788 results about "Stabilization control" patented technology

The present application belongs to the technical field of material processing, and relates to a mold-free mirror image filament laying method and a mold-free mirror image filament laying system. The method lays a filament ribbon in a mirror image symmetry, without a mold, thereby improving production flexibility and efficiency. The method acquires the temperature and pressure of the filament ribbon in real time, calculates the output power of a heater and the modification value of a filament laying end motion mechanism path by using temperature and pressure differences, and optimizes controller parameters through reinforcement learning, so as to realize stable control of the temperature and pressure. The system comprises a hardware part and a control system. The hardware part includes pressure and heat source components. The control system adjusts through real-time feedback to ensure the quality of filament laying. The present application solves the problem that the temperature and pressure are difficult to accurately control in the process of mold-free mirror image filament laying, and improves the performance of composite products.

The invention provides a medical RFQ accelerator low-level signal phase stability control method and system. The method comprises the following steps: constructing a time-frequency energy spectrum feature vector based on wavelet packet transformation; extracting a second disturbance feature based on a lightweight convolutional neural network and an attention mechanism; constructing a phase dynamic trend prediction module based on a long short-term memory network, and obtaining a first prediction phase error; constructing a phase compensation module based on a residual control network to obtain a second phase compensation amount; and outputting a real-time driving control signal based on the extended Kalman filter. According to the method, the time-frequency energy spectrum feature vector based on wavelet packet transformation is constructed, accurate characterization of the multi-scale disturbance features of the low-level signals is achieved, a medical RFQ accelerator phase dynamic compensation system is established in combination with a deep learning network and an extended Kalman filtering algorithm, the control precision and the anti-interference capability of signal phase stability are remarkably improved, and the method is suitable for popularization and application. The method is suitable for a high-precision medical particle accelerator control system.

The invention relates to the technical field of automatic control, and discloses a pressure closed-loop self-calibration method for an ultrahigh-speed jet injection process, and the method comprises the steps: initializing a system, and building a pressure and temperature combined compensation model; a high-precision sensor is used for collecting real-time pressure and temperature data; by calculating a pressure deviation intelligent switching control strategy, PID is combined with feed-forward compensation in a steady state, and a deep reinforcement learning algorithm is switched to realize quick response in a transient state; automatically triggering closed-loop self-calibration according to operation time or a deviation threshold value, executing zero point and full scale calibration and updating compensation parameters; and carrying out residual analysis by using a digital twinborn model to realize fault diagnosis and early warning. According to the invention, the problems of low control precision and poor long-term stability of an ultra-high-speed jet flow process under nonlinear and large-lag working conditions are solved, and high-precision stable control and system self-adaptive calibration under a wide speed range are realized.

The invention provides an overhead and portal crane lifting appliance control method based on multi-stage model predictive control, and relates to the field of data processing. The method comprises the following steps: firstly, acquiring a control parameter and an initial state variable so as to define an operation boundary and an initial state, and establishing a dynamic model containing a coupling relationship among a trolley acceleration, a sling rope length acceleration and a sling swing angle; acquiring obstacle distribution by using space sensing equipment, and calculating the dynamic safety height of the lifting appliance by combining obstacle parameters and control parameters; judging whether the lifting appliance is in an obstacle avoidance stage or a target tracking stage according to the initial state variable and the dynamic safety height; constructing a model prediction controller and dynamically adjusting a state weight matrix and a control input weight matrix; finally, a control input sequence is generated through an optimization algorithm, and track safety and attitude stability control of the lifting appliance is achieved. According to the technical scheme, the swing angle of the lifting appliance is restrained, meanwhile, the obstacles are effectively avoided, and the safety of the lifting appliance in the whole operation process is guaranteed.

The invention relates to the technical field of cold box control methods, in particular to a rapid and stable control method and device for a cold box. According to the technical scheme, the system comprises a cold box historical state feature library, a dynamic feed-forward compensation calculation module and a cooperative control output module; the method specifically comprises the following steps: S1, constructing a cold box historical state feature library; and S2, historical state modeling and dynamic feed-forward compensation control strategy. The feed-forward dominant control is performed by using the historical optimal moving trajectory, so that the valve can be adjusted more actively and more closely to the actual thermal state of the cold box, and the time required for the cold box to reach the target stable working condition is remarkably shortened. The temperature control stability and safety are remarkably improved, the risks of cracks, leakage and even damage of equipment are greatly reduced, and the service life of the cold box is prolonged; the comprehensive utilization efficiency of applications such as liquid-air energy storage is improved; and by reducing the risk of thermal stress damage, the equipment maintenance cost and the accidental shutdown loss are reduced.

The invention discloses a dynamic environment robot adaptive control method and system, and relates to the technical field of robot adaptive control. According to the invention, dynamic compensation is realized based on multi-sensor fusion and real-time anomaly detection in combination with impedance compliance control; through a lightweight error model and a trajectory interpolation technology, the calculation efficiency is improved compared with traditional model prediction control, and high-frequency real-time correction is supported; the system adopts a modular design, and adapts to a heterogeneous robot platform by adjusting equivalent mass-damping-spring parameters; for sudden disturbance, trajectory smoothing and impedance control technologies are fused, the oscillation amplitude of the system is reduced, and execution jitter is effectively inhibited; according to the method, high-precision force tracking and stable control are achieved in scenes such as complex terrain walking and dynamic grabbing, the problems that traditional fixed parameter control response is lagged, model dependence is high and an actuator is overheated are solved, and the adaptive capacity of the robot to the dynamic environment and the task completion rate are remarkably improved.

The invention discloses a numerical control machine tool machining state monitoring method and device, and belongs to the technical field of digital machine tool control. The method comprises the following steps: step 1, constructing a double-layer sensing network system consisting of an environment layer and a machine tool layer, and realizing preliminary physical isolation of environment parameters and a machine tool thermal state; 2, forming a multi-dimensional parameter mapping library of environmental influence and self-heating; 3, decomposing the temperature change signal into a low-frequency environment component and a high-frequency processing thermal response component, respectively extracting environment characteristics and processing characteristics in the low-frequency environment component and the high-frequency processing thermal response component, and realizing real-time classification and decoupling of the temperature signal; 4, constructing a heat influence cross matrix, and quantitatively describing the influence degree and interaction effect of the environmental parameter change and the machine tool heating on the precision of each shaft; and 5, designing a dual-channel parallel compensation control mechanism based on an analysis result of the thermal influence cross matrix, generating a final compensation instruction, and implementing and executing the final compensation instruction to realize precision stable control.

The invention relates to the technical field of coal underground gasification control, in particular to a stable control method for the gasification process of deep coal passing through dirt band. The gas pressure distribution data and the pore change characteristic data of the deep coal gasification area are collected in real time through the distributed sensor array, the gas dynamic correction permeability is generated, the gas injection pressure is adjusted and dynamically corrected according to the gas dynamic correction permeability, and the gas pressure is kept stable; screening a potential risk area through a main stress direction deviation angle and a stress concentration coefficient in the dirt band layer, analyzing a shear stress threshold value of the potential risk area based on a stress-strain coupling model, and judging a stability evaluation index of the potential risk area; and when the stability evaluation index is lower than a threshold value, a multi-stage emergency regulation and control mechanism is triggered, and a dirt band layer reinforcement intervention scheme is generated. By means of multi-source data fusion and a dynamic feedback mechanism, the limitation of a traditional method for lagging response of the instability risk of the dirt band layer is broken through, and full-closed-loop intelligent stable control over the gasification process is achieved.

The invention discloses a data-driven event trigger control method for a linear variable-parameter nonlinear system, which comprises the following steps: for a discrete-time nonlinear system with an unknown model, expressing the nonlinear system as a parameter-dependent linear form by using a linear variable-parameter embedding method; constructing a convex polyhedron-based noise matrix set for unknown bounded noise in the measurement data, and proposing polyhedral data-driven LPV system representation by using offline collected state, input and scheduling variable data; designing a bounded dynamic event trigger transmission mechanism, and optimizing the use of communication resources by adjusting a trigger threshold in real time and setting the upper and lower bounds of a transmission interval; based on a discrete time cycle functional analysis method, controller gain and trigger parameters are jointly designed through a linear matrix inequality tool. The method does not depend on an accurate system model, stable control over a nonlinear system is achieved only through historical data, the communication frequency is remarkably reduced, and meanwhile the system performance and robustness are guaranteed.

The invention relates to the technical field of sensor data fusion, in particular to a real-time dynamic attitude stability control method and system based on multi-sensor fusion, and the method comprises the following steps: collecting multi-source sensor data, and correcting to generate a synchronous sensor data set; calculating a stability coefficient, a signal quality coefficient and a consistency coefficient, weighting the signal quality coefficient and the consistency coefficient to generate a dynamic fusion weight coefficient, executing weighted fusion based on the weight, outputting a fusion attitude state estimation result through adaptive extended Kalman filtering, and generating an optimization control instruction sequence by combining with dynamic constraint model rolling optimization; according to the method, a dynamic weight mechanism based on noise and signal strength is introduced to achieve self-adaptive fusion, the synchronization precision and reliability are improved by combining consistency verification, abnormal signals are corrected through self-adaptive filtering, the attitude estimation stability is enhanced, and the performance of the system is improved. And a control instruction is generated through rolling optimization, so that rapid and accurate adjustment is realized, and attitude keeping and control consistency in a complex environment is improved.

The invention discloses a satellite attitude system anti-interference finite time control method under complex dynamic disturbance, and the method comprises the steps: building a rigid satellite attitude maneuver control model according to satellite attitude dynamics and kinematics equations; designing a self-adaptive fine disturbance observer to estimate the total disturbance of a satellite attitude system by combining the influence of the external disturbance variable on the rigid satellite attitude maneuver process, and outputting an estimated value of the external disturbance variable; a three-stage segmented sliding mode control method is designed, dynamic continuity of a three-stage sliding mode is ensured, and segmented sliding mode control output is obtained; and compensating the segmented sliding mode control output by using an estimated value of an external disturbance variable output by a self-adaptive fine disturbance observer to realize satellite attitude stable control. According to the method, the problem that the stability of the satellite is reduced in the attitude maneuvering performance process when external disturbance exists is solved, better observation performance and shorter attitude stabilization time are achieved, and the control precision of the satellite is effectively improved.

The invention provides a vehicle control method, electronic equipment and a storage medium, and the method comprises the steps: controlling the driving torque of wheels according to the actual slip rate and the target slip rate of the wheels under the condition that a low-load starting stability control function of a vehicle is activated, a first deviation between the target slip rate and the actual slip rate is maintained in a first set range; and according to the actual yaw velocity and the target yaw velocity of the vehicle, the rear wheel rotation angle is controlled, so that a second deviation between the target yaw velocity and the actual yaw velocity is maintained within a second set range. According to the technical scheme, the acceleration performance of the vehicle under the low-load starting working condition is effectively improved, the steering wheel correction amplitude and frequency of a driver are effectively reduced, the control confidence of the driver is enhanced, and the driving control experience is improved.

The invention discloses a multifunctional hydraulic system experiment table, which relates to the technical field of hydraulic system experiment tables and comprises a time base line synchronous control module, a phase lock correction stability control module, a false peak identification and correction module, a multi-dimensional fault-tolerant judgment control module and a reverse energy slow-release anti-reverse module. And the time base line synchronous control module is used for establishing a cross-sensor unified time base line control structure, generating a synchronous reference surface by using a high-stability crystal oscillator signal, and executing nanosecond phase calibration on sampling signals of the pressure sensor and the flow sensor by taking the synchronous reference surface as a unified time reference. According to the invention, high-precision synchronous acquisition of pressure and flow signals is realized through unified time base line and phase locking correction, and high-pressure transient test data is ensured to be real and stable; and meanwhile, control logic is reconstructed, and an energy slow release strategy is introduced, so that the pressure relief process is stable and controllable, pump reverse rotation and structural impact are avoided, and the safety, reliability and self-healing stability of the experiment table are remarkably improved.

The invention discloses a micro-grid layered stability control method and system, and relates to the technical field of micro-grid control. Periodic data and instruction signals of upper and lower layer control links of a micro-grid are collected, and reverse adjustment delay amount and an idle stroke deviation value during period switching are calculated; processing to obtain a period difference index and a collaborative adaptation index containing an impact coefficient; analyzing a time sequence action relationship between the period difference index and a micro-grid adjusting link, and calculating a connection deviation coefficient of a control rhythm by counting lagging frequency and amplitude of instruction response; potential problems of a micro-grid control link can be found in advance, stable operation time is prolonged through strategy adjustment when the instability risk is low, maintenance is conducted in time before the risk rises, power failure accidents caused by layered control mismatch are reduced, and the operation stability and reliability of the micro-grid are improved especially for the micro-grid with the high new energy proportion and large fluctuation.

The invention discloses an unmanned ship formation maneuvering control method considering intermittent communication failure and based on a memory cache mechanism, and belongs to the field of unmanned ship cooperative control. The method and the device are used for solving the problems of poor control robustness, insufficient formation flexibility and strong dependence on global information in a communication interruption scene in the prior art. The method comprises the following steps: establishing an unmanned ship kinematics and dynamics model; constructing a cache region and endowing historical data with different weights to realize state prediction compensation; defining a cluster communication topology and an affine transformation relationship, and dividing a leader and a follower; designing a positive minimum interval event triggering mechanism to reduce communication frequency; constructing a fully distributed state observer based on memory cache; and designing a distributed formation controller to realize flexible formation control. The method is suitable for stable control and dynamic formation in cooperative tasks of multiple unmanned ships in a limited water area or a complex environment.

The invention provides a non-linear flight control method and system for an anti-wind disturbance unmanned aerial vehicle. The method comprises the following steps: acquiring wind field disturbance characteristics in real time by using a preset meteorological radar; inputting the wind field disturbance characteristics into a preset aerodynamic disturbance prediction model to generate an aerodynamic torque fluctuation prediction value; preset dynamic filtering processing is applied to the amplitude characteristic of the aerodynamic torque fluctuation predicted value so as to generate a control instruction correction signal; and the control instruction correction signal is coupled with a preset nonlinear control law of an unmanned aerial vehicle flight control system, so that unmanned aerial vehicle attitude offset caused by wind disturbance is inhibited in real time, and unmanned aerial vehicle nonlinear flight control is carried out. According to the method, the composite defect of hysteresis and filtering mismatch of traditional linear control in a strong wind sudden change scene is overcome, stable attitude control of the unmanned aerial vehicle in low-altitude wind shear and gust sudden attack is realized, the anti-interference response speed of the unmanned aerial vehicle is remarkably improved, and the out-of-control risk of the unmanned aerial vehicle is greatly reduced.

The embodiment of the invention provides a method and device for stably controlling an airplane in the auxiliary landing process, computer equipment and a medium, and the method comprises the following steps: judging whether the airplane is in a gliding stage, if so, activating a gliding stage control law, and if not, controlling the airplane to stably control the airplane through the gliding stage control law. The aircraft is controlled through the elevator centering instruction and the horizontal stabilizer automatic trimming instruction until the aircraft quits the gliding stage, and the gliding stage control law is quitted; if the aircraft enters the pull-up stage from the glide stage, activating the leveling stage control law, generating an elevator control instruction based on the steering column displacement and the steering column displacement nonlinear gain through the leveling stage control law, generating a rudder control instruction based on the pedal displacement signal and the pedal displacement nonlinear gain, and controlling the elevator control instruction and the rudder control instruction according to the pedal displacement signal and the pedal displacement nonlinear gain. And controlling the aircraft through the elevator control instruction and the rudder control instruction until the aircraft is grounded. According to the scheme, the landing quality and safety are improved through the staged aircraft auxiliary landing control law.

The invention discloses a welding wire production control system and method based on visual feedback, and belongs to the technical field of precision machining. The system comprises a multi-mode intelligent sensing subsystem, a self-adaptive model prediction controller and a safety and exception handling subsystem, and a two-stage control architecture of a quality closed loop and an execution closed loop is constructed. According to the method, the microcosmic roughness, macroscopic geometry, defects and other multi-dimensional quality characteristics of the surface of the welding wire are obtained in real time through multi-modal sensing and fused into a comprehensive quality index; carrying out rolling optimization by adopting a model prediction control algorithm for updating parameters on line, and generating a control instruction; meanwhile, trend early warning based on statistical process control and sudden fault diagnosis based on model residual analysis are operated in parallel, and active safety protection is achieved. According to the method, the problems of unstable quality, control lag and passive safety caused by supplied material fluctuation and tool time variation in the welding wire flaking machining process are solved, and self-adaptive accurate control and intelligent safety protection in the machining process are achieved.

The invention discloses an intelligent control method for a tailing filling process based on data driving, which relates to the technical field of automatic control, and comprises the following steps: collecting multi-source working condition data, and constructing a working condition feature vector after fusion denoising and normalization; splicing the working condition feature vectors in a preset time window, training a three-day age intensity prediction model and a pipe blockage risk scoring model, and generating a filling evolution state vector; clustering the filling evolution state vectors, calculating a state center, constructing a safety operation window according to a state category, and calculating a safety margin; constructing a stability margin index under the constraint of a safe operation window, and solving a stability control quantity through rolling optimization; and forming an incremental sample set through the latest operation data, and performing unified incremental updating on the prediction model and the safety operation window. According to the method, the filling evolution state vector and data-driven three-day-age intensity prediction model and the pipe blocking risk scoring model are constructed, so that the fine quantification and the advanced pre-judgment of the tailing filling working condition and the key safety performance are realized.

The invention belongs to the technical field of compressors, and particularly relates to an MVR (mechanical vapor recompression) vapor compressor, a detection control system with multi-stage recognition capability is introduced on the basis of compressor basic equipment, and the system collects vapor parameters, mechanical states and process state data in real time through a multi-dimensional state sensing module; the operation stage identification module intelligently divides the system operation process into an initial starting stage, a transition stage and a stable operation stage according to the data; and the self-adaptive control module calls a corresponding preset strategy set according to the identified different stages and dynamically adjusts the rotating speed and the compression ratio of the compressor, for example, low-speed soft start is executed in the initial stage of start, smooth tracking adjustment is performed in the transition period, and accurate and stable control is implemented in the stable operation period. Self-adaptive and refined regulation and control of the whole process from starting to stabilization of the system are achieved, mechanical and electrical impact is effectively reduced, variable working condition adaptability and operation stability are improved, and the overall energy efficiency is optimized.

The invention discloses a control method and system of a miniature four-rotor unmanned aerial vehicle. The method comprises the following steps: acquiring a sensor signal sent by the miniature four-rotor unmanned aerial vehicle; according to the attitude angle information in the sensor signal and the total moment output to the miniature quadrotor unmanned aerial vehicle at the previous moment, acquiring a state quantity and a disturbance signal which are output by a linear extended state observer LESO in the controller and are associated with the attitude angle signal of the miniature quadrotor unmanned aerial vehicle; according to the state quantity, the disturbance signal, expected attitude information corresponding to the reference trajectory, and position information and speed information of the miniature quadrotor unmanned aerial vehicle in the sensor signal, a control instruction is output to the miniature quadrotor unmanned aerial vehicle, so that the miniature quadrotor unmanned aerial vehicle realizes high-dynamic flight based on the reference trajectory; wherein the reference track comprises a dynamic window drilling track penetrating through the target window. According to the method, the problem that the miniature unmanned aerial vehicle carries out fine tasks under a high dynamic condition is solved, and multi-state-quantity rapid tracking, stable control and planning are realized.

The invention relates to the technical field of gas turbine devices, and particularly provides a gas turbine hybrid propulsion control method for response matching and energy management. The method generates a gas turbine power variation curve and a response delay trajectory of the electrical power output unit, and forms a sequence of response reverse evolution trajectories. A response lag trend is identified based on the sequence, a reverse dynamic traction instruction set is generated, and reverse torque cooperative intervention is triggered when the electric excitation frequency is abnormal. And constructing an accumulated energy curved surface through time integration, and identifying an energy level coupling critical region and generating a system control response path in combination with a dynamic margin sequence. In the path execution process, the system continuously identifies non-structural disturbance, constructs a disturbance factor combination vector, projects the disturbance factor combination vector to a power principal axis vector space and reconstructs a control path. And finally, integrating the multiple types of instruction sets into a polymorphic coupling stable control instruction set to realize stable cooperative control and smooth power transfer between the gas turbine and the electric power output unit.

The invention provides a flying robot control method and device based on force feedback and a medium, and the method comprises the steps: deploying a six-dimensional force torque sensor at an operation end effector of a flying robot, and obtaining and screening effective torque data in real time to obtain a force error signal; a compensation layer based on the Lyapunov self-adaptive law is utilized, the total disturbance is cooperatively estimated in combination with double observers, and the disturbance serves as a feed-forward quantity to be injected into an attitude controller; and calculating the adjustment amount according to the target impedance model and the force error, and generating an execution mechanism control instruction. According to the technical scheme provided by the invention, stable control of air interaction operation can be realized, and the anti-disturbance capability and interaction force control precision of the flying robot are effectively improved.

The invention discloses a spacecraft Hall propulsion device test working medium flow stability control system, which comprises a sensing module for detecting working condition state parameters of working medium supply equipment, and an adaptation module for exploring current working condition control parameters by combining detection data of the sensing module and similar working condition control parameter empirical data fusion, the adjusting module is used for receiving the control parameters and dynamically adjusting the adjusting weight of the adjusting device according to different phase change periods, an experience library unit and a self-adaption unit are arranged in the adaption module, the experience library unit provides experience data of similar working conditions and control parameters, and the self-adaption unit provides self-adaption data of the control parameters. And the autonomous adaptation unit fuses and explores control parameters by constructing a neural network adaptation model, so that working condition automatic identification and control parameter autonomous adaptation under the environment that the working medium type or the working medium state rapidly changes are realized; the problems of low control precision and slow response speed caused by manual presetting of control parameters of different working media in a traditional control technology are solved, and stable control of the working medium flow is realized.

The invention discloses a network construction type energy storage transient stability optimization control method and system considering reactive power degradation, and belongs to the field of power system transient stability control. According to the method, a network construction type energy storage grid-connected system model is constructed, a reactive power degradation effect dynamically triggered by a reactive power control loop is analyzed, and an active power loop optimization control equation is established according to the reactive power degradation effect. On the basis, a self-adaptive torque adjusting module is embedded in an active control module, and when it is monitored that the internal voltage of the inverter is reduced to 50% of a rated value, the reference torque is automatically and dynamically corrected so as to improve the power angle transient stability margin of the system. Simulation results show that the method can effectively restrain the instability of the network construction type energy storage power angle, obviously enhance the transient stability of the system, and guarantee the safe and reliable operation of the power grid.

The invention belongs to the technical field of material processing, and relates to a composite mirror image fiber placement method and a system capable of realizing stable pressure control. The mirror image fiber placement method for the composite material comprises the following steps: laying two fiber ribbons in a mirror image symmetry manner without using a mold, and repeating the fiber placement process for multiple times; and real silk ribbon pressure is obtained in real time in the silk placement process, the pressure difference is calculated in real time, the modified value of the silk placement tail end movement mechanism path is calculated in real time according to the pressure difference, and the silk placement tail end movement mechanism path is updated in real time. The system capable of realizing stable pressure control comprises a hardware part and a control system, the hardware part comprises a fiber placement tail end movement mechanism and a pressure sensor; the control system comprises a pressure stability control subsystem, a control instruction generation subsystem and a fiber placement tail end movement mechanism control subsystem. The problem that the pressure is difficult to accurately control in the mold-free mirror image fiber placement process is solved, and the performance of a composite product is improved.

The invention belongs to the technical field of fluid control, and particularly relates to a system for predicting nuclear power plant valve opening and flow nonlinear sudden change. The preprocessing and mechanism analysis module is responsible for performing deep processing and consistency review on the data acquired by the sensor, and performing modeling and parameter correction on flow sections of different types of valves in combination with a physical mechanism; the data driving prediction module is responsible for performing XGBoost modeling and reasoning on historical and real-time collected multi-dimensional data on the basis of a physical mechanism analysis result, outputting a fine prediction value of the valve flow and providing a more sensitive response for a nonlinear abrupt change region; and the hybrid model fusion and adaptive updating module is responsible for organically fusing prediction results of the physical mechanism model and the XGBoost model, dynamically adjusting model parameters according to real-time operation data, and realizing high-precision prediction and stable control of the valve flow. According to the invention, real-time and high-precision prediction of non-linear abrupt changes possibly occurring in different opening degree intervals of the valve is realized.

The invention belongs to the technical field of multi-agent cooperative intelligent control, and particularly relates to a multi-mechanical-arm cooperative control method under unknown disturbance, which comprises the following steps: establishing a dynamic model of a strict feedback nonlinear multi-mechanical-arm cooperative system; constructing a communication topological structure of the system through a virtual coupling mechanism; constructing a unified system collaborative error model; introducing a preset time function and a global preset performance function, mapping errors to an adjustable constraint performance space, and ensuring that all error signals are dynamically converged in a performance range set by a user; a task layer shape control force and a pose control force are designed under a distributed gradient descent method framework, a task layer overall control force is constructed, and multiple mechanical arms are driven to move cooperatively and keep a stable formation in a task space; designing a joint layer distributed adaptive control law under unknown disturbance through passive characteristics of a nonlinear system; according to the method, cooperative convergence and stable control of the multi-mechanical-arm system within the preset time can be achieved under unknown disturbance.

The invention relates to the technical field of shield tunnel reinforcement, and particularly discloses a foundation correction unit and a monitoring correction device for shield tunnel segments. The basic correction unit is composed of a duct piece support and a sliding rail base and is fixed to the surface of a duct piece in a lossless mode through a vacuum suction cup. The monitoring and correcting device is formed by connecting a plurality of annular correcting units and / or longitudinal correcting units, and the annular / longitudinal correcting units are formed by connecting basic correcting units and bidirectional force application rods and are integrated with monitoring sensors. The monitoring and correcting device is also provided with an automatic control system which comprises a data acquisition module and a servo module, the data acquisition module acquires monitoring data of the displacement sensor, the angle sensor and the vacuum gauge in real time, the servo module resolves the monitoring data in real time and generates a control instruction, and the suction force of the suction cup and the tension and compression load of the hydraulic oil cylinder are dynamically adjusted. And active correction of duct piece deformation and structural stability control are achieved. The tunnel deformation development can be effectively inhibited while the structural integrity of the duct piece is guaranteed.

The invention discloses a single-loop droop control method and system for a wind generating set, and the method comprises the following steps: constructing a doubly-fed fan-power converter-power grid three-module coupling model, and completing the dynamic adaptation of the characteristics of a doubly-fed fan of a single-loop droop control architecture without inner-loop current control; based on the input signal-model collaborative integration body and the adaptive architecture, MIMO-GBC is adopted to analyze a phase margin and a resonance peak value of an open-loop transfer function matrix eigenvalue of a dynamic small signal model, and double risks are identified in a full slip rate interval; aiming at the resonance risk, a current induction type virtual impedance strategy is adopted; aiming at insufficient phase margin, adopting a transient phase calibration strategy; and according to the real-time slip ratio of the DFIG and the stator power change, inter-partition linkage optimization is carried out on the virtual resistance and the phase calibration angle so as to minimize a dual-power step response fluctuation square mean value, a parameter setting period and a rotor side converter control period are synchronously matched, and all-working-condition stable control is realized.