Switching power supply dynamic response adjusting system based on digital control

Abstract

The invention relates to the technical field of digital control switching power supplies, and particularly discloses a switching power supply dynamic response adjusting system based on digital control, which comprises a digital controller, a multi-channel analog-to-digital conversion module, a parameter identification module, a self-adaptive control law adjusting module, a pulse width modulation driving module and a stability monitoring module. On-line identification of key parameters of a system is realized by constructing a nonlinear state space model and combining an extended Kalman filtering algorithm, dynamic compensation is carried out for non-minimum phase characteristics such as a right half plane zero point, and a self-adaptive control law adjustment module optimizes a control strategy in real time according to an updated model. A Lyapunov stability criterion and a predictive control mechanism are introduced, the robustness and response speed of the system are improved, and a stability monitoring module identifies an abnormal state through sliding window variance analysis and peak detection and triggers a fault-tolerant mechanism to guarantee safe operation of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of digital controlled switched-mode power supplies, and particularly to a dynamic response regulation system for a switched-mode power supply based on digital control. Background Art

[0002] With the continuous development of power electronics technology, switched-mode power supplies are widely used in fields such as communication equipment, industrial control, new energy conversion, and aerospace due to their advantages of high efficiency, small volume, and light weight. In these application scenarios, the system places higher requirements on the dynamic response ability, stability, and reliability of the power supply. Due to the disadvantages of fixed parameters and difficulty in adapting to complex working condition changes of traditional analog control methods, they have gradually been replaced by digital control technology. Digital control not only has higher flexibility and reconfigurability but also supports the implementation of advanced control algorithms such as adaptive control, predictive control, and intelligent optimization control, thereby effectively improving the dynamic performance and robustness of the system. In practical applications, many switched-mode power supply topologies (such as Boost, Flyback, Cuk, etc.) exhibit non-minimum phase characteristics, that is, there are right-half plane zeros (RHP Zero), resulting in reverse responses when the load changes suddenly, affecting stability. Therefore, how to achieve high-precision modeling and adaptive regulation of such systems under a digital control architecture has become one of the key research directions.

[0003] The existing technology has the following deficiencies: In some complex power systems, especially in the design of high-order resonant converters or digital controlled switched-mode power supplies with non-minimum phase characteristics, there may be right-half plane zeros (RHP Zero) in the system transfer function, resulting in significant differences in its frequency response characteristics compared with traditional minimum phase systems. Such non-minimum phase systems exhibit non-intuitive behaviors such as "reverse response" during the dynamic response process, making it difficult for traditional stability criteria based on gain margin and phase margin to be effectively applied. Summary of the Invention

[0004] The purpose of the present invention is to provide a dynamic response regulation system for a switched-mode power supply based on digital control to solve the problems in the above background.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A dynamic response regulation system for a switched-mode power supply based on digital control includes: A digital controller for executing an adaptive control algorithm and generating a control signal; A multi-channel analog-to-digital conversion module connected to the digital controller for real-time acquisition of the input voltage, output voltage, and inductor current signals of the switched-mode power supply system; A parameter identification module, integrated in the digital controller, is used to perform online identification of key system parameters based on the extended Kalman filter algorithm to update the system model; An adaptive control law adjustment module, coupled with the parameter identification module, is used to dynamically adjust the control gain and control strategy according to the updated system model to compensate for the impact of non-minimum phase characteristics on system stability; A pulse width modulation drive module, connected to the digital controller, is used to generate corresponding PWM control pulses according to the adjusted control signal to drive the power switch device; A stability monitoring module is used to monitor the system operation status and trigger a fault tolerance mechanism in case of anomalies to maintain the basic functions of the system.

[0006] As a further solution of the present invention: The parameter identification module performs the following steps: Construct a non-linear state space model of the switching power supply system, including the state equations and observation equations of the inductor current and output voltage; Based on the extended Kalman filter algorithm, perform real-time prediction and update on the state equations to estimate the internal state variables and unknown parameters of the system; Use the input voltage, output voltage, and inductor current data collected by the multi-channel analog-to-digital conversion module as the observation input to drive the parameter identification process; Periodically output the updated system parameters to the adaptive control law adjustment module to achieve dynamic compensation.

[0007] As a further solution of the present invention: A noise covariance adaptive adjustment mechanism is introduced in the extended Kalman filter algorithm, specifically including: Real-time monitor the system operation status and evaluate the observation residuals; Dynamically adjust the process noise covariance matrix Q and the observation noise covariance matrix R according to the residual change trend; Improve the parameter identification accuracy and enhance the robustness of the system under load mutation or input disturbance.

[0008] As a further solution of the present invention: The parameter identification module further includes the steps of identifying and compensating the position of the right half-plane zero: Extract the transfer function information after the system model is updated to determine whether there is a right half-plane zero; If it exists, feedback its position information to the adaptive control law adjustment module; The controller adjusts the control strategy according to this information, including gain limitation, phase compensation, or switching control mode, to suppress the dynamic instability caused by non-minimum phase behavior; The parameter identification module achieves fast convergence through the following methods: Inject a small-amplitude excitation signal with a limited duration during the system startup phase; Process the excitation response data using the extended Kalman filter algorithm to accelerate the initial parameter estimation process; Shorten the identification time in the system cold startup phase and improve the power-on response speed and stability.

[0009] As a further solution of the present invention: the adaptive control law adjustment module performs the following steps: Receive the updated system model information from the parameter identification module, including the inductor current dynamics, output voltage response characteristics, and the position of the right half-plane zero; Judge whether the current operating state deviates from the stable region based on the change trend of the system model; Dynamically adjust the proportional, integral, and derivative gain coefficients of the PID controller; Output the updated control law to the pulse width modulation drive module to optimize the transient response performance under load mutation.

[0010] As a further solution of the present invention: the adaptive control law adjustment module further includes a stability criterion evaluation step based on the Lyapunov function: Construct a Lyapunov candidate function applicable to the current system model; Calculate its derivative in real time to judge the energy convergence of the system; If an unstable trend is detected, trigger the control gain attenuation mechanism or switch to a preset safety control mode; Maintain the closed-loop stability of the system without sacrificing the response speed.

[0011] As a further solution of the present invention: the adaptive control law adjustment module automatically switches the control strategy according to the presence of the right half-plane zero, specifically including: When it is recognized that the system has non-minimum phase characteristics, enable the lead-lag compensation control structure; Limit the controller bandwidth to avoid phase inversion and oscillation in the high-frequency band; Introduce a feedforward term to offset the reverse response behavior caused by the right half-plane zero; Dynamically reconstruct the control law to achieve robust control of the non-minimum phase system; The adaptive control law adjustment module also executes the following enhanced control strategy: Predict the possible future operating states according to the change rate of the system model; Adjust the control gain in advance to cope with the upcoming load jump or input disturbance; Combine historical data with the current identification results for multi-step rolling optimization; Improve the smoothness and anti-interference ability of the system dynamic response through the predictive control strategy.

[0012] As a further solution of the present invention: The pulse width modulation driving module performs the following steps: Receive the dynamic adjustment control signal from the digital controller and convert it into a high-resolution PWM waveform; Generate complementary symmetric PWM driving pulses according to the current switching frequency set value and dead time configuration; During the generation process, combine the turn-on and turn-off delay characteristics of the power switching device, dynamically calculate and insert the optimal dead time; Output to the power switching device to achieve efficient and low-distortion energy conversion, while preventing the risk of shoot-through between the upper and lower bridge arms.

[0013] As a further solution of the present invention: The pulse width modulation driving module also performs the following enhanced control and protection strategies: Implement soft start control during the system power-on stage, gradually increase the PWM duty cycle to suppress the start-up inrush current; Real-time monitor overcurrent, overvoltage and temperature abnormal signals, and immediately limit or turn off the PWM output when a fault is detected; Automatically restart the PWM output and synchronize the controller status after the fault recovery to ensure the safe and reliable operation of the system; At the same time, dynamically adjust the switching frequency according to the controller instruction to optimize the efficiency and stability of the system under different load conditions.

[0014] As a further solution of the present invention: The stability monitoring module performs the following steps: Real-time collect and analyze the time series data of the output voltage, inductor current and controller output control quantity; Based on the sliding window variance analysis and peak detection algorithm, identify whether the system enters the oscillation or unstable state; When it is detected that the overshoot exceeds the set threshold, the recovery time is abnormally extended or the phase margin drops to the critical value, it is determined that the stability is abnormal; Trigger the fault tolerance mechanism, including switching to the preset stable control parameter set, limiting the controller bandwidth or starting the soft restart process, to restore the system stability and maintain the basic power supply function.

[0015] The beneficial effects of the present invention: (1) The present invention realizes high-precision modeling and adaptive control of the operating state of the switching power supply system by constructing an online parameter identification mechanism based on the Extended Kalman Filter (EKF), combined with a real-time identification and dynamic compensation strategy for the right-half plane zero (RHP Zero), which is a key feature in non-minimum phase systems. This parameter identification module can continuously update key parameters including inductance value, capacitance value, load impedance, and the position of system poles / zeros based on the input voltage, output voltage, and inductor current signals collected from multiple channels, using a non-linear state space model and a recursive estimation algorithm, thus ensuring that the controller always makes decisions according to the current actual system characteristics.

[0016] Especially in complex topologies with right-half plane zeros, the system may exhibit non-intuitive behaviors such as "reverse response" during the dynamic response process. Traditional control methods based on fixed gain or linear compensation are difficult to effectively handle this situation, and it is extremely easy to lead to deterioration of stability or even system instability. However, by feeding back the RHP zero information to the adaptive control law adjustment module, the present invention triggers an intelligent switch of the control strategy, such as introducing a lead-lag compensation structure, restricting the controller bandwidth, or activating a feedforward regulation mechanism, significantly enhancing the robustness and controllability of the system under the influence of non-minimum phase characteristics.

[0017] Compared with the static control parameter configuration method commonly used in the prior art, the present invention breaks through the limitations of traditional model-matching-based control, effectively solves the problem of control failure caused by system parameter drift, operating condition changes, or modeling errors, and significantly enhances the dynamic response ability and closed-loop stability of the switching power supply under complex operating conditions such as load mutation, input disturbance, and environmental changes, providing a practical technical path for the intelligent and adaptive development of high-performance digital control power supply systems.

[0018] (2) The present invention breaks through the technical bottlenecks such as fixed control strategy, response lag, and limited fault tolerance ability in traditional switching power supplies by constructing a cooperative control system integrating an adaptive control law adjustment module and an intelligent stability monitoring mechanism. Based on the real-time updated model information provided by the parameter identification module, this system dynamically optimizes the core parameters of the controller (such as proportional, integral, and differential gains), and automatically switches the control structure according to the changing trend of the system operating state, realizing a flexible transition from PID control to lead-lag compensation, feedforward regulation, and even predictive multi-step rolling optimization control.

[0019] At the control strategy level, the present invention introduces the Lyapunov function as an evaluation tool for the energy convergence of the system, and judges whether the system is in the stable operation region by calculating its time derivative in real time. Once the energy divergence trend is detected, the control gain attenuation or mode switching mechanism is triggered to maintain the stability of the closed-loop system without sacrificing the response speed. In addition, the system also has the ability of predictive control, which can predict possible load jumps or input disturbances in the future based on historical data and the current model, and adjust the control strategy in advance, thus significantly improving the anti-interference performance and dynamic response smoothness of the system.

[0020] To enhance the system's ability to identify and respond to abnormal operating conditions, the present invention further integrates a multi-level stability monitoring and fault tolerance mechanism. Through the sliding window variance analysis and peak detection algorithm, the system can accurately identify unstable features such as output voltage overshoot, extended recovery time, and control signal oscillation, and accordingly initiate corresponding fault tolerance measures, including switching to a preset stable control parameter set, restricting the controller bandwidth, or executing a soft restart process, to ensure that the system can still maintain the basic power supply function after a fault occurs.

[0021] At the same time, the pulse width modulation drive module adopts high-resolution PWM waveform generation technology, combined with the online identification of the turn-on and turn-off delay characteristics of power switch devices, to achieve dynamic optimization and configuration of the dead time, effectively preventing the risk of shoot-through between the upper and lower bridge arms, and improving the power conversion efficiency and operation safety. This module also supports frequency adaptive adjustment, soft start control, and multiple protection mechanisms, enabling the system to maintain efficient and stable operation under different load conditions. Brief Description of the Drawings

[0022] The present invention will be further described below with reference to the accompanying drawings.

[0023] Figure 1 It is a flow block diagram of a switching power supply dynamic response regulation system based on digital control according to the present invention. Detailed Embodiments

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] Please refer to Figure 1 As shown, the present invention is a switching power supply dynamic response regulation system based on digital control, including: A digital controller for executing an adaptive control algorithm and generating a control signal; A multi-channel analog-to-digital conversion module, connected to the digital controller, for real-time acquisition of the input voltage, output voltage and inductor current signals of the switching power supply system; A parameter identification module, integrated in the digital controller, for online identification of key system parameters based on the extended Kalman filter algorithm to update the system model; An adaptive control law adjustment module, coupled with the parameter identification module, for dynamically adjusting the control gain and control strategy according to the updated system model to compensate for the impact of non-minimum phase characteristics on system stability; A pulse width modulation drive module, connected to the digital controller, for generating corresponding PWM control pulses according to the adjusted control signal to drive the power switch device; A stability monitoring module, for monitoring the system operation status and triggering a fault tolerance mechanism in case of anomalies to maintain the basic functions of the system; The key parameters include: the inductor value, capacitor value, load impedance, controller gain, system poles, system zero positions and right half-plane zeros of the switching power supply.

[0026] Among them, the digital controller uses an embedded digital signal processor (DSP) or a field programmable gate array (FPGA) with floating-point operation capabilities, and an adaptive control algorithm module is integrated inside, for real-time execution of advanced control strategies including but not limited to model reference adaptive control (MRAC), parameter estimation-based adaptive control, etc. The controller constructs a complete information map of the current system operation status by periodically receiving data inputs from the multi-channel analog-to-digital conversion module, and dynamically adjusts the control law parameters accordingly, thereby improving the dynamic response performance and stability of the system under the influence of load mutations, input disturbances and non-minimum phase characteristics.

[0027] The multi-channel analog-to-digital conversion module consists of multiple 16-bit ADC channels with high precision and synchronous sampling, respectively connected to the input voltage terminal, output voltage terminal of the switching power supply and the current detection node of the power inductor. This module is used for real-time acquisition of the input voltage (Vin), output voltage (Vout) and inductor current (IL) signals, and converts the analog quantity into digital signals and then transmits them to the digital controller. To ensure the accuracy and timing consistency of signal acquisition, the multi-channel ADC module supports the hardware trigger synchronous sampling function and is built-in with an anti-aliasing filter to suppress high-frequency noise interference.

[0028] Furthermore, during the system initialization phase, the digital controller generates an initial PWM control signal according to preset startup control parameters and drives the power switch device to operate. At the same time, the multi-channel analog-to-digital conversion module starts to continuously collect system operation data and feedback it to the parameter identification module for online modeling. The controller automatically adjusts the control gain and control strategy based on the updated system model to achieve a smooth transition from cold start to steady-state operation and maintain good response characteristics and stability during the dynamic process.

[0029] The specific process of the parameter identification module is as follows: The parameter identification module is integrated inside the digital controller and constructs a state-space model based on the nonlinear dynamic behavior of the switching power supply system. This model is used to describe the relationship between key variables in the system, including the change processes of inductor current and output voltage.

[0030] The state-space model consists of two core parts: State equation: Describes the law of change of the internal state of the system over time. Among them, the state evolution of the inductor current and output voltage is affected by the current input control quantity (such as duty cycle) and the inherent parameters of the system (such as inductance value, capacitance value, load impedance, etc.).

[0031] Observation equation: Describes the mapping relationship between the measurable variables of the system (such as input voltage, output voltage, inductor current) and the internal state, and is used to infer the unmeasurable state variables through the observable variables.

[0032] After completing the state modeling, the parameter identification module uses the extended Kalman filter algorithm to estimate the system state and unknown parameters in real time. Specifically, this algorithm includes the following steps: Prediction stage: According to the current known system state and control input, predict the system state and its uncertainty at the next moment; Update stage: Use the actual input voltage, output voltage, and inductor current data collected by the multi-channel analog-to-digital conversion module to correct the prediction result; Recursive calculation: Continuously repeat the above prediction and update processes to gradually approach the true system state and parameter values.

[0033] To improve the accuracy and robustness of parameter identification, the module also introduces a noise covariance matrix adaptive adjustment mechanism. Specifically: The system continuously monitors the difference between the actual observed value and the predicted value, that is, the observation residual; According to the change trend of the residual, automatically adjust two important parameters used to describe the system uncertainty: the process noise covariance matrix and the observation noise covariance matrix; This mechanism enables the system to maintain high identification accuracy and stability in the face of sudden load changes, input disturbances, or environmental variations.

[0034] In addition, to handle systems with non-minimum phase characteristics, especially those with right-half plane zeros, the parameter identification module also includes an identification and compensation mechanism. The specific operations are as follows: After each system model update is completed, extract the transfer function information of the current system; Determine whether there are zeros located on the right side of the complex plane; If such right-half plane zeros are detected, feedback their position information to the adaptive control law adjustment module; The controller takes corresponding measures accordingly, such as restricting the controller gain, introducing a phase compensation link, or switching to a more stable control mode, so as to suppress the transient instability phenomenon caused by the reverse response.

[0035] To accelerate the parameter convergence speed during the cold start phase of the system, the parameter identification module is also configured with an excitation signal injection strategy. The specific implementation method is as follows: In the initial stage of system power-on, the controller actively sends a small-amplitude high-frequency excitation signal with a limited duration, such as making a small periodic perturbation to the duty cycle; The multi-channel analog-to-digital conversion module synchronously collects the changes in input voltage, output voltage, and inductor current caused thereby; The parameter identification module uses this response data to drive the extended Kalman filter algorithm to accelerate the initial parameter estimation process; This method significantly shortens the identification time during the cold start phase and improves the response speed and operation stability of the system after power-on.

[0036] In summary, the present invention realizes high-precision online identification of the key parameters of the switching power supply system by establishing a nonlinear state space model, introducing the extended Kalman filter algorithm, combining the noise covariance adaptive adjustment mechanism, the right-half plane zero identification and compensation strategy, and the excitation signal injection method during the cold start phase, and significantly improves the dynamic response performance and stability of the system under complex operating conditions.

[0037] The specific implementation process of the adaptive control law adjustment module is as follows: The adaptive control law adjustment module is integrated inside the digital controller, and its core function is to dynamically adjust the control strategy and controller parameters according to the system model update information output by the parameter identification module to achieve high-performance closed-loop control of the switching power supply system.

[0038] The adaptive control law adjustment module performs the following steps: First, receive real-time updated information from the parameter identification module, including key features such as the change trend of inductor current, output voltage response speed, system time constant, and the presence of right-half plane zeros. This information reflects the current operating state and stability boundary of the system.

[0039] Next, based on the updated system model above, the module determines whether the current operating state deviates from the stable region by analyzing the system's dynamic change trend. For example, when it is detected that the output voltage recovery time becomes longer, the control gain fluctuates more severely, or the system response shows a delay, it is determined that the system may enter an unstable or critically stable state.

[0040] Subsequently, the module automatically adjusts the core parameters of the controller, including proportional gain, integral time constant, and derivative gain, etc. This adjustment process is not a fixed value setting, but continuous optimization according to the current system characteristics, enabling the controller to maintain good steady-state accuracy and transient response performance under different load conditions.

[0041] After the adjustment is completed, the new control law is output to the pulse-width modulation drive module to generate a PWM control signal adapted to the current system state, thereby driving the power switch device to work. This process effectively improves the system's response speed and anti-interference ability under load mutation or input disturbance conditions.

[0042] To further enhance the system's stability, the adaptive control law adjustment module also introduces a stability evaluation mechanism based on the Lyapunov function. Specifically, it includes: Construct a reasonable energy function based on the current system model as the Lyapunov candidate function; Calculate the rate of change of this function over time in real-time to evaluate whether the overall energy of the system tends to converge; If it is found that the rate of change of energy increases abnormally, indicating that there is a risk of system instability, immediately trigger the control strategy switching mechanism; After being triggered, the controller automatically reduces the gain, limits the bandwidth, or switches to a preset safe control mode to ensure that the system continues to operate without losing control.

[0043] In addition, for systems with non-minimum phase characteristics, especially when it is identified that there are right-half plane zeros, the module will automatically enable an improved control structure, the lead-lag compensation control strategy. The specific operations are as follows: Enable the lead link to increase the system phase margin and improve the response speed; At the same time, add a lag link to suppress the phase inversion phenomenon in the high-frequency band and prevent oscillation; Limit the overall bandwidth of the controller to avoid system instability caused by the reverse response due to right-half plane zeros; Introduce a feedforward control term to compensate in advance for the reverse change trend of the output voltage caused by the right-half plane zero; Dynamically reconstruct the entire control law structure so that the system can still maintain good control performance under non-minimum phase conditions.

[0044] To further enhance the system's ability to cope with future disturbances, the adaptive control law adjustment module also has a predictive control function. Specifically, it includes: Based on the change rate of the system model and historical operation data, predict the possible operating states within a certain period in the future; Before the load is about to jump or the input voltage fluctuates, adjust the controller parameters in advance; Use a multi-step rolling optimization algorithm, combine the current identification results with the historical response curve, and dynamically optimize the control gain configuration; Through this forward-looking control strategy, significantly improve the smoothness of the system's dynamic response, reduce overshoot and recovery time, and enhance the system's robustness to external disturbances.

[0045] In summary, the present invention realizes high-precision, high-stability, and high-response-speed dynamic control of a complex switching power supply system by introducing a variety of advanced control strategies and technical means, including adaptive adjustment of control parameters based on system model updates, Lyapunov stability criterion, right-half plane zero compensation mechanism, and predictive control strategy, and is particularly suitable for high-performance digital power applications with non-minimum phase characteristics.

[0046] The specific implementation process of the pulse width modulation drive module is as follows: The pulse width modulation drive module is integrated around the digital controller or configured independently. Its core function is to convert the dynamic control signal output by the controller into a drive signal suitable for power switching devices, and while ensuring efficient energy conversion, provide multi-level safety protection mechanisms and operation optimization strategies.

[0047] The pulse width modulation drive module performs the following steps: First, receive the real-time control signal output from the digital controller. This signal is dynamically adjusted according to the current system state and the adaptive control algorithm, and contains information such as the target duty cycle and the set value of the switching frequency. Subsequently, this module converts the received control signal into a pulse width modulation waveform with high resolution to achieve precise control of the power switching device.

[0048] Next, the module generates a pair of complementary symmetric PWM drive pulses according to the currently set switching frequency and dead time parameters. This symmetric pulse is used to drive the upper and lower arm power devices in a half-bridge or full-bridge topology, such as MOSFET or IGBT, to ensure that the main circuit operates in an ideal state, reduce voltage distortion, and improve efficiency.

[0049] During the PWM signal generation process, the module also dynamically calculates and inserts the optimal dead time in combination with the actual turn-on and turn-off delay characteristics of the power switch device. The setting of this dead time is not fixed, but is adjusted online according to the device type, temperature feedback, and system operating status, thereby effectively preventing the through short-circuit risk caused by the simultaneous conduction of the upper and lower bridge arms and improving the safety and reliability of the system.

[0050] To ensure the stable operation during the system startup phase, the pulse width modulation drive module also integrates a soft start control function. At the initial stage of system power-on, the module gradually increases the duty cycle of the PWM signal instead of directly loading it to the full-power operation state. This process can significantly suppress the current impact that may occur at the moment of startup and avoid damage to the input power supply, filter components, and load.

[0051] In addition, the module also has a variety of enhanced control and protection mechanisms. Specifically, it includes: Real-time monitoring of key electrical parameters under the system operating state, such as output current, output voltage, and the operating temperature of power devices; When detecting that overcurrent, overvoltage, or temperature anomaly signals exceed the preset threshold, immediately limit the PWM output duty cycle or completely turn off the PWM drive signal to prevent the expansion of the fault; After the fault is removed, the module automatically restarts the PWM output and synchronously updates the status information of the controller, enabling the system to resume operation smoothly without manual intervention; At the same time, the module can dynamically adjust the switching frequency according to the instructions of the digital controller, reduce the frequency under light load conditions to reduce switching losses, and increase the frequency under heavy load conditions to improve the response speed and control accuracy, thereby maintaining a high overall efficiency and stability under different load conditions.

[0052] In summary, the present invention realizes the efficient and safe drive of power switch devices by constructing a high-precision and dynamically adjustable PWM generation mechanism, combined with innovative means such as intelligent dead time control, soft start strategy, multiple fault protection, and frequency adaptive regulation, and is particularly suitable for high-performance and high-reliability digital control switching power supply systems.

[0053] The specific implementation process of the stability monitoring module is as follows: The stability monitoring module is integrated inside the digital controller and is used to monitor the operating state of the switching power supply system in real time. When detecting that the system enters an unstable or critically stable state, it actively triggers the corresponding fault tolerance mechanism to maintain the basic power supply function of the system and prevent the expansion of the fault.

[0054] The stability monitoring module performs the following steps: First, continuously collect the key operating parameters of the switching power supply system, including time series data such as output voltage, inductor current, and control signals output by the controller. These data are obtained in real time through a multi-channel analog-to-digital conversion module and analyzed online by the stability monitoring module.

[0055] Next, the module processes the collected data using the sliding window variance analysis algorithm. Specifically, historical data within a certain time period is selected as the analysis window, and the variance change trend is calculated to determine whether there are abnormal fluctuations in the system. At the same time, combined with the peak detection algorithm, identify whether there are unstable characteristics such as overshoot, oscillation, or slow recovery in the output voltage or inductor current.

[0056] When the analysis results show that any of the following situations occur, it is determined that the system has stability anomalies: The overshoot of the output voltage exceeds the preset safety threshold; After a load mutation or input disturbance occurs, the voltage recovery time is significantly extended, exceeding the normal response time range; The control signal output by the controller shows high-frequency oscillation or periodic fluctuation, indicating that the phase margin has dropped to the critical level; The system exhibits unexpected dynamic behaviors, such as an increase in response delay or an abnormal increase in control gain.

[0057] Once it is determined that there is a stability anomaly, the module immediately activates the corresponding fault tolerance mechanism, which specifically includes one or more of the following measures: Switch to a set of pre-set stable control parameter sets, which are optimized and designed to significantly improve the system stability at the cost of a small amount of response speed; Actively limit the bandwidth of the controller, reduce the gain in the high-frequency band, and prevent the oscillation from spreading due to phase inversion or right-half plane zeros; Start the soft restart process, gradually turn off the current PWM drive signal, re-initialize the controller state, and re-establish a stable output according to the soft start strategy to avoid the interruption risk caused by direct reset; At the same time, feedback the abnormal information to the system main control unit to record the fault event and provide a basis for subsequent diagnosis.

[0058] In addition, to meet the stability requirements under different working conditions, the stability monitoring module also supports the function of adaptive switching of operating modes. For example, under light load conditions, the system is more likely to have stability problems. At this time, the module automatically enhances the sensitivity of the stability criterion and intervenes in the control parameter adjustment in advance; while in the case of heavy load or frequent changes in dynamic load, the stability trigger threshold is appropriately relaxed to balance the response speed and system robustness.

[0059] In summary, the present invention realizes the intelligent monitoring and dynamic intervention of the operating state of the switching power supply system by constructing a stability criterion based on sliding window variance analysis and peak detection algorithms, combined with a multi-level fault tolerance mechanism and control parameter switching strategy, significantly improving the anti-interference ability and long-term operating reliability of the system under complex working conditions, and is particularly suitable for high-performance digital power systems with high dynamic response requirements and non-minimum phase characteristics.

[0060] Working principle of the present invention: The present invention aims to solve the problems of poor stability and slow response speed of traditional control methods in non-minimum phase systems. The system includes a digital controller, a multi-channel analog-to-digital conversion module, a parameter identification module, an adaptive control law adjustment module, a pulse width modulation drive module, and a stability monitoring module. Among them, the digital controller uses a high-performance DSP or FPGA to execute an adaptive control algorithm; the multi-channel ADC module collects input voltage, output voltage, and inductor current signals in real time; the parameter identification module online identifies key system parameters based on the extended Kalman filter algorithm and updates the system model, especially for identifying and compensating right-half plane zeros; the adaptive control law adjustment module dynamically adjusts the control strategy according to the updated model, introduces the Lyapunov function to evaluate stability, and combines predictive control to improve robustness; the pulse width modulation drive module generates a high-resolution PWM signal with functions of dynamic dead-time adjustment, soft start, and frequency adaptability; the stability monitoring module judges the system state through sliding window variance analysis and peak detection, and triggers the fault tolerance mechanism when abnormal to ensure the stable operation of the system. The present invention realizes high-precision modeling, intelligent control, and dynamic optimization of complex switching power supply systems, significantly improving the response performance and stability of the system under load mutation, input disturbance, and non-minimum phase characteristics, and is suitable for high-reliability digital power application scenarios.

[0061] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by software simulation of a large amount of collected data to get a formula closest to the actual situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0062] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more sets of available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0063] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context.

[0064] It should be understood that in various embodiments of the present application, the sequence numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0065] The above has described in detail one embodiment of the present invention, but the content described is only the preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the scope covered by the patent of the present invention.

Claims

1. A digital control-based switching power supply dynamic response regulation system, characterized in that, Including: A digital controller for executing an adaptive control algorithm and generating a control signal; A multi-channel analog-to-digital conversion module connected to the digital controller for real-time acquisition of the input voltage, output voltage, and inductor current signals of the switching power supply system; A parameter identification module integrated in the digital controller for online identification of key system parameters based on the extended Kalman filter algorithm to update the system model; An adaptive control law adjustment module coupled to the parameter identification module for dynamically adjusting the control gain and control strategy according to the updated system model to compensate for the impact of non-minimum phase characteristics on system stability; A pulse width modulation driving module connected to the digital controller for generating corresponding PWM control pulses according to the adjusted control signal to drive the power switching device; A stability monitoring module for monitoring the system operation status and triggering a fault tolerance mechanism in case of anomalies to maintain the basic functions of the system.

2. The dynamic response regulation system of a switching power supply based on digital control according to claim 1, characterized in that, The parameter identification module performs the following steps: Construct a non-linear state space model of the switching power supply system, including the state equations and observation equations of the inductor current and output voltage; Perform real-time prediction and update on the state equations based on the extended Kalman filter algorithm to estimate the internal state variables and unknown parameters of the system; Use the input voltage, output voltage, and inductor current data collected by the multi-channel analog-to-digital conversion module as the observation input to drive the parameter identification process; Periodically output the updated system parameters to the adaptive control law adjustment module to achieve dynamic compensation.

3. The dynamic response regulation system of a switching power supply based on digital control according to claim 2, wherein A noise covariance adaptive adjustment mechanism is introduced in the extended Kalman filter algorithm, specifically including: Real-time monitoring of the system operation status and evaluation of the observation residual; Dynamically adjust the process noise covariance matrix Q and the observation noise covariance matrix R according to the residual change trend; Improve the parameter identification accuracy and enhance the robustness of the system under load mutations or input disturbances.

4. A digital control-based switching power supply dynamic response regulation system according to claim 2, characterized in that, The parameter identification module also includes the steps of identifying and compensating the position of the right half-plane zero: Extract the transfer function information after the system model is updated to determine whether there is a right half-plane zero; If it exists, feedback its position information to the adaptive control law adjustment module; The controller adjusts the control strategy according to this information, including gain limitation, phase compensation, or switching the control mode, to suppress the dynamic instability caused by non-minimum phase behavior; The parameter identification module achieves fast convergence through the following methods: Inject a small-amplitude excitation signal with a limited duration during the system startup phase; Use the extended Kalman filter algorithm to process the excitation response data to accelerate the initial parameter estimation process; Shorten the identification time in the system cold start phase and improve the power-on response speed and stability.

5. A digital control-based switching power supply dynamic response regulation system according to claim 1, characterized in that, The adaptive control law adjustment module performs the following steps: Receive the updated system model information from the parameter identification module, including the inductor current dynamics, output voltage response characteristics, and the position of the right half-plane zero; Judge whether the current operation state deviates from the stable region based on the system model change trend; Dynamically adjust the proportional, integral, and differential gain coefficients of the PID controller; Output the updated control law to the pulse width modulation driving module to optimize the transient response performance under load mutations.

6. A digital control-based switching power supply dynamic response regulation system according to claim 5, characterized in that, The adaptive control law adjustment module further includes a stability criterion evaluation step based on the Lyapunov function: Construct a Lyapunov candidate function applicable to the current system model; Calculate its derivative in real time to judge the convergence of the system energy; If an unstable trend is detected, trigger the control gain attenuation mechanism or switch to a preset safe control mode; Maintain the closed-loop stability of the system without sacrificing the response speed.

7. A digital control-based switching power supply dynamic response regulation system according to claim 5, characterized in that The adaptive control law adjustment module automatically switches the control strategy according to the existence of right-half plane zeros, specifically including: When it is recognized that the system has non-minimum phase characteristics, enable the lead-lag compensation control structure; Limit the controller bandwidth to avoid phase inversion and oscillation in the high-frequency band; Introduce a feedforward term to cancel the reverse response behavior caused by the right-half plane zeros; Dynamically reconstruct the control law to achieve robust control of the non-minimum phase system; The adaptive control law adjustment module also executes the following enhanced control strategies: Predict the possible future operating states according to the change rate of the system model; Adjust the control gain in advance to cope with upcoming load jumps or input disturbances; Perform multi-step rolling optimization by combining historical data with the current identification results; Improve the smoothness and anti-interference ability of the system dynamic response through predictive control strategies.

8. A digital control-based switching power supply dynamic response regulation system according to claim 1, characterized in that, The pulse width modulation driving module executes the following steps: Receive the dynamically adjusted control signal from the digital controller and convert it into a high-resolution PWM waveform; Generate complementary symmetric PWM drive pulses according to the current switching frequency set value and dead time configuration; During the generation process, combine the turn-on and turn-off delay characteristics of the power switch device, and dynamically calculate and insert the optimal dead time; Output to the power switch device to achieve efficient and low-distortion energy conversion, while preventing the risk of shoot-through between the upper and lower bridge arms.

9. A digital control-based switching power supply dynamic response regulation system according to claim 8, characterized in that, The pulse width modulation driving module also executes the following enhanced control and protection strategies: Implement soft start control during the system power-on stage, gradually increase the PWM duty cycle to suppress the starting inrush current; Real-time monitor overcurrent, overvoltage and temperature anomaly signals, and immediately limit or turn off the PWM output when a fault is detected; Automatically restart the PWM output and synchronize the controller state after the fault is recovered to ensure the safe and reliable operation of the system; At the same time, dynamically adjust the switching frequency according to the controller instruction to optimize the efficiency and stability of the system under different load conditions.

10. A digital control-based switching power supply dynamic response regulation system according to claim 1, characterized in that, The stability monitoring module executes the following steps: Real-time collect and analyze the time series data of the output voltage, inductor current and controller output control quantity; Based on the sliding window variance analysis and peak detection algorithm, identify whether the system enters the oscillation or unstable state; When it is detected that the overshoot exceeds the set threshold, the recovery time is abnormally extended or the phase margin drops to the critical value, it is determined that the stability is abnormal; Trigger the fault tolerance mechanism, including switching to the preset stable control parameter set, limiting the controller bandwidth or starting the soft restart process, to restore the system stability and maintain the basic power supply function.

Images