CN-121770410-B - Terminal sliding mode phase synchronization control method and system based on improved particle swarm optimization

CN121770410BCN 121770410 BCN121770410 BCN 121770410BCN-121770410-B

Abstract

The invention relates to the technical field of particle swarm optimization, in particular to a terminal sliding mode phase synchronization control method and system based on improved particle swarm optimization. The method comprises the steps of carrying out phase synchronization on fundamental voltage components of three-phase voltage based on a terminal sliding mode, carrying out stability analysis on the terminal sliding mode based on the phase synchronization, optimizing parameter vectors of the terminal sliding mode by adopting a particle swarm optimization algorithm, constructing a phase synchronization performance fitness function and setting terminal sliding mode parameters, and outputting global optimal parameters. According to the scheme, the terminal sliding mode controller is creatively adopted to realize accurate synchronization of harmonic distortion voltage phases, stable synchronization state is achieved in fixed time, and the terminal sliding mode controller has strong disturbance resistance after entering a sliding mode surface, so that the external disturbance resistance is greatly improved.

Inventors

LI YAN
ZHU CHAO
XING XIANGYANG
ZHANG RUI

Assignees

山东大学

Dates

Publication Date: 20260508
Application Date: 20260302

Claims (8)

1. The terminal sliding mode phase synchronization control method based on improved particle swarm optimization is characterized by comprising the following steps of: Acquiring a three-phase voltage signal; Performing coordinate transformation on the three-phase voltage based on the obtained three-phase voltage signal; carrying out phase synchronization on fundamental voltage components of the three-phase voltages based on a terminal sliding mode; carrying out stability analysis on the terminal sliding mode based on phase synchronization; optimizing a parameter vector of a terminal sliding mode by adopting a particle swarm optimization algorithm, wherein the optimization comprises phase synchronization performance fitness function construction and terminal sliding mode parameter setting; Outputting global optimal parameters; The coordinate transformation is performed on the three-phase voltages based on the obtained three-phase voltage signals, including transforming the obtained grid-connected point three-phase alternating-current voltages va, vb and vc from a static coordinate system to a synchronous rotation coordinate system to obtain a d-axis fundamental wave voltage component vd and a q-axis fundamental wave voltage component vq, wherein the Clark transformation is performed on the three-phase alternating-current voltages va, vb and vc firstly, and the three-phase alternating-current voltages va, vb and vc are transformed from the static coordinate system abc to alpha beta components vα and vβ under the static coordinate system, which are expressed as: In order to meet the requirements of high-precision phase locking under voltage distortion and background harmonic waves, the dynamic response is ensured, the background harmonic waves and noise interference are restrained, the SOGI is adopted to realize the real-time extraction of alternating-current fundamental wave components, an alpha-axis fundamental wave voltage vector vα1 and a beta-axis fundamental wave voltage vector vβ1 are obtained, and fundamental wave components vα1 and vβ1 are extracted through a second-order generalized integrator SOGI: Wherein Finally, the d-axis direct current voltage vector vd and the q-axis direct current voltage vector vq under a rotating coordinate system are converted through Park conversion processing: ; The method comprises the steps of inputting d-axis fundamental voltage components vd and vq under a rotating coordinate system to a terminal sliding mode controller based on a terminal sliding mode controller, outputting frequency correction u by the controller, superposing u and w0 to obtain output angular frequency w', integrating to obtain an estimated phase angle, and executing 2 pi remainder to obtain a three-phase voltage output phase theta, namely synchronizing the three-phase voltage output phase theta with a three-phase voltage signal, and providing a phase angle for park coordinate transformation by the aid of the phase, wherein a sliding mode surface of the terminal sliding mode controller is as follows: The terminal sliding mode control law is as follows: Wherein a, b >0, h1>0, alpha+beta=1 and 0< alpha, beta <1, sig x (y)=sign(y)*|y| x , defining the parameter vector to be set as x= [ a, b, h0, h1, alpha ], synchronizing the output phase of the final controller with the three-phase voltage phase to obtain the real phase of the voltage signal, and simultaneously utilizing the output phase to provide the phase transformation angle for the system from alpha beta to dq coordinate system transformation.
2. The method for controlling phase synchronization of terminal sliding mode based on improved particle swarm optimization according to claim 1, wherein the method for phase synchronizing fundamental voltage components of three-phase voltages based on terminal sliding mode further comprises solving an error dynamics equation based on phase synchronization, wherein fundamental voltage in a three-phase voltage signal obtained by SOGI extraction is expressed as: Where Vm is the three-phase voltage amplitude, φ 0 is the a-phase voltage initial phase, and a-phase voltage phase is The phase extracted by the terminal sliding mode controller is expressed as Wherein , In order to control the signal of the power supply, For the extracted initial phase, the three-phase alternating current signal cannot directly acquire phase information, and the three-phase signal is transformed from a natural coordinate system to a synchronous rotation coordinate system, wherein a coordinate transformation formula is as follows: , multiplying the fundamental voltage in the three-phase voltage signal with the second row of the matrix P (theta') to obtain vq: 。
3. The method for controlling phase synchronization of a terminal sliding mode based on improved particle swarm optimization according to claim 2, wherein the method for solving an error dynamics equation based on phase synchronization further comprises multiplying fundamental voltage in a three-phase voltage signal by a matrix P (θ') to obtain vd: And finally, deriving phase-locked loop error dynamics, wherein the initial phase phi 0 exists in vq, and the relation between the vq change rate and the phase deviation change rate is expressed as follows: The phase deviation change rate is: Bringing the phase deviation change rate to Obtaining And the control output quantity of the terminal sliding mode is just Replacing the terminal sliding mode control output quantity , Written as Meanwhile, the d-axis voltage expression is simplified by Park conversion and is as follows: The scaling factor k=v d ≡vm is defined, so the error dynamics equation is: 。
4. the method for controlling phase synchronization of a terminal sliding mode based on improved particle swarm optimization according to claim 3, wherein the method for analyzing stability of the terminal sliding mode based on phase synchronization comprises analyzing whether a sliding mode system is stable or not through Lyapunov stability criteria, selecting an energy function V(s), selecting Lyapunov function as V= |s|, and deriving two sides of a sliding mode surface: as can be derived from the phase-locked loop error dynamics equation, Then deriving the two sides of the control law equation, and obtaining the control law equation by eliminating the cross terms: from the lyapunov function v= |s| we get Wherein h0, h1>0, |s| α >0, then Is not more than 0;V positive degrees, Secondly, solving the arrival time Tr and the sliding time Ts of the stable state of the terminal sliding mode controller, wherein Tr is expressed as; Wherein Ts is the time taken for the terminal sliding mode system to gradually reach 0 after the terminal sliding mode system reaches the sliding mode surface s=0, and vq=0 when the terminal sliding mode system reaches the balance point, the controller completes phase synchronization, and Ts is expressed as: Finally, the system stabilization time T is the sum of the arrival times Tr and Ts, i.e 。
5. The method for controlling phase synchronization of a terminal sliding mode based on improved particle swarm optimization according to claim 4, wherein the phase synchronization performance fitness function is constructed and comprises a synchronization time index T lock , which is defined as the earliest time when an error signal enters a threshold value zone epsilon and is continuously kept at not less than T hold , a steady-state ripple index R measures the mean square value of vq in a steady-state window, a jitter index C measures the average absolute value of the change rate deltau of a control quantity u in the steady-state window, a penalty term P is given to a penalty value when the particle parameter violates a hard constraint and diverges in the evaluation process, and the fitness function is expressed as: The method comprises the steps of carrying out initial position and speed of particles randomly generated in parameter boundaries, wherein w1, w2 and w3 are weight coefficients, then carrying out particle swarm iteration update, carrying out initial position and speed of the particles randomly generated in parameter boundaries, wherein a position vector is a parameter to be set, an individual optimal position pBest i is a position corresponding to the minimum fitness obtained by the particles i in historical iteration, a global optimal position gBest is a position corresponding to the minimum fitness obtained by all particle historical iteration, setting a particle swarm scale as N and the maximum iteration number as Nmax, carrying out initial position and speed into the calculated initial fitness J 0 ,pBest i and gBest, further updating inertia weight w (t), and updating the speed of the particles i according to the individual optimal pBest and the global optimal gBest by the following formula: Wherein r1 and r2 are independent uniform random numbers for introducing random disturbance to avoid sinking into local optimum, c 1 、c 2 is a learning factor, and the intensities of the particles for learning to individual optimum pBest and global optimum gBest are respectively represented.
6. The method for controlling phase synchronization of a terminal sliding mode based on improved particle swarm optimization according to claim 5, wherein the setting of the terminal sliding mode parameter comprises defining key parameters in a terminal sliding mode phase synchronization controller as parameter vectors x= [ a, b, h0, h1, α ], wherein a, b are sliding mode face weight coefficients, h0, h1 are arrival law intensity correlation coefficients, α is a terminal index, and satisfies α+β=1 and 0< α, β <1, and a search dimension d=5, and at the t-th iteration, the position vector and the velocity vector of the i-th particle are respectively expressed as: Setting up upper and lower bounds [ lbd, ubd ] for each dimension parameter, wherein the upper and lower bounds can be set by system parameters and experience, ensuring that the parameters have physical meaning and engineering realizability, and the hard constraints a, b >0, h1>0, alpha+beta=1 and 0< alpha, beta <1 of x are required to be satisfied, when any parameter crosses the bounds or violates the hard constraint, adopting a boundary projection/reflection mode to correct, setting up a particle number N, and the maximum iteration number Nmax, wherein the inertia weight is linearly decreased, and taking into consideration the characteristics of accelerating the exploration later convergence in the early stage: Limiting the speed to inhibit evaluation distortion or closed loop instability caused by excessive parameter jump: 。
7. the method of claim 6, wherein outputting the global optimum parameter comprises performing clipping for each dimension d to prevent the search from diverging due to the step size being too large: The location update is: when a certain dimension crosses the boundary after the position is updated, the method is executed Writing x i(t+1) into the terminal sliding mode controller to operate, and then calculating J i（t+1） if Then update pBest i , if And updating gBest i , and finally outputting gBest the corresponding optimal parameter vector when the iteration reaches the maximum iteration number or the global optimal improvement amplitude of the successive n-generation iteration orders is smaller than the threshold delta.
8. A terminal sliding mode phase synchronization control method system based on improved particle swarm optimization, which performs the terminal sliding mode phase synchronization control method based on improved particle swarm optimization according to claim 1, comprising: the data acquisition module is configured to acquire three-phase voltage signals; a coordinate transformation module configured to perform coordinate transformation on the three-phase voltages based on the acquired three-phase voltage signals; a phase synchronization module configured to phase synchronize fundamental voltage components of the three-phase voltages based on the terminal slip mode; The stability module is configured to perform stability analysis on the terminal sliding mode based on phase synchronization; the particle swarm optimization module is configured to optimize a parameter vector of a terminal sliding mode by adopting a particle swarm optimization algorithm, and comprises phase synchronization performance fitness function construction and terminal sliding mode parameter setting; and the output module is configured to output the global optimal parameters.

Description

Terminal sliding mode phase synchronization control method and system based on improved particle swarm optimization Technical Field The invention relates to the technical field of particle swarm optimization, in particular to a terminal sliding mode phase synchronization control method and system based on improved particle swarm optimization. Background The phase extraction and phase synchronization control of the three-phase voltage signals are basic links in the measurement and control and synchronization operation of the alternating current system, and the phase estimation result is usually used as a phase reference for coordinate transformation and synchronization control. In engineering application, three-phase voltage at a public connection point is often influenced by background harmonic wave, noise, waveform distortion and other factors, and is expressed as non-sinusoidal, high-order component or unbalanced component superposition, under the working condition, phase synchronization control is required to have a relatively fast phase tracking capability, relatively small synchronization error and ripple in a steady state, and has enough robustness to disturbance and noise, otherwise, the problems of prolonged synchronization time, phase overshoot oscillation or unreliable locking and the like are easy to occur. In the existing phase extraction scheme, hardware implementation is dependent on zero crossing judgment and analog phase discrimination, the structure is visual, but the phase extraction scheme is sensitive to harmonic waves and noise, and phase jitter is easily caused by repeated zero crossing misjudgment. The software implementation generally builds closed-loop adjustment based on synchronous coordinate system error feedback, and can be matched with a filtering or decoupling structure to inhibit distortion influence, but typical contradictions still exist that locking time is longer and tracking is lagged when adjustment parameters are more conservative, overshoot oscillation easily occurs when the parameters are more aggressive, and steady-state ripple waves are difficult to be depressed under harmonic conditions. In order to improve robustness, sliding mode control is used for a phase extraction link due to high disturbance rejection capability, limited time convergence structures such as a terminal sliding mode and the like can also be used for improving convergence speed, however, engineering effects of a sliding mode scheme are highly dependent on key parameter configuration, experience setting cost is high, indexes such as fast, stable, low buffeting and the like are difficult to ensure to be met simultaneously under different harmonic content and distortion levels, strong jitter is easy to be introduced and measurement noise influence is amplified when parameter selection is biased to converge rapidly, and slow synchronization process or stable residual error increase can be caused when the parameter selection is biased to inhibit jitter. Since the tuning problem generally presents a non-linear, non-convex and multi-index compromise feature, it is difficult to obtain stable and reproducible parameter combinations under multiple working condition constraints simply by means of manual tuning or local empirical rules. Therefore, a parameter setting method oriented to the harmonic background and with indexes such as locking time, steady-state ripple and jitter is needed, so that the key parameters of the terminal sliding mode phase extraction controller can realize optimal searching and optimizing configuration. The intelligent algorithm of particle swarm optimization and the like does not depend on the conductivity of an objective function, is suitable for solving the problems of multi-parameter coupling and nonlinear evaluation, is used for optimizing and setting of key parameters of sliding mode control, and is beneficial to obtaining parameter combination considering dynamic and steady-state performance under harmonic and distortion conditions. Disclosure of Invention The invention provides a terminal sliding mode phase synchronous control method and system based on improved particle swarm optimization, which aims to solve the problems that the existing three-phase voltage signal phase extraction is easy to have slow locking, unstable locking and the controller parameter depends on experience setting under harmonic wave and waveform distortion conditions. The fundamental frequency phase of the three-phase voltage signal is accurately extracted within fixed time, so that the defects of low accuracy and low convergence speed of the traditional phase synchronization are overcome, and on the other hand, for the problems of multiple parameters and difficult regulation and control of the terminal sliding mode controller, the performance index is taken as a traction parameter setting thought, the key parameters of the terminal sliding mode controller are automatically optimized by utilizing