Parameter adaptive optical frequency comb repetition frequency phase locking system and method

Abstract

The invention discloses a parameter adaptive optical frequency comb repetition frequency phase locking system and method, and belongs to the field of optical frequency combs. The system comprises an optical fiber optical frequency comb, a repetition frequency detection module, a phase discriminator module, a parameter adaptive phase lock control module, a PZT frequency actuator and a frequency reference source module, the repetition frequency detection module is used for detecting a repetition frequency signal of the optical fiber optical frequency comb, and the frequency reference source module generates a target repetition frequency signal; the two paths of signals generate repetition frequency phase errors through the phase discriminator module, the repetition frequency phase errors enter the parameter self-adaptive phase lock control module, the parameter self-adaptive phase lock control module generates phase lock signals through a parameter self-adaptive phase lock controller, and control over repetition frequency of the optical fiber optical frequency comb is achieved through a PZT frequency actuator. The phase-locked controller is based on a single-neuron network PID controller, and can optimize PID control parameters in real time according to the current phase-locked condition so as to improve the phase-locked precision and the autonomous locking capability of the repetition frequency of the optical frequency comb in a complex dynamic environment.

Description

Technical Field

[0001] The present invention relates to the field of optical frequency combs, and in particular to a parameter adaptive optical frequency comb re-frequency phase locking system and method. Background Art

[0002] The optical frequency comb is a phase-locked mode-locked laser, named for its unique comb-shaped distribution characteristics in the frequency domain. The optical frequency comb has the advantages of wide spectrum, narrow pulse width, and low phase noise, which has brought revolutionary progress to the precision measurement of parameters such as frequency, time, and distance. The absolute distance measurement based on dual optical combs has the characteristics of high precision, high speed measurement, and large unambiguous distance, and has broad application prospects in precision manufacturing, aerospace alignment, high-precision three-dimensional topography scanning, and other fields.

[0003] In order to improve the coherence and ranging accuracy of the dual optical comb, it is usually necessary to phase lock the two optical combs. Since the ranging accuracy of the dual optical comb is only related to the stability of the optical frequency comb repetition rate, phase locking the dual optical comb repetition rate is an important means to improve the ranging accuracy. Traditional optical frequency comb repetition rate locking usually uses a PID controller with fixed control parameters. The control parameters need to be set before locking. When the working environment of the optical frequency comb changes, the repetition rate locking effect deteriorates, and the control parameters need to be manually adjusted to ensure the optimal repetition rate locking state. And with the advancement of the miniaturization of optical frequency combs, it has become a trend to achieve full digital locking of optical frequency comb repetition rate phase locking on a single-chip microcomputer. At this time, it is even more inconvenient to manually adjust the control parameters. Summary of the invention

[0004] In response to the current problems faced by dual-optical comb ranging, the present invention provides a parameter-adaptive optical frequency comb repetition rate phase-locking system and method, which can optimize the PID control parameters in real time according to the current locking situation to ensure that the system always maintains the best working state, and improve the locking accuracy and autonomous locking capability of the optical frequency comb repetition rate in complex dynamic environments.

[0005] To achieve the above purpose, the technical solution provided by the present invention is:

[0006] It includes a fiber optical frequency comb, a repetition frequency detection module, a phase detector module, a parameter adaptive phase-locked control module, a PZT (piezoelectric ceramic) frequency actuator and a frequency reference source module;

[0007] The repetition frequency detection module is used to obtain a signal through a photoelectric detector and obtain a fiber optical frequency comb repetition frequency signal through amplification and filtering operations. Generally, the repetition frequency first harmonic is extracted as the fiber optical frequency comb repetition frequency signal;

[0008] The frequency reference source module uses an atomic clock or other frequency reference source as a reference and generates a target repetition frequency signal through an arbitrary waveform generator;

[0009] The phase detector module is used to identify the repetition frequency phase error between the fiber optical frequency comb repetition frequency signal detected by the repetition frequency detection module and the target repetition frequency signal generated by the frequency reference source module;

[0010] The parameter adaptive phase-lock control module is used to generate a phase-lock signal by a parameter adaptive phase-lock controller according to the repetition frequency phase error identified by the phase detector module;

[0011] The PZT frequency actuator is adhered to the optical fiber cavity of the optical fiber frequency comb and is used to change the size of the PZT expansion and contraction according to the phase-locking signal generated by the parameter adaptive phase-locking control module to achieve real-time compensation of the repetition frequency phase error.

[0012] Furthermore, the parameter adaptive phase-locked controller is based on a single neuron network PID controller, and can optimize the PID control parameters in real time according to the current phase-locked situation, so as to improve the locking accuracy and autonomous locking capability of the optical frequency comb repetition rate in a complex dynamic environment.

[0013] Furthermore, the input of the single neuron network PID controller is the repetition frequency phase error output by the phase detector module. It uses an incremental PID controller, and the input quantities x1(k), x2(k), and x3(k) of the proportional term, integral term, and differential term are respectively:

[0014]

[0015] Where k represents the current iteration round of the controller, the output of the single neuron network PID controller is:

[0016] u(k)=u(k-1)+∈[ω1(k)x1(k)+ω2(k)x2(k)+ω3(k)x3(k)]

[0017] Wherein, ∈ is the proportional coefficient of the single neuron network PID controller, ω1(k), ω2(k), ω3(k) are the connection weights of the proportional term, integral term and differential term of the PID controller respectively.

[0018] Furthermore, the single neuron network PID controller adopts a supervised Hebb learning rule, and the connection weights ω1(k), ω2(k), ω3(k) of its proportional term, integral term and differential term are continuously updated with the iteration rounds:

[0019]

[0020] Where η1, η2, and η3 are the learning rates of the proportional term, integral term, and differential term, respectively. After each iterative update obtains the connection weights of the proportional term, integral term, and differential term, it is necessary to normalize them as follows:

[0021] ω1(k)=ω1(k) / (ω1(k)+ω2(k)+ω3(k))

[0022] ω2(k)=ω2(k) / (ω1(k)+ω2(k)+ω3(k))

[0023] ω3(k)=ω3(k) / (ω1(k)+ω2(k)+ω3(k)

[0024] Based on the control method of the above-mentioned parameter adaptive optical frequency comb repetition frequency phase-locking system, before entering the feedback control, the single neuron network PID controller first updates the connection weights of the proportional term, the integral term and the differential term according to the current repetition frequency phase error and the control signal output in the previous iteration round, and then outputs the control signal with the updated connection weights to achieve the parameter adaptation of the optical frequency comb repetition frequency phase-locking. Since only the parameter iteration update of the single neuron network is adopted, the single neuron network PID controller has a small computing power requirement in the actual phase-locking control, and is easy to be integrated into the lower computer such as FPGA to achieve the phase locking of the optical frequency comb repetition frequency.

[0025] Compared with the traditional optical frequency comb repetition rate phase-locking system, the advantage of the parameter adaptive repetition rate phase-locking system proposed in the present invention is that the control parameters can be updated in real time according to the current phase-locking state, and the optimal phase-locking state can be maintained without manual adjustment of the control parameters when the external environment changes, which greatly improves the repetition rate locking accuracy and autonomous locking capability of the optical frequency comb in a complex and dynamic environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are merely embodiments of the present application and should not be regarded as limiting the scope. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 This is a schematic diagram of the structure of the parameter adaptive optical frequency comb re-frequency phase locking system in the embodiment of the present application;

[0028] Figure 2 Schematic diagram of a single neuron network PID controller in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the purpose, features, and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0030] See also Figure 1 The present invention provides a parameter adaptive optical frequency comb repetition frequency phase locking system, the system comprising: an optical fiber optical frequency comb, a repetition frequency detection module, a phase detector module, a parameter adaptive phase locking control module, a PZT frequency actuator and a frequency reference source module;

[0031] Among them, the repetition frequency detection module obtains and amplifies and filters the repetition frequency signal of the optical fiber optical frequency comb through a photoelectric detector; generally, the first harmonic of the repetition frequency is extracted as the repetition frequency signal of the optical fiber optical frequency comb;

[0032] The frequency reference source module uses an atomic clock or other frequency reference source as a reference and generates a target repetition frequency signal through an arbitrary waveform generator;

[0033] The phase detector module identifies the repetition frequency phase error between the optical fiber optical frequency comb repetition frequency signal detected by the repetition frequency detection module and the target repetition frequency signal generated by the frequency reference source module;

[0034] The parameter adaptive phase-lock control module generates a phase-lock signal by a parameter adaptive phase-lock controller according to the repetition frequency phase error identified by the phase detector module;

[0035] The PZT frequency actuator is adhered to the optical fiber cavity of the optical fiber frequency comb, and the PZT expansion and contraction amount is changed according to the phase-locking signal generated by the parameter adaptive phase-locking control module to achieve real-time compensation of the repetition frequency phase error.

[0036] In one embodiment of the present application, the parameter adaptive phase-locked controller is implemented based on a single neuron network PID controller, see Figure 2 , the PID control parameters can be optimized in real time according to the current phase-locking situation to improve the locking accuracy and autonomous locking capability of the optical frequency comb repetition rate in complex dynamic environments. Figure 2 Z -1 Represents a delay module, which is a conventional module in this field.

[0037] In one embodiment of the present application, the input of the single neuron network PID controller is the repetition frequency phase error output by the phase detector module. It uses an incremental PID controller, and the input quantities x1(k), x2(k), and x3(k) of the proportional term, integral term, and differential term are respectively:

[0038]

[0039] Where k represents the current iteration round of the controller, the output of the single neuron network PID controller is:

[0040] u(k)=u(k-1)+Δu(k)=u(k-1)+∈[ω1(k)x1(k)+ω2(k)x2(k)+ω3(k)x3(k)](4)

[0041] Wherein, ∈ is the proportional coefficient of the single neuron network PID controller, ω1(k), ω2(k), ω3(k) are the connection weights of its proportional term, integral term and differential term respectively.

[0042] In one embodiment of the present application, the single neuron network PID controller adopts a supervised Hebb learning rule, and the connection weights ω1(k), ω2(k), ω3(k) of its proportional term, integral term and differential term are continuously updated with the iteration rounds:

[0043]

[0044] Among them, η1, η2, η3 are the learning rates of the proportional term, integral term and differential term respectively. When the system is learning for the first time, there is no special requirement for the selection of the initial values ​​of the connection weights ω1(0), ω2(0), ω3(0). The learning rates of the proportional term, integral term and differential term can be adjusted according to the current response rate, overshoot, etc. of the system to set the optimal learning rate of the system.

[0045] After each iterative update obtains the connection weights of the proportional term, integral term, and differential term, they need to be normalized:

[0046] ω1(k)←ω1(k) / (ω1(k)+ω2(k)+ω3(k)) (8)

[0047] ω2(k)←ω2(k) / (ω1(k)+ω2(k)+ω3(k)) (9)

[0048] ω3(k)←ω3(k) / (ω1(k)+ω2(k)+ω3(k)) (10)

[0049] Among them, ← represents the assignment operation.

[0050] Before entering feedback control, the single neuron network PID controller first updates the connection weights of the proportional term, the integral term and the differential term according to the current repetition phase error and the output signal of the previous iteration round, as shown in formulas (5)-(10), and then outputs the control signal with the updated connection weights according to formulas (1)-(4), thereby realizing parameter adaptation of the optical frequency comb repetition phase locking.

[0051] Since the above embodiment only uses the iterative update of the parameters of the single neuron network, the single neuron network PID controller requires less computing power in actual phase-locked control and can be easily integrated into a lower computer such as an FPGA to achieve phase locking of the optical frequency comb repetition rate.

[0052] The above is the parameter-adaptive repetition-locked phase-locked system and method provided in the present application. For technicians in this field, according to the ideas of the embodiments of the present application, there may be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A parameter adaptive optical frequency comb repetition frequency locking system, characterized in that: It includes a fiber optical frequency comb, a repetition frequency detection module, a phase detector module, a parameter adaptive phase-locked control module, a PZT frequency actuator and a frequency reference source module; The repetition frequency detection module is used to obtain a signal through a photoelectric detector and obtain a fiber optical frequency comb repetition frequency signal through amplification and filtering operations; The frequency reference source module is used to generate a target repetition frequency signal; The phase detector module is used to identify the repetition frequency phase error between the fiber optical frequency comb repetition frequency signal detected by the repetition frequency detection module and the target repetition frequency signal generated by the frequency reference source module; The parameter adaptive phase-lock control module is used to generate a phase-lock signal by a parameter adaptive phase-lock controller according to the repetition frequency phase error identified by the phase detector module; The PZT frequency actuator is adhered to the optical fiber cavity of the optical fiber frequency comb and is used to change the size of the PZT expansion and contraction according to the phase-locking signal generated by the parameter adaptive phase-locking control module to achieve real-time compensation of the repetition frequency phase error.

2. The parameter adaptive optical frequency comb repetition frequency locking system according to claim 1, characterized in that: The parameter adaptive phase-locked controller is based on a single neuron network PID controller.

3. The parameter adaptive optical frequency comb repetition frequency locking system according to claim 2, characterized in that: The input of the single neuron network PID controller is the repetition frequency phase error output by the phase detector module. It uses an incremental PID controller, and the proportional term, integral term, and differential term x1(k), x2(k), and x3(k) are respectively: Where k represents the current iteration round of the PID controller; The output of the PID controller is: u(k)=u(k-1)+∈[ω1(k)x1(k)+ω2(k)x2(k)+ω3(k)x3(k)] Among them, ∈ is the proportional coefficient of the PID controller, ω1(k), ω2(k), ω3(k) are the connection weights of the proportional term, integral term and differential term of the PID controller respectively.

4. The parameter adaptive optical frequency comb re-frequency phase locking system according to claim 3, characterized in that: The single neuron network PID controller adopts the supervised Hebb learning rule, and the connection weights ω1(k), ω2(k), ω3(k) of its proportional term, integral term and differential term are continuously updated with the iteration rounds: Among them, ηη1, ηη2, and ηη3 are the learning rates of the proportional term, integral term, and differential term respectively; After each iterative update obtains the connection weights of the proportional term, integral term and differential term, they need to be normalized.

5. A control method for the parameter adaptive optical frequency comb repetition frequency phase locking system according to claim 3, characterized in that: Before entering feedback control, the single neuron network PID controller first updates the connection weights of the proportional term, the integral term and the differential term according to the current repetition frequency phase error and the output control signal of the previous iteration round, and then outputs the control signal with the updated connection weights to achieve parameter adaptation of the optical frequency comb repetition frequency phase locking.

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