122 results about "Integral coefficient" patented technology

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

The invention 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 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 belongs to the field of process equipment control, and provides a PID (Proportion Integration Differentiation) controller optimization method (BCGSSA-PID) based on an improved sparrow search algorithm in order to solve the problem that the system temperature is difficult to control due to nonlinearity, time lag and the like in the production process of a typical thermotechnical object continuous stirred tank reactor (CSTR). According to the method, firstly, three parameters of a PID controller are optimized through a BCGSSA algorithm, an optimal parameter combination of a proportionality coefficient Kp, an integral coefficient Ki and a differential coefficient Kd is found, and then the optimal parameter combination is used for temperature control of a CSTR system. Compared with a traditional PID control method, the method can automatically select a better parameter combination, and avoids the problems that time and labor are consumed and an ideal control effect cannot be achieved when parameters are selected manually depending on experience. According to the method, the high response speed is guaranteed, the overshoot suppression is higher, the system can reach the steady state more quickly, and the dynamic performance of the system is remarkably improved. Meanwhile, the method has high robustness and adaptivity, and the system temperature can be ideally controlled even under the condition that disturbance is introduced into the system and a system model is mismatched.

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 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 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 invention discloses a current control parameter optimization method and device based on a whale optimization algorithm. The method comprises the following steps: firstly, detecting an unbalanced signal in a current system, wherein the unbalanced signal comprises unbalanced magnetic potential and / or unbalanced voltage; secondly, inputting the unbalanced signal into a whale optimization PID (Proportion Integration Differentiation) controller; (inputting the unbalanced magnetic potential into the whale optimization PID controller); then, the whale optimization PID controller dynamically adjusts a proportionality coefficient, an integral coefficient and a differential coefficient of the PID controller through a whale optimization algorithm based on the imbalance signal so as to optimize control parameters; and finally, according to the optimized control parameters, adjusting the output current of the current source to realize balance control of the current system. Compared with a traditional control method, the method has the advantages that the response speed is higher, the fluctuation range is smaller, operation is convenient, the evaluation process is quantized through a fitness function, and the fitness value of whale optimization PID controller parameters updated every time is smaller.

The invention discloses a flow pressure control method and a related device, and the method comprises the steps: adaptively adjusting an integral coefficient and a proportionality coefficient in an incremental proportional-integral control algorithm in a control process, i.e., the integral coefficient is determined according to a sensitivity gain at a current moment and a difference value at the current moment; the proportion coefficient is determined according to the sensitivity gain at the current moment, the sensitivity gain characterization at the current moment is determined according to fitting of the historical actual flow pressure and the historical frequency of the frequency converter, the situation of excessive adjustment or under-adjustment is avoided, and the self-adaptive integral coefficient and the proportion coefficient can adapt to the pressure attenuation characteristics in the middle and later periods of mining.

The invention discloses a method for suppressing broadband oscillation of an energy storage power station. The suppression method adopted by the invention comprises the following steps: if broadband oscillation information is detected and the oscillation amplitude is greater than a preset value, judging whether oscillation is in a divergent, convergent or equal-amplitude form through an amplitude comparison method, and if the oscillation is in the convergent form, not adjusting and belonging to a normal phenomenon; if the mode is a divergent or constant amplitude mode, the next step is adopted for intervention; a proportionality coefficient and an integral coefficient of a PI controller in the energy storage converter control system are switched to another set of parameters which are input in advance; after the parameters are switched, if the oscillation is still in a divergent or constant-amplitude form, the next step is adopted for further intervention; if the oscillation is changed into a convergent form, adjustment is not carried out any more; and according to an oscillation divergence slope formula, carrying out dynamic locking on the energy storage converter of which the oscillation is still in a divergence or constant-amplitude form after parameter switching so as to suppress the oscillation. According to the invention, generation of broadband oscillation can be effectively suppressed.

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 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.

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 invention provides a loop parameter adaptive adjustment method and device for a digital power supply loop and a readable storage medium, and the method comprises the steps: switching a digital loop feedback source to a protection measurement value when the protection measurement value (such as Kelvin voltage drop) triggers an alarm, and setting a reference value as a safety value; pID control parameters are dynamically adjusted based on a reinforcement learning algorithm (such as a depth deterministic strategy gradient algorithm), increment adjustment of a proportionality coefficient, an integral coefficient and a differential coefficient is included, and rapid alarm elimination is achieved in combination with forced parameter switching (such as increasing the proportionality coefficient to two times and limiting the adjustment range of the integral coefficient by + / -5%). After the alarm is triggered, the adjustment time is shortened to 50 microseconds, the overshoot is reduced to be within 5%, the problem of circuit overheating caused by disconnection delay or invalid adjustment in a traditional scheme is solved, meanwhile, additional hardware is not needed, and the method is suitable for an embedded power supply control system.

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.