CN119342650B - Dual control loop charge management method and system - Google Patents
Dual control loop charge management method and system Download PDFInfo
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Abstract
The present invention relates to the field of charge management technologies, and in particular, to a method and a system for dual control loop charge management. The method comprises the steps of establishing a nonlinear charge-discharge mathematical model, designing a model prediction controller, feeding back the charge management system output at the current moment and the control input at the previous moment into the model prediction controller through the charge management system output at the current moment, constructing an objective function, calculating an optimal control quantity according to constraint conditions of the objective function and ultraviolet lamplight power to be used as reference optical power of a mixed gain fuzzy PID controller, adjusting the optical power of an ultraviolet lamp through the mixed gain fuzzy PID controller of an inner ring to be matched with the reference optical power, measuring actual output optical power by using an optical power meter and using the actual output optical power as a feedback signal of the model prediction controller, using the actual output optical power as a control input, updating the current state of the system, and using the updated current state as input of next prediction to form closed loop control. The ultraviolet light transmission device has the advantages of accurate control and stable transmission of ultraviolet light.
Description
Technical Field
The present invention relates to the field of charge management technologies, and in particular, to a method and a system for dual control loop charge management.
Background
Charge management techniques are an extremely important ring in space gravitational wave detection tasks. The basic principle of space gravitational wave detection is to detect gravitational waves by using a laser interferometer to detect the relative position change of the test mass in two satellites far apart. The high-energy particles widely existing in the space bombard the spacecraft and accumulate on the surface of the test quality through direct or indirect charging effect. This can cause additional coupling of the test mass to the surrounding frame structure, affecting the gravitational wave detection accuracy. Therefore, a charge management system is needed to ensure the stability of the residual charge quantity on the surface of the test mass, and the coulomb force generated by the action of the accumulated charge on the test mass and the conductor and the lorentz force generated by the coupling of the charge and the magnetic field are eliminated. Most research teams currently use a charge-discharge method using ultraviolet lamps to irradiate sensitive structures, and the basic principle of the charge-discharge method is shown in fig. 1. When ultraviolet light irradiates the surface of the test mass, if the energy of photons exceeds the work function of the metal, free electrons in the metal absorb the energy of photons and escape as photoelectrons leaving the test mass. In order to enable the test mass to emit charge under irradiation by an ultraviolet lamp, it is necessary to irradiate the test mass surface with high energy (short wavelength) light.
The current charge management discharge method can be classified into a direct current discharge method and an alternating current discharge method according to the discharge principle. The direct current discharge method is to continuously irradiate the surface of the test quality by using a direct current driven ultraviolet light source. The charge or discharge of the test quality is realized by controlling the polarity and the magnitude of the bias voltage between the test quality and the electrode cage. The alternating current discharge method no longer controls the test quality and the bias voltage between the electrode cages, but directly drives the ultraviolet lamp through alternating current. The discharge method can not additionally introduce bias voltage signals, and can realize more complex discharge strategies.
According to the difference of the current magnitude and the irradiation time for driving the ultraviolet lamp, the charge management can also be carried out by using a continuous discharge and rapid discharge method. The test quality is continuously charged and discharged by using the ultraviolet lamp with small current and low power output, or is rapidly charged and discharged by using the ultraviolet lamp with large current and high power output.
The existing charge management method has no feedback loop in the implementation process, namely, the open-loop control method is directly used for charging and discharging the test mass, the surface potential of the test mass cannot be regulated and controlled in real time, the photoelectric characteristics inside the inertial sensor are highly dependent for accurately calibrating, and the surface potential of the test mass cannot be regulated and controlled to a specified level rapidly and accurately. There is a need for a charge management system with closed loop control that can regulate the test mass and relative electrode cage surface potential to a specified level for subsequent additional investigation.
Disclosure of Invention
The present invention is directed to a dual control loop charge management method and system for solving the above-mentioned problems.
The first object of the present invention is to provide a dual control loop charge management method, which specifically includes the following steps:
s1, establishing a nonlinear charge management system charge-discharge mathematical model;
s2, designing a model predictive controller based on a nonlinear charge management system charge-discharge mathematical model;
S3, the model prediction controller feeds back the charge management system output at the current moment and the charge management system control input at the previous moment into the model prediction controller through the charge management system output at the current moment to obtain a future system output sequence;
S4, constructing an objective function, and calculating an optimal control quantity according to constraint conditions of the objective function and ultraviolet lamplight power;
s5, taking the solved optimal control quantity as a current control input, wherein the control input is used as the reference light power of the mixed gain fuzzy PID controller;
S6, measuring the actual output light power of the ultraviolet lamp by using a light power meter, and taking the actual output light power as a feedback signal of a model predictive controller;
S7, the actual output light power of the ultraviolet lamp is used as a control input to update the current state of the charge management system, and the updated state is used as the input of the next prediction to form closed loop control.
Preferably, the step S1 specifically includes the following sub-steps:
S101, obtaining test quality and the number of photoelectrons escaping from an electrode cage under different optical powers through a simulation experiment, and fitting by using a linear function;
S102, regarding the electrode cage as a reference ground, setting the potential to be 0V, fitting and irradiating the test quality, ultraviolet lamplight power of the electrode cage and bias voltage of the potential carried by the surface of the test quality and the potential carried by the surface of the electrode cage by using a converted Sigmoid function, and establishing a nonlinear charge management system charge-discharge mathematical model.
Preferably, in the step S102, the transformed Sigmoid function includes a transformed Sigmoid function when irradiating the test mass and a transformed Sigmoid function when irradiating the electrode cage;
The transformed Sigmoid function when the test quality is illuminated is:
;
The transform Sigmoid function at the time of illuminating the electrode cage is:
;
In the formula, Representing the optical power of the uv lamp illuminating the test mass,Representing the optical power of an ultraviolet lamp illuminating the electrode cage; Representing the number of photoelectrons escaping from the test mass surface upon irradiation of the test mass, Representing the number of photoelectrons escaping from the surface of the electrode cage when the electrode cage is irradiated; a bias voltage representing the potential carried by the surface of the test mass and the potential carried by the surface of the electrode cage; Is that Is mapped to;
the relation between the optical power and the number of photoelectrons escaping per second when the test quality is irradiated is as follows:
;
the relation between the optical power and the number of photoelectrons escaping per second when the electrode cage is irradiated is as follows:
;
the expression of (2) is as follows:
;
In the formula, In order to test the electrical potential carried by the quality surface,The electric potential carried by the surface of the electrode cage;
the expression of (2) is as follows:
。
preferably, step S1 further comprises a substep S103 of rewriting the nonlinear charge management system charge-discharge mathematical model to the following equation, taking into account the external charge accumulation rate:
;
In the formula, Representing the transformed Sigmoid function when the test quality is illuminated,Representing the transformed Sigmoid function when the electrode cage is illuminated,Representing external charge accumulation noise.
Preferably, the hybrid gain fuzzy PID controller is expressed as:
;
In the formula, The gain P m、Im、Dm of the mixed gain fuzzy PID controller is expressed as follows:
;
In the formula, fuzzy PID The gain output is of the magnitude ofThe fuzzy logic controller will depend on the error magnitudeAnd error rate of changeOutput ofThe regulation formula is as follows:
;
gain factor of the magnitude of ,The size of (2) is determined by the following formula:
;
In the formula, As the difference between the current optical power and the target optical power level,Is a preset threshold.
Preferably, the expression of the objective function is as follows:
;
Wherein k represents a control step, Represents the reference potential of the sample,Controlling a prediction step length for model prediction;
The constraint conditions are as follows: ;
;
wherein, Representing the predicted potential at time k + i +1 calculated at time k, s.t. representing the constraint,Representing a unit time, k representing a control step,Representing the actual potential of the sample,Represents the reference potential of the sample,Representing the amount of residual charge at time k,Representing the charge constant of the sample,Representing the test mass and the amount of capacitance between the electrode cages,The prediction step size is controlled for model prediction,、Representing the minimum and maximum optical powers that can be output when the test mass is illuminated,、Representing the minimum and maximum optical powers that can be output when the electrode cage is illuminated,Representing external charge accumulation noise.
Preferably, the ultraviolet lamp is an AlGaN-based ultraviolet lamp, and the rated wavelength is 250-260 nm.
The second object of the invention is to provide a dual control loop charge management system, comprising a model predictive controller, a mixed gain fuzzy PID controller, an ultraviolet lamp and an optical power meter;
The inner loop precisely controls the optical power of the ultraviolet lamp through the mixed gain fuzzy PID controller to ensure that the ultraviolet lamp is stably output and realize quantitative control of the surface potential of the test quality;
The outer ring monitors and feeds back the charge through the model prediction controller, predicts and optimizes the charge management system by using the feedback signal, updates the state of the charge management system, and the updated state is used as the input of the next prediction to form a feedback loop.
Compared with the prior art, the invention has the following beneficial effects:
The invention establishes a nonlinear model for testing the charge and discharge of the mass, the model has higher precision and can reflect the charge and discharge process of the mass, and designs a double-control loop charge management method which introduces a closed loop feedback link and can accurately adjust the surface potential of the mass in the inertial sensor. The outer ring is introduced with a charge control link based on model predictive control, monitors and feeds back charges, predicts and optimizes the system behavior of charge management, realizes quantitative control of the surface potential of the test quality by precisely regulating and controlling an ultraviolet light source system, and precisely controls the optical power of the UV LED based on a mixed gain fuzzy PID control method based on the characteristics of high response speed and good dynamic performance of the UV LED, so that the UV LED stably outputs given optical power. And the UV LED has good stability at low power output and responds to the system requirement in time. And the stable output state of the UV LEDs of the core executive component of the charge management system is ensured by using the control inner ring, and the reliable transmission of ultraviolet light is ensured.
Drawings
Fig. 1 is a schematic diagram of a charge-discharge method using an ultraviolet lamp (UV LED) to irradiate a sensitive structure.
Fig. 2 is a technical roadmap of a dual control loop charge management method provided in accordance with an embodiment of the invention.
FIG. 3 is a graph showing the result of the change in the number of photoelectrons escaping collected when the test quality is irradiated under different bias voltages at 1-60 nW optical power according to the embodiment of the present invention.
FIG. 4 is a graph showing the result of the change in the number of photoelectrons escaping collected when the electrode cage is irradiated under different bias voltages at 1-60 nW optical power according to the embodiment of the present invention.
FIG. 5 is a graph showing the change in the number of photoelectrons emitted from a test mass irradiated with different light powers, -2.5V bias voltages according to an embodiment of the present invention.
FIG. 6 is a graph showing the result of the change in the number of photoelectrons escaping collected when the electrode cage is irradiated under different light powers, -2.5V bias voltages, according to an embodiment of the present invention.
Fig. 7 is a function fit of illumination test quality provided in accordance with an embodiment of the present invention.
FIG. 8 is a functional fit of an illuminated electrode cage provided in accordance with an embodiment of the present invention.
Fig. 9 is a block diagram of a model predictive controller provided in accordance with an embodiment of the invention.
Fig. 10 is a control block diagram of a hybrid gain fuzzy PID controller provided according to an embodiment of the present invention.
FIG. 11 is a schematic diagram of the performance of a hybrid gain fuzzy PID controller provided according to an embodiment of the invention.
FIG. 12 is a graph showing the actual potential change of a test mass surface at +20e/s, provided in accordance with an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the following description, like modules are denoted by like reference numerals. In the case of the same reference numerals, their names and functions are also the same. Therefore, a detailed description thereof will not be repeated.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not to be construed as limiting the invention.
The invention provides a charge management method of a double control loop, which is shown in a technical route chart as shown in fig. 2 and specifically comprises the following steps:
S1, establishing a nonlinear charge management system charge-discharge mathematical model, obtaining the mathematical model by an inertial sensor charge-discharge method based on an ultraviolet light charge management technology designed in advance, and specifically comprising the following sub-steps:
S101, obtaining test quality and the number of photoelectrons escaping from an electrode cage under different optical powers through a simulation experiment, and fitting by using a linear function;
the simulation experiment specifically comprises the steps of simulating the application of different bias voltages to an electrode cage, using 1-60 nW optical power to irradiate the test quality and the number of photoelectrons escaping collected when the electrode cage is shown in fig. 3 and 4, and fitting by using the relation between the optical power and the number of photoelectrons at 0V to obtain the relation between the optical power and the number of photoelectrons escaping per second when the test quality is irradiated, wherein the relation is as follows:
;
In the formula, Indicating the number of photoelectrons escaping when the test mass is irradiated,Indicating the optical power of the ultraviolet lamp irradiating the test quality;
the relation between the optical power and the number of photoelectrons escaping per second when the electrode cage is irradiated is as follows:
;
In the formula, Indicating the number of photoelectrons escaping when the electrode cage is irradiated; indicating the optical power of the ultraviolet lamp illuminating the electrode cage;
To evaluate the fit effect, the decision coefficients are used And evaluating the fitting effect with respect to the root mean square error RELATIVE RMSE, the calculation formula being:
;
The results obtained by calculation are shown in Table 1;
TABLE 1 evaluation index of fitting effect of optical power and number relation of escaped photoelectrons
AndIs the coefficient of determination of (2)All approach 1, and the fitting effect is quite excellent.
The magnitude of the bias voltage between the test mass and the electrode cage in addition to the magnitude of the optical power, which affects the amount of photoelectrons escaping per second of the test mass.
S102, regarding the electrode cage as a reference ground, setting the potential to be 0V, fitting and irradiating the test quality, the ultraviolet lamplight power of the electrode cage and the bias voltage of the potential carried by the surface of the test quality and the potential carried by the surface of the electrode cage by using a converted Sigmoid function;
The transformed Sigmoid function when the test quality is illuminated is:
;
The transform Sigmoid function at the time of illuminating the electrode cage is:
;
In the formula, Representing the optical power of the uv lamp illuminating the test mass,Representing the optical power of an ultraviolet lamp illuminating the electrode cage; Representing the number of photoelectrons escaping from the surface of the test mass upon irradiation of the test mass, and Representing the number of photoelectrons escaping from the surface of the electrode cage when the electrode cage is irradiated; The bias (i.e., potential difference) representing the potential carried by the surface of the test mass and the potential carried by the surface of the electrode cage is expressed as follows:
;
In the formula, In order to test the electrical potential carried by the quality surface,The electric potential carried by the surface of the electrode cage;
Order the The size of (2) is from-2.5V to 2.5V, -2.5V to 2.5V is mapped to 0 to 1000, and the following formula is obtained:
。
Based on the designed model, the light power output of the ultraviolet lamp is respectively set as follows The test quality and the number of photoelectrons escaping per second from the electrode cage under different optical powers are obtained, as shown in fig. 5 and 6.
Brief description of the principles according to the test results of University of Trento David DAL Bosco, the maximum kinetic energy of photoelectrons escaping from the surface of the test mass was 0.98eV. I.e. whenThe test quality only undergoes a discharge process whenWhen the test quality is only charged, the influence of the factors on the charge management system is considered, and in order to build a complete test quality charge-discharge mathematical model, the charge-discharge mathematical model is set up byFrom-2.5V to 2.5V.
The conventional Sigmoid function isThe transformed Sigmoid function form used fits the optical power and bias as follows:
;
Wherein P is Or (b),Representing the optical power of the uv lamp illuminating the test mass,Represents the light power of an ultraviolet lamp irradiating the electrode cage, and n isOr (b),Representing the number of photoelectrons escaping from the test mass surface upon irradiation of the test mass,Representing the number of photoelectrons escaping from the surface of the electrode cage when the electrode cage is irradiated; And The coefficients obtained by fitting are respectively referred to as fitting,Is a natural constant which is a function of the natural constant,Is a correction term.
Meanwhile, in order to facilitate fitting, the value of the abscissa in simulation is mapped from-2.5V to 0 to 1000, and the mapping relation is as follows:
;
Fitting to obtain a result, wherein the conversion Sigmoid function when the test quality is irradiated is as follows:
;
The transform Sigmoid function at the time of illuminating the electrode cage is:
;
the obtained function fitting diagrams are shown in fig. 7 and 8.
Using decision coefficientsAnd the relative root mean square error RELATIVE RMSE to evaluate the fit effect, the results are shown in table 2.
TABLE 2 bias voltageFitting effect evaluation index in relation to number of escaped photoelectrons
By fitting the simulation model data, a correlation is obtainedAndAnd the nonlinear function of the number of photoelectrons escaping from the surface of the test quality can be used for finding out that the fitting effect is better through an evaluation index.
S103, under the condition of considering the external charge accumulation rate, the nonlinear charge management system charge and discharge mathematical model is rewritten as the following formula:
;
In the formula, Representing the transformed Sigmoid function when the test quality is illuminated,Representing the transformed Sigmoid function when the electrode cage is illuminated,Representing external charge accumulation noise.
S2, designing a Model Predictive Controller (MPC) based on a nonlinear charge management system charge-discharge mathematical model, wherein the established model predictive controller is shown in a block diagram of FIG. 9.
S3, the model prediction controller feeds back the charge management system output at the current moment and the charge management system control input at the previous moment into the model prediction controller through the charge management system output at the current moment, and a future system output sequence is obtained.
S4, constructing an objective function, and calculating an optimal control quantity according to constraint conditions of the objective function and ultraviolet lamplight power;
The expression of the objective function is as follows: ;
Wherein k represents a control step, Represents the reference potential of the sample,Controlling a prediction step length for model prediction;
The constraint conditions are as follows: ;
In the above-mentioned method, the step of, Representing the predicted potential at time k + i +1 calculated at time k, s.t. representing the constraint (abbreviation of subject to),Representing a unit time, k representing a control step,Representing the actual potential of the sample,Represents the reference potential of the sample,Representing the amount of residual charge at time k,Representing the charge constant of the sample,Representing the test mass and the amount of capacitance between the electrode cages,The prediction step size is controlled for model prediction,、Representing the minimum and maximum optical powers that can be output when the test mass is illuminated,、Representing the minimum and maximum optical powers that can be output when the electrode cage is illuminated,Representing external charge accumulation noise.
S5, taking the solved optimal control quantity as a current control input, wherein the control input is used as the reference light power of the mixed gain fuzzy PID controller, and adjusting the light power of the ultraviolet lamp through the mixed gain fuzzy PID controller of the inner ring to enable the light power of the ultraviolet lamp to be matched with the reference light power.
S6, measuring the actual output light power of the ultraviolet lamp by using a light power meter, and taking the actual output light power as a feedback signal of a model predictive controller.
S7, the actual output light power of the ultraviolet lamp is used as a control input to update the current state of the charge management system, and the updated state is used as the input of the next prediction to form closed loop control.
Specifically, in the optimization solving process of the model predictive controller, the optimization problem is defined as being in the prediction time domain in each control step kThe difference between the reference potential and the actual potential is minimized and the dynamic equations of the system and the input constraints need to be satisfied simultaneously.
The specific optimization problem is as follows:
In the formula, Representing a unit time, k representing a control step,Representing the actual potential of the sample,Represents the reference potential of the sample,Representing the amount of residual charge at time k,Representing the charge constant of the sample,Representing the test mass and the amount of capacitance between the electrode cages,The prediction step size is controlled for model prediction,、、、Representing the test quality of the illumination, the minimum and maximum optical power that can be output when the electrode cage is illuminated,Representing external charge accumulation noise.
Specifically, the ultraviolet lamp selects UVTOP-HL-TO 39 series UV LEDs with AlGaN base. Since the test quality surface is plated with gold-platinum alloy, its surface work function is about 3.9eV after being contaminated with hydrocarbons in air. Through calculation, the wavelength of the ultraviolet lamp is less than 270nm to enable the surface to generate photoelectric effect and escape photoelectrons. The maximum working current of the ultraviolet lamp of the model is 20mA, the rated wavelength is 255nm, and the use requirement of a charge management system can be met. At present, the research of AlGaN-based UV LEDs in various circles is still in a starting stage, and the rated luminous efficiency is only that of the LED due to the element characteristicsThis also highlights the necessity of high precision modeling and control exertion of UV LEDs during their application.
The low power photo-electric thermal model of an AlGaN-based UV LED can be represented by the following formula:
;
Wherein P v represents the actual light power of the ultraviolet lamp, c is a correction constant, b and d are introduced constant correction terms for correcting the difference between the calibration working point and the actual working point; as a thermal characteristic coefficient, a linear coefficient representing a decrease in luminous efficiency of the UV LED with an increase in temperature during the period; representing the measured temperature of the UV LED; Where k is a Boltzmann constant, n is a constant, T is a thermodynamic temperature, q is an electron charge amount, Is the reverse saturation current, i is the present input current magnitude.
Specifically, the hybrid gain fuzzy PID controller is described as:
;
In the formula, The gain P m、Im、Dm of the mixed gain fuzzy PID controller is expressed as follows:
;
In the formula, fuzzy PID The gain output is of the magnitude ofThe fuzzy logic controller will depend on the error magnitudeAnd error rate of changeOutput ofThe regulation formula is as follows:
;
gain factor of the magnitude of ,The size of (2) is determined by the following formula:
;
In the formula, As the difference between the current optical power and the target optical power level,Is a preset threshold.
Brief description of the principles control output of a fuzzy PID controllerThe basic calculation formula of (2) is:
;
In the formula, Representing the current error value, representing the difference between the target value and the actual value; is the integral value of the error, representing the accumulation of the error; Is the differentiation of the error, which reflects the change speed of the error, P, I, D is the gain of three adjusting links of proportion, integral and differentiation.
With fuzzy PIDThe gain output is of the magnitude ofThe fuzzy logic controller will depend on the error magnitudeAnd error rate of changeOutput ofThe regulation formula is as follows:
;
In charge control of the double-control closed loop, the inner loop needs to be controlled to have good dynamic performance, the optical power output by the model predictive controller is tracked in time, and high optical power tracking precision is maintained after the final state is reached. Based on the above requirements, the method of introducing the mixed gain factor to improve the controller based on the fuzzy PID controller is characterized in that the magnitude of the mixed gain fuzzy PID gain is determined by the following formula:
;
The mixed gain fuzzy PID gain number used in the invention is based on the error magnitude to carry out the condition, and the gain factor is assumed to be the magnitude ,The size of (2) is determined by the following formula:
;
In the formula, As the difference between the current optical power and the target optical power level,Is a preset threshold.
Thus, the controller described above can be described as:
。
FIG. 10 is a block diagram of a hybrid gain fuzzy PID controller For a given optical power of the light,For the actual output optical power, I is the controller given current. In the mixed gain fuzzy PID, the input of the controller is the optimized data result obtained by the outer loop model predictive controller. The controller calculates the errors and the error change rates of the reference light power and the actual light power at the current moment and inputs the errors and the error change rates into the fuzzy rule reasoning system. Reasoning to obtain output result of fuzzy PID controller. And mix it with the gain coefficientAnd mixing and calculating to obtain final output gains P, I and D. The controller has better dynamic performance in the adjusting stage and better steady-state performance in the stabilizer.
A corresponding hybrid gain fuzzy PID controller was built in MATLAB. Assuming that the uv light source system is subjected to thermal management techniques, its shell temperature may be maintained at 25 ℃. The current is output by a current source approximated as a first order inertial unit, the specific parameters are calibrated experimentally, and the controller performance is shown in fig. 11.
Through simulation, the used mixed gain PID can obtain better control effect and output stable ultraviolet lamplight power signals.
The invention provides a double-control loop charge management system, which comprises a model prediction controller, a mixed gain fuzzy PID controller, an ultraviolet lamp and an optical power meter, wherein the model prediction controller is used for predicting the charge of a light source;
The inner loop precisely controls the optical power of the ultraviolet lamp through the mixed gain fuzzy PID controller to ensure that the ultraviolet lamp stably outputs and realizes quantitative control on the surface potential of the test quality;
The outer ring monitors and feeds back the charge through the model prediction controller, predicts and optimizes the charge management system by using the feedback signal, updates the state of the charge management system, and the updated state is used as the input of the next prediction to form a feedback loop.
Application example:
to verify the performance of the designed dual control loop charge controller, the charge management system under normal operating conditions was simulated assuming that the charge accumulation rate of the charge management system remained stable. The whole simulation process comprises a potential rising period and a potential falling period, and the charging performance and the discharging performance of the designed double-control loop charge controller are respectively tested. The set reference potential U is-0.08V, and the single charge and discharge time is 100s. A designated potential of 0V represents complete removal of charge accumulated on the surface of the test mass; representing a residual charge just less than that of 34.2pF when the test mass and the capacitance between the electrode cages were equal in magnitude The potential at that time; A specified potential of 0.08V is the ability of the test charge control technique to output the specified potential. The above potential selections verify that the dual control loop charge management method maintains the test mass residual charge at 0 The ability to track a given potential, while the residual charge remains around 10 7 e. The potential rises by 0.04V in each cycle of 100s to 400s and drops by 0.04V in each cycle of 500 to 900 s. Furthermore, according to literature, the shot noise one-sided spectral density of particle charging in a real model is set toThe charge measurement noise is。
Simulation was performed according to the above parameter simulation setup, as shown in FIG. 12, which shows the dynamic performance of the dual control loop charge manager while tracking-0.08V, -0.04V, 0V, 0.04V, 0.08V potentials. It can be seen that in the normal working state, the designed double-control loop charge controller can well track the reference potential and has higher output stability.
In the process of tracking reference potential by a charge management system, firstly, acquiring the system output of a nonlinear mathematical model based on a test quality charge-discharge simulation model at the current moment, feeding back the system output and the control input at the previous moment into a test quality charge-discharge prediction model to obtain a future system output sequence, then calculating the optimal control quantity through a constructed objective function and constraint conditions on ultraviolet lamplight power, and utilizing the input quantity of the first step as the control input of the next step to control the charge-discharge of the test quality. In addition, due to factors such as interference errors and the like existing in the outside, after the residual potential of the surface of the test quality is obtained by obtaining the test quality charge-discharge simulation model added with noise, the residual potential value is used as the current state of the system, and the next optimal input calculation is carried out.
The invention utilizes the established charge management charge-discharge simulation model based on ultraviolet discharge to fit a set of nonlinear dynamic model conforming to the charge-discharge rule of test quality. On this basis, the model predictive controller will calculate the target error from the set reference potential and construct an optimization problem to minimize this error and the variation of the control input, solving the optimal control input using an optimization function. And selecting a first control input from a control input sequence obtained by solving, taking the first control input as the reference light power of the mixed gain fuzzy PID, controlling the light power of the UV LEDs through the mixed gain fuzzy PID of the inner ring, finally reading out the actual light power of the UV LEDs through a light power meter, and taking the actual light power output by the UV LEDs as the control input of the charge management charge-discharge simulation model based on ultraviolet discharge, thereby updating the state of the system. This updated state will be used as input for the next prediction, forming a feedback loop. This process is continued for each time step, ensuring that the system state is always close to the target value in a dynamic environment.
In summary, the control accuracy of the surface potential of the test quality is improved, the stability of the surface potential of the test quality is maintained, and the test requirement of the specified relative potential is output based on the closed-loop control requirement of the charge management system. Firstly, a nonlinear model of charge and discharge of the test mass is established by a charge and discharge simulation method of the test mass based on an ultraviolet light charge management technology designed in the prior stage, and a double control loop charge management method is designed, and aims to introduce a closed loop feedback link and accurately adjust the surface potential of the test mass in an inertial sensor. The outer ring is introduced with a charge control link based on model predictive control, monitors and feeds back charges, predicts and optimizes the system behavior of charge management, realizes quantitative control of the surface potential of the test quality by precisely regulating and controlling an ultraviolet light source system, and precisely controls the optical power of the UV LED based on a mixed gain fuzzy PID control method based on the characteristics of high response speed and good dynamic performance of the UV LED, so that the UV LED stably outputs given optical power. And the UV LED has good stability at low power output and responds to the system requirement in time. And the stable output state of the UV LEDs of the core executive component of the charge management system is ensured by using the control inner ring, and the reliable transmission of ultraviolet light is ensured.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (8)
1. The double control loop charge management method is characterized by comprising the following steps:
s1, establishing a nonlinear charge management system charge-discharge mathematical model;
s2, designing a model predictive controller based on a nonlinear charge management system charge-discharge mathematical model;
S3, the model prediction controller feeds back the charge management system output at the current moment and the charge management system control input at the previous moment into the model prediction controller through the charge management system output at the current moment to obtain a future system output sequence;
S4, constructing an objective function, and calculating an optimal control quantity according to constraint conditions of the objective function and ultraviolet lamplight power;
s5, taking the solved optimal control quantity as a current control input, wherein the control input is used as the reference light power of the mixed gain fuzzy PID controller;
S6, measuring the actual output light power of the ultraviolet lamp by using a light power meter, and taking the actual output light power as a feedback signal of a model predictive controller;
S7, the actual output light power of the ultraviolet lamp is used as a control input to update the current state of the charge management system, and the updated state is used as the input of the next prediction to form closed loop control.
2. The method for dual control loop charge management as set forth in claim 1, wherein said step S1 comprises the following sub-steps:
S101, obtaining test quality and the number of photoelectrons escaping from an electrode cage under different optical powers through a simulation experiment, and fitting by using a linear function;
S102, regarding the electrode cage as a reference ground, setting the potential to be 0V, fitting and irradiating the test quality, ultraviolet lamplight power of the electrode cage and bias voltage of the potential carried by the surface of the test quality and the potential carried by the surface of the electrode cage by using a converted Sigmoid function, and establishing a nonlinear charge management system charge-discharge mathematical model.
3. The method according to claim 2, wherein in the step S102, the transformed Sigmoid function includes a transformed Sigmoid function when irradiating the test mass and a transformed Sigmoid function when irradiating the electrode cage;
The transformed Sigmoid function when the test quality is illuminated is:
;
The transform Sigmoid function at the time of illuminating the electrode cage is:
;
In the formula, Representing the optical power of the uv lamp illuminating the test mass,Representing the optical power of an ultraviolet lamp illuminating the electrode cage; Representing the number of photoelectrons escaping from the test mass surface upon irradiation of the test mass, Representing the number of photoelectrons escaping from the surface of the electrode cage when the electrode cage is irradiated; a bias voltage representing the potential carried by the surface of the test mass and the potential carried by the surface of the electrode cage; Is that Is mapped to;
the relation between the optical power and the number of photoelectrons escaping per second when the test quality is irradiated is as follows:
;
the relation between the optical power and the number of photoelectrons escaping per second when the electrode cage is irradiated is as follows:
;
the expression of (2) is as follows:
;
In the formula, In order to test the electrical potential carried by the quality surface,The electric potential carried by the surface of the electrode cage;
the expression of (2) is as follows:
。
4. A dual control loop charge management method according to claim 2 or 3, wherein said step S1 further comprises the substep S103 of adapting a nonlinear charge management system charge-discharge mathematical model to the following equation, taking into account the external charge accumulation rate:
;
In the formula, Representing the transformed Sigmoid function when the test quality is illuminated,Representing the transformed Sigmoid function when the electrode cage is illuminated,Representing external charge accumulation noise.
5. The method of claim 1, wherein the hybrid gain fuzzy PID controller is expressed as:
;
In the formula, The gain P m、Im、Dm of the mixed gain fuzzy PID controller is expressed as follows:
;
In the formula, fuzzy PID The gain output is of the magnitude ofThe fuzzy logic controller will depend on the error magnitudeAnd error rate of changeOutput ofThe regulation formula is as follows:
;
gain factor of the magnitude of ,The size of (2) is determined by the following formula:
;
In the formula, As the difference between the current optical power and the target optical power level,Is a preset threshold.
6. A dual control loop charge management method as defined in claim 3 wherein said objective function is expressed as follows:
;
Wherein k represents a control step, Represents the reference potential of the sample,Controlling a prediction step length for model prediction;
The constraint conditions are as follows: ;
;
wherein, Representing the predicted potential at time k + i +1 calculated at time k, s.t. representing the constraint,Representing a unit time, k representing a control step,Representing the actual potential of the sample,Represents the reference potential of the sample,Representing the amount of residual charge at time k,Representing the charge constant of the sample,Representing the test mass and the amount of capacitance between the electrode cages,The prediction step size is controlled for model prediction,、Representing the minimum and maximum optical powers that can be output when the test mass is illuminated,、Representing the minimum and maximum optical powers that can be output when the electrode cage is illuminated,Representing external charge accumulation noise.
7. The method of claim 1, wherein the ultraviolet lamp is an AlGaN-based ultraviolet lamp with a rated wavelength of 250-260 nm.
8. A dual control loop charge management system for performing a dual control loop charge management method as claimed in any one of claims 1-7, comprising a model predictive controller, a hybrid gain fuzzy PID controller, an ultraviolet lamp, an optical power meter;
The inner loop precisely controls the optical power of the ultraviolet lamp through the mixed gain fuzzy PID controller to ensure that the ultraviolet lamp is stably output and realize quantitative control of the surface potential of the test quality;
The outer ring monitors and feeds back the charge through the model prediction controller, predicts and optimizes the charge management system by using the feedback signal, updates the state of the charge management system, and the updated state is used as the input of the next prediction to form a feedback loop.
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| CA3010261A1 (en) * | 2018-06-29 | 2019-12-29 | Mitchell B. Miller | A system and method utilizing deflection conversion for increasing the energy efficiency of a circuit and time rate while charging an electrical storage device, different circuit configurations composing a group termed deflection converters, where this invention utilizes a current loop and or feedback |
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| CA3010261A1 (en) * | 2018-06-29 | 2019-12-29 | Mitchell B. Miller | A system and method utilizing deflection conversion for increasing the energy efficiency of a circuit and time rate while charging an electrical storage device, different circuit configurations composing a group termed deflection converters, where this invention utilizes a current loop and or feedback |
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