An optimal super-hyperbolic-spiral sliding mode compound control method for three-level boost converter with constant power load

Abstract

Aiming at three-level Boost converter with constant power load, due to the inherent negative impedance characteristic of constant power load, it is easy to cause system low frequency oscillation, bus voltage instability, dynamic response lag, weak anti-disturbance ability, and single linear control robustness is poor, nonlinear control steady state accuracy is low. The invention provides an optimal super spiral sliding mode compound control strategy which takes into account the steady state accuracy and dynamic anti-disturbance performance. First, the state space average method is used to establish the mathematical model of the system, and then the precise feedback linearization technology is used to realize the linearization of the original nonlinear system. For the linearized mathematical model, the optimal control law and the super spiral sliding mode control law are designed in turn, and the complete compound control is formed on this basis. Finally, the robust stability of the system is verified, and the correctness of the theoretical analysis and the effectiveness of the control scheme are further verified through simulation experiment.

Description

Technical Field

[0001] This invention belongs to the field of power electronics technology, specifically relating to an optimal super-spiral sliding mode composite control method for a three-level Boost converter with constant power load. Background Technology

[0002] Compared to traditional Boost converters, three-level Boost converters exhibit lower voltage stress on switching devices and a greater number of output levels, thus attracting widespread attention from researchers both domestically and internationally. To better simulate real-world applications, this invention introduces a three-level Boost converter with a constant power load as the subject of this study, investigating the corresponding control strategies.

[0003] However, simple optimal control can only operate with small signals near the equilibrium point, leading to instability under load fluctuations; simple sliding mode control lacks optimal performance indicators, exhibiting dynamic overshoot and unconstrained energy consumption. Therefore, to address the weaknesses of single optimal control in robustness and the poor dynamic performance of single super-spiral sliding mode control, this invention integrates linear quadratic optimal control with super-spiral sliding mode control to construct an optimal super-spiral sliding mode composite control strategy. The method for selecting the output function is studied to ensure the system meets the exact feedback linearization condition, transforming the nonlinear system into a pseudo-linear system, and a corresponding controller is designed. Simulation experiments are used to verify the effectiveness of the proposed control method. Summary of the Invention

[0004] This invention aims to overcome the shortcomings of existing technologies and provide an optimal super-spiral sliding mode composite control method for a three-level Boost converter with constant power load.

[0005] To achieve the above objectives, the optimal super-spiral sliding mode composite control method for a three-level Boost converter with a constant power load includes the following steps: S1. Using the state-space averaging method, select inductor current and output voltage as state variables to establish a state-space mathematical model of a three-level Boost converter with constant power load. S2. Based on differential geometry theory, nonlinear mathematical models are transformed into Brunofsky canonical forms through precise feedback linearization techniques. S3. Design the optimal control law and the superspiral sliding mode control law respectively, and construct the complete optimal superspiral sliding mode composite control law by parallel superposition. S4. Perform robust stability analysis to achieve high-precision and stable control of the output voltage.

[0006] Preferably, step S1 specifically includes the following process: Take the inductor current of a three-level Boost converter with a constant power load i L and output voltage vo As a state variable, assuming the converter operates in the continuous inductor current mode, the system has two operating modes: switch off and switch on.

[0007] In these two modes, the state equations can be obtained using the KCL and KVL laws: in V in This is the power supply voltage. C For capacitors, L It's an inductor. R For load, the duty cycle of the switching transistor d ∈(0,1).

[0008] Preferably, step S2 specifically includes: Let's consider an initial state as... x ( t 0) = x For a nonlinear system with zero, its state equation can be expressed as: For the affine nonlinear system above, let the state variables be... x = ( x 1, x 2, … , x n ) T ∈ R n Control input u ∈ R Control output y ∈ R ,in f ( x ), g ( x Both ) represent vector fields. When there exists x 0's neighborhood Φ ∈ R n This ensures that the output function satisfies the following recurrence relation: L g L f k h ( x )=0, 0≤ k ≤ r -1 L g L f r-1h ( x )≠0 This system is said to have a relative order within the specified domain. r .

[0009] In the above formula, L f k h ( x )= ( L f k-1 h ( x )) / f ( x )= express h ( x Along the vector field f ( x )of k The first-order Lie derivative is: L f h ( x )= h ( x ) / f ( x Similarly, L g L f k h ( x )= ( L f k h ( x )) / g ( x )= express L f k h ( x Along the vector field g ( x The first-order Lie derivative of ).

[0010] For a single-input single-output system, the necessary and sufficient condition for achieving exact feedback linearization is that the relative order of the system is equal to the dimension of the state space. n At this point, the following two constraints must be met: (1) Inx All near 0 x ,matrix[ g ( x ) ad f g ( x ... ad f n-2 g ( x ) ad f n-1 g ( x Maintain full rank and keep the rank value constant. n ; (2) Vector field set B ={ g ( x ), ad f g ( x ),…, ad f n-2 g ( x )}, at point x The involution condition is satisfied at point 0. The Lie bracket operation between vector fields is defined as follows: ad f g ( x )= f ( x )- g ( x ).

[0011] When the above conditions are met, there exists a function η ( x ), so that at point x The relative order of the system at point 0 is equal to n At this point, coordinate transformation can be used: z = φ ( x )= = have to: = In the formula, α ( x )= L f n η (x ), β ( x )= L g L f n-1 η ( x All of them are x , a nonlinear scalar function. If we let: v = α ( x )+ β ( x ) u The original system can be precisely linearized to the Brunovsky standard form: = Az + Bv In the formula, A = , B = .

[0012] Based on this standard model, design a feedback control law: u =- + v In the formula v These are the control variables for a linear system. Based on this, we can target... v Design an effective linear controller.

[0013] To verify whether the mathematical model of the three-level Boost converter with a constant power load satisfies the exact feedback linearization condition, state variables are taken... x =[ x 1, x 2] T =[ i L , v o ] T The mathematical model is written as an affine nonlinear mathematical model. = f ( x ) +g ( x ) d = + The vector field D of the system can be obtained from the above formula: g (x )= , ad f g ( x )= D={ g ( x ), ad f g ( x )}= From the above equation, it can be seen that the rank of the vector field D is 2, which is equal to the order of the system, and the vector field D is in x = x At position 0, the circuit is closed, satisfying the necessary and sufficient condition for precise feedback linearization. Therefore, a three-level Boost converter system with a constant power load can achieve precise feedback linearization.

[0014] Selecting inductor current i L As the system's output function y The duty cycle can be obtained by taking the derivative and performing a coordinate transformation. d With control v The relationship is as follows: Preferably, step S3 specifically includes: The core of the optimal control problem lies in the selection of the weighting matrix. This is achieved by rationally determining the state weighting matrix in the performance index function. Q and control weighting matrix R The optimal state feedback control law can be derived from this. The linear quadratic optimal control algorithm aims to achieve the best control effect of the system under certain performance indicators by minimizing the weighted combination of state error and control energy. According to the theory of linear quadratic regulators, the state equation and output equation for an infinite-time linear time-invariant system are as follows: In the formula, m ( t )yes e dimensional state vector, v ( t )for r An uncontrolled control vector. y 1 is n 3D output vector, A , B , C It is a constant matrix. The control objective is to find the optimal control function. vopt This minimizes the quadratic performance index functional defined below: In the formula, Q 1 is e×e A positive semi-definite constant matrix, Q 2 is r×r A positive definite constant matrix.

[0015] According to the LQR theorem, when { A , B When it is fully controllable, its optimal control v opt It exists and is unique, and its value is determined by the following formula: v opt =- Q 2 -1 BFm In the formula, F express s×s A symmetric positive definite constant matrix of dimension 1, which satisfies the following Riccati matrix algebra equation: A T F+FA-FBS -1 B T F+Q =0 From the above analysis, it can be seen that the three-level Boost converter with a constant power load has been completely linearized into a purely integral linear system. Now, we design a linear quadratic optimal state regulator for the three-level Boost converter system with a constant power load. Therefore, we take the aforementioned new state variables... m =[ m 1, m 2] T ,in, m 1= x 1- x 1ref , m 2= x 2- x 2ref .so m The first derivative can be expressed as: The above formula can be written in the following form: in, A = , B = First, we need to verify the controllability of the system: rank [ B AB ] = rank =2 Obviously { A , B The condition of complete controllability is satisfied, therefore the corresponding optimal control law is... v opt It exists and is unique.

[0016] Since this system is a single-input single-output system, therefore it is assumed that... Q 1= , Q 2 = ( q 2), put A , B , Q 1, Q Substituting 2, we get: Summarized as follows: because P It is a 2×2 symmetric positive definite constant matrix, so let p 12 = p 21 Seeking P for: Simplifying the above equation, we get: make k 1= q 1 1 / 2 q 2 -1 / 2 , k 2= q 1 1 / 4 q 2 -1 / 4 ,so k 1 = 1 / 2 k 2 2 ,so: The superspiral sliding mode control algorithm is an advanced sliding mode control method that significantly reduces chattering in the system by introducing integral quantities into the reaching law.

[0017] Select the sliding surface as s = i L -i Lref ; Taking the first derivative with respect to the sliding surface, we get: = α ( x ) +β ( x ) d ; in, α ( x (This does not include control quantities) d Item, β ( x ) is the control quantity d The coefficient term; The standard superspiral sliding mode control law is: v sta = v 1+ v 2; ; ; In the formula, w 1. w 2 represents the gain coefficient of the superspiral algorithm, and all of them are greater than 0. z It is an integral auxiliary state.

[0018] in, v 2 is the equivalent control term, used to offset the nominal dynamics of the system: v 2=- α ( x ) / β ( x ); Substituting into the original model, the superhelical sliding mode control law is obtained as follows: v sta =1-2 V in / v o , ; The optimal control output is linearly superimposed with the superspiral sliding diaphragm compensation, which constitutes the final output duty cycle control quantity of this invention: v = v opt + v sta ; The optimal control component ensures optimal nominal dynamic performance of the system, while the superspiral sliding mode component dynamically compensates for system nonlinearity and disturbances. Under steady-state conditions, the sliding mode compensation effect is weak. The system primarily relies on optimal control; however, under conditions of sudden load changes, parameter drift, and input voltage fluctuations, the superspiral sliding mode provides rapid output compensation to suppress oscillations and instability.

[0019] Preferably, step S4 specifically includes the following process: Since the linearized system is fully controllable, the positive definite weight matrix is ​​chosen to satisfy the observability condition, and the closed-loop system matrix formed by the LQR optimal state feedback is the Hurwitz matrix. Under the nominal operating conditions, the closed loop gradually stabilizes.

[0020] For the standard control law of superspiral sliding mode, system parameter perturbations, load jumps, and input voltage fluctuations are uniformly classified as lumped disturbances. k ( t ), satisfying the boundedness of the perturbation derivative: | |≤ U , ( U (is a constant); As long as the control gain satisfies: w 1> , w 1> U ; synovial variables s Globally converged in finite time s =0 sliding surface (stable during the reaching stage); after reaching the sliding surface, the sliding mode is maintained, and the tracking error continues to converge (stable during the sliding stage); control quantity v sta It is continuous and does not exhibit the high-frequency chattering characteristic of traditional sliding mode.

[0021] In summary, the proposed optimal superspiral sliding mode composite control achieves nominal optimal dynamic performance based on linear quadratic optimal control theory. It suppresses nonlinearity, parameter perturbation, and external disturbances with constant power loads by relying on superspiral sliding mode control, while fully completing the reachability and closed-loop stability verification, and the system is stable over a wide range. Attached Figure Description

[0022] Figure 1 This is a topology diagram of a three-level Boost converter with a constant power load; Figure 2 This is a system control block diagram for a three-level Boost converter with a constant power load. Figure 3 This is a simulation model of a three-level Boost converter with a constant power load; Figure 4 For a three-level Boost converter with constant power load RSimulated waveform during the change.

[0023] Figure 5 The input voltage of a three-level Boost converter with a constant power load V in Simulated waveform during the change. Detailed Implementation

[0024] The embodiments of the present invention will be described in further detail and clearly below with reference to the accompanying drawings and specific implementation methods.

[0025] The specific implementation scheme of the present invention to solve the above-mentioned technical problems is as follows: The first step is to use the state-space averaging method to select inductor current and output voltage as state variables and establish a state-space mathematical model of a three-level Boost converter with constant power load. The topology of a three-level Boost converter with constant power load is as follows: Figure 1 As shown in the figure V in Indicates the input voltage. v o For output voltage, L This is the value of the energy storage inductance. C For output capacitor, R The load resistance is the duty cycle of the switching transistor. d ∈(0,1).

[0026] Take the inductor current of a three-level Boost converter with a constant power load i L and output voltage v o As a state variable, assuming the converter operates in the continuous inductor current mode, the system has two operating modes: switch off and switch on.

[0027] In these two modes, the state equations can be obtained using the KCL and KVL laws: The second step is to transform the nonlinear mathematical model into the Brunofsky canonical form using precise feedback linearization techniques, based on differential geometry theory. Let's consider an initial state as... x ( t 0) = x For a nonlinear system with zero, its state equation can be expressed as: For the affine nonlinear system above, let the state variables be... x = ( x 1, x2, … , x n ) T ∈ R n Control input u ∈ R Control output y ∈ R ,in f ( x ), g ( x Both ) represent vector fields. When there exists x 0's neighborhood Φ ∈ R n This ensures that the output function satisfies the following recurrence relation: L g L f k h ( x )=0, 0≤ k ≤ r -1 L g L f r-1 h ( x )≠0 This system is said to have a relative order within the specified domain. r .

[0028] In the above formula, L f k h ( x )= ( L f k-1 h ( x )) / f ( x )= express h ( x Along the vector field f ( x )of k The first-order Lie derivative is: L f h ( x )= h ( x ) / f ( x Similarly, L g L f k h ( x )= ( L f k h ( x )) / g ( x )= express L f k h ( x Along the vector field g ( x The first-order Lie derivative of ).

[0029] For a single-input single-output system, the necessary and sufficient condition for achieving exact feedback linearization is that the relative order of the system is equal to the dimension of the state space. n At this point, the following two constraints must be met: (1) In x All near 0 x ,matrix[ g ( x ) ad f g ( x ... ad f n-2 g ( x ) ad f n-1 g ( x Maintain full rank and keep the rank value constant. n ; (2) Vector field set B ={ g ( x ), ad f g ( x ),…, ad f n-2 g ( x )}, at point x The involution condition is satisfied at point 0. The Lie bracket operation between vector fields is defined as follows:ad f g ( x )= f ( x )- g ( x ).

[0030] When the above conditions are met, there exists a function η ( x ), so that at point x The relative order of the system at point 0 is equal to n At this point, coordinate transformation can be used: z = φ ( x )= = have to: = In the formula, α ( x )= L f n η ( x ), β ( x )= L g L f n-1 η ( x All of them are x , a nonlinear scalar function. If we let: v = α ( x )+ β ( x ) u The original system can be precisely linearized to the Brunovsky standard form: = Az + Bv In the formula, A = , B = .

[0031] Based on this standard model, design a feedback control law: u =- + v In the formula v These are the control variables for a linear system. Based on this, we can target... v Design an effective linear controller.

[0032] To verify whether the mathematical model of the three-level Boost converter with a constant power load satisfies the exact feedback linearization condition, state variables are taken... x =[ x 1, x 2] T =[ i L , v o ] T The mathematical model is written as an affine nonlinear mathematical model. = f ( x ) +g ( x ) d = + The vector field D of the system can be obtained from the above formula: g ( x )= , ad f g ( x )= D={ g ( x ), ad f g ( x )}= From the above equation, it can be seen that the rank of the vector field D is 2, which is equal to the order of the system, and the vector field D is in x = x At position 0, the circuit is closed, satisfying the necessary and sufficient condition for precise feedback linearization. Therefore, a three-level Boost converter system with a constant power load can achieve precise feedback linearization.

[0033] Selecting inductor current i L As the system's output function y The duty cycle can be obtained by taking the derivative and performing a coordinate transformation. d With control v The relationship is as follows: The third step is to design the optimal control law and the superspiral sliding mode control law respectively, and to construct the complete optimal superspiral sliding mode composite control law by parallel superposition. The core of the optimal control problem lies in the selection of the weighting matrix. This is achieved by rationally determining the state weighting matrix in the performance index function. Q and control weighting matrix R The optimal state feedback control law can be derived from this. The linear quadratic optimal control algorithm aims to achieve the best control effect of the system under certain performance indicators by minimizing the weighted combination of state error and control energy. According to the theory of linear quadratic regulators, the state equation and output equation for an infinite-time linear time-invariant system are as follows: In the formula, m ( t )yes e dimensional state vector, v ( t )for r An uncontrolled control vector. y 1 is n 3D output vector, A , B , C It is a constant matrix. The control objective is to find the optimal control function. v opt This minimizes the quadratic performance index functional defined below: In the formula, Q 1 is e×e A positive semi-definite constant matrix, Q 2 is r×r A positive definite constant matrix.

[0034] According to the LQR theorem, when { A , B When it is fully controllable, its optimal control v opt It exists and is unique, and its value is determined by the following formula: v opt =- Q 2 -1 BFm In the formula, F express s×s A symmetric positive definite constant matrix of dimension 1, which satisfies the following Riccati matrix algebra equation: A TF+FA-FBS -1 B T F+Q =0 From the above analysis, it can be seen that the three-level Boost converter with a constant power load has been completely linearized into a purely integral linear system. Now, we design a linear quadratic optimal state regulator for the three-level Boost converter system with a constant power load. Therefore, we take the aforementioned new state variables... m =[ m 1, m 2] T ,in, m 1= x 1- x 1ref , m 2= x 2- x 2ref .so m The first derivative can be expressed as: The above formula can be written in the following form: in, A = , B = First, we need to verify the controllability of the system: rank [ B AB ] = rank =2 Obviously { A , B The condition of complete controllability is satisfied, therefore the corresponding optimal control law is... v opt It exists and is unique.

[0035] Since this system is a single-input single-output system, therefore it is assumed that... Q 1= , Q 2 = ( q 2), put A , B , Q 1, Q Substituting 2, we get: Summarized as follows: because PIt is a 2×2 symmetric positive definite constant matrix, so let p 12 = p 21 Seeking P for: Simplifying the above equation, we get: make k 1= q 1 1 / 2 q 2 -1 / 2 , k 2= q 1 1 / 4 q 2 -1 / 4 ,so k 1 = 1 / 2 k 2 2 ,so: The superspiral sliding mode control algorithm is an advanced sliding mode control method that significantly reduces chattering in the system by introducing integral quantities into the reaching law.

[0036] Select the sliding surface as s = i L - i Lref ; Taking the first derivative with respect to the sliding surface, we get: = α ( x ) +β ( x ) d ; in, α ( x (This does not include control quantities) d Item, β ( x ) is the control quantity d The coefficient term; The standard superspiral sliding mode control law is: v sta = v 1+ v 2; ; ; In the formula, w 1.w 2 represents the gain coefficient of the superspiral algorithm, and all of them are greater than 0. z It is an integral auxiliary state.

[0037] in, v 2 is the equivalent control term, used to offset the nominal dynamics of the system: v 2=- α ( x ) / β ( x ); Substituting into the original model, the superhelical sliding mode control law is obtained as follows: v sta =1-2 V in / v o , ; The optimal control output is linearly superimposed with the superspiral sliding diaphragm compensation, which constitutes the final output duty cycle control quantity of this invention: v = v opt + v sta ; The optimal control component ensures optimal nominal dynamic performance of the system, while the superspiral sliding mode component dynamically compensates for system nonlinearity and disturbances. Under steady-state conditions, the sliding mode compensation effect is weak. The system primarily relies on optimal control; however, under conditions of sudden load changes, parameter drift, and input voltage fluctuations, the superspiral sliding mode provides rapid output compensation to suppress oscillations and instability.

[0038] The fourth step is to perform robust stability analysis to achieve high-precision and stable control of the output voltage.

[0039] Since the linearized system is fully controllable, the positive definite weight matrix is ​​chosen to satisfy the observability condition, and the closed-loop system matrix formed by the LQR optimal state feedback is the Hurwitz matrix. Under the nominal operating conditions, the closed loop gradually stabilizes.

[0040] For the standard control law of superspiral sliding mode, system parameter perturbations, load jumps, and input voltage fluctuations are uniformly classified as lumped disturbances. k ( t ), satisfying the boundedness of the perturbation derivative: | |≤ U , ( U (is a constant); As long as the control gain satisfies: w 1> , w 1>U ; synovial variables s Globally converged in finite time s =0 sliding surface (stable during the reaching stage); after reaching the sliding surface, the sliding mode is maintained, and the tracking error continues to converge (stable during the sliding stage); control quantity v sta It is continuous and does not exhibit the high-frequency chattering characteristic of traditional sliding mode.

[0041] In summary, the proposed optimal superspiral sliding mode composite control achieves nominal optimal dynamic performance based on linear quadratic optimal control theory. It suppresses nonlinearity, parameter perturbation, and external disturbances with constant power loads by relying on superspiral sliding mode control, while fully completing the reachability and closed-loop stability verification, and the system is stable over a wide range.

[0042] To verify the effectiveness of the optimal superspiral sliding mode control method proposed in this invention, this embodiment uses the Matlab / Simulink numerical simulation platform to construct a simulation model of a three-level Boost converter with a constant power load for research. The specific circuit is as follows: Figure 3 As shown in the table below, the parameters of the three-level Boost converter with constant power load used in this embodiment are as follows: Figure 4 Given R Simulated waveforms of the system when the ohmmeter jumps from 50Ω to 80Ω at 0.35s and 0.3s respectively, and when it drops from 80Ω back to 50Ω. R When a disturbance occurs, the output current i o Capable of rapid tracking R Transformation, while the optimal superspiral sliding mode control strategy can enable v o Stable at 15V, which is the reference value. v oref Simulation data show that the proposed optimal superspiral sliding mode control strategy can maintain excellent control performance under load disturbance conditions, and the overshoot is almost negligible.

[0043] Figure 5 Given V in Simulated waveforms of the system when the voltage jumps from 5V to 7V at 0.4s and 0.45s, respectively, and when the voltage jumps back from 7V to 5V. V in During the transition, the optimal superspiral sliding mode control strategy can enable... v o It is stabilized at 15V, achieving fast and accurate tracking of the output voltage to the reference value. It has better dynamic and static regulation characteristics in suppressing disturbances and exhibits stronger robustness. In summary, this invention proposes an optimal superspiral sliding mode control method for a three-level Boost converter with a constant power load. First, a mathematical model of the system is established using the state-space averaging method. Then, precise feedback linearization technology is applied to linearize the original nonlinear system. An optimal superspiral sliding mode controller is designed, taking full account of external disturbances. Finally, simulation experiments verify that the proposed control method has advantages in resisting disturbances and improving dynamic and static performance, demonstrating good engineering application value.

[0044] The embodiments described above should be understood only as specific illustrations of this invention and are not intended to limit the specific scope of protection of this invention. After reading the description of this invention, those skilled in the art will understand that this invention can have various changes and modifications. Any changes, modifications, substitutions, combinations, simplifications, improvements, etc., made within the spirit and principles of this application should be considered equivalent substitutions and are included within the scope of protection of this invention.

Claims

1. An optimal superspiral sliding mode composite control method for a three-level Boost converter with a constant power load, characterized in that: Includes the following steps: S1. Using the state-space averaging method, select inductor current and output voltage as state variables to establish a state-space mathematical model of a three-level Boost converter with constant power load. S2. Based on differential geometry theory, the nonlinear mathematical model of the converter is accurately linearized and decoupled into a linear integral system. S3. Design the optimal control law and the super-spiral sliding mode control law respectively, and construct a composite control strategy by superimposing the control quantities. S4. Conduct robust stability analysis to achieve high-precision and stable control of the closed-loop system.

2. The optimal superspiral sliding mode composite control method for a three-level Boost converter with a constant power load according to claim 1, characterized in that: In step S1, the three-level Boost converter with constant power load operates in two modes: on and off. Let the system duty cycle be... d The duty cycle ranges from (0,1). Under these two modes, the state-space average equations are obtained using the KCL and KVL laws.

3. The optimal superspiral sliding mode composite control method for a three-level Boost converter with a constant power load according to claim 1, characterized in that: In step S2, the mathematical model is transformed into an affine nonlinear form. By calculating the system's vector field, it is found that the rank of the matrix is ​​equal to the order of the system, and the vector field is integrable, satisfying the necessary and sufficient condition for the system to achieve precise feedback linearization. The linearization matrix is ​​constructed, and the relationship between the output duty cycle and the control law is solved, completing the linearization and decoupling of the nonlinear system.

4. The optimal superspiral sliding mode composite control method for a three-level Boost converter with a constant power load according to claim 1, characterized in that: In step S3, the optimal control law is designed. v opt To ensure optimal dynamic performance of the system; design a super-spiral sliding mode control law. v sta It is responsible for dynamically compensating for nonlinearity and disturbances. The optimal linear quadratic reference control quantity and the superspiral sliding mode compensation quantity are superimposed and fused in real time to form the optimal superspiral sliding mode composite control law, and a unified output duty cycle signal is generated to form a complete closed-loop control, achieving voltage regulation control that balances optimal dynamics and strong robustness.

5. The optimal superspiral sliding mode composite control method for a three-level Boost converter with a constant power load according to claim 1, characterized in that: In step S4, nominal optimal dynamic performance is achieved by relying on linear quadratic optimal control theory, and nonlinearity and disturbances with constant power load are suppressed by super-helical sliding mode control, while accessibility and closed-loop stability are demonstrated.

6. The optimal superspiral sliding mode composite control method for a three-level Boost converter with a constant power load according to claim 1, characterized in that: This control method can be applied to DC-DC converter topologies with constant power loads, such as various interleaved parallel converters, bidirectional DC-DC converters, dual active bridge isolation converters, and various isolated switching converters.

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