208 results about "Time constant" patented technology

The invention discloses a cross-system fault diagnosis method and system combined with multi-dimensional anomaly detection, and relates to the technical field of fault diagnos.The method comprises the steps that a graph neural network with a liquid time constant network unit as a node is constructed through a dynamic topology dependency relationship and a multi-dimensional key performance index flow; each unit describes state evolution through a coupled ordinary differential equation system, and a liquid state time constant can be adaptively adjusted. A time back propagation algorithm is adopted to train a model to learn a normal behavior track contour reference, and anomaly is detected through a dynamic time warping distance. And determining a fault propagation path and a root cause through anti-fact intervention and forward integral solution. And generating an optimal diagnosis action sequence in a liquid graph neural network simulation environment, and calculating a reward value based on execution efficiency, accuracy and a repair effect to carry out strategy optimization. The abnormal detection accuracy and the root cause positioning precision are improved, the fault repair time is shortened, the operation and maintenance cost is reduced, and an intelligent fault diagnosis solution is provided for a complex information technology system.

The invention relates to the technical field of industrial process automation control, and discloses an intelligent adjusting method for an industrial waste liquid low-temperature evaporation process, which comprises the following steps of: superposing pressure step test excitation to a vacuum adjusting valve, synchronously acquiring temperature response data flow, calculating absolute error integral and SIAE and reply time characteristics of a response curve, and calculating the temperature response data flow according to the absolute error integral and SIAE and reply time characteristics of the response curve; substituting into an inverse model to solve an equivalent process gain and a time constant of the controlled object; based on the internal model control principle, PID controller parameters are dynamically calculated and updated through the calculated gain and the time constant, a control law is reconstructed to generate an execution instruction, and the problem of control divergence of a non-linear time-varying object under model mismatch is solved through active energy feature identification and a pole assignment mechanism; decoupling control and self-adaptive adjustment of fluid viscosity sudden change and equipment scaling are achieved, and the stability and control precision of the system are improved.

The invention discloses a server energy-saving system and method based on a lag compensation type dynamic thermal impedance model, and relates to the field of server energy saving.By collecting operation data of a server hardware bottom layer in real time, a multi-dimensional thermal-computing force coupling time sequence atlas is constructed, and based on the multi-dimensional thermal-computing force coupling time sequence atlas, a dynamic thermal impedance model is established. Calculating a heat conduction time constant of hardware in a current environment; establishing a lag compensation type dynamic thermal impedance model based on the heat conduction time constant; constructing a thermodynamic phase space according to operation data; analyzing a noise reduction evolution trajectory in combination with the lag compensation type dynamic thermal impedance model; the method comprises the steps of generating a weighted thermal resonance state vector, activating an adaptive gain MPC predictive damping scheduling strategy based on the weighted thermal resonance state vector, constructing and solving a dynamic weighted multi-objective optimization function, generating an optimal damping scheduling instruction, and thoroughly solving the fan asthma phenomenon that the fan PWM duty ratio fluctuates substantially in a sine mode under the constant computing power load.

The invention relates to the technical field of power system stability control, in particular to a new energy station transient voltage and frequency coordination stability control method, which comprises the following steps of: analyzing a transient energy evolution rule of an equivalent synchronous motor and stored energy by constructing an alternating current and direct current hybrid dynamic model and fusing with multi-time scale characteristics; based on dynamic weight matrix optimization and a multi-target coordination control strategy, self-adaptive balance of power distribution is realized; a nonlinear feedback algorithm and a real-time compensation mechanism are designed in combination with the Lyapunov theory, and voltage frequency fluctuation in a disturbance scene is suppressed; establishing a multivariable cooperative control architecture, and dynamically adjusting a power adjustment priority and an inertia time constant through coupling iterative optimization of a source storage cooperative strategy to realize adaptive compensation of a transient energy propagation path; according to the method, the dynamic stability and the anti-interference capability of the new energy station under transient impact are remarkably improved, and safe operation of a high-proportion new energy power grid is guaranteed.

The invention relates to a rigid spacecraft attitude control method and system based on finite time constraint, and belongs to the technical field of spacecraft attitude control. Comprising the following steps: respectively constructing a spacecraft attitude control system model and a finite time convergence performance function containing a preset time constant; according to the finite time convergence performance function, dynamic attitude constraint is applied to the system state of the spacecraft attitude control system model; converting the attitude constraint into differential homeomorphic mapping of an unconstrained space; obtaining an error conversion variable according to differential homeomorphic mapping; and designing a virtual control law and constructing an error compensation module according to the error conversion variable, and designing an actual control input law according to the virtual control law and the error compensation module. According to the method, rapid convergence of the spacecraft attitude within the preset time is ensured, the dynamic response precision of the spacecraft in the rapid attitude maneuver process is remarkably improved, the control period delay is effectively avoided, and the power consumption is reduced.

The invention discloses a complex medium controllable source electromagnetic multi-parameter three-dimensional inversion method and system, and the method comprises the steps: carrying out the three-dimensional space discretization of an exploration region, and carrying out the multi-time iteration inversion of a discrete exploration region through initializing a multi-parameter geologic model based on a multi-parameter inversion target function, and obtaining a multi-parameter three-dimensional inversion result; wherein the multi-parameter inversion objective function comprises a data fitting constraint, a model constraint and a cross gradient constraint, and the multi-parameter model comprises resistivity, magnetic conductivity, a charging rate, a frequency correlation coefficient and a time constant; and a hexahedral mesh discrete calculation region is adopted in inversion, and a finite element linear equation set is obtained through a vector finite element method, so that multi-parameter three-dimensional forward modeling calculation is realized. According to the method, the induced polarization effect and the magnetic conductivity influence are considered at the same time, multi-parameter three-dimensional inversion is achieved, the application precision and reliability of the controllable source electromagnetic method under the complex geological condition are remarkably improved, and rich geophysical basis is provided.

The invention discloses a multi-modal robot control method and system based on space-time fusion and a liquid neural network. The method comprises the following steps: collecting asynchronous time sequence data of a multi-source heterogeneous sensor, and establishing a unified reference clock and time grid; through a neural phase-locked loop and soft-DTW, learnable synchronization is realized, and an alignment sequence, confidence and a residual error are output; after modal feature coding, fusion features are formed through confidence-gated layered space-time cross attention; a nominal control instruction is generated by the liquid neural network of the self-adaptive time constant; and the command is optimized and corrected in combination with CLF / CBF and QP, and a safe and feasible control command is output. According to the method, uncertainty caused by asynchronization, shielding and the like is effectively inhibited, the path deviation and the collision rate are remarkably reduced, and high precision, high robustness and provable safety are kept in a dynamic unstructured environment.

The invention discloses a first-order linear active disturbance rejection controller parameter setting method based on a phase margin method, and the method comprises the following steps: S1, obtaining simplified first-order inertia delay object parameters through an open-loop step response curve on site, and the simplified first-order inertia delay object parameters comprise the steady-state gain K, the inertia time constant T and the delay time tau of a controlled object; and S2, discussing and setting parameters of the controller according to conditions according to the ratio theta of the delay time tau of the controlled object to the inertia constant T. According to the first-order linear active-disturbance-rejection controller parameter setting method based on the phase angle margin method, the phase angle margin of the first-order linear active-disturbance-rejection controller is subjected to theoretical analysis, and the phase angle margin of the first-order linear active-disturbance-rejection controller and a closed-loop stable system of a controlled object is directly configured; and therefore, the problem of overshoot in parameter setting of the linear active disturbance rejection controller can be solved.

The invention relates to the technical field of industrial automation control and dynamic simulation, and discloses a centralized control console and 3D model linkage virtual-real simulation system, which comprises a control signal sampling interface, a load response modulation unit, a dynamic model evolution unit and a virtual-real closed-loop feedback unit, the load response modulation unit performs energy consumption weight accumulation on all the virtual controlled objects in transient action to generate a global time scaling factor so as to correct an inertia time constant of the system in real time; the dynamic model evolution unit introduces a hard limiting boundary by using an amplitude limiting link and calculates a process variable; the virtual-real closed-loop feedback unit extracts a control deviation signal and drives a physical instrument to generate a nonlinear damping action, and by establishing a global load modulation model based on energy constraint, a discrete control system spontaneously emerges a nonlinear hysteresis characteristic conforming to physical energy conservation under the low calculation power condition without complex fluid network solution.

The invention provides a PI-GAN-based MMT-PMSLM dynamic performance modeling optimization method, equipment and a medium, and the method comprises the steps: building an MMT-PMSLM dynamic response performance analysis model based on thrust performance, mechanical and electrical time constants, motor constants and thrust bandwidth based on the requirement of a linear servo system for high dynamic performance; based on the performance analysis model, constructing an MMT-PMSLM dynamic performance prediction model based on PI-GAN; and performing iterative optimization on the dynamic performance prediction model through a dream optimization DOA algorithm to generate optimized structure parameters. The dynamic performance modeling optimization method disclosed by the invention has the characteristics of high precision, strong generalization ability and interpretability, so that the result of optimizing the motor structure by the algorithm has high reliability.

The invention discloses a thermal working time lag process ADRC design method with time lag robustness. The thermal working time lag process ADRC design method comprises the steps that 1, a transfer function model of a first-order inertia time lag process of a thermal process is established; step 2, establishing a time-delay ADRC structure based on model information driving; 3, obtaining a proportional gain with expected closed-loop dynamic representation and a corresponding observer bandwidth setting rule through low-frequency approximation; step 4, scaling control parameters of the ADRC system according to the transfer function model established in the step 1, and setting default adjustment parameters of proportional gain and observation bandwidth; 5, carrying out equivalent two-degree-of-freedom conversion on the closed-loop system, analyzing the nominal stability of the ADRC system based on a double-track method, and obtaining a nominal stability domain of the control parameters; and step 6, in the nominal stability domain obtained in the step 4, according to the regularization rule of the ADRC scaling parameter and the demand of comprehensive robustness, obtaining the time constant of the low-pass filter in the compensation channel by establishing a monotonically decreasing amplitude curve of the time-delay ADRC open-loop Bode diagram.

Disclosed is an integrated energy system optimized dispatching method based on a variable time constant gradient algorithm. A Markov decision making process model is established based on an economic dispatching characteristic of an integrated energy system first, and a target optimization function is established. Then, a neural network is established and trained by applying a double-delay depth deterministic strategy gradient algorithm, effective experience is determined before updating a target network, and a variable time constant is set according to a reward value of a current round and a reward value of the last round of soft update. Finally, a trained intelligent agent is used for intra-day dispatching of the integrated energy system, so as to realize optimal economic cost operation of the integrated energy system.

The invention discloses a VSG coordinated control method and device based on improved self-adaption and feed-forward compensation, and the method comprises the steps: building a model of a VSG optical storage grid-connected system, and analyzing a power angle characteristic and a frequency oscillation curve; introducing an arc tangent function to optimize a traditional adaptive control strategy, and smoothly adjusting rotational inertia and a damping coefficient; a feed-forward compensation control strategy is added, an active compensation expression and a rotor motion equation are established, a compensation coefficient and a filtering time constant are set in a coordinated mode, and configuration of a small-signal model change zero-pole pair of an active power reference value under disturbance is reconstructed; adjusting virtual rotational inertia and a damping coefficient based on the optimized adaptive control strategy, and correcting a power reference value in advance by predicting frequency fluctuation based on a feed-forward compensation control strategy; according to the method, power overshoot and frequency change deviation are effectively suppressed, smooth adjustment of rotational inertia and VSG dynamic performance optimization are realized, and the system response speed and stability are enhanced.

The invention discloses an intelligent self-adaptive injection flow regulation and control system for geological storage. The system comprises a sensor module, a data processing module, an execution mechanism module and a self-adaptive algorithm module, the sensor modules are distributed in an injection well and a surrounding monitoring well and are used for acquiring pressure, temperature and flow data in real time; the data processing module performs normalization processing on the monitoring data and extracts dynamic characteristics; the adaptive algorithm module integrates a multi-parameter coupling regulation and control model constructed by fuzzy PID and an LSTM neural network, predicts the trend of a seepage field and generates a regulation and control instruction; the execution mechanism module adjusts an electric control valve group and a variable-frequency injection pump according to instructions, so that the error between an actual injection curve and a target parameter curve is smaller than 5%. All the modules form a closed-loop control system through an industrial Internet of Things platform, the LSTM neural network updates weight parameters every 30 minutes, and a fuzzy PID controls an integral time constant to be automatically adjusted. The system is suitable for geological storage of CO2, accurate regulation and control of the injection flow can be achieved, and the leakage risk and the injection energy consumption are reduced.

The invention discloses a vibration test and state monitoring method and system for an in-operation high-voltage circuit breaker, and the method comprises the steps: carrying out the energy propagation time sequence test of a multi-measurement-point vibration signal, constructing an energy flow direction topological graph, and precisely positioning a vibration source region through energy ratio analysis and path backtracking; acquiring a response time constant by adopting an impact response attenuation test, and converting a vibration source into a fault space positioning coordinate through space grid division and rate matching; a frequency-space mapping relation is established based on a fault position, and vibration characteristics are comprehensively described through peak frequency time sequence tracking and nonlinear component identification such as frequency multiplication, modulation and transient state; performing dispersion analysis on the continuous action impact peak value to form an action consistency deviation, and fusing a nonlinear feature set to quantitatively evaluate the mechanical degradation degree; the grading test density is generated according to the degradation state, the time period test unit is determined, the state grading test benchmark is established to realize mechanical state grade judgment, and the equipment operation reliability and the monitoring efficiency are improved.

The invention relates to a frequency converter dynamic performance optimization control method, and belongs to the technical field of power electronics. The method comprises the steps that frequency converter operation and device characteristic signals and external working condition correlation signals are collected in real time and integrated into a multi-dimensional operation data set, an analysis model is built, and a mapping relation is preset; extracting transient characteristics of a device switch, calculating a dynamic impedance parameter based on a mapping relation, and matching a parameter self-tuning rule base to generate a current loop proportionality coefficient, an integral time constant and a modulation wave duty ratio correction; a rotating speed and current double-loop fusion framework is built, the weight of an outer loop is dynamically adjusted according to rotating speed deviation and load sudden change, an inner loop adopts an adaptive reaching law and disturbance compensation, and a cooperative control instruction is generated through inter-loop interaction; monitoring instruction execution data to form feedback, correcting a model mapping relation and optimizing control parameters. The dynamic response precision of the frequency converter under complex working conditions is improved, the anti-disturbance capability is enhanced, and meanwhile, the device operation loss and the manual debugging cost are reduced.

This numerical control device comprises a distance control unit, a filter unit, a determination unit, and a setting unit. The distance control unit controls the distance between a first object and a second object to be close to a target distance. The filter unit filters a signal indicating the distance. The determination unit determines, on the basis of the target distance, a time constant obtained from the relationship between the distance and an output signal from a distance sensor that measures the distance. The setting unit sets a time constant of the filter to the time constant determined by the determination unit.

The invention relates to the technical field of motor control, and discloses an induction motor rotor time constant adaptive control method, system and device, and the method comprises the steps: determining a rotor time constant estimation value based on the reactive power deviation of a model reference adaptive system; determining a rotor resistance estimation value according to the rotor time constant estimation value and a rotor inductance parameter value obtained in real time; performing low-pass filtering on the rotor resistance estimation value to generate a filtering value; updating a rotor time constant feed-forward value based on the rotor inductance parameter value and the filtering value; and based on the rotor time constant feedforward value, optimizing a convergence process of the rotor time constant estimation value so as to perform indirect vector control of the induction motor. The method has the beneficial effect that the convergence speed and robustness of adaptive identification of the rotor time constant are improved.

The invention relates to a high-voltage SF6 circuit breaker asymmetric short-circuit current breaking result prediction method, equipment and a medium. The method comprises the following steps: acquiring a plurality of groups of arc voltage and arc current test data obtained by performing a T100a test on a target circuit breaker under a first time constant; based on the test data, establishing a black box arc model, and fitting to obtain arc dissipation power and arc time constant corresponding to each group of test data through numerical solution and parameter optimization algorithms, thereby obtaining an on-off critical value; fitting is carried out in an arc breaking critical parameter fitting model, and values of a first parameter, a second parameter, a third parameter and a fourth parameter are determined; and obtaining a predicted value of an on-off value under the working condition through an arc on-off critical parameter fitting model, if the predicted value is greater than an on-off critical value, determining that on-off is successful, otherwise, determining that on-off is failed. Compared with the prior art, the method has the advantages of high accuracy, high practicability, simple process and the like.

The invention discloses a speed loop two-degree-of-freedom PI control method and device based on feedforward and a medium, and relates to the technical field of speed loop control methods.According to the method, on the premise that the bandwidth of an inner current loop is higher than that of a speed loop, a PI feedback steady state is adopted, and a disturbance observer is used for load disturbance estimation and compensation; feedforward forming is introduced to a given side, a'given-output 'closed loop is shaped into a first-order or critical damping second-order target model, and a disturbance observer time constant, a target bandwidth and a sampling period are systematically set. The device is composed of an error acquisition module, a PI feedback module, a disturbance observation module, a feed-forward forming module and an execution interface module. According to the scheme, under the condition that hardware is not changed, rapid low-overshoot tracking is achieved, the anti-interference performance is not weakened, parameters can be reused, and the method is suitable for servo scenes such as numerical control, robots and stabilized platforms.

The invention provides a design method of an adaptive signal conditioning system of a flexible gait sensor, and belongs to the technical field of flexible sensor signal conditioning. The method comprises the following steps: establishing a gait feature database by analyzing gait features in different states; obtaining design reference values of a gain G and a time constant according to stride frequencies and signal amplitudes of different gait states and requirements on dynamic response characteristics, and calculating corresponding accurate RC values under different gait states through mathematical relationships between the design reference values and capacitors and resistors in a charge amplifier and a low-pass filter circuit; carrying out simulation verification, and carrying out iterative optimization on the key parameters according to a result; designing a complete hardware system, and completing the design and layout of a PCB; and finally, circuit parameters are dynamically adjusted based on a pre-stored stride frequency RC mapping relation, and dynamic adaptive adjustment of the stride frequency is realized. According to the invention, high-precision conditioning output of mV-level weak signals is realized, the precision and stability of signal acquisition are remarkably improved, and the application scene of the system is expanded.

The invention relates to the technical field of general control or regulation systems, and discloses an AI-based thermal load prediction and multi-heat-source optimization scheduling system, which comprises a source characteristic storage unit, which is used for dividing heat source equipment into an inertial base load group and an agile regulation group according to a response time constant; the load trend prediction unit is used for calculating a thermal load change slope by adopting a time sequence prediction model; the control instruction generation unit is used for decoupling the total heat load demand by utilizing a low-pass filtering algorithm according to the change slope; the collaborative scheduling unit is used for establishing a frequency division mapping mechanism, mapping a low-frequency base quantity demand to an inertial base load group and mapping a high-frequency increment demand to an agile adjustment group; and the feedback correction unit is used for generating a correction compensation amount and only superposing the correction compensation amount to a control instruction for the agile adjustment group when the change rate of the total return water temperature of the heat supply network exceeds the limit, and adjustment oscillation caused by heat supply network lag is avoided through frequency division decoupling and a targeted feedback framework.

This invention discloses a method for directional experimental verification and performance testing guided by computational simulation in materials chemistry, belonging to the field of materials performance testing technology. The method includes: acquiring the structural parameters of semiconductor devices and initial parameters of interface defects; calculating the characteristic time constant of carrier trapping by interface traps; simulating and generating a theoretical capacitance-voltage hysteresis loop; then performing bidirectional voltage scan tests within a sensitive scan rate range; finally, updating the inversion parameters and resimulating, iteratively adjusting until the characteristic deviation between the theoretical loop and the measured data meets the convergence condition, thus outputting an interface state density distribution map. This invention, through computational simulation-guided directional experiments, achieves accurate capture and non-destructive in-situ characterization of the dynamic response characteristics of interface states, effectively establishing the dynamic structure-property relationship between microscopic interface defects and macroscopic device performance, and significantly improving the accuracy and reliability of interface defect parameter inversion.

The invention relates to a method for setting the parameters of a control of a pressure supply system of a hydraulic system, wherein the pressure supply system has a motor (4) and a hydraulic machine (2) that are controlled with a manipulated variable, wherein the control (160) is implemented by a control algorithm, wherein the control algorithm is parameterised by one or more parameters that can be set or changed during operation, the method comprising: carrying out (110), during operation of the hydraulic system, an estimation method based on a physical model in order to determine an estimated value for at least one characteristic variable of the hydraulic system, wherein the at least one characteristic variable includes a hydraulic capacity of the hydraulic system; determining (120) an adjustment time constant as equal to or greater than a target time constant, by means of which a maximum pressure build-up rate of the hydraulic system is achieved, which is determined by the estimated value for the hydraulic capacity and a maximum volumetric flow rate of the hydraulic machine; setting (150) at least one parameter of the one or more parameters, wherein the at least one parameter is determined (130, 140) by a respective function dependent on the setting time constant.

The invention discloses an intelligent control method and system for a heat supply system, and the method comprises the steps: calculating a temperature control response deviation ratio of each control period according to the difference between actual room temperatures and the difference between predicted room temperatures of adjacent control periods, calculating a response deviation duration index according to the time domain characteristics of a temperature control response deviation ratio sequence, and calculating the temperature control response deviation of each control period; according to mean value characteristics and fluctuation characteristics of a temperature control response deviation ratio sequence and a first-order difference sequence thereof, calculating a thermal characteristic change mode identification index, and combining the two to calculate update quantities of a heat transfer coefficient and a thermal inertia time constant; the room temperature of the next control period is predicted according to the updated heat transfer coefficient and the updated thermal inertia time constant, and an objective function of a multi-objective convex optimization problem is constructed based on the predicted room temperature and the valve adjustment amplitude of all users in the unit; and solving to obtain an optimal valve opening instruction to regulate and control the valve. The precision and stability of thermodynamic balance control are improved.

This invention discloses a method for the collaborative optimization of turbine governor parameters and hydraulic system parameters. The method involves synchronously collecting multi-source operating data from a hydropower station using a sensor network to construct a hydraulic-governing coupled state-space model. Based on the UKF unscented Kalman filter algorithm, the method identifies the water flow inertial time constant, water hammer wave velocity, and turbine integrated transfer coefficient online, and evaluates the reliability of the identification results using a parameter identification confidence index. In a joint high-dimensional space of the control parameter domain and the hydraulic parameter domain, the method uses regulation quality, hydraulic safety, and grid stability as three objective optimization functions to solve for the Pareto front candidate set, and selects robust parameter schemes using a robust stability margin index. A three-level differentiated push strategy is implemented based on the parameter change amplitude, and real-time monitoring and an automatic anomaly backoff mechanism are implemented during the gradual push process. This invention achieves full-cycle collaborative optimization and safe tuning of hydraulic system parameters and governor control parameters.

The invention discloses a circuit reduction method and system based on sparse processing, and the method comprises the steps: A, carrying out the node elimination of a circuit matrix through employing a time constant balance reduction (TICER) algorithm, and obtaining a matrix which is smaller in scale and is dense due to filling; b, deleting redundant non-zero elements by using a spectrogram sparsification algorithm, and meanwhile, keeping the core characteristics of the matrix to obtain a sparsification matrix; and C, judging the density of the matrix, if the sparse effect reaches the expectation, outputting a new matrix after reduction, otherwise, returning to the step of the initial matrix. By the adoption of the method, circuit reduction can be carried out through the method of combining spectrogram sparsification and the TICER algorithm, the matrix density degree is effectively reduced, and the simulation speed is greatly increased; and the circuit reduction effect can be ensured by setting a rollback mechanism.

The invention relates to a method and a device for determining and using a diagnostic tool comprising a temperature ageing spectrum, the method (P) comprising a step (E1) of receiving at least one temperature curve relating to a given geographical location, a processing step (E2) comprising a sequence of consecutive substeps (E2A, E2B, E2C, E2D, E2E), implemented iteratively for different values of a characteristic time associated with a type of material, comprising a substep (E2A) of filtering the temperature curve using a first-order filter having the characteristic time as the time constant, a substep (E2B) of applying an ageing law, a substep (E2C) of performing a cumulative calculation over a given sliding time period, a substep (E2D) of extracting a value corresponding to an ageing criterion and a substep (E2E) of associating this extracted value with the characteristic time, wherein the pairs of values obtained at the end of the iterations form a temperature ageing spectrum, and a step (E3) of performing, from at least this spectrum, comparisons in order to carry out a diagnosis.

This application provides a control method, apparatus, equipment, medium, and program product for a cleaning device, which can be applied to the field of liquid-cooled server technology. The method includes: determining the pressure difference between a reference pressure value and the real-time pressure value of the fluid at the outlet of a target pump in the cleaning device; processing the pressure difference based on a hysteresis relationship using preset pressure control parameters to determine a speed adjustment signal, wherein the hysteresis relationship indicates the degree of lag between the moment the target pump speed changes and the moment the fluid pressure value change is acquired; controlling the target pump to operate at the speed indicated by the speed adjustment signal to adjust the output flow rate of the target pump, so that the adjusted pressure value is close to the reference pressure value; wherein the pressure control parameters are obtained by simulation calculation of the hysteresis relationship based on the inertial time constant of the fluid at the outlet of the target pump and the pressure wave propagation delay time.

This invention discloses a hierarchical continuous attractor network based on intrinsic time constant gradients, belonging to the fields of artificial neural networks and cognitive computing. The network includes a spatial input extraction module, multiple continuous attractor layers, a spatial projection module corresponding to each layer, and a wave packet decoding module. Each layer has a preset and fixed time constant during initialization, and the time constants of each layer monotonically increase from the bottom layer to the top layer. The same external spatial input is projected to each layer in parallel. The bottom layer tracks instantaneous spatial changes with a shorter relaxation time, while the top layer accumulates slowly varying spatial statistics with a longer relaxation time. The cyclic connection weights of each layer are initialized with translation-invariant functions to form a continuous attractor manifold, and are fine-tuned online by superimposing Hebbian enhancement and weight decay. This invention can form multi-timescale spatial representations, improving the stability and precision of representations in high-frequency spatial regions.