111 results about "Fuzzy adaptive control" patented technology

The invention relates to the technical field of temperature control, in particular to a mass concrete water cooling water temperature control method and system. The method comprises the following steps: collecting concrete key parameters through a multi-source sensor, constructing a microenvironment model based on information geometry, and generating a thermosensitive characteristic spectrum; forming a distributed thermodynamic model by utilizing a mutual information routing algorithm and heat-fluid-solid coupling analysis, and calculating an optimal cooling strategy; water flow path and flow optimization is realized in combination with fractional order particle swarm optimization; a pump set and a valve are adjusted through fuzzy self-adaptive control; and a potential instability region is identified through the spectrum energy gradient, and risk early warning is triggered. The precision and reliability of mass concrete cooling temperature control are remarkably improved, and intelligent, efficient and safe temperature control adjustment in the whole process is achieved.

The invention belongs to the technical field of signal processing, and particularly relates to a lower limb motion intention recognition method and system based on electromyographic signals. The method comprises the following steps: S1, arranging electromyographic sensors on a hip key muscle group, a knee joint key muscle group and an ankle joint key muscle group in sequence, and collecting electromyographic signals; s2, performing time-frequency-space domain feature fusion and dimension reduction processing on the electromyographic signals acquired at the hip key muscle group and the knee joint key muscle group, and performing corresponding motion intention prediction by using a dynamic weight distribution method and a decoder based on an LSTM-attention mechanism; electromyographic signals collected at key muscle groups of ankle joints are processed through a muscle force distribution matrix, and meanwhile a time-varying weight adjustment strategy and impedance control are adopted for corresponding motion intention prediction; s3, according to the predicted motion intention, the system controls a direct-current brushless motor on rehabilitation training equipment, a fuzzy self-adaptive PID control method is adopted to regulate and control joint motion, and a walking posture is simulated.

The invention discloses an energy router inversion grid-connected port control method for optimizing a VSG, and the LADRC can dynamically compensate the influence of external disturbance on a system through the real-time observation of the state of the system, especially the monitoring of the disturbance and the change of the system, thereby enhancing the anti-interference capability of the system. When the load is suddenly changed or is externally disturbed, the LADRC can quickly identify the disturbance and generate an adaptive control signal, so that the inverter system is quickly recovered to a stable state. And the fuzzy adaptive PI controller adaptively adjusts the proportionality coefficient and the integral coefficient of the PI controller according to the real-time deviation and the change rate of the system, so that the parameters of the controller can be automatically adjusted according to the state of the system, and the limitation of a fixed parameter controller under complex working conditions is avoided. The self-adaptive adjustment not only improves the control precision, but also greatly improves the dynamic response speed of the system, so that the inverter can maintain an efficient and stable working state under the conditions of power grid disturbance, load change and the like.

The invention discloses a focusing control method and related equipment, and the method comprises the steps: synchronously collecting the data of a multi-modal sensor, extracting features and parameters, inputting a multi-modal fusion model subjected to joint optimization to generate a motor control instruction, and achieving the focusing through the hierarchical control of rough adjustment, fine adjustment and dynamic tracking. The dynamic weight fusion network deploys the weight of each modal data according to the environmental sensitivity coefficient, and combines the historical memory and trajectory pre-judgment of the alignment trajectory prediction network to reduce invalid calculation and repeated search and greatly improve the focusing speed; the multi-mode sensor works cooperatively to replace a special hardware function, so that the cost and the power consumption are reduced; the dynamic weight fusion network can adjust the modal confidence according to the environment and enhance the anti-interference capability in the complex light environment; the alignment trajectory prediction network and the fuzzy self-adaptive PID controller are in hierarchical cooperation, the problem of erroneous judgment of a complex scene is solved, and the micro-distance and dynamic tracking precision is improved; the model is subjected to pruning, distillation and quantitative optimization, light weight is achieved, and low-cost equipment is adapted.

The embodiment of the invention provides a hydrochloric acid PH control device in a germanium oxide production process and a control method thereof, and belongs to the field of chemical process automatic control. The device comprises an acid liquor storage tank used for storing raw liquor hydrochloric acid and connected to an acid mixing tank through a raw acid feeding control valve; the acid mixing tank is used for mixing an acid solution with a diluent and is connected to the pH regulation reaction tank through a mixed acid feeding control valve; the alkali liquor storage tank is connected to the pH regulation reaction tank through an alkali liquor adding control valve; the pH regulation reaction tank is used for receiving the mixed acid liquor and the alkali liquor and regulating the pH value of a reaction system, and is provided with a pH sensor for detecting the pH value in real time; and the control unit is used for dynamically adjusting the opening degree of each valve by adopting an improved fuzzy self-adaptive PID control algorithm according to a detection result of the pH sensor so as to control the pH value to be within a target range. According to the scheme, the problems of overshoot and lag caused by traditional fixed parameter PID adjustment are solved, and therefore the stability of the pH value of the solution and the consistency of the technology in the germanium oxide production process are guaranteed.

The invention discloses a mechanical arm control method and system based on fuzzy self-adaptive PID control, relates to the technical field of mechanical arm control, and solves the problem that mechanical arm control is insufficient in flexibility when facing different working conditions. According to the embodiment of the invention, the universe expansion and contraction factor is adjusted through the error, then the close linkage of the quantization factor and universe expansion and contraction is realized through the self-adaptive quantization factor calculation, the fuzzy reasoning technology is combined, the intelligent mapping from the error information to the PID parameter increment is realized, the real-time updating of the PID parameter and the control output calculation are realized, and the real-time updating of the PID parameter is realized. The flexibility and adaptability of the control system are improved; and then output is controlled through incremental PID, so that a complete control link from parameter increment to actuator driving is realized, a complete closed loop is formed by a cascade control architecture, functional modules are tightly coupled, parameters are coordinated, and the whole-process intelligence from error sensing to execution control is realized.

The invention provides a heat collecting coil temperature adjusting device and a control method thereof, and relates to the field of temperature adjusting equipment, and the heat collecting coil temperature adjusting device comprises a temperature sensor, a controller, a heating module and a cooling module. The temperature sensor is installed at a key temperature measuring point of the heat collecting coil, the measuring precision is + / -0.1 DEG C, and data are collected according to the characteristics of a thermistor and wirelessly transmitted to the controller. The controller receives the data, calculates deviation and change rate according to a preset target, and obtains a control quantity by using a fuzzy adaptive control algorithm; the heating module adjusts current according to control quantity to change power temperature rise, and the cooling module adjusts rotating speed of a water pump to control flow speed temperature reduction. The control method comprises the steps of target presetting, data acquisition and transmission, deviation and fuzzy control quantity calculation, temperature adjustment, parameter adjustment and the like, fuzzy control rule parameters are optimized through a genetic algorithm, and the problems that an existing device is insufficient in precision, complex in structure, inflexible in control strategy and the like are solved.

The invention discloses a UPA pressure automatic compensation system and method for mask substrate polishing. The UPA pressure automatic compensation system comprises a pressure execution module, a distributed sensing feedback network and an intelligent control unit. Wherein the pressure execution module is used for directly polishing a mask base plate and comprises a force application shaft, a polishing head, an air source, a UPA air bag and an electric proportional valve, the distributed sensing feedback network comprises an air path pressure sensor and a tail end contact pressure sensor, and the intelligent control unit receives a collection signal of the distributed sensing feedback network and sends the collection signal to the polishing head. On the basis of a current process formula and process parameter coupling model, a data fusion algorithm, a feed-forward compensation algorithm and a fuzzy PID algorithm are operated to obtain a feed-forward compensation amount and a fuzzy PID output amount, the feed-forward compensation amount and the fuzzy PID output amount are superposed, a total control voltage is generated and output to an electric proportional valve, and then the input air pressure of a UPA air bag is adjusted. Therefore, closed-loop control over the polishing pressure of the mask substrate is achieved. Through multi-sensor data fusion, fuzzy PID self-adaptive control and intelligent feed-forward compensation based on a process parameter coupling model, real-time, accurate and constant control of the polishing pressure is realized, so that the surface precision and yield of the mask substrate are improved.

The invention provides a compensation balance system and method of an electrodynamic transducer, and aims to solve the following problems in the prior art: a traditional electrodynamic sound source transducer needs to realize large-volume displacement in a low-frequency application scene, but the flexibility of an elastic suspension support of the traditional electrodynamic sound source transducer is insufficient to bear hydrostatic pressure; meanwhile, traditional passive and active compensation modes have challenges in the aspects of delay and stability. In order to solve the problems, the compensation balance system and method of the electrodynamic transducer mainly comprise an underwater acoustic transducer, a low-pressure middle cabin and a high-pressure gas cylinder, and a system self-checking function, a transducer piston position balance control function and a transducer fuzzy self-adaptive control function are integrated. The defects in the prior art are effectively overcome, and balance between the inner cavity of the transducer and the external hydrostatic pressure can be rapidly achieved. In addition, the control process is further simplified by determining the target control quantity, and the overall performance of the system is improved.

The invention discloses a storage tank pressurization control method and system based on LNG gas station fuzzy self-adaptive PID control, and aims to solve the technical problems that a traditional pressurization control method of an LNG storage tank is low in control precision, poor in stability and rapid in equipment abrasion. According to the control method, dynamic compensation for the target pressure is introduced, so that the system can aim at a more accurate control target in the initial stage, the steady-state control deviation is reduced, and the control precision is improved. And static pressure head change disturbance caused by liquid level change is overcome through dynamic compensation, the adjusting burden of the controller is reduced, the controller can focus on processing other dynamic disturbance, and therefore the control process is more stable, and overshoot is smaller. Through the design of a dynamic compensation mechanism and a special fuzzy rule base, the system can automatically adapt to various complex working conditions, and fast, stable and overshoot-free pressure control is always kept. Therefore, frequent and large-amplitude action and surge phenomena of the valve are avoided, and the energy consumption of an executing mechanism is reduced.

The embodiment of the invention discloses a fly ash coal oxygen-enriched melting intelligent control method based on multi-mode coupling prediction, and belongs to the technical field of solid waste recycling and intelligent control crossing. The method comprises the steps that S101, multi-source data collected by a sensor is obtained; step S102, obtaining control parameters through an intelligent control algorithm according to the multi-source data; s103, according to the control parameters, controlling an oxygen-enriched spray gun, a slurry outlet and a material ratio; wherein the step S102 comprises the sub-steps of performing decoupling prediction on the temperature T, the hearth negative pressure P, the flue gas oxygen concentration CO and the molten slurry yield Qp by adopting a multivariable decoupling prediction model; carrying out fuzzy control on the hearth negative pressure P by adopting a fuzzy self-adaptive PID (Proportion Integration Differentiation) controller; and a multi-objective optimization algorithm is adopted to calculate and obtain control parameters. The control method is small in melting temperature fluctuation, high in hearth negative pressure stability, high in quartz sand utilization rate, low in energy consumption per ton of molten slurry and high in heat preservation cotton qualification rate.

The invention discloses a fuzzy self-adaptive PID (Proportion Integration Differentiation) control method for a high-temperature environment of a small closed space. According to the method, a fuzzy logic controller and PID controller cooperative control architecture based on the variable universe theory is constructed, and PID parameters are adjusted on line by utilizing a fuzzy inference rule by collecting the temperature deviation and the change rate of the closed space in real time. The fuzzy rule base design adopts a variable universe theory, a membership function and a universe range are dynamically adjusted according to a system state, and the adjustment direction and amplitude of PID parameters are accurately mapped. A real-time monitoring mechanism based on feedback of a temperature sensor is introduced, high-frequency sampling is carried out on the temperature of the space, and timeliness and accuracy of control signals are ensured. According to the method, by setting a temperature threshold value and an overshoot limiting mechanism, the phenomena of temperature overshoot and oscillation are effectively avoided, and the stability and reliability of the system are improved. According to the invention, the temperature can be quickly and accurately controlled in a high-temperature environment of a complex small closed space, and the temperature fluctuation range is obviously reduced.

The invention belongs to the technical field of new energy hydrogen production, and particularly relates to an operation optimization control method and system for a solid oxide electrolytic hydrogen production system, and the method comprises the steps: building a dual-time scale dynamic model of the electrolytic hydrogen production system, and outputting a thermal-electric coupling dynamic process of the solid oxide electrolytic hydrogen production system; the actual electrolysis efficiency, the accumulated thermal load and the power grid interaction power at each time are extracted, a dynamic trajectory optimization functional is constructed, and optimal control is solved; establishing a power grid auxiliary service three-dimensional decision space for primary optimization, and generating a demand decision; establishing a fuzzy control rule of the fuzzy self-adaptive PID controller to carry out secondary optimization; a dynamic safety constraint mechanism is established, and the heat flow gradient adjustment amount, the gas circulation rate and the temperature are adjusted in time; and defining a system efficiency optimization index to evaluate a system operation optimization effect. According to the method, the thermal-electric coupling dynamic process of the solid oxide electrolytic hydrogen production system can be accurately depicted at multiple time scales, and safe and stable operation of the system is guaranteed.

The invention relates to the technical field of ship stabilization control, and discloses a rudder fin combined stabilization system cooperative control method comprising the following steps: 1, building a ship motion model; step 2, designing a fuzzy adaptive PID controller; 3, constructing a rudder fin interaction model; and 4, introducing a prediction control algorithm, and optimizing a control input sequence based on a model prediction principle. By establishing a ship motion model, designing a fuzzy self-adaptive PID controller, analyzing rudder fin interaction and introducing a predictive control algorithm, the problems that an existing rudder fin combined stabilization system is insufficient in cooperative control, in the ship navigation process, a ship is affected by external factors such as sea waves and sea wind, the ship is prone to swing motion, and the stability of the ship is poor are solved. Therefore, the stabilization effect and the course stability of the ship are improved.

The invention discloses a harmonic suppression and dynamic reactive compensation control method for an energy router, which is suitable for a micro-grid and a distributed energy access system. According to the method, three-phase current and voltage signals of an alternating current port of the energy router are collected, five-time and seven-time main harmonic components are extracted through fast Fourier transform, harmonic compensation current instructions equal in amplitude and opposite in phase are generated and injected into an inverter to be output, and active counteracting of main harmonics is achieved. Meanwhile, the bus voltage deviation and the change rate thereof are detected, a reactive current instruction is adjusted on line by adopting a fuzzy self-adaptive PI controller, rapid and smooth dynamic reactive compensation is realized, and the bus voltage is stabilized. Decoupling control of active / reactive and harmonic components is realized in combination with Park conversion, and virtual impedance is introduced to enhance system damping and harmonic suppression capabilities. Compared with the prior art, harmonic suppression and voltage support can be simultaneously realized under a single control framework, the response speed is high, the stability is high, and the method is suitable for high-performance grid-connected operation of the multi-port energy router.

The invention discloses a solid powder intelligent weighing system based on fuzzy adaptive PID. The system comprises a material transfer module, a weighing unit, a material information identification module and an intelligent control unit. The material transfer module realizes automatic transfer and positioning of the weighing container; the weighing unit comprises a weighing container, a high-precision sensor and a discharging module, and the discharging module is provided with a material bin and a feeding valve mechanism; the information identification module is used for automatically identifying and inputting material information; the intelligent control unit is internally provided with a fuzzy self-adaptive PID controller, receives weight and material information, identifies valve-flow model parameters on line based on a recursive least square method and performs self-tuning, dynamically adjusts PID parameters according to a fuzzy rule, and outputs an instruction to realize three-stage control of rapid blanking, fuzzy fine adding and inching compensation. Through a parameter self-tuning and segmentation strategy, the method is adaptive to various material characteristics, the efficiency is improved and the static error is eliminated under the condition of ensuring high precision, and safe and traceable intelligent weighing is realized by relying on full-process automation and information tracing.

The invention provides an airway atomization flow intelligent drug delivery control method and system, and relates to the technical field of medical instruments.The method comprises the steps that basic information of the age, the weight and the illness state severity of a patient is obtained, and physiological parameters of the respiratory rate and the tidal volume of the patient are collected in real time through a sensor; inputting the basic information and the physiological parameters into a fuzzy adaptive control algorithm, and initializing an individual administration rule base according to the basic information; based on the real-time change trend of the respiratory rate and the tidal volume, three initial control index values including an atomization flow value, a drug concentration value and a time interval are dynamically generated through a membership function. According to the invention, through the full-process design of data acquisition, intelligent modeling, accurate execution and data closed loop, intelligentization of atomization treatment is realized.

The invention relates to the technical field of intelligent control in the converter steelmaking process, and particularly discloses a converter steelmaking furnace mouth pressure intelligent balancing method with self-adaptive image segmentation, which comprises the following steps: image acquisition: acquiring a furnace mouth flame image in real time through an industrial camera; image preprocessing: adopting a dynamic gamma correction algorithm to adaptively adjust a correction coefficient according to an R channel mean value of the image; in the flame feature extraction stage, the corrected image is subjected to bilateral filtering to remove noise, and then an improved OTSU segmentation algorithm is input to extract a flame main reaction area; in the pressure intelligent control stage, a flame characteristic-furnace pressure nonlinear model is constructed, and finally the rotating speed of an ID fan is dynamically adjusted through a fuzzy self-adaptive controller; the furnace mouth flame image is intelligently monitored, then the furnace mouth pressure is analyzed, the system pressure fluctuation standard deviation is controlled to be reduced, the gas recovery rate is improved, the false detection rate is reduced, the energy efficiency of converter steelmaking is improved, and the production safety is improved.

The invention belongs to the technical field of robot control, and discloses a fuzzy adaptive control method and system for uncertain robot system constraints. A dead zone model is integrated into an uncertain robot kinetic equation, a robot system module is established, feedback joint displacement state information is output in real time through the robot system module, and unmeasurable speed and acceleration state information is processed through a filter module, a virtual controller module and a self-adaptive law module. And a virtual control signal and a fuzzy adaptive law parameter are obtained, and dynamic change information is obtained through a fuzzy logic system in a fuzzy adaptive controller module. According to the method, parameter uncertainty caused by unknown robot system parameters or uncertainty and dead zone characteristics caused by non-controlled object factors such as external disturbance are solved, and accurate tracking control of the system state under boundary constraint is realized.

The invention provides a permanent magnet direct drive fan bus voltage oscillation suppression method after power grid fault recovery, and belongs to the technical field of permanent magnet direct drive fans. The technical problem of DC bus voltage oscillation after symmetric fault recovery is solved. According to the technical scheme, the method comprises the following steps that S1, the power difference value P between a computer side and a network side during a fault period and the maximum unbalanced power Pmax absorbed by the rotational inertia of a fan rotor are included, if P is smaller than or equal to Pmax, the step S2 is executed, and if P is larger than Pmax, the step S3 is executed; s2, controlling a direct-current bus voltage outer ring by a grid-side converter, and turning to S5; s3, a DC bus voltage outer ring is controlled by a fuzzy PI adaptive controller; and S4, carrying out fuzzy processing. According to the invention, adaptive adjustment of DC bus voltage outer loop PI parameters is realized, the dynamic response capability is enhanced, voltage oscillation is effectively suppressed, and the stability is improved.

The invention provides an unmanned aerial vehicle flight control method and device based on multi-sensor data fusion, and the method comprises the following steps: carrying out the denoising and clustering weight fusion processing of flight control initial data collected by multiple sensors, and generating fusion data; performing real-time state estimation on the fused data by adopting an extended state observer to obtain real-time flight state parameters; performing deviation compensation based on a deviation value between a preset target state and a real-time flight state parameter, optimizing a fuzzy adaptive PID control algorithm of parameters through a genetic algorithm, and dynamically adjusting the parameters of a control machine in a global optimization mode; and outputting the optimal control quantity to realize accurate flight control of the unmanned aerial vehicle. According to the method, the data confidence is improved through a clustering weighting mechanism, parameter global optimization is carried out in combination with disturbance observation of an extended state observer and a fuzzy adaptive PID control algorithm, and the problem that the flight control precision is insufficient due to the fact that a current unmanned aerial vehicle cannot realize control parameter global optimization is effectively solved.

The invention relates to the technical field of intelligent power grids, and provides a wind turbine generator comprehensive inertia frequency control method based on fuzzy adaptive parameters. In the method, an adaptive parameter method based on frequency and rotating speed is adopted in a frequency support stage of a wind turbine generator, and a comprehensive inertia frequency control parameter is dynamically corrected according to the proportion of residual adjustable kinetic energy of a fan to adjustable total kinetic energy and a first system frequency deviation and according to a first fuzzy adaptive control law; the maximum deviation of the frequency is reduced and the secondary drop of the frequency is relieved; in the rotating speed recovery stage, according to the proportion of the residual adjustable kinetic energy of the fan to the total adjustable kinetic energy and the frequency deviation of the second system, the frequency secondary drop and the rotating speed recovery duration are comprehensively considered, and the output power reference value of the wind turbine generator is dynamically corrected through fuzzy self-adaptive control; the output power reference value dynamically changes along with the steady-state frequency change after the fan frequency is close to the system disturbance, the frequency secondary drop is relieved, the rotating speed recovery time is prevented from being too long, and the system operation stability is improved.

The invention relates to the technical field of illumination control, in particular to a shop illumination control system with an automatic adjustment function and a control method thereof, and the method comprises the following steps: 1, data collection: collecting the illumination value E of the environment inside and outside a shop in real time through an ambient light sensor, obtaining customer flow distribution and pupil diameter D through a camera or an infrared sensor; the main control chip calculates the environment illumination deviation e and the deviation change rate delta e according to the environment illumination value and a preset scene illumination threshold value, and through fusion of environment light, the visitor flow rate and customer pupil diameter data, a PSO optimized fuzzy self-adaptive PID control and dynamic mode switching mechanism is adopted, so that the environment illumination deviation e and the deviation change rate delta e are calculated; dual optimization of shop illumination energy saving and display effect is realized, and the total energy consumption is reduced by 19% while the commodity exposure is ensured; color temperature and illumination are adjusted in real time in combination with pupil biological characteristic feedback, so that the visual fatigue index of customers is reduced by 28%, and the staying time is prolonged by 15 minutes.

The invention provides a fuzzy adaptive control method and system for a steer-by-wire system, and relates to the technical field of automobile steering control, and the method comprises the steps: obtaining a motor current initial value, a rack force estimation value and a system initial road feeling state of the steer-by-wire system, and constructing a steering torque prediction model; predicting future torque output of the steer-by-wire system by using the steering torque prediction model based on the fuzzy adaptive control algorithm to obtain a predicted torque value and a fuzzy control parameter set; on the basis of a self-adaptive road feeling planning control model, the influence of motor current hysteresis and mechanical transmission efficiency is compensated, and an optimized motor current predicted value and a steering execution torque value are obtained; on the basis of the optimized motor current prediction value and the steering execution torque value, a fuzzy self-adaptive road feeling planning control signal is output and obtained; and the output of the steer-by-wire torque is updated in real time by using the fuzzy self-adaptive road feeling planning control signal feedback, so that the real-time control of the road feeling of the vehicle is realized.

The invention relates to the technical field of industrial automation and intelligent control, in particular to a centrifuge operation data real-time visualization monitoring system which comprises a distributed data acquisition unit, a data analysis and processing unit, a real-time monitoring and visualization unit, a decentralized control system unit and a remote access and support unit. According to the method, on-line incremental learning and hybrid modeling are fused with a physical mechanism and data-driven analysis, so that dynamic prediction, anomaly recognition and causal reasoning of the running state of the centrifugal machine are realized, and lightweight deployment of the edge side is supported; based on the multi-physics coupling real-time simulation and augmented reality technology, multi-phase flow state high-precision dynamic visualization and operation risk intelligent space early warning in the centrifugal process are achieved, and multi-parameter dynamic optimization regulation and control in the centrifugal process are achieved by means of a fuzzy self-adaptive control strategy and a distributed intelligent cooperation mechanism; and the intelligent analysis, real-time monitoring and accurate control capability and the complex working condition adaptability of the system to the operation of the centrifugal machine are obviously improved.

The invention discloses an active vibration absorber control strategy for vibration at the tail end of a flexible arm, and relates to the technical field of mechanical arm control, and the active vibration absorber control strategy comprises the following steps: building a three-dimensional model for a two-degree-of-freedom flexible mechanical arm, describing the joint flexibility of a system by using a linear spring, and representing the rigidity coefficient of a flexible joint by using the elastic coefficient of the linear spring; fuzzy RBF adaptive PID control is trained in combination with a real object, the identification precision of the model is improved, and vibration suppression is realized; in the fuzzy control, input variables are fuzzified by simulating the thinking mode of human beings, reasoning is carried out in combination with expert experience rules, and finally a system of an accurate dynamic model is established. According to the control strategy, the limitation of a traditional control technology based on a model during control is reduced, dynamic hysteresis nonlinearity generated in actual work is effectively corrected, the control precision is improved, fuzzy rule parameters are adjusted through modal analysis in combination with system characteristics, and the control precision is improved. Therefore, the vibration suppression force synthesis in different scenes is more accurate, and the vibration suppression effect is better.

The invention relates to the related technical field of lead conduction current control, in particular to an overhead line connection device control method and system, an intelligent terminal and a storage medium, and the method comprises the steps: obtaining the dynamic contact parameters of an overhead line connection point, triggering a contact pressure correction instruction through a fuzzy self-adaptive PID control unit, and adjusting the parameters of a clamping mechanism; meanwhile, environment interference data are collected, a compensation coefficient is generated in combination with the operation parameters, and the coordination action parameters are continuously adjusted until the contact stability verification is passed. The technical problem that the contact stability of the overhead line connection point is affected by uneven contact pressure distribution of the overhead line connection point due to interference of environmental interference factors is solved, a contact pressure correction instruction is adjusted in real time through the fuzzy self-adaptive PID control unit, and the contact stability of the overhead line connection point is improved in combination with a contact pressure compensation coefficient. And cooperative action parameters of the buffer mechanism and the clamping mechanism of the guiding and connecting device are continuously adjusted, so that the technical effect of effectively improving the contact stability of the overhead line connecting point is achieved.

The invention provides a dynamic balance device for branch resistance of a ship cooling water system, which solves the problems of non-uniform flow distribution and the like caused by unbalanced resistance distribution of a traditional cooling water system and comprises a flow sensor, a temperature sensor, a variable-aperture throttling orifice plate and a controller. And the controller adopts a fuzzy self-adaptive PID control strategy based on the feedback of the flow and the temperature, generates a pulse signal by calculating the deviation between the real-time flow and the reference flow, accurately controls the rotation angle of the stepping motor, and dynamically adjusts the opening degree of the branch. The controller integrates a self-adaptive control strategy, dynamically adjusts fuzzy self-adaptive PID parameters according to errors, limits the flow deviation range, prevents system instability, and ensures flow distribution balance in combination with the mass balance principle. Closed-loop control is achieved through the high-precision flow sensor and the high-precision temperature sensor in combination with the variable-aperture throttling orifice plate, the fuzzy self-adaptive PID algorithm is adopted for dynamically optimizing the adjusting response, the distribution error of branch flow is reduced, and the cooling efficiency and the system reliability are improved.

The present application belongs to the technical field of seawater desalination equipment control, and relates to a hydraulic fan driven high-pressure water pump speed control method based on fuzzy adaptive PID, which comprises: S1, obtaining the high-pressure water pump speed error of the hydraulic fan, and determining the input variable of the fuzzy adaptive PID controller; S2, analyzing the stability of the hydraulic fan, establishing a high-pressure water pump variable motor swing angle control model, and determining the output variable of the fuzzy adaptive PID controller; S3, determining the fuzzy control set of the fuzzy adaptive PID controller of the hydraulic fan; S4, using the Mamdani method to perform fuzzy reasoning on the fuzzy reasoning table, and calculating the fuzzy control subset by the barycenter method; and S5, controlling the swing angle adjusting variable motor displacement of the high-pressure water pump variable motor according to the output value of the fuzzy control subset. The present application is based on the hydraulic fan driven high-pressure water pump passing through the reverse osmosis membrane to produce fresh water, and uses fuzzy control and PID control theory to improve the rapidity, accuracy and stability of the water pump speed control.

The invention relates to the technical field of terminal sterilization and filtration in a radiopharmaceutical preparation process, in particular to a filter membrane sterilization and filtration device and system. Comprising the steps that a state sensing module collects liquid medicine radioactive activity data and filter membrane structure strain data and generates real-time data flow; the twinborn modeling module constructs a filter membrane digital twinborn body, and outputs an accumulated radiation damage prediction result through data assimilation; the prediction decision module generates a filtering parameter optimization sequence by using a deep reinforcement learning agent; the control execution module adjusts the flow velocity of the liquid medicine through fuzzy self-adaptive PID control and feed-forward compensation; and the verification feedback module performs an integrity test and transmits data back to the twin modeling module to realize model parameter correction. All the modules form a closed-loop control system through a high-speed data bus, so that the damage of radiation to a filter membrane material is effectively inhibited, and the integrity and the sterile guarantee level of a membrane structure in the filtering process are maintained.