100 results about "Integral coefficient" patented technology

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 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 discloses a single-phase phase-locked loop system capable of intelligently adjusting parameters, and the system comprises a spectrum analysis unit which outputs a fundamental wave frequency fc, a fundamental wave angular velocity omega c, and a cascade delay signal elimination parameter ni; the self-adaptive single-phase phase-locked loop unit comprises a third-order generalized integrator, a dq converter, a cascade delay signal canceller CDSC, a PI controller, an integrator and a modulus taking device, and the cascade delay signal canceller CDSC takes a fundamental wave frequency fc as a reference frequency and takes a fundamental wave angular velocity omega c as a reference angular velocity of an input end of the integrator; an angular velocity increment delta omega output by the PI controller and a fundamental wave angular velocity omega c are added to jointly determine a phase locking angle theta, and a proportionality coefficient kp and an integral coefficient ki of the PI controller are refreshed online from the outside and take effect immediately; and the control parameter intelligent optimization unit is used for iteratively solving the optimal [kp, ki] based on a mirage search optimization algorithm MSO and writing the optimal [kp, ki] into the nonvolatile memory. According to the single-phase phase-locked loop system capable of intelligently adjusting the parameters, manual parameter adjustment is avoided, and phase locking is rapid, accurate and stable for a long time.

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 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 provides a combustion control system for an industrial kiln. The combustion control system comprises a data acquisition and preprocessing module; the BP neural network module is used for operating three parallel BP neural network models which are respectively used for flame temperature control, flame length control and pollutant emission control, and each BP neural network model is provided with an input layer, a hidden layer and an output layer; the PID parameter adjusting module is used for dynamically adjusting the proportionality coefficient Kp, the integral coefficient Ki and the differential coefficient Kd of the PID controller module according to the output of the BP neural network module; the PID controller module is used for calculating a control quantity according to the parameters provided by the PID parameter adjusting module and outputting a control signal; and the execution mechanism module is used for receiving the control signal of the PID controller module and adjusting the mixing proportion and the flow of the first fuel and the second fuel. According to the invention, the PID control loop is optimized through the three parallel BP neural networks, and cooperative control based on flame temperature, flame length and pollutant discharge is realized.

The invention relates to the field, and discloses a parallel power supply efficiency optimization method and system, and the method comprises the steps: collecting the output current of each power supply module in real time through a current sensor of each power supply module, and collecting the total output current of a parallel power supply system, and the input voltage and output voltage of each power supply module; calculating a current sharing error of each power supply module, and adjusting a proportionality coefficient, an integral coefficient and a differential coefficient of a fuzzy PID controller through a fuzzy inference rule; the voltage regulator is used for regulating the power supply module through the control signal; calculating the efficiency of each power supply module according to the input voltage, the output voltage and the output current of each power supply module, and determining the optimal working point of each power supply module and adjusting the input power of each power supply module according to the efficiency and the load condition of each power supply module so as to complete the efficiency optimization of the whole parallel power supply; according to the invention, the working state of the power supply module can be adjusted in real time under different working conditions, and the method has high adaptability and stability.

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 discloses an automatic control method and system for fumaric acid production. The method comprises the following steps: collecting process variables in a fermentation process; constructing a soft measurement model fusing physical modeling and a residual neural network to obtain an acid production rate prediction value and prediction confidence; calculating a feed-forward control quantity, and adjusting the weight according to the prediction confidence to obtain a feed-forward control output; constructing a state vector, and establishing a Markov decision process; training a neural network control strategy by adopting a near-end strategy optimization algorithm, and outputting a proportionality coefficient, an integral coefficient and a differential coefficient; calculating feedback control quantity, fusing the feedback control quantity with feed-forward control output, and applying change rate and amplitude limitation to obtain final control output; and switching to a feedback priority control mode under a specific condition, and regularly updating a soft measurement model and a control strategy parameter. According to the invention, high-precision stable control of pH in the fumaric acid fermentation process is realized, the production efficiency and the process robustness are improved, and the method is suitable for automatic control of the large-scale fermentation process.

The invention discloses a vehicle parking control method and device and a vehicle. The method comprises the steps that when an accelerator of a vehicle is released, a rotating speed integral term, an acceleration integral term, a first integral coefficient and a second integral coefficient of a rotating speed control strategy are made to be zero; in each rotating speed control period, determining an output value of a rotating speed control strategy according to the target rotating speed of the current rotating speed control period and the actual rotating speed of the motor, and controlling the motor to decelerate according to the output value of the rotating speed control strategy; when the actual rotating speed of the motor is smaller than the preset rotating speed and the target rotating speed is zero, the first integral coefficient and the second integral coefficient are not zero; and in each rotating speed control period, determining an output value of a rotating speed control strategy according to the value of the rotating speed proportional term, the value of the rotating speed integral term and the value of the acceleration integral term, and controlling the motor to operate according to the output value of the rotating speed control strategy until the actual rotating speed of the motor is zero. According to the technical scheme, the vehicle can be well controlled to be parked on the ramp and the flat ground.

The application provides a double-fed variable-speed pumped storage unit cooperative control method based on a fuzzy PID, and belongs to the field of pumped storage unit control methods.The method comprises the following steps: S1, obtaining an error and an error change rate in a pumped storage unit; S2, inputting the error and the error change rate into a designed fuzzy controller to output a proportional coefficient increment and an integral coefficient increment; S3, combining an original proportional coefficient quantity and an original integral coefficient quantity of the pumped storage unit to output updated control parameters; S4, obtaining an actual water head and a theoretical water head of the pumped storage unit, dynamically adjusting a proportional coefficient gain coefficient and an integral coefficient gain quantity, and combining the updated proportional coefficient quantity of the pumped storage unit and the updated integral coefficient quantity of the pumped storage unit to jointly input into a PID controller; and S5, outputting an opening degree signal by the PID controller to an actuating mechanism, so that the actuating mechanism controls the opening degree of the variable-speed pumped storage unit.The method has high adaptability.

The application discloses a vehicle parking control method, device and vehicle. The method comprises the following steps: when the accelerator of the vehicle is released, setting the speed integral term, the acceleration integral term, the first integral coefficient and the second integral coefficient of the speed control strategy to zero; in each speed control period, determining the output value of the speed control strategy according to the target speed and the actual speed of the motor in the current speed control period, and controlling the motor to decelerate according to the output value of the speed control strategy; when the actual speed of the motor is less than the preset speed and the target speed is zero, setting the first integral coefficient and the second integral coefficient to be non-zero; in each speed control period, determining the output value of the speed control strategy according to the value of the speed proportional term, the value of the speed integral term and the value of the acceleration integral term, and controlling the motor to operate according to the output value of the speed control strategy until the actual speed of the motor is zero. The technical scheme of the application can better control the vehicle to park on a slope and a flat ground.

The present application belongs to the technical field of secondary frequency modulation control of virtual synchronous generator, and discloses a VSG secondary frequency modulation control method and system based on segmented integral coefficients, which proposes the determination of the value of the frequency integral coefficient based on the segmentation of the frequency offset, and determines two fixed integral coefficients respectively. When the frequency deviation is lower than the threshold value, the integral coefficient value is small, and when the frequency deviation is higher than the threshold value, the integral coefficient value is large. The control method proposed in the present application reduces the frequency integral coefficient adjustment frequency while reducing the maximum frequency deviation, improves the frequency dynamic adjustment performance of the virtual synchronous generator and the stability of the system, and through the segmented setting of the integral coefficient, not only the frequency deviation is reduced, but also the frequency dynamic adjustment time is shortened. The control method proposed in the present application changes the integral coefficient only twice in the dynamic adjustment process, reduces the change frequency of the integral coefficient, and improves the stability of the frequency change in the dynamic process.

The invention relates to the technical field of pressure controller optimization methods, provides a PID (Proportion Integration Differentiation) pressure controller optimization method, and solves the problem of pressure fluctuation in a methanol supply system. The method comprises the following steps: S100, establishing a process dynamic model of the marine methanol fuel supply system, and determining key equipment and operation conditions; s200, constructing a fitness function according to an integral value of an error between a set value SP and a process value PV of a PID pressure controller of the methanol fuel supply system along with time; s300, taking a proportionality coefficient and an integral coefficient of a PID pressure controller of the methanol fuel supply system as optimization variables, and forming a search space of two dimensions in a particle swarm algorithm; s400, performing multi-working-condition dynamic simulation on the methanol supply system process, and optimizing the performance of a PID pressure controller of the marine methanol fuel supply system under different working conditions by using a particle swarm algorithm; adjusting controller parameters through a multi-objective optimization algorithm; and S500, adjustment is carried out based on an actual application scene, pressure fluctuation is reduced, and the energy efficiency and the system stability are improved.

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.

The invention provides a fishery pan-tilt equipment self-adjustment control optimization method, and belongs to the field of pan-tilt control, and the method specifically comprises the steps: S1, constructing a fishery pan-tilt equipment control model which comprises a corner control model, an improved artificial travel mouse algorithm and a position type PID controller model; s2, improving a standard artificial squirrel algorithm, and setting a proportionality coefficient, an integral coefficient and a differential coefficient of a position type PID of the holder equipment controller by using the improved artificial squirrel algorithm to realize optimization of the holder equipment controller; and S3, inputting a difference value between the target rotation angle and the real-time rotation angle of the holder into a holder equipment controller, outputting a control signal through a position type PID, inputting the control signal into a rotation angle control model, and outputting a real-time rotation angle value of the holder. Experimental simulation proves that the method disclosed by the invention can solve the problems of easy oscillation and overshoot under the conditions of large rotation angle range and frequent speed abrupt change of the holder.

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 application discloses a new energy grid-connected inverter adaptive transient synchronous stability control method under power grid asymmetric fault. During the power grid asymmetric fault, the system adaptively adjusts the proportional coefficient and integral coefficient of the positive sequence or negative sequence phase-locked loop to change the positive and negative sequence phase-locked loop output angular frequency when the additional controller is used during the fault duration, so that the positive and negative sequence phase-locked loop output angular frequency deviation is 0 during the fault duration, thereby realizing the transient synchronous stability control of the new energy grid-connected inverter under the power grid asymmetric fault. On the basis of not adding an additional control device, according to the fault information of the system, by improving the control structure of the positive and negative sequence phase-locked loop of the new energy grid-connected inverter, the transient synchronous stability of the new energy grid-connected inverter during the power grid asymmetric short-circuit fault can be obviously improved, and the risk of transient synchronous instability of the system is reduced.

The application discloses a kind of slope parking control method and device of vehicle.The method comprises: when vehicle is forward driving on slope, when accelerator is released, the sign of initial rotational speed direction of motor and the sign of initial integral term in rotational speed control strategy are determined;Integral coefficient of integral term in rotational speed control strategy is zero;If the sign of initial rotational speed direction is same with the sign of initial integral term, then periodically reduce integral term in rotational speed control strategy;According to proportional term and integral term corresponding to each rotational speed control period, motor is controlled to decelerate;After integral term is reduced to zero, if the actual rotational speed of motor is greater than target rotational speed of current rotational speed control period, then the output value of rotational speed control strategy is controlled to be zero;When actual rotational speed is less than first threshold, the output value of rotational speed control strategy is not zero, motor is controlled to decelerate according to rotational speed control strategy, until the actual rotational speed of motor is zero.The technical scheme of the application can better control vehicle to decelerate and park on slope.

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 application belongs to the technical field of automation control, and specifically discloses a robot constant force polishing control method and system based on improved SAC reinforcement learning, wherein the method comprises the following steps: establishing a contact simulation model of a polishing robot on a MuJoCo platform; modeling a Markov decision process for the control process of constant force polishing of the polishing robot, setting a state space, an action space and a reward function, and establishing a robot constant force polishing control model; constructing a position-based impedance controller, and controlling the polishing robot to perform constant force polishing based on the impedance controller; the impedance controller comprises unknown impedance parameters, and the impedance parameters comprise a proportional coefficient and an integral coefficient; the impedance parameters in the impedance controller are solved based on improved SAC reinforcement learning, the optimal control strategy of the polishing robot is determined, and constant force polishing control of the polishing robot is realized based on the optimal control strategy. The application has better performance in the scene of robot constant force polishing control of continuous state and action space.

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 invention discloses a fuzzy PID (Proportion Integration Differentiation) control method for an automatic frequency locking system of a laser, which comprises the following steps of: mixing a signal detected by a cavity-front photoelectric detector with a path of radio frequency driving reference signal of an electro-optical modulator to obtain a frequency discrimination error signal and an error signal change rate; after sampling by an analog-to-digital converter, inputting into a fuzzy PID (Proportion Integration Differentiation) controller based on a microprocessor, carrying out fuzzification processing, fuzzy reasoning and defuzzification operation, and outputting a proportionality coefficient increment, an integral coefficient increment and a differential coefficient increment; control parameters are calculated, the driving voltage of the piezoelectric ceramic PZT is adjusted according to the control parameters, the output frequency of the laser is changed, and automatic frequency locking of the laser is achieved. According to the invention, the proportional control parameter, the integral control parameter and the differential control parameter are calculated through the fuzzy PID controller, the output frequency of the laser is adjusted according to the control parameters, automatic frequency locking of the laser is realized, and the control precision and robustness of the frequency locking system are improved.

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.

The invention relates to a jitter suppression method and device of a motor actuator and computer equipment. Comprising the steps of determining a running direction and a first angle error by combining a target angle and a current angle, and providing a basis for adjustment; different target adjustment coefficients are determined according to the motion direction and the error condition so as to adapt to the control requirement; and then the output torque is determined according to the adjustment result corresponding to the integral coefficient obtained by the front and back period error, the proportionality coefficient and the range constraint, the real-time and accurate control of the motor output torque is realized, and the stability and the precision of the operation of the actuator are ensured.

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.

The present invention provides a high-precision motion control method and system for a stacker based on a fuzzy immune algorithm, which belongs to the field of stacker control and solves the problems of low operating accuracy and poor control efficiency of existing stackers. The system includes a multi-axis motion control module, a dual 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 stacker. The method includes the following steps: constructing a three-level control architecture; adjusting the integral coefficient and the differential coefficient; establishing a feedback quantity calculation model; constructing machine learning parameters; and optimizing the parameter input system. Based on the fuzzy immune algorithm, the system achieves high precision, strong adaptability and high reliability in the motion control of the stacker and reduces the failure rate. The stacker adopts a modular design and an integrated intelligent control system, which is efficient and stable. The method combines fuzzy logic with the immune algorithm to give the stacker intelligent decision-making capabilities and adapt to different warehouses.