88 results about "Differential coefficient" patented technology

The invention relates to the technical field of industrial automation and intelligent control, in particular to a general control system strategy optimization method based on reinforcement learning, and the method comprises the steps: firstly collecting the operation data of a system, constructing a state vector of reinforcement learning, and enabling a reinforcement learning agent to fully understand the current operation condition of the system; then, the state vector is input into a reinforcement learning strategy network, an action for adjusting a control strategy is generated by the network, and the action can be used for modifying the proportion, integral or differential coefficient of PID and can also be used for adjusting the prediction step length, weight coefficient or constraint strength of model prediction control, so that the adaptive capacity of a controller to external changes is enhanced; then, a reward signal is constructed according to a response result of the reference controller; the reward function comprehensively considers the error size, the steady-state characteristic, the system energy consumption, the control smoothness and the stability requirement, so that the reinforcement learning not only pays attention to the error minimization when optimizing the strategy, but also considers the low energy consumption, the smooth action and the anti-interference performance at the same time.

The invention provides a stacker high-precision motion control method and system based on a fuzzy immune algorithm, belongs to the field of stacker control, and solves the problems that an existing stacker is low in operation precision, poor in control efficiency and the like. The system comprises a multi-axis motion control module, a double-closed-loop feedback module, a parameter self-learning module, a safety protection and diagnosis module, a positioning detection module, a path planning module, an environment and maintenance management module and a stacking machine. The method comprises the following steps: constructing a three-level control architecture; adjusting an integral coefficient and a differential coefficient; establishing a feedback quantity calculation model; constructing machine learning parameters; and optimizing a parameter input system. The system is based on a fuzzy immune algorithm, high precision, strong adaptability and high reliability of motion control of the stacker are realized, and the failure rate is reduced. The stacker adopts a modular design, integrates an intelligent control system, and is efficient and stable. According to the method, fuzzy logic and an immune algorithm are combined, the stacker is endowed with intelligent decision ability, and the method adapts to different warehouses.

The invention relates to an air conditioner chilled water PID parameter optimization method based on an improved sparrow search algorithm. The method comprises the steps that population initialization, a discoverer updating formula and a follower updating formula in the sparrow search algorithm are improved; a return water temperature difference signal of the air conditioner chilled water system is detected and input to the improved sparrow search algorithm optimization PID controller, and the improved sparrow search algorithm dynamically adjusts the proportionality coefficient, the integral coefficient and the differential coefficient of the PID controller; and the improved sparrow search algorithm iteratively calculates an optimal parameter combination, and the PID controller performs optimal control of the chilled water system based on the optimal parameter combination. The improved sparrow search algorithm carries out population initialization by introducing a reverse learning strategy optimized by a refraction principle so as to enhance the diversity of an initial population; respectively introducing sine and cosine transform and a Cauchy variation mechanism in a position updating stage of the discoverer and the follower; and the PID controller dynamically adjusts Kp, Ki and Kd based on an improved algorithm so as to realize optimal parameter setting.

The embodiment of the invention provides a non-directional force sensor control method and system based on real-time force trend prediction, and the method comprises the steps: collecting a real-time force signal sequence generated when a target mechanical device carries out the contact operation, and inputting the real-time force signal sequence into a pre-trained force trend prediction model; and obtaining a force direction trend prediction result output by the force trend prediction model, generating a multi-dimensional force compensation signal according to the matching degree of the force direction trend prediction result and the current closed-loop control parameter, adjusting a proportion-integral-differential coefficient in the current closed-loop control parameter based on the multi-dimensional force compensation signal, generating an updated closed-loop control parameter, and outputting the updated closed-loop control parameter. The updated closed-loop control parameters are input into an actuator of the target mechanical device, and the contact operation track of the target mechanical device is dynamically adjusted through the actuator according to the updated closed-loop control parameters, so that the multi-dimensional force amplitude data output by the non-directional force sensor are converged to a preset force control target interval. The response speed and stability of the force control system can be improved.

The invention discloses an automobile semi-active suspension PID parameter adaptive adjustment and vibration control method and system based on reinforcement learning, and the method mainly comprises the following working steps: 1, constructing a reinforcement learning environment comprising a suspension dynamics high-fidelity simulation model and a PID controller; 2, defining a state space including a vehicle body vertical acceleration error e (t), an error integral term summa e (t) dt, an error differential term de (t) / dt, a suspension dynamic stroke zdef (t), a driving vehicle speed v (t) and road surface unevenness estimation xi (t); and 3, defining an action space including a proportion coefficient increment delta Kp, an integral coefficient increment delta Ki, a differential coefficient increment delta Kd and an output compensation amount delta e (t) of the PID controller. According to the method, the problem that the suspension performance is reduced due to the fact that control parameters of a traditional PID control method are fixed under the non-linear and time-varying working conditions is solved, and the riding comfort and the handling stability of the vehicle are remarkably improved.

The invention relates to the technical field of refrigeration equipment control, in particular to a wine cabinet compressor self-adaptive control method and system based on environmental parameters. The method comprises the steps that the external environment temperature, the internal actual temperature and the target storage temperature set by a user of the wine cabinet are collected in real time; an environment thermal potential energy index representing external environment thermal invasion intensity is constructed by calculating static deviation characteristics and dynamic change rate characteristics of the environment temperature; and correcting a proportionality coefficient of a PID control algorithm in real time based on the environmental thermal potential energy index, calculating a compressor control quantity through the PID algorithm in combination with a preset integral coefficient and a differential coefficient, mapping the compressor control quantity into a target operation frequency, driving the wine cabinet compressor to operate, and realizing self-adaptive control of the wine cabinet compressor based on the environmental parameters. According to the method, the environment thermal load change can be actively sensed, the control lag is eliminated, the smoothness of steady-state operation is considered while the thermal shock is inhibited, and the control precision of the wine cabinet compressor is improved.

A PID (Proportion Integration Differentiation) control method and system for realizing non-contact centering of a vehicle relates to the field of combined control of vehicle subsystems, and the method comprises the following steps: acquiring a real-time image of a current position of a target vehicle through an image acquisition device, and preprocessing the real-time image to obtain a vehicle contour feature map; vehicle feature point coordinates are extracted according to the vehicle contour feature map, a first coordinate deviation value between the vehicle feature point coordinates and preset target position coordinates is calculated, a vehicle correction instruction is obtained through calculation by adopting a PID controller according to the deviation value, and the PID controller comprises a proportionality coefficient, an integral coefficient and a differential coefficient; the vehicle correction instruction comprises a transverse displacement correction value and an angle correction value; the vehicle correction instruction is sent to an execution mechanism, and a second coordinate deviation value is obtained; and when the second coordinate deviation value is smaller than a preset coordinate threshold value, it is determined that vehicle centering operation is completed. By implementing the method, the mechanical wear during centering of the four-wheel positioning station of the automobile production line can be reduced.

A liquid-cooling dynamic flow control method includes performing by a control device: obtaining at least one temperature difference between a set temperature and at least one current operating temperature of at least one power component; obtaining a set of target control parameters corresponding to the at least one temperature difference according to a pre-stored parameter table, wherein the pre-stored parameter table records the correspondence between a plurality of preset temperature intervals and a plurality of sets of preset control parameters, and each of the plurality of sets of preset control parameters includes a proportional coefficient, an integral coefficient and a differential coefficient; using the target control parameter and the at least one temperature difference to obtain a heat dissipation control parameter; and adjusting a rotational speed of a liquid-cooling pump with the heat dissipation control parameter.

The invention discloses an underwater brushless direct current motor control method based on fuzzy PID, and belongs to the technical field of underwater brushless direct current motor control. The problems that in an existing fuzzy PID technology, a brushless direct current motor is insufficient in control precision, a control rule is difficult to adapt to changes, and the parameter self-adjusting capacity is poor are solved. Input parameters and output parameters of fuzzy PID are set, the input parameters are rotation speed errors and rotation speed error change rates, and the output parameters are correction coefficients of proportionality coefficients, correction coefficients of integral coefficients and correction coefficients of differential coefficients; genetic gene coding is carried out on the membership function and the fuzzy rule of the fuzzy PID, and genetic gene coding is initialized; selecting a fitness function; a genetic algorithm rule is formulated, genetic manipulation is carried out by adopting a fitness proportion method and an elitist strategy combination rule, and then a new individual is generated based on a self-adaptive crossover and variation rule; and calculating the individual fitness based on the generated new individual, repeating until iteration is finished, and decoding to obtain an output parameter.

The invention belongs to the technical field of steelmaking equipment, and discloses a blast furnace pulverized coal injection real-time injection rate deviation control system and method and application. Comprising a PLC system, a PID controller, a blowing rate detector and a blowing system, the PLC system is connected with the PID controller, the blowing rate detector and an actuator, and the PLC system comprises a real-time monitoring module, an accumulated deviation calculation module and a feedback parameter selection module. By monitoring the injection rate in real time and dynamically switching feedback parameters (an hour accumulated deviation value and a real-time deviation value), the response time of the system is remarkably shortened, and the overshoot phenomenon caused by hysteresis is effectively reduced. By combining the self-adaptive PID controller, proportion, integral and differential coefficients can be automatically adjusted according to the size of the deviation value, real-time fluctuation is inhibited while accumulative errors are eliminated, oscillation adjustment of the coal flow valve is greatly reduced, and stability and continuity of the injection rate are guaranteed.

The invention discloses an unmanned surface vehicle robust track tracking method based on track curvature adaptive segmentation control, and relates to the technical field of unmanned surface vehicle autonomous navigation control, and the method comprises the steps: calculating the track curvature of a current leg in real time, and dividing a control section based on a preset threshold; executing a corresponding control strategy according to a control section, dynamically adjusting a proportionality coefficient, an integral coefficient and a differential coefficient by adopting fuzzy PID, and generating a steering lag prediction compensation amount based on a planning energy optimal speed; and steering compensation is carried out based on the steering lag prediction compensation amount, so that steering lag is reduced. And finally, judging whether the terminal point of the current flight segment is reached or not so as to obtain an optimized flight path tracking result. Through a curvature-driven three-section control strategy, a dynamic foresight distance dual constraint and an energy consumption optimization mechanism, the problems of tracking drift, control switching oscillation and energy waste of a traditional method in a sharp turn leg are solved, and the tracking precision and the system robustness under a complex track are remarkably improved.

The invention relates to an electric compressor hierarchical control method and system based on Fuzzy-PID and climate coupling, belongs to the field of new energy automobile thermal management systems, and aims to solve the problems of sudden energy consumption increase caused by climate mismatch, system oscillation caused by multi-physical field coupling deficiency and reliability reduction caused by multi-target conflict in traditional PID control. A season recognition layer judges a winter / summer / transition season mode through a 24-hour Gaussian weighted temperature algorithm; the fuzzy reasoning layer is fused with three variables of temperature deviation, humidity deviation and battery SOC change rate to dynamically output PID parameter correction; and the PID execution layer is combined with the seasonal influence factor, the SOC attenuation function and the humidity gain function to dynamically adjust the proportional / integral / differential coefficient to control the rotating speed of the compressor. Collaborative optimization of long-term climate characteristics and short-term disturbance is achieved, and the energy efficiency ratio of the system is increased; non-linear increase of power consumption in a high-humidity environment is inhibited; and cabin comfort, battery safety and energy consumption multi-target global optimization are compatible.

The invention provides a servo motor control method and device based on PID and a neural network, and the method comprises the steps: obtaining a system error of a servo motor in real time, and obtaining first target data; predicting a proportionality coefficient, an integral coefficient and a differential coefficient of a PID algorithm according to the first target data through the target neural network to obtain second target data; performing fuzzy processing on the second target data through a fuzzy controller to obtain third target data; and updating set operation parameters of the servo motor according to the third target data through a PID algorithm to obtain fourth target data, and controlling the servo motor to operate according to the fourth target data. According to the method, the problem that in the prior art, parameter adjustment is difficult based on a PID algorithm in a servo motor which is a complex nonlinear system and a changeable working environment, and consequently control precision is low is solved.

The invention discloses an underground water pumping and in-situ remediation system and a control method thereof. The system comprises a data acquisition module, a fuzzy PID control module, a repairing agent adding control module and an execution mechanism. The data acquisition module is used for acquiring pH value and conductivity parameters in the underground water treatment process; the fuzzy PID control module is used for adjusting the suction rate according to the deviation between the parameters and the set target value, and comprises three fuzzy rule libraries for respectively adjusting the proportion coefficient, the integral coefficient and the differential coefficient of a PID controller; the repairing agent adding control module adjusts the adding amount of a repairing agent according to the control signal; and the executing mechanism comprises a suction pump and a repairing agent dosing pump. The system further comprises a random number module which generates random disturbance parameters conforming to preset probability distribution and dynamically corrects control output. The suction pump is used for sucking and adding a repairing agent through a composite pipeline with an inner and outer pipe structure. The system can stably and efficiently control the groundwater remediation process, and the remediation effect is improved.

The invention relates to the technical field of shield tunneling machines, in particular to a shield tunneling machine continuous counter-pull control system for tunnel shield construction, which comprises a master control base station unit, a hydraulic pump station unit and a hydraulic execution module, the shield tunneling machine is subjected to continuous counter-pull starting driving through the hydraulic execution module, and the hydraulic pump station unit is communicated with the hydraulic execution module through a hydraulic pipeline. The hydraulic pump station unit provides a power source for the hydraulic execution module, and drive control over the hydraulic execution module is achieved. According to the control system, data are collected in real time through various sensors and fused, accurate state information is provided for the system, high-precision synchronous telescopic operation of all the hydraulic execution modules is achieved, proportion, integral and differential coefficients can be dynamically adjusted in cooperation with a self-adaptive PID control algorithm, and when errors are large due to the change of working conditions, the control precision is improved. And the proportionality coefficient can be quickly adjusted.

This application provides a papermaking pulping control method, system, storage medium, and program product, relating to the field of industrial process automation control technology. By performing weighted and differential arithmetic operations on current and historical errors based on preset proportional, integral, and differential coefficients, the ideal control increment is calculated, initially determining the adjustment force required to eliminate system errors. A weighted smoothing mechanism based on filter coefficients is introduced, i.e., by multiplying the ideal control increment with preset filter coefficients and combining this with the multiplication of the increment calculated at the previous moment with the complement of the filter coefficients, two partial results are generated and summed. This ensures that the commands received by the electric regulating valve are smoothly corrected, thereby eliminating high-frequency valve jitter and system oscillation caused by signal noise without reducing the system response speed, achieving high-stability control of the pulping process.

The present invention belongs to the field of laboratory environment control technology, and in particular relates to an artificial intelligence-based intelligent monitoring and regulation method for laboratory temperature and humidity. The method first establishes laboratory temperature and humidity PID control and designs temperature and humidity PID controllers. Next, an objective function is constructed, integrating indicators such as overshoot and rise time and performing normalization processing, and optimizing temperature and humidity regulation performance by adjusting weight coefficients. Then, an improved starfish optimization algorithm (SFOA) is used to optimize the proportional, integral, and differential coefficients of the PID controller through parameter setting and population initialization. Finally, a simulation is performed to obtain a response curve. Compared with traditional PID control technology, the present invention can more efficiently and accurately regulate temperature and humidity, effectively improving the stability of the experimental environment and the reliability of experimental results.

The present invention proposes a method, device and readable storage medium for adaptively adjusting loop parameters of a digital power supply loop, including: when a protection measurement value (such as Kelvin voltage drop) triggers an alarm, switching the digital loop feedback source to the protection measurement value and setting the reference value to a safe value; dynamically adjusting the PID control parameters based on a reinforcement learning algorithm (such as the Deep Deterministic Policy Gradient algorithm), including incremental adjustment of the proportional coefficient, integral coefficient and differential coefficient, and combining forced parameter switching (such as doubling the proportional coefficient and restricting the integral coefficient adjustment range to ±5%) to quickly eliminate the alarm. In the present invention, the adjustment time is shortened to 50 microseconds after the alarm is triggered, and the overshoot is reduced to less than 5%, solving the problem of circuit overheating caused by disconnection delay or ineffective adjustment in the traditional scheme. At the same time, no additional hardware is required, and it is applicable to embedded power control systems.

The invention relates to the technical field of charging piles, and discloses a power module fan rotating speed adjusting method based on fuzzy PID control, and the method comprises the steps: obtaining an air inlet temperature fuzzy value according to a preset air inlet temperature given value and a plurality of detected air inlet temperature real-time values of a power module; quantizing the air inlet temperature fuzzy values to the corresponding fuzzy domains so as to respectively calculate the membership degrees of the air inlet temperature fuzzy values in the respective corresponding fuzzy domains; and determining an incremental proportion coefficient real-time adjusting quantity, an incremental integral coefficient real-time adjusting quantity and an incremental differential coefficient real-time adjusting quantity in an incremental PID control scene according to each membership degree, so as to determine a fan rotating speed adjusting quantity of the power module based on the above. According to the method, the fuzzy PID control mode is combined on the basis of conventional PID control, the influence of internal and external factors on fan conversion control can be effectively reduced, the control precision of the fan rotating speed of the power module is improved, and the fan operation stability of the power module is further improved.

A PID control method and system for realizing non-contact centering of a vehicle, which relates to the field of joint control of vehicle subsystems. The method includes: obtaining a real-time image of the current position of a target vehicle through an image acquisition device, and preprocessing the real-time image to obtain a vehicle contour feature map; extracting the coordinates of vehicle feature points according to the vehicle contour feature map, calculating a first coordinate deviation value between the coordinates of the vehicle feature points and the preset target position coordinates, and calculating a vehicle correction instruction by using a PID controller according to the deviation value. The PID controller includes a proportional coefficient, an integral coefficient, and a differential coefficient, and the vehicle correction instruction includes a lateral displacement correction amount and an angle correction amount; sending the vehicle correction instruction to an actuator and obtaining a second coordinate deviation value; when the second coordinate deviation value is less than a preset coordinate threshold, it is determined that the vehicle centering operation is completed. Implementing this method can reduce mechanical wear during centering at the four-wheel alignment station of an automobile production line.

The invention relates to a servo press control method and system based on multi-modal perception, and the method comprises the steps: collecting and preprocessing multi-modal data reflecting the operation state of a servo press in real time, the multi-modal data comprising stamping tonnage, sliding block position, stamping speed, hydraulic flow, mechanical deformation and safety perception information; multi-modal data fusion is realized by using a mixed strategy combining weighted fusion and a BP neural network; based on the servo press system state reflected by the fusion data, parameters of a PID controller for controlling the current of a motor are adjusted in a self-adaptive mode, and the method comprises the steps that the current operation condition is automatically judged to be no-load, light-load or heavy-load; dynamically adjusting a proportionality coefficient, an integral coefficient and a differential coefficient of a PID (Proportion Integration Differentiation) controller for controlling the current of the motor in combination with a Ziegler-Nichols setting method and a fuzzy control rule; and under the control of the self-adaptive PID controller, an S-shaped acceleration and deceleration curve is adopted to plan the movement track of the sliding rail according to the fused data and a preset stamping process curve.

The invention provides an active air supply type transformer substation main transformer chamber cooling method and system, and the method comprises the steps: obtaining an oil temperature set value Ts, a top oil temperature measurement value Tc, and a radiation temperature Td, calculating a temperature difference value delta T according to Ts and Tc, calculating a correction value delta T according to Td through a proportional function Fw, and inputting the difference value between the temperature difference value delta T and the temperature correction value delta T into a PID algorithm, temperature control feedback used for adjusting the air supply amount is output; the PID algorithm comprises a proportionality coefficient Kp, a differential coefficient Kd and an integral coefficient Ki, and the integral coefficient Ki is equal to 0. According to the method, the integral part in the PID algorithm is deleted, and the correction value delta T is introduced, so that the corrected temperature difference value delta T is directly associated with the top oil temperature measurement value Tc, and frequent start and stop of the fan are avoided while the response speed of the fan for cooling is increased.

The invention relates to a temperature control method and system suitable for an MEMS heater. The method comprises the following steps: providing a target MEMS heater and a temperature control device; the temperature control device carries out PID control on the target MEMS heater based on PID control parameters, the PID control parameters are at least formed based on PID reference parameters and PID regulation and control parameters, when the PID reference parameters are configured, reference parameter configuration processing is carried out based on heating characteristic parameters of the target MEMS heater and a genetic particle swarm optimization method, and when the PID regulation and control parameters are configured, PID control parameters are obtained. Generating a reference proportionality coefficient, a reference integral coefficient and / or a reference differential coefficient in the PID reference parameter; and when the PID regulation and control parameters are configured, regulation and control parameter configuration processing is carried out based on the temperature state of the target MEMS heater in the temperature control process and a fuzzy control method so as to generate an adjustable proportionality coefficient, an adjustable integral coefficient and / or an adjustable differential coefficient in the PID regulation and control parameters. According to the invention, the temperature control adaptability and the temperature control precision of the MEMS heater can be improved.

The invention relates to the technical field of water conservancy automation control and edge computing, in particular to a self-adaptive PID control system for a water conservancy reservoir environment, which comprises an edge computing gateway, a water level sensor, a flow sensor and a servo execution mechanism, fluid static geometric parameters are obtained through a topological mapping module, an initial state matrix of a fluid momentum state observer is established, a momentum decoupling module inputs a dam front water level, upstream incoming water flow and opening data to update the state matrix, and transient fluctuation energy characteristics and real reserve residual characteristics are generated through decoupling. The priori fitting module calculates proportion, integral and differential coefficients according to the parameters, and the closed-loop evolution module generates a control instruction and corrects bottom resistance parameters; physical separation of real reservoir capacity change and surface wave disturbance is achieved, invalid oscillation of the gate is reduced, control stability under the flood peak working condition is improved, and the service life of an executing mechanism is prolonged.

The invention discloses a fixed star spectrum simulation method based on genetic algorithm and fuzzy PID compound control. Firstly, a fuzzy PID controller structure with double inputs: spectral intensity deviation # imgabs0 # and deviation rate # imgabs1 # and three outputs: proportionality coefficient increment # imgabs2 #, integral coefficient increment # imgabs3 # and differential coefficient increment # imgabs4 # is established. Then, basic work such as membership function selection, fuzzy rule making and defuzzification is completed; and finally, by means of a genetic algorithm, through coding mode formulation, initial population generation, fitness function selection and genetic operator determination, a fuzzy PID algorithm process is optimized. Practice verifies that in 3000K-9000K typical color temperature spectrum simulation, compared with a traditional fuzzy PID control algorithm, the error is remarkably reduced, and the simulation precision is greatly improved. And the performance is excellent when the full spectrum band simulation of the AM1.5 solar spectrum is carried out. The algorithm can accurately simulate a spectrum curve containing complex details, greatly enhances the accuracy and reliability of spectrum simulation, and provides key technical support for the fields of solar research, optical detection and the like.

The embodiment of the invention relates to the technical field of seismic wave numerical simulation, and provides an elastic wave numerical simulation and wave field separation method and device.The method comprises the steps that firstly, the time-space domain longitudinal wave and transverse wave frequency dispersion relation of an elastic wave equation is derived based on a constructed mixed type space difference operator; further deriving a differential coefficient general solution based on a time-space domain longitudinal wave and transverse wave frequency dispersion relationship, then decoupling elastic wave equations to respectively obtain longitudinal wave and transverse wave elastic wave equations, and deriving a longitudinal wave and transverse wave differential discrete equation based on the constructed mixed space differential operator; and finally, a longitudinal wave and transverse wave differential discrete equation is solved through general solution iteration of a differential coefficient derived from a time-space domain longitudinal wave and transverse wave dispersion relation, so that elastic wave numerical simulation is realized, and wave field separation of longitudinal waves and transverse waves is automatically realized. According to the embodiment of the invention, the numerical dispersion of longitudinal waves and transverse waves can be effectively suppressed at the same time, so that the elastic wave numerical simulation precision is improved.

The invention discloses a medicament adding control method and system, and the method combines the advantages of a PID control algorithm and a random forest control method, builds a medicament adding calculation model, and can dynamically adjust the medicament adding amount. A medicament delivery calculation model is established on the basis of PID control, a proportion coefficient, an integral coefficient and a differential coefficient of PID are processed and updated by a random forest algorithm, and a result at each moment is used as a reference at a subsequent moment, so that the processing process is faster; meanwhile, the traditional PID algorithm only operates past control errors and does not predict future control errors, so that the control performance is limited, the random forest algorithm is introduced, the future control errors are limited and corrected, the control performance is made up, and more accurate control is achieved. According to the invention, accurate and intelligent dosing of chemicals can be realized, and the effluent total phosphorus of a sewage treatment system is effectively promoted to stably reach the standard.

The application discloses an intelligent PID control method for the temperature of a reaction kettle, and comprises the following steps: constructing a reaction kettle temperature model, and adopting a first-order inertia plus delay to describe the dynamic characteristics of the reaction kettle temperature; constructing a Kalman filter PID control model based on an improved RBF neural network; performing normalization processing on the deviation value of the target temperature of the reaction kettle and the real-time temperature; inputting the normalized temperature deviation value into the Kalman filter PID control model, outputting a temperature control signal to an adjusting valve, and adjusting the temperature of the reaction kettle. The improved RBF neural network algorithm is used to intelligently set the PID control parameters, and the Kalman filter is introduced, so that the temperature system can still realize fast response under the environment of nonlinearity, large lag and disturbance. Through real-time dynamic adjustment of the proportional coefficient, the integral coefficient and the differential coefficient, overshoot is inhibited, the steady-state error is reduced, and the system stable time is accelerated.

A unified variable force / variable admittance control method and system based on neural energy functions is disclosed. The method includes: 1. Correcting the force sensor measurements based on the solved zero-point offset, and performing gravity compensation on the force / torque data based on the end-effector's gravity and center of mass position; 2. Defining a unified force / admittance control model for the robot and performing stability analysis; 3. Introducing a variable stiffness encoded energy function and a variable proportional / differential encoded energy function to learn variable stiffness parameters and variable proportional / differential coefficients online; 4. Solving for the analytical expressions of state-dependent variable admittance parameters; 5. Solving for the analytical expressions of the unified variable force / variable admittance control formula; 6. Calculating the pose adjustment amount and correcting the robot's current trajectory based on the pose adjustment amount. This invention achieves compliant and precise control of contact forces, enabling the system to maintain compliance while ensuring the stability and consistency of force output when interacting with the external environment.

The invention provides a CPPS small interference stability control method of fuzzy adaptive PID based on LSTM, and belongs to the technical field of power and small interference stability control, and the method comprises the steps: collecting historical network delay data to train an LSTM model, and obtaining an LSTM prediction model; the rotating speed deviation (error) and the rotating speed deviation change rate (error change rate) of the synchronous generator are collected; predicting the network delay at the current moment by using an LSTM prediction model, and dynamically setting the proportionality coefficient, the integral coefficient and the differential coefficient of the PID controller through a fuzzy logic decision in combination with the error and the error change rate; and inputting the set proportionality coefficient, integral coefficient and differential coefficient into a PID controller to generate a control signal, and enabling the control signal to act on a synchronous generator of the information physical power system to realize small-interference stable control of the information physical power system. According to the invention, the problem of system instability caused by network delay randomness in CPPS is solved.