by stress release or deformation after emission, and a real-time pointing coordinate system of in-orbit operation of the laser terminal. And S2, establishing a laser terminal installation error model, wherein the model defines an installation error angle through a direction relation of a coordinate system before and after terminal emission. According to the method, the installation error angle is dynamically estimated through the recursive least square method, high-precision dynamic correction of the laser terminal pointing error is achieved in combination with the rotation matrix pointing correction model, meanwhile, error feedback and time sequence control are introduced, and the problems of nonlinear error accumulation, insufficient fixed gain response and long-term error accumulation in the prior art are solved.

The invention relates to the technical field of automatic advanced control theory and application, and provides a non-matching disturbance suppression method and equipment based on an extended compensation function observer, and the method aims at a non-integral chain system with non-matching disturbance, carries out the order expansion processing of the non-integral chain system, and obtains an extended system for displaying and presenting the order derivative of the non-matching disturbance. Designing an expansion compensation function observer according to the expansion system, performing error analysis on the expansion compensation function observer, and selecting gain of the expansion compensation function observer according to a convergence principle of an expansion error equation; and a model compensation control strategy is designed according to the extended compensation function observer and the state error feedback, so that the non-matching disturbance of the non-integral chain system is inhibited. According to the method, the non-matching disturbance of which the order derivative approaches zero can be estimated, so that the limitation on the disturbance is greatly relaxed, and an anti-disturbance control solution with higher precision and wider applicability is provided.

The invention discloses a ship rust removal mechanical arm anti-interference motion control method introducing jet flow counter-acting force, and relates to the technical field of ship rust removal equipment control. Aiming at the problems of poor robustness, easy saturation of an integral term and poor dynamic response effect when a ship rust removal mechanical arm is faced with water jet reaction force and other interferences in traditional PID control, the invention provides an active disturbance rejection control (ADRC) scheme introducing jet reaction force. The method comprises the following steps: constructing a jet reaction force model, mapping the jet reaction force model into a joint torque compensation item based on a Jacobian matrix, and integrating the joint torque compensation item to an ADRC control law; an improved tracking differentiator, a nonlinear extended state observer (ESO) and a nonlinear state error feedback (NLSEF) module are designed, real-time estimation and compensation of internal and external disturbance of a system are achieved, and joint control performance is optimized. Experiments show that by means of the method, the joint angular displacement tracking error can be reduced by 10% or above, the adjusting time is shortened to 2 s from 10 s, the absolute value of the transient error is smaller than 0.3 rad, and the anti-interference capacity and the control precision of the mechanical arm are remarkably improved.

The invention relates to the field of control, in particular to a flight attitude control method and system for an unmanned aerial vehicle, and the method comprises the steps: obtaining an expected attitude angle instruction and actual attitude angle feedback of the unmanned aerial vehicle, calculating an attitude angle error, employing a tracking differentiator to calculate a transition process for the expected attitude angle instruction, and enabling a tracking rate factor to achieve the control of the flight attitude of the unmanned aerial vehicle when the instruction is subjected to step change. Based on initial attitude angle error setting, instruction smooth transition is ensured, based on a transition signal output by a tracking differentiator and an estimated value of an expansion state observer, a basic control quantity is generated through nonlinear state error feedback, and control gain is adjusted on line according to a lumped disturbance amplitude. And predicting the lumped disturbance historical sequence by using a grey prediction model, calculating a predicted value at a future moment, and carrying out algebraic summation on the basic control quantity, a compensation component of the lumped disturbance predicted value and a gyroscopic moment decoupling component to generate an attitude control moment signal so as to realize stable flight of the unmanned aerial vehicle.