22results about How to "Ensure control" patented technology

The invention discloses an iterative learning control optimization method for a direct current motor with non-repetitive disturbance, and relates to the technical field of direct current motor control, and the method comprises the steps: lifting a nominal model of a nonlinear system to a high-dimensional linear space through a deep Koopman operator, and obtaining the description of a high-dimensional state space model of the nonlinear system; converting the state space model into a linear repetition process model, and obtaining a linear matrix inequality condition of system convergence in a high-dimensional space by using a two-dimensional iterative learning control method; further, the intelligent agent is trained in a high-dimensional state space model iterative learning control system with model mismatch and a non-repetitive uncertainty nonlinear system, and finally the intelligent agent is applied to an actual system. The control law gain obtained by the method can better adapt to an original nonlinear system, a deep reinforcement learning algorithm is designed to compensate non-repetitive disturbance, and zero-error tracking of expected output is basically achieved.

The invention relates to an intelligent industrial control parameter self-tuning method and equipment. The method comprises the following steps: performing piecewise linearization processing on an actuator input and output characteristic curve in the industrial control system, constructing an upper-layer agent model and a lower-layer agent model, and combining to obtain a system dynamic characteristic prediction model; performing state observer design and gain matrix optimization on the industrial control system based on the system dynamic characteristic prediction model to obtain a system state observation vector and an interference compensation vector; inputting the system state observation vector and the interference compensation vector into a fixed time convergence controller for control parameter calculation to obtain a system control input matrix; and performing adaptive gradient descent operation and momentum item optimization on the system control input matrix, and outputting an optimal control parameter matrix in combination with the system dynamic characteristic prediction model. According to the invention, real-time automatic adjustment of the control parameters is realized, the steady-state error of the system is effectively reduced, and the control performance of the control system under different working conditions is ensured.

The invention relates to the technical field of under-actuated crane system motion control, in particular to an enhanced coupling positioning anti-swing control method and system for a crane with distributed mass loads. Based on a Lagrange kinetic equation, establishing a six-degree-of-freedom bridge crane nonlinear model with distributed loads, and analyzing the kinetic characteristics of the six-degree-of-freedom bridge crane nonlinear model; establishing an energy function of the model based on the bridge crane nonlinear model, constructing a new coupling signal based on a displacement signal of the model to enhance dynamic coupling among a trolley, a lifting hook and a load, and constructing a new state vector based on the constructed coupling signal to enhance dynamic coupling among the trolley, the lifting hook and the load. Substituting the constructed new state vector into an energy function of the model so as to obtain a new class energy function; establishing a nonlinear coupling controller with swing angle information according to the proposed new energy-like function; according to the method, linear processing does not need to be carried out on a kinetic equation of a crane system in controller design, and finally efficient trajectory tracking and positioning and load swing suppression are achieved.

The invention discloses a string type network energy storage converter control method, and the method comprises the steps: enabling an energy storage converter to take an SOC mean value as the feedback of an SOC equalization ring, and obtaining an SOC equalization ring output value; superposing the output value of the secondary frequency modulation ring, the output value of the SOC equalization ring and the output value of the primary frequency modulation ring as an active given value, and obtaining a reference value of the frequency through a VSG active frequency control ring; taking the output value of the secondary voltage regulating ring as a reactive given value, obtaining a reference value of a VSG reactive amplitude control ring through the primary voltage regulating ring, and obtaining a reference value of voltage through the amplitude control ring; inputting the obtained reference value of the frequency and the reference value of the voltage into a voltage and current double closed loop to obtain an output signal for following the reference values, and further generating a driving signal for controlling a switching tube of the energy storage converter; according to the invention, the communication load rate can be reduced, when large frequency and voltage fluctuation occurs, the voltage and frequency stability problem can be independently solved, the self-recovery control of secondary regulation is realized, and the frequency and the output voltage of the system are dynamically regulated in real time.

The invention relates to the technical field of industrial management, in particular to a control system and method for float glass production, and the system comprises a raw material batching control module, a smelting process control module, a forming and cooling control module, a cutting and fragmenting module, a quality detection module, a data recording and analyzing module and a man-machine interaction module. Compared with the defects of complicated operation, insufficient proportioning precision and difficulty in accurate evaluation of mixing uniformity in the raw material proportioning process in the prior art, the scheme adopts the optimized raw material proportioning control module, and the module receives and reads production plan and formula data through the man-machine interaction module, accurately weighs various raw materials, and accurately evaluates the mixing uniformity. The raw materials are fully mixed in sequence through the premixing machine and the mixing machine, the density of each sample is subjected to spot check, and the mixing uniformity is calculated according to a specific formula, so that the raw material proportioning accuracy and the mixing uniformity are effectively improved, the high-quality preparation of the float glass production raw materials is ensured, and the production efficiency and the product quality are remarkably improved.

The invention discloses a dynamic event triggering preset time fault-tolerant control method considering a non-affine fault. The method comprises the following steps: carrying out online approximation on an unknown nonlinear term in a dynamic decoupling model by adopting a fuzzy logic system to obtain an optimized system model; constructing a segmented preset time performance function, and introducing an instruction filter based on a dynamic surface control technology to process a virtual control signal of the constructed adaptive virtual control law so as to obtain a filtering error; constructing a dynamic signal compensation mechanism based on the filtering error in combination with a sectional preset time performance function, and obtaining a compensated final tracking error; and constructing a dynamic event triggering mechanism to obtain a final fault-tolerant controller, and realizing dynamic event triggering preset time fault-tolerant control considering the non-affine fault according to the final fault-tolerant controller. According to the method, the technical problems of uncontrollability of convergence time, influence of actuator faults and nonlinearity on control performance and limitation of communication and computing resources in the existing method are solved.

The invention relates to a pseudo-random high-frequency quarter sinusoidal signal injection method and system for permanent magnet synchronous motor sensorless control, and belongs to the technical field of motor control. The method aims at solving the problems that noise is remarkable, torque ripple is aggravated and rotor position estimation precision is limited due to signal injection during zero-low-speed operation of a traditional high-frequency injection method. According to the technical scheme, the method comprises the following steps: constructing a pseudo-random high-frequency windowing quarter sine injection signal to suppress noise and torque ripple; high-frequency response current containing rotor position information is obtained through Clark transformation and Park transformation; designing a layered second-order generalized integrator band-pass filtering method to accurately extract position signals; and a cosine delay elimination normalization demodulation method is provided to eliminate the influence of the delay effect. According to the invention, synchronous improvement of noise suppression, torque ripple attenuation and rotor position estimation precision is realized, and the system stability and reliability are significantly enhanced.

The invention discloses an embedded frameless torque servo motor, and relates to the technical field of frameless motors, the embedded frameless torque servo motor comprises an embedded frameless torque servo motor stator body, and the interior and the bottom of the embedded frameless torque servo motor stator body are respectively provided with a self-inspection early warning mechanism and a mounting mechanism; according to the invention, after the stator body of the embedded frameless torque servo motor is started, a controller can start an electric push rod, the electric push rod enables a mounting box to be close to a rotor body, and a detection separation blade is automatically attached to the inner wall of the stator of the motor and the outer wall of the rotor body, so that the consistency of measurement references is ensured; the gear ring and the mounting box are driven to rotate around the rotor body, so that the detection separation blade can detect the air gap around the whole rotor body, the detection range is ensured to cover the whole air gap area, local errors caused by fixed detection points are avoided, and the detection accuracy is improved.

The invention provides a micro-grid fixed time dynamic event trigger control method based on an observer, and belongs to the technical field of micro-grid operation control. The control method comprises the following steps: judging whether the voltage and frequency of primary droop control of a power control variable of an ith DG unit in the time-delay island micro-grid deviate from reference values or not, if so, performing secondary control, and if not, performing secondary droop control; by designing a voltage recovery variable, a frequency recovery variable and an active power recovery variable of micro-grid fixed time dynamic event trigger control based on an observer, the output voltage and the output frequency of a distributed generator are recovered to reference values within convergence time. According to the optimization method, the fixed-time dynamic event triggering observer with the confidence factor observes the transmission delay state, the adverse effect of delay on the control performance is limited, operation of each DG unit in the micro-grid is coordinated, the control performance of the micro-grid is guaranteed, and the stability of the system is improved.

The invention relates to the technical field of motor control, in particular to a permanent magnet motor model predictive current control method based on a current source type inverter. Comprising the following steps: collecting the operation state quantity of a motor system, and carrying out Park conversion to obtain an operation measured value; according to the operation measured value, an alternating current side parallel filter capacitor branch model and a permanent magnet synchronous motor mathematical model are established, a unified discrete prediction model is constructed, and an inverter output current vector and a capacitor current in the next period are obtained through calculation; constructing a capacitance current steady-state reference component and a capacitance current deviation component; and constructing a cost function, selecting an output current vector with the minimum cost function as an optimal control vector of the current control period, and generating an inverter switch driving signal to drive CSI to operate. According to the method, stator current tracking and alternating current side oscillation suppression are considered at the same time under a unified prediction model framework, and compared with a traditional strategy, the dynamic response speed and the steady-state waveform quality can be better considered.

The invention discloses an intelligent monitoring system for an AIPFIMS plasma furnace. The intelligent monitoring system comprises the following steps: step 1, configuring a corresponding sensor; step 2, data analysis and processing; step 3, remote monitoring and control; 4, intelligent early warning and alarming are carried out; and 5, automatically adjusting and optimizing. In addition, trend analysis and prediction can be carried out according to historical data and real-time data through the data processing module, and the performance change and possible faults of the plasma furnace can be predicted in advance.

The application belongs to the technical field of robot control, and particularly relates to a multi-robot arm preset performance event trigger predefinition time control method. In the preset performance control framework, the application fuses a predefinition time stability theory, designs a fixed time performance function, and eliminates strict constraints of initial errors of traditional preset performance control. A predefinition time command filter is used to replace analytical derivation of a virtual control signal in a traditional backstepping method, so as to avoid a 'complexity explosion' problem and ensure that filter errors converge within an accurately set time. A dynamic event trigger mechanism is introduced, a trigger threshold is adaptively adjusted, the update frequency of a controller and the consumption of communication resources are significantly reduced while the control performance is ensured, and RBF neural networks are used to perform online estimation on unknown functions of the system, so that effective control is realized on a non-strict feedback system in combination with an error compensation mechanism.

The application discloses a multi-four-rotor safety formation control method and system based on event triggering and anti-self-locking, and the multi-four-rotor safety formation control method comprises the following steps: establishing an underactuated four-rotor unmanned aerial vehicle dynamics model under external uncertainty, establishing a multi-four-rotor unmanned aerial vehicle formation, constructing an expected formation trajectory model, and designing multi-four-rotor unmanned aerial vehicle collision avoidance constraints; designing an outer loop formation controller based on event triggering; generating expected angular velocity and angular acceleration of the four-rotor unmanned aerial vehicle by using a designed differential flatness method; and designing a Lie algebra attitude controller for realizing global attitude stabilization and compensating for attitude uncertainty in a limited time. The application adopts a control barrier function to realize safety constraints, including collision avoidance and direct collision avoidance of robots, so as to avoid self-locking of an output of the control barrier function due to falling into a local optimum, and further avoid failure of the safety formation. The application proposes an event-triggered control barrier function to solve the self-locking problem.

The invention relates to a facility for manufacturing a wind turbine rotor blade and a gas exhaust system. The facility (200) for manufacturing a wind turbine rotor blade (110) comprises a plurality of stationary molds (202) for manufacturing parts of the wind turbine rotor blade (110), a gas exhaust system (203) comprising a plurality of gas exhaust terminals (204), each gas exhaust terminal (204) being fixedly arranged relative to the molds (202), and a vacuum pump (208) generating exhaust gases during operation, wherein the vacuum pump (208) is movable relative to the molds (202) and the plurality of gas exhaust terminals (204) such that the vacuum pump (208) can be selectively connected to one of the plurality of gas exhaust terminals (204) for exhausting the exhaust gases of the vacuum pump (208) to the outside (210) of the facility (200).

The invention provides a construction method of credible data service for hydroelectric power generation industry, which comprises the following steps of: constructing a credible data space, establishing a data model by collecting metadata of a multi-service system, and carrying out classification and differential encryption; a controllable data service is generated, a single-table and multi-table association interface is automatically generated based on a data model or an interface is generated through a custom SQL, and a row-column level permission is configured to control a data range; dynamic service authorization: generating a dynamic key based on role configuration calling times and a validity period, and encrypting access parameters; and service monitoring and tracing: monitoring service node resources and calling behaviors, and recording a calling message for tracing. According to the invention, through the establishment of the trusted data space, the generation of the controllable data service, the dynamic service authorization and the service monitoring traceability, the whole process of integration, governance and service sharing of the hydroelectric data is safe and controllable, and the problems of data islands, weak safety and framework rigidity are effectively solved.

The invention discloses a fault-tolerant attitude tracking control method and device, a medium and a product, and relates to the technical field of automatic control, and the method mainly comprises the steps: determining a continuous control signal outputted by an attitude tracking controller according to an aircraft attitude angle, an aircraft attitude angular rate, an aircraft expected attitude angle, an RBF neural network and a disturbance observer at a current moment; inputting the continuous control signal into an event triggering strategy to judge whether a triggering condition is met or not, determining the actual control input of the actuator at the next moment as the actual control input of the current moment when the triggering condition is not met, and processing the continuous control signal when the triggering condition is met, according to the method, discrete control signals of the next stage are obtained and input to the actuator, actual control input of the actuator at the next moment is obtained, the problem that system communication resources and computing resources are wasted due to the fact that the signals output by the attitude tracking controller are continuously transmitted to the actuator is solved, and the system communication resources are saved.

The invention discloses a predictive current control method, device and equipment for a permanent magnet hub motor and a medium, and relates to the technical field of vehicle control, and the method comprises the steps: obtaining prior input voltage data and prior output current data of a preset length, and converting the prior input voltage data and the prior output current data into a Hankel matrix form, and taking the prior input voltage data and the prior output current data as prior data; jointly representing the trajectory to be predicted, the decision vector, the initial trajectory and the prior data as a data prediction model of a complete input and output trajectory; constructing a cost function and a data prediction model, converting the cost function and the data prediction model into a quadratic programming function configuration, and solving the quadratic programming function to obtain a reference voltage vector; and carrying out cost function evaluation on the candidate voltage vector so as to obtain an optimal voltage vector through screening to act on the motor. According to the method, the problem of uncertainty of parameters can be effectively solved, the robustness of a motor system is improved, and meanwhile, the number of to-be-evaluated voltage vectors can be effectively reduced, so that optimization of calculation efficiency is realized.

The invention discloses a dq-axis saturation inductance detection method for a synchronous reluctance motor. The method comprises the following steps of: firstly, pre-positioning a magnetic pole position of a rotor; injecting a direct-current voltage in the d-axis direction, and detecting d-axis inductance values under different d-axis currents according to a d-axis current response curve; dC voltage in the q-axis direction is injected, and q-axis inductance values under different q-axis currents are detected according to the q-axis current response curve. According to the invention, the current change rates of a current rising stage under given voltage and a current falling stage under zero voltage are respectively detected, and the dq-axis inductance value of the current rising stage and the dq-axis inductance value of the current falling stage are calculated according to the current change; and the dq inductance value under the current is obtained by averaging the inductance value at the rising stage and the dq inductance value at the falling stage under the same current. The method does not depend on a motor characteristic parameter table provided by a motor manufacturer, improves the versatility of the frequency converter, and enables the frequency converter to drive the synchronous reluctance motor to achieve the optimal performance.

This application discloses an automated vehicle window ventilation and temperature regulation method and system based on fuzzy control, belonging to the field of automated vehicle window control technology. The method includes: real-time acquisition of in-vehicle and out-of-vehicle environmental data, preprocessing to obtain preprocessed in-vehicle and out-of-vehicle environmental data; inputting the preprocessed in-vehicle and out-of-vehicle environmental data into a fuzzy control system to construct a fuzzy rule base for the fuzzy control system; optimizing the fuzzy control system based on the Zebra optimization algorithm and the preprocessed in-vehicle and out-of-vehicle environmental data to obtain an optimized fuzzy control system; and dynamically adjusting the opening and closing degree of the vehicle window through a window motor actuator using the optimized fuzzy control system based on subsequently obtained in-vehicle and out-of-vehicle environmental data. This application, based on in-vehicle and out-of-vehicle environmental data and combined with a fuzzy control system for optimized control, overcomes the shortcomings of existing technologies in complex environment adaptability, multi-objective optimization capability, and global convergence performance, achieving efficient and precise vehicle window ventilation and temperature regulation.

The formula machine reactor comprises a reaction tank, feeding pipes are arranged at the three ends of the outer side of the reaction tank in a penetrating mode, a connecting shell is arranged at the tops of the feeding pipes in a penetrating mode, a feeding opening is formed in the top of the connecting shell in a penetrating mode, and a fixing frame is fixedly connected to the interior of the connecting shell. According to the present invention, the connecting shells, the feeding pipe and the feeding opening are mounted at the three ends of the top of the reaction tank, such that the batch feeding of a variety of materials can be achieved, and the weighing box, the weighing sensor and the fixing frame are mounted in each connecting shell so as to weigh the materials; therefore, a worker can control the dosage of each formula in the activating agent mixing process, and the reaction effect of the whole device is improved.

The invention discloses an event-based unmanned aerial vehicle formation intermittent control method, system and device, and a medium, and relates to the technical field of unmanned aerial vehicle control. The method comprises the following steps: constructing a kinetic model of the unmanned aerial vehicle formation; constructing a state space model of the unmanned aerial vehicle formation under the spoofing attack based on a graph theory; and constructing an intermittent control strategy based on the observer. The dynamic model and the state space model of the unmanned aerial vehicle formation are finely constructed by using a mathematical tool of a graph theory, an efficient and economical intermittent control strategy based on the observer is designed on this basis, and the unmanned aerial vehicle formation can be accurately controlled by accurately defining an expected relative position and a tracking error and carefully designing the spoofing attack observer. According to the method, external interference can be detected and compensated in real time, so that the calculation amount and energy consumption are greatly reduced while the control performance is maintained, and in addition, the energy efficiency of the unmanned aerial vehicle formation is further optimized by intelligently adjusting and controlling the input frequency through the constructed intermittent control strategy.

The application discloses a kind of rocket artillery electromechanical servo system fault-tolerant control methods based on neural network observer, and method steps are as follows: first, the mathematical model of rocket artillery electromechanical servo system is established, second, speed signal fast fourier transform (FFT) is used as HBF neural network input after, HBF neural network state observer and the adaptive robust controller based on HBF neural network state observer are designed;Finally, the stability of HBF neural network state observer and the adaptive robust active fault-tolerant control system based on HBF neural network state observer is proved using Lyapunov stability theory.The application solves the problem of additive fault detection and active fault-tolerant control of rocket artillery electromechanical servo system under various working conditions.