106results about How to "Small overshoot" patented technology

The invention provides a photovoltaic VSG control method based on virtual inertia and damping, and the method comprises the steps: designing a topological structure of a photovoltaic virtual synchronous generator for modeling, and obtaining a power and power angle equation of the virtual synchronous generator; constructing a function expression of the active power of the virtual synchronous generator and combining the function expression with a power and power angle equation of the virtual synchronous generator to obtain a second-order transfer function so as to obtain a step response curve of the output power and the angular frequency of the virtual synchronous generator; secondly, analyzing an influence mechanism of changes of virtual inertia and damping on the dynamic performance of the virtual synchronous generator based on a step response curve, obtaining self-adaptive principles of the virtual inertia and damping in different states based on the influence mechanism to construct a self-adaptive function, and finally setting parameters in the self-adaptive function and designing a starting criterion. Therefore, the photovoltaic virtual synchronous generator can be controlled. Compared with the prior art, the fluctuation of power and frequency can be better suppressed, and the stability of the system is improved.

The invention discloses a multi-stage temperature accurate control method based on a neural network algorithm, relates to the field of oven temperature control, and particularly comprises the steps of setting a final target temperature # imgabs0 #, and dividing a heating process of heating to the final target temperature # imgabs1 # into a rapid temperature rise stage, a temperature rise control stage and an accurate temperature control stage, an intermediate target temperature # imgabs2 # is set in each stage so as to gradually approach the final target temperature # imgabs3 #; according to the established oven system model, the influence of different intermediate target temperatures # imgabs4 # on temperature response is analyzed, and a proper intermediate target temperature # imgabs5 # combination is found; the heating temperature # imgabs6 # of the heating wire and the temperature # imgabs7 # in the oven are detected in real time through a temperature sensor, and then segmented control is conducted; through segmented control, the temperature rise rate and control precision of each stage are optimized, overshoot is reduced, the response speed is increased, the target temperature is gradually approached, and temperature overshoot caused by one-time large-amplitude temperature rise is avoided.

The invention discloses a disc type permanent magnet motor control method and system with adaptive dead zone compensation, and the method comprises the steps: constructing a state equation, a state estimation equation and a state-space equation of a permanent magnet synchronous motor through the structure of a Luenberger observer, constructing an observable matrix through an output matrix and a system matrix, and verifying the output of an observable system; establishing a characteristic equation to enable the designed observer to be finally converged, reducing an error between an estimated value of the disturbance observer and an actual value of the system, and realizing digital control of an actual servo platform through a discrete observable matrix; a phase-A bridge arm of an inverter is analyzed, three-phase current is subjected to Fourier decomposition, and stator harmonic components are analyzed to obtain three-phase harmonic current of the motor; an adaptive filter is designed based on an NLMS algorithm, and an online dead-zone compensation strategy is improved for a dead-zone effect. According to the method, by introducing the Luenberger disturbance observer, real-time measurement and adjustment of a nonlinear system can be realized, so that the performance index of the system is effectively improved.

The invention discloses a direct current control method and system for improving transient stability of a grid-connected converter, and the method comprises the steps: judging whether a power angle out-of-limit-based fault judgment module or a voltage out-of-limit-based fault judgment module has a voltage drop or phase jump fault or not when any one module judges that a power grid has a voltage drop or phase jump fault; processing an angular velocity control signal of a synchronous control link through a direct current port transient energy correction module, and performing temporary storage unbalanced power-oriented lifting and inertia correction-oriented lifting on a direct current voltage reference value; the voltage value of the direct-current port capacitor is compared with a direct-current voltage reference value, and is processed by the steady-state direct-current voltage control module to obtain a direct-current voltage control reference value; the output data of the converter at the common coupling point obtains a synchronous control signal according to a synchronous control link; and based on the synchronous control signal, an internal potential reference value is obtained according to an internal potential control link, and then a converter driving signal is generated. According to the invention, the stability problem of the grid-connected converter when the power grid has a transient fault can be effectively solved.

The invention discloses a ship-aircraft cooperative path tracking method based on a prediction LOS guidance law, and the method comprises the steps: building an improved LOS guidance law for predicting a path tracking error, and obtaining a ship target course, so as to obtain a ship course error; then, an unmanned aerial vehicle position control controller is established by obtaining an estimated value of the longitudinal speed of the ship and an estimated value representing the transverse speed of the ship and combining actual position coordinates of the ship; and meanwhile, through the established differentiator, a pitching control target and a rolling control target of the unmanned aerial vehicle are obtained, an unmanned aerial vehicle attitude controller is finally established, and in combination with an unmanned aerial vehicle position controller, aircraft-ship cooperative path tracking control is realized. According to the invention, the problem of large overshoot frequently appearing at the steering position of the aircraft-ship cooperative path tracking can be solved, the safety of the aircraft-ship cooperative operation can be improved, and the overshoot of the aircraft-ship cooperative path tracking at the steering position can be reduced.

The invention discloses a terminal sliding mode control method based on an arc tangent function and application of the terminal sliding mode control method. The traditional terminal sliding mode control is fast in convergence, but has a singular problem. The traditional nonsingular terminal sliding mode control solves the singular problem at the cost of sacrificing the convergence time. Therefore, the arc tangent function and the power function are introduced on the basis of the terminal sliding mode, the novel non-singular fast terminal sliding mode control method is constructed, and compared with a traditional terminal sliding mode control method, the method is continuous at a balance point, the singular problem is solved, and the method has the advantages that the method is simple and convenient to operate. Compared with the traditional linear sliding mode control, integral sliding mode control and nonsingular terminal sliding mode control, the method ensures that the speed regulation system has higher convergence speed, higher tracking precision and stronger anti-interference performance.

The invention relates to a PMSM control method based on a BP neural network and a superspiral sliding mode. Comprising the following steps: (1) constructing a mathematical model of a permanent magnet synchronous motor (PMSM); (2) on the basis of the mathematical model in the step (1), constructing a BP neural network PI controller which takes an expected value omega *, an actual value omega and an error e as inputs, takes a proportionality coefficient Kp and an integral coefficient Ki of the PI controller as outputs, and contains seven nodes in a hidden layer; the rotating speed ring continuously updates the weight value through the BP neural network so as to adjust the values of Kp and Ki in real time; (3) based on the mathematical model in the step (1), constructing an STA current loop controller for super-spiral sliding mode and feedforward decoupling control; and (4) PMSM control is realized based on the BP neural network PI controller in the step (2) and the STA current loop controller established in the step (3). The method has smaller overshoot and anti-interference capability, and has very positive significance for improving the control performance of the permanent magnet synchronous motor.

The invention discloses a self-adaptive energy-saving refrigeration constant-temperature control method and system, and the method comprises the steps: starting a refrigeration system, comparing the exhaust temperature of a compressor with the environment temperature, controlling the opening degree of a main valve according to the exhaust temperature, monitoring the real-time temperature of controlled equipment based on a preset PID program, adjusting the opening degree of an auxiliary valve after comparing the real-time temperature with a preset target temperature, and completing the control of the auxiliary valve; performing auxiliary valve self-adaptive energy-saving control in combination with the real-time temperature and the working frequency of the compressor, and starting a self-tuning mode: enabling the compressor, the main valve and the auxiliary valve to run in a preset mode, calculating a mean square error of the real-time temperature in a preset period, and if the error is smaller than a preset threshold value, updating a PID parameter to execute constant-temperature control in the next period; otherwise, the original PID program is kept for constant temperature control. According to the invention, the quick response after the refrigeration system is started is realized, and the parameter self-tuning control logic can obtain better control parameters so as to realize higher-precision control.

The invention discloses a valve positioner setting and control method based on a valve position stable value. The valve positioner setting and control method comprises a setting mode and a control mode, wherein the setting mode comprises setting of positioner characteristic parameters, PID parameter setting, actuator performance parameters and comprehensive control parameters. And the control mode adopts a subsection control method, and the control of the valve positioner based on the valve position stable value is realized by utilizing parameters set by the setting mode. According to the invention, overshoot in the control process can be effectively suppressed, and the control stability is maintained; and meanwhile, the regulation and control speed of the valve position can be increased in the rapid area.

The invention discloses an inertia and damping adaptive VSG control method based on neural network optimization. The method comprises the steps that S1, a VSG rotor motion equation is obtained through equivalent conversion; s2, introducing a speed regulator into the active power-frequency control loop to obtain a VSG reactive power-voltage control equation; s3, performing circuit model equivalence on the VSG grid-connected system to obtain an output active power equation, and obtaining a relation between inertia and damping; s4, analyzing power angle characteristics and angular frequency oscillation under a disturbance condition, and summarizing an inertia self-adaptive mechanism; and S5, establishing an artificial neural network, analyzing and predicting frequency and voltage changes of the power grid, and adjusting weight values to realize self-adaptive adjustment of inertia and damping. According to the inertia and damping adaptive VSG control method based on neural network optimization provided by the invention, the inertia and damping of the system can be cooperatively adjusted, the frequency is stabilized, the overshoot is reduced, and the method has faster response time in the aspect of recovering to a stable state.

The invention discloses a network construction type converter control method and device based on virtual excitation and terminal equipment, an internal potential amplitude is calculated according to a voltage effective value of a grid connection point and a preset voltage reference value by setting an internal potential amplitude generation model, and specifically, a plurality of PID control units are set in the internal potential amplitude generation model, and the internal potential amplitude is calculated according to the voltage effective value of the grid connection point and the preset voltage reference value. And the PID control unit is adopted, so that the response capability of the network-forming converter to disturbance can be effectively enhanced, and rapid adjustment of the internal potential is realized. Secondly, delaying an output result of the PID control unit through the inertia unit so as to maintain the stability of an internal potential amplitude, and then carrying out filtering compensation on the output result of the PID control unit through the correction unit. Therefore, the internal potential is adjusted through the internal potential amplitude generation model to maintain the network construction characteristic to the greatest extent, so that the voltage adjusting function of the converter is enhanced, the grid-connected point voltage level of the network construction converter is maintained, and meanwhile, good dynamic response performance is achieved after an external system is disturbed.

The invention discloses a double-ring segmented PID feedforward control charging method and system for an electromagnetic emission energy storage device, and the method specifically comprises the steps: firstly obtaining a current voltage set value, obtaining the charging voltage and charging current of an energy storage capacitor in real time, and calculating a voltage error; calculating a current error according to the voltage error, and calculating a control quantity according to the current error for charging; when the actual voltage reaches a voltage threshold value, a proportional controller coefficient of a voltage inner loop is reduced, trickle charging is carried out, feedforward estimation is adopted, a steady-state control quantity corresponding to a system when charging reaches a target value is used as an estimated value, and a final steady-state voltage is constrained; when the system detects that the capacitance voltage attenuation exceeds 2V, trickle charging is adopted to supplement the voltage; after an electromagnetic emission command is received, the system sends out a control pulse to conduct the silicon controlled rectifier, and the electromagnetic emission process is completed. The charging speed of the electromagnetic emission energy storage device in the middle and later periods of charging is increased, the charging efficiency is improved, overshoot is reduced, and the charging safety is improved.

The invention provides a virtual synchronization micro-grid adaptive secondary frequency modulation control method matched with load fluctuation, and the method comprises the steps: building an inverter island operation model based on VSG control, and generating a transfer function; determining stable operation conditions of the system according to the transfer function; and according to stable operation conditions of the system, optimizing values of a droop coefficient K [omega], a virtual inertia J, a virtual damping D, a proportionality coefficient Kp and an integral coefficient Ki according to change of a switching load by utilizing a discrete particle swarm algorithm, and controlling operation of the VSG. The droop coefficient K omega, the virtual damping D, the virtual inertia J, the proportionality coefficient Kp and the integral coefficient Ki in the secondary frequency modulation controller can be automatically adjusted according to the size of the switching load, and the problem that the system frequency exceeds the safe operation range in the adjusting process due to the fact that the switching load of the system is too large is solved.

The invention belongs to the technical field of aviation aircraft control, and particularly relates to a four-rotor unmanned aerial vehicle disturbance rejection control method based on model compensation, which comprises the following steps: S1, establishing a four-rotor unmanned aerial vehicle attitude dynamic model with unknown disturbance; s2, based on output feedback, designing a model compensation expansion state observer under a discrete time domain, and performing observation feedback on an attitude output signal and unknown disturbance; s3, designing an incremental model prediction controller according to the attitude dynamics model; the control method gives consideration to input limitation and input change rate limitation, can achieve a better effect with smaller control input, and can effectively reduce energy loss caused by frequent high-power maneuvering of the unmanned aerial vehicle. Compared with a traditional method for limiting input by adding a saturation function, the method achieves a better control effect with better input limitation. According to the control method, stable attitude control of the quad-rotor unmanned aerial vehicle in the discrete time domain can be realized under the condition of reasonably considering input constraints.

The invention discloses a PWM / PFM (Pulse Width Modulation / Pulse Frequency Modulation) self-detection switching method of a DC-DC converter based on a neural network and a control circuit, the working state quantity of the DC-DC converter under PWM and PFM control is collected, a neural network is utilized to train and fit a plurality of working conditions to generate a neural network controller, the working state of the converter is monitored in real time during actual control, and the PWM / PFM self-detection switching method of the DC-DC converter is realized. Therefore, the PWM duty ratio and the PFM frequency can be automatically switched and adjusted.

The invention relates to the technical field of sliding mode control, in particular to a double-sliding-mode sensorless control method based on a PMSMS, and the method comprises the steps: setting a terminal sliding mode surface function, optimizing the rotating speed through a nonlinear control item, and introducing a variable gain coefficient; a Sigmoid function is introduced in combination with an approaching law in the design of a speed controller; the terminal sliding mode controller takes the given speed and the estimated rotating speed error of the motorized spindle as the input and takes the q-axis current as the output; carrying out stability analysis on the speed ring controller; the sliding-mode observer takes an actual current value and an observer current error as input, takes the speed and position information of an electric spindle rotor as output, improves buffeting of a sliding-mode control law in combination with a Sigmoid function, and is integrated with a phase locking ring for extracting the position and speed of the rotor; and carrying out stability judgment on the design of the sliding-mode observer. The problems of overshoot, buffeting, slow response and the like of a control system in practical application of a traditional sensorless control scheme are solved.

The invention belongs to the related technical field of motor control, and discloses a flexible servo system mechanical resonance suppression method and suppression system based on quasi-resonance, and the method comprises the steps: carrying out the speed PID regulation and control of a motor actual rotating speed omega m (k) and a rotating speed instruction omega ref (k) at the kth moment, and obtaining a speed initial regulation and control value u0 (k); inputting q-axis current values iq (k) and omega m (k) at the kth moment into a discretized extended state observer, observing a rotating speed disturbance estimated value # imgabs0 # and compensating the rotating speed disturbance estimated value # imgabs0 # into u0 (k) to obtain u1 (k); discretized quasi-resonance processing is carried out based on the motor rotating speed errors at the (k-2) th moment and the kth moment, OutQR (k) is obtained and compensated to u1 (k), u2 (k) is obtained and input into a current loop, and vector control over the motor inverter bridge is achieved. By means of the method, mechanical resonance can be actively suppressed, meanwhile, system response overshoot is reduced, and the response speed is increased.

The invention relates to the technical field of electronic expansion valve control, and particularly discloses an electronic expansion valve control method based on a deep dynamic fuzzy neural network, and the method comprises the steps: obtaining the operation data of a heat pump unit; normalizing the operation data of the heat pump unit to obtain normalized operation data of the heat pump unit, and dividing the normalized operation data of the heat pump unit into a training set and a test set; constructing a deep dynamic fuzzy neural network model, and optimizing various parameters of the deep dynamic fuzzy neural network model by using a genetic algorithm and the data in the training set to obtain a trained deep dynamic fuzzy neural network model; and inputting data in the test set into the trained deep dynamic fuzzy neural network model for prediction so as to output an optimal control strategy of the electronic expansion valve. The deep dynamic fuzzy neural network model is used for effectively controlling the electronic expansion valve, so that the overshoot of the heat pump system is small, the response speed is high, and the operation performance of the system is improved.

The invention provides a driving planning method for a high-speed movement mechanism, which comprises the following steps of: planning a first driving stage and a second driving stage which are continuous from the maximum overshoot of inertial vibration and vibration duration; the first driving stage is a high-speed and high-acceleration motion driving stage; and the second driving stage is a dynamic low-speed and low-acceleration S-shaped curve driving stage. Rapid movement is still achieved in the first driving stage, and high efficiency of the movement process is guaranteed; by setting a certain gap, overshoot and continuous oscillation of a positioning target caused by high-speed large-inertia motion are avoided, and the positioning target is prevented from being impacted or damaged by a motion mechanism; according to the method, the positioning target is reached through the second driving stage, overshoot and inertial oscillation at the final target can be avoided, it can be guaranteed that the influence of high-speed motion inertial impact on the positioning precision is avoided, high-precision positioning is achieved, the whole positioning operation time is not prolonged, and high efficiency of the whole operation is guaranteed.

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to an unmanned aerial vehicle near obstacle control method based on a complex environment, and the method comprises the following steps: 1, obtaining a curve between obstacles through employing a binocular camera; 2, estimating the collision force of the obstacle according to the curve to obtain a {p, v} pair; 3, designing a gradient-based trajectory optimizer to extract information of an obstacle collided with the current trajectory; 4, numerical optimization is carried out; and 5, designing an MPC controller according to the obtained {p, v} pairs, and outputting an optimal control trajectory of the unmanned aerial vehicle near the obstacle based on the MPC controller. According to the invention, the obtained distance field information and height information are used to predict the performance of the unmanned aerial vehicle in a certain time period in the future so as to carry out optimization control, and the distance field, the height and the acceleration are constrained. And safe flight, very small overshoot, very small steady-state error and trajectory prediction of the unmanned aerial vehicle in near obstacle control are ensured.

The invention discloses a rotating speed control method of a permanent magnet synchronous motor. The method comprises the following steps: firstly, designing an adaptive switching expansion state observer of the permanent magnet synchronous motor, and adding the adaptive switching expansion state observer into a rotating speed loop control process; and then inputting the rotating speed of the permanent magnet synchronous motor and a q-axis current reference value output by a rotating speed ring into an extended state observer, performing adaptive parameter switching control at the same time, and outputting the rotating speed and an observed value of lumped disturbance after processing so as to continue to perform rotating speed ring control and realize rotating speed control of the permanent magnet synchronous motor. The method can improve the dynamic and steady state performance of the permanent magnet synchronous motor under inertia mismatch, weaken the overshoot of the motor in the dynamic process, greatly accelerate the response speed, reduce the rotation speed fluctuation and oscillation in the adjustment process, reduce the dependence of the parameter design of a motor control system on the rotational inertia parameter, and improve the stability of the motor control system. And meanwhile, the estimation capability of rapid change lumped disturbance is enhanced, and more complex lumped disturbance types can be dealt with.

The invention discloses a micro-flow fluid medium flow temperature control system, a temperature control method and an electrolytic bath, and the system is characterized in that a multi-stage temperature control strategy is adopted on a fluid medium circulation loop, and a cooling device and double heaters are combined; the plurality of temperature measuring devices are respectively arranged at the outlet of the cooling device, the outlets of the double heaters and the inlet of the heated component; the system further comprises a PID controller, the PID controller is connected with the cooling device, the double heaters and the multiple temperature measuring devices, the PID controller adjusts power output of the heaters, the heat dissipation power and the heating power of outlets of the heaters and inlets of the heated parts are balanced, and the debugging efficiency and the system stability are improved.

The invention provides an anti-interference control method for the concentration of a main reactant in a continuous stirring reaction kettle process, belongs to the technical field of chemical process control, and solves the problem that in the chemical process of producing cyclopentanol by catalyzing electrophilic water with cyclopentadienoic acid, the concentration of the main reactant is not influenced. The technical problem that the concentration of a main reactant is difficult to track a set value without steady-state errors under the conditions of fluctuation of feeding concentration, uncertainty and external disturbance of the continuous stirring reaction kettle is solved. According to the technical scheme, the method comprises the steps of constructing a model pre-estimation compensator and an anti-interference control structure, designing a four-dimensional decision model, carrying out parameter collaborative optimization by adopting a multi-target genetic optimization algorithm, and carrying out optimal solution selection based on a TOPSIS method. Under the condition of feed concentration fluctuation, the dynamic response speed and the anti-interference capability of the system can be remarkably improved, and faster adjustment time, smaller overshoot and stronger robustness can be realized in linear and nonlinear models.

The invention relates to a double-sliding-mode control method, device and system for a ship electric propulsion motor. The method comprises the following steps: acquiring a given rotating speed and an actual rotating speed of a permanent magnet synchronous motor; and based on the given rotating speed and the actual rotating speed of the permanent magnet synchronous motor, the ship electric propulsion motor is controlled through a pre-constructed double-sliding-mode control model. In order to solve the problems that a traditional current loop PI controller is sensitive to motor parameter changes and poor in robustness, a double-sliding-mode control strategy that sliding-mode control is adopted in a current inner loop on the basis that sliding-mode control is adopted in a rotating speed outer loop is provided, and meanwhile a variable exponential reaching law sliding-mode control algorithm is introduced to design a novel controller. And when the distance is far away from the sliding mode surface, the approaching speed is increased, and when the distance is close to the sliding mode surface, the switching band of the system is reduced. According to the method, a discontinuous sign function is replaced by a continuous and smooth hyperbolic tangent function, so that the overshoot of the system is reduced, the buffeting of the system is also reduced, and the response speed and robustness of the system are enhanced.

The invention discloses a method for controlling the spraying speed of a greening wet spraying machine, which belongs to the technical field of PID control optimization. The specific steps are as follows: step one, constructing a control system model of the greening wet spraying machine; step two, improving the mathematical model of the aurora optimization algorithm, and the specific improvement strategies are as follows: D1, using an adaptive scaling Levy flight strategy to improve the mathematical model of the aurora elliptical complex variant Ao in the aurora optimization algorithm; D2, using a transition perturbation strategy to improve the mathematical model of the particle collision stage of the aurora optimization algorithm; step three, using the improved aurora optimization algorithm to optimize the PID controller parameters of the control system model of the greening wet spraying machine, and obtaining the optimal three parameters of Kp, Ki, and Kd; step four, using the optimal three parameters of Kp, Ki, and Kd obtained in step three for the spraying speed control of the greening wet spraying machine, and optimizing the control effect of the spraying speed of the greening wet spraying machine.

The invention discloses a plasma activated water preparation system based on fuzzy PID (Proportion Integration Differentiation) adaptive temperature and power matching cooperative control. The plasma activated water preparation system comprises a human-computer interface, a main controller, a temperature / power sensor, a parallel double fuzzy PID controller, an intelligent coordinator, a power / temperature actuator and a plasma reaction machine, a temperature / power sensor sends a water body temperature Tfb and a discharge power Pfb to a main controller in real time, a temperature fuzzy PID controller and a power fuzzy PID controller output suggested powers Ut and Up, an intelligent coordinator outputs a final power instruction and a cooling control signal after arbitration according to a state machine that Tfb is smaller than or equal to Tset normal power, Tfb is larger than Tset and Pfb is larger than Pmin and power is preferentially reduced, and Tfb is larger than Tset and Pfb is smaller than or equal to Pmin and is forcibly cooled. And the power actuator continuously adjusts the discharge power according to the discharge power, and the temperature actuator implements auxiliary heat dissipation, so that the water temperature is accurately locked in the optimal active matter generation interval under the nonlinear and time-varying working conditions, the discharge intensity is ensured not to be lower than Pmin, and high-activity, high-energy-efficiency, continuous and stable plasma activated water preparation is realized.

The invention provides a prediction control method based on improved locust optimization, and relates to the technical field of data processing and control engineering, and the method comprises the steps: carrying out the parameter identification of a mass regulation channel of a heat exchange station system through employing a recursive least square method with a forgetting factor, and building a controlled autoregressive moving average integral model; based on the controlled autoregressive moving average integral model, generating a prediction output through implicit generalized prediction control and constructing a target function, the implicit generalized prediction control directly identifying a prediction matrix and a prediction vector; when the control quantity increment exceeds a preset constraint range, an improved locust optimization algorithm is adopted to optimize the target function, the improved locust optimization algorithm is combined with a double-differential evolution strategy and a reverse learning mechanism, the double-differential evolution strategy updates the locust position through differential variation, and the locust position is updated through differential variation; the variant basis vector is based on the current optimal location and the random individual location.

The present invention relates to a fractional-order PI control method for a fractional-order dual-active bridge converter, specifically, according to the system parameters of the fractional-order dual-active bridge converter, the fractional-order transfer function from control to output of the fractional-order dual-active bridge converter is calculated; according to the fractional-order transfer function, the open-loop transfer function of the fractional-order dual-active bridge converter control system is determined; according to the open-loop transfer function, the minimum objective function of the parameters to be optimized of the fractional-order PI controller is designed; according to the minimum objective function, the control parameters of the fractional-order PI controller are optimized using a genetic algorithm. The present invention guides the parameter design of the optimal fractional-order PI controller of the fractional-order dual-active bridge converter based on the fractional-order model of the dual-active bridge converter and the expected effect, so as to obtain the optimal performance of the system, so that the system has a faster response speed, a smaller overshoot, a stronger anti-disturbance ability, and better control quality.

The present invention discloses a fuzzy control method for the cooling capacity of a liquid cooling unit, a liquid cooling unit and an energy storage system, and relates to the technical field of refrigeration equipment control methods, which includes taking the temperature control error e of the liquid cooling unit as an input quantity, and taking at least one controllable parameter of the liquid cooling unit as a control quantity, to establish a fuzzy control system; the fuzzy control system controls at least one controllable parameter in the liquid cooling unit according to the temperature control error e, so as to reduce the temperature control error e. The present invention mainly solves the problem that traditional automatic control theory is difficult to bring good control effects to liquid cooling units; compared with traditional temperature control systems, the present invention has the characteristics of short response time, small overshoot, high steady-state accuracy, rapid recovery to steady state when encountering interference, and good dynamic and static performance. At the same time, it also has strong adaptability to the inertial lag temperature link, thereby bringing better temperature control effects to the energy storage system.

The invention provides a PI controller parameter optimization method, a PI controller and a grid-connected inverter, and the method comprises the steps: firstly, determining an allowable range of a current loop bandwidth, taking the value range of controller parameters as a constraint, and taking the minimum overshoot, the highest response speed and the minimum reactive current change as targets; and parameters of the current loop dynamic performance model are optimized according to a simple gradient method. According to the method, high accuracy can be achieved through less test data through the current loop dynamic performance model, the relation between controller parameters and output variables can be accurately reflected, a reliable basis is provided for parameter optimization, the parameter optimization process is more efficient due to application of the simple gradient algorithm, and the method is suitable for large-scale popularization and application. The optimal solution can be found in a short time, the optimized controller can achieve the good decoupling performance of a current loop, and especially when the active current changes greatly, the optimized controller can remarkably reduce the change of the reactive current, so that the dynamic performance of the system is improved.