A two-degree-of-freedom internal model control method based on three-state boost converter

Abstract

In order to solve the problem of right half plane zero in continuous inductor current mode of three-state Boost converter, a two-degree-of-freedom internal model control method is proposed. Firstly, the state-space averaging method is used to establish the mathematical model of the system, and then the precise feedback linearization technology is used to linearize the original nonlinear system. Under the condition of fully considering external disturbance, a two-degree-of-freedom internal model controller is designed. Under dynamic response, the output current can quickly track the jump of load resistance, and the output voltage can quickly adjust to the vicinity of the reference value. The experimental results fully verify the correctness of the theoretical analysis and the effectiveness of the control scheme, which shows that the proposed control strategy can significantly improve the steady-state and dynamic regulation performance of the system.

Description

Technical Field

[0001] This invention belongs to the field of DC-DC converter control strategy technology, specifically involving a two-degree-of-freedom internal model control method based on a three-state Boost converter, which is suitable for DC conversion scenarios with stringent requirements for output accuracy, dynamic response speed, and system stability. Background Technology

[0002] Traditional Boost DC-DC converters suffer from unstable zero dynamics, resulting in narrow bandwidth and poor dynamic response. To address this, the three-state Boost converter innovates its topology by introducing a freewheeling loop with an additional inductor current. Its core principle is to extend the discharge time while maintaining the charging time, thereby effectively eliminating the system's non-minimum phase characteristic. Compared to traditional Boost converters, the improved three-state structure avoids the negative modulation phenomenon caused by the non-minimum phase characteristic during duty cycle adjustment, significantly improving system stability.

[0003] However, when the three-state Boost converter operates in the continuous conduction mode of the inductor current, the open-loop transfer function exhibits a right-half-plane zero, significantly limiting the transient response performance of the closed-loop system. Furthermore, existing control schemes are mostly based on small-signal models near the operating point, and the designed control schemes are linear controllers and highly sophisticated, failing to reflect the nonlinear characteristics of the converter and making it difficult to achieve global stability over a wide range.

[0004] Therefore, to fully utilize the potential of the three-state Boost converter and further improve its performance, this invention proposes a two-degree-of-freedom internal model control method based on differential geometry theory. The method for selecting the output function is studied to ensure that the system satisfies the exact feedback linearization condition, thus linearizing the nonlinear system into a pseudo-linear system, and a corresponding controller is designed. Simultaneously, simulation experiments are used to verify the effectiveness of the proposed control method. Summary of the Invention

[0005] This invention aims to overcome the shortcomings of existing technologies and provide a two-degree-of-freedom internal model control method based on a three-state Boost converter.

[0006] To achieve the above objectives, the two-degree-of-freedom internal model control method based on a three-state Boost converter 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 the three-state Boost converter. S2. Based on differential geometry theory, nonlinear mathematical models are transformed into Brunofsky canonical forms through precise feedback linearization techniques. S3. Construct a two-degree-of-freedom internal model control structure, set up a tracking controller and an anti-disturbance controller, and independently adjust the system's reference tracking performance and anti-disturbance robustness performance respectively; S4. Design low-pass filters that enable the controller to function, and tune the filter parameters to obtain the transfer functions of the tracking controller and the disturbance rejection controller. S5. Under the two operating conditions of precise model matching and mismatch, robust stability analysis is performed to suppress input voltage fluctuations and load step disturbances, thereby achieving high-precision and stable control of the output voltage.

[0007] Preferably, step S1 specifically includes: Take the inductor current of the three-state Boost converter i L and output voltage v o As a state variable, assuming the converter operates in continuous inductor current mode, based on the different on / off states of the two switches, the three-state Boost converter has three operating states, each with a different duty cycle. d c This refers to the duty cycle during the capacitor charging phase. d a This represents the duty cycle during the capacitor discharge phase. d f This refers to the duty cycle during the continuous flow phase.

[0008] The duty cycle in the three states satisfies the following constraints: d c + d a + d f = 1 Under these three 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 c , d a 、d f ∈(0,1).

[0009] 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 F ∈ 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 .

[0010] 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: Lf 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 ).

[0011] 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 ),..., adf 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 ).

[0012] When the above conditions are met, there exists a function or ( 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 = f ( x )= = have to: = In the formula, α ( x )= L f n or ( x ), β ( x )= L g L f n-1 or ( 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 = .

[0013] 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.

[0014] To verify whether the mathematical model of the three-state Boost converter satisfies the exact feedback linearization condition, we take the state variables... 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 = + Among them, matrix f ( x )=[0, - x 2 / RC ] T ,matrix g ( x )=[ g 1( x ), g 2( x )] T ,and g 1( x )=[ V in / L , 0] T , g 2( x )=[ ( V in - x 2) / L , x 1 / C ] T The system output is taken as y =[ y 1( x ), y 2( x )] T =[ x 1, x 2] T .

[0015] right y 1( x Finding the Lie derivative, we get: L g1 L f 0 y 1( x )= g 1= = V in / L ≠0 L g2 L f 0 y 1( x )= g 2= =( V in - x 2) / L ≠0 It can be seen that, y 1( x relative order r 1 = 1.

[0016] right y 2( x Finding the Lie derivative, we get: L g1 L f 0 y 2( x )= g 1= =0 L g2 L f 0 y 2( x )= g 2= = x 1 / C ≠0 It can be seen that, y 2( x relative order r 2 = 1. Because r 1+ r 2=2, which equals the system dimension, indicating that the three-state Boost converter model satisfies the requirement of exact feedback linearization. Define a new matrix. β ( x )for: β ( x )= = Design control law f =[ f 1, f 2] T for: =- β -1 ( x ) + β -1 ( x ) = β -1 ( x ) + β -1 ( x ) Right now: Preferably, step S3 specifically includes: As can be seen from the above analysis, the three-state Boost converter has been completely linearized into a first-order pure integral linear system. Now, a two-degree-of-freedom internal model controller is designed for the three-state Boost converter system.

[0017] The two-degree-of-freedom internal model controller consists of Q r ( s )and Q d ( s These components are used to adjust the system's reference input tracking performance and enhance its anti-interference capability and robust stability. G m ( s () is the internal model, and the controlled object is G ( s ). R ( s ), Y (s )and D ( s These represent the input, output, and disturbance signals of the control system, respectively. Y m ( s ) is the output of the internal model.

[0018] Therefore, the closed-loop output of the system Y ( s )for: Y ( s )= When the model is accurate, that is G ( s )= G m ( s )hour: Y ( s )= G m ( s ) Q r ( s ) Q d ( s ) R ( s )+(1- G m ( s ) Q d ( s )) D ( s ) Preferably, step S4 specifically includes the following process: Q d ( s The design method of using an internal mold controller is adopted: Q d ( s )= G -1 ( s )× F 2( s ) F 2( s ) = 1 / ( l 2 s+ 1) m in, F 2( s To enable Qd ( s The filter that the controller can implement, order m Depends on the order of the system to ensure the controller Q d ( s This is achievable. To enable independent adjustment of the system's reference input tracking performance and anti-interference capability, [the following will be implemented]. Q r ( s Set as: Q r ( s )= F 1( s ) / F 2( s ) F 1( s ) = 1 / ( l 1 s+ 1) n in, F 1( s To enable Q r ( s The filter that the controller can implement, order n Depending on the order of the system, the controller Q r ( s If this is achievable, then the above formula becomes: F 1( s ) = 1 / ( l 1 s+ 1) The controllers are designed as follows: Q d ( s )= s / ( l 2 s+ 1) Q r ( s )=( l 2 s+ 1) / ( l 1 s+ 1) By optimizing filter parameters l 1 and l 2 can achieve independent adjustment of the system's reference input tracking performance and anti-interference capability.

[0019] Preferably, step S5 specifically includes the following process: When the model matches, i.e. G ( s )= G m ( s From this, the input-output closed-loop transfer function of the capacitor voltage can be obtained as follows: Y ( s ) / R ( s )=1 / ( l 1 s+ 1) In the formula, Y ( s The Laplace transform of the reference output voltage across the flying capacitor is given. R ( s The Laplace transform of the reference input across the capacitor voltage is given. When the adjustable parameter... l When 1 is a positive number, all characteristic roots are located in the left half of the complex plane, and the system is asymptotically stable.

[0020] When model mismatch exists, define G ( s )= G m ( s )[1+Δ( s )], where Δ( s ) represents the model error, and satisfies ||Δ( s )‖ ∞ ≤ d , d This is the upper bound of the error. Substitute it into the closed-loop characteristic equation 1+ Q d ( s )[ G ( s ) -G m ( s )]=0, so we get 1+ Q d ( s ) G m ( s )=0. The necessary and sufficient condition for closed-loop stability under model mismatch is: ‖Δ( s )· Q d ( s ) G m ( s )‖ ∞ <1. Combining the upper bound of the error ‖Δ‖ ∞ < d The sufficient condition can be simplified to: d|| Q d ( s ) G m ( s )‖ ∞ <1. Among them, || Q d ( s ) G m ( s )‖ ∞ The smaller d The larger the value, the stronger the system's robustness. Therefore, by adjusting the parameters... Q d ( s This ensures that the system has good robust stability. Attached Figure Description

[0021] Figure 1 This is a topology diagram of a three-state Boost converter; Figure 2 This is a topology diagram of a three-state Boost converter during the capacitor charging stage. Figure 3 This is a topology diagram of a three-state Boost converter during the capacitor discharge stage. Figure 4 This is a topology diagram of a three-state Boost converter in the freewheeling phase; Figure 5 This is the system control block diagram of a three-state Boost converter; Figure 6 This is a simulation model of a three-state Boost converter; Figure 7 For the load of the three-state Boost converter R Simulated waveform during the change.

[0022] Figure 8 The input voltage of the three-state Boost converter V in Simulated waveform during the change. Detailed Implementation

[0023] 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.

[0024] 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 the state-space mathematical model of the three-state Boost converter. The topology of the three-state Boost converter is as follows: Figure 1As 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 For load resistance, Q e and Q t It forms a dual-switch structure. D and D t These are the main diode and the freewheeling diode, respectively.

[0025] Assuming the converter operates in continuous inductor current mode, according to the switching transistor Q e and Q t The three-state Boost converter has three operating states depending on the on / off conditions, and their topology diagrams are as follows: Figure 2 , Figure 3 and Figure 4 As shown. The duty cycle is different in each state, assuming... d c This refers to the duty cycle during the capacitor charging phase. d a This represents the duty cycle during the capacitor discharge phase. d f This refers to the duty cycle during the continuous flow phase.

[0026] The duty cycle in the three states satisfies the following constraints: d c + d a + d f = 1 Under these three 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,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 F ∈ 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 .

[0027] 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 ).

[0028] 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 xThe 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 ).

[0029] When the above conditions are met, there exists a function or ( 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 = f ( x )= = have to: = In the formula, α ( x )= L f n or ( x ), β ( x )= L g L f n-1 or ( 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 = .

[0030] 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.

[0031] To verify whether the mathematical model of the three-state Boost converter satisfies the exact feedback linearization condition, we take the state variables... 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 = + Among them, matrix f ( x )=[0, - x 2 / RC ] T ,matrix g ( x )=[ g 1( x ), g 2( x )] T ,and g 1( x )=[ V in / L , 0] T , g 2( x )=[ ( V in - x 2) / L , x 1 / C ] T The system output is taken as y =[ y 1( x ) , y 2( x )] T =[ x 1,x 2] T .

[0032] right y 1( x Finding the Lie derivative, we get: L g1 L f 0 y 1( x )= g 1= = V in / L ≠0 L g2 L f 0 y 1( x )= g 2= =( V in - x 2) / L ≠0 It can be seen that, y 1( x relative order r 1 = 1.

[0033] right y 2( x Finding the Lie derivative, we get: L g1 L f 0 y 2( x )= g 1= =0 L g2 L f 0 y 2( x )= g 2= = x 1 / C ≠0 It can be seen that, y 2( xrelative order r 2 = 1. Because r 1+ r 2=2, which equals the system dimension, indicating that the three-state Boost converter model satisfies the requirement of exact feedback linearization. Define a new matrix. β ( x )for: β ( x )= = Design control law f =[ f 1, f 2] T for: =- β -1 ( x ) + β -1 ( x ) = β -1 ( x ) + β -1 ( x ) Right now: The third step is to construct a two-degree-of-freedom internal model control structure, set up a tracking controller and an anti-disturbance controller, and independently adjust the system's reference tracking performance and anti-disturbance robustness performance, respectively. As can be seen from the above analysis, the three-state Boost converter has been completely linearized into a first-order pure integral linear system. Now, a two-degree-of-freedom internal model controller is designed for the three-state Boost converter system.

[0034] The two-degree-of-freedom internal model controller consists of Q r ( s )and Q d ( s These components are used to adjust the system's reference input tracking performance and enhance its anti-interference capability and robust stability. G m ( s () is the internal model, and the controlled object is G ( s ). R ( s ), Y ( s )andD ( s These represent the input, output, and disturbance signals of the control system, respectively. Y m ( s ) is the output of the internal model.

[0035] Therefore, the closed-loop output of the system Y ( s )for: Y ( s )= When the model is accurate, that is G ( s )= G m ( s )hour: Y ( s )= G m ( s ) Q r ( s ) Q d ( s ) R ( s )+(1- G m ( s ) Q d ( s )) D ( s ) The fourth step is to design low-pass filters that enable the controller to function, and then tune the filter parameters to obtain the transfer functions of the tracking controller and the disturbance rejection controller. Q d ( s The design method of using an internal mold controller is adopted: Q d ( s )= G -1 ( s )× F 2( s ) F 2( s ) = 1 / ( l 2 s+ 1) m in, F 2(s To enable Q d ( s The filter that the controller can implement, order m Depends on the order of the system to ensure the controller Q d ( s This is achievable. To enable independent adjustment of the system's reference input tracking performance and anti-interference capability, [the following will be implemented]. Q r ( s Set as: Q r ( s )= F 1( s ) / F 2( s ) F 1( s ) = 1 / ( l 1 s+ 1) n in, F 1( s To enable Q r ( s The filter that the controller can implement, order n Depending on the order of the system, the controller Q r ( s If this is achievable, then the above formula becomes: F 1( s ) = 1 / ( l 1 s+ 1) The controllers are designed as follows: Q d ( s )= s / ( l 2 s+ 1) Q r ( s )=( l 2 s+ 1)( l 1 s+ 1) By optimizing filter parameters l 1 and l 2 can achieve independent adjustment of the system's reference input tracking performance and anti-interference capability.

[0036] The fifth step involves performing robust stability analysis under both model matching and mismatch conditions to suppress input voltage fluctuations and load step disturbances, thereby achieving high-precision and stable control of the output voltage.

[0037] When the model matches, i.e. G ( s )= G m ( s From this, the input-output closed-loop transfer function of the capacitor voltage can be obtained as follows: Y ( s ) / R ( s )=1 / ( l 1 s+ 1) In the formula, Y ( s The Laplace transform of the reference output voltage across the flying capacitor is given. R ( s The Laplace transform of the reference input across the capacitor voltage is given. When the adjustable parameter... l When 1 is a positive number, all characteristic roots are located in the left half of the complex plane, and the system is asymptotically stable.

[0038] When model mismatch exists, define G ( s )= G m ( s )[1+Δ( s )], where Δ( s ) represents the model error, and satisfies ||Δ( s )‖ ∞ ≤ d , d This is the upper bound of the error. Substitute it into the closed-loop characteristic equation 1+ Q d ( s )[ G ( s ) -G m ( s )]=0, so we get 1+ Q d ( s ) G m ( s )=0. The necessary and sufficient condition for closed-loop stability under model mismatch is: ‖Δ( s )· Q d ( s ) G m (s )‖ ∞ <1. Combining the upper bound of the error ‖Δ‖ ∞ < d The sufficient condition can be simplified to: d || Q d ( s ) G m ( s )‖ ∞ <1. Among them, || Q d ( s ) G m ( s )‖ ∞ The smaller d The larger the value, the stronger the system's robustness. Therefore, by adjusting the parameters... Q d ( s This ensures that the system has good robust stability.

[0039] To verify the effectiveness of the two-degree-of-freedom internal model control method proposed in this invention, this embodiment uses the Matlab / Simulink numerical simulation platform to construct a simulation model of a three-state Boost converter for research. The specific circuit is as follows: Figure 5 As shown in the table below. The parameters of the three-state Boost converter used in this embodiment are as follows: Figure 7 Given R Simulated waveforms of the system when the ohmmeter jumps from 30Ω to 80Ω at 0.3s and 0.35s, and when it drops back to 30Ω. R When a disturbance occurs, the output current i o Capable of rapid tracking R Transformation, while a two-degree-of-freedom internal model control strategy can enable v o Stable at 8.5V, which is the reference value. v oref Simulation data show that the proposed two-degree-of-freedom internal model control strategy can maintain excellent control performance under load disturbance conditions, and the overshoot is almost negligible.

[0040] Figure 8 Given V in Simulated waveforms of the system when the voltage jumps from 5V to 7V at 0.15s and 0.2s, and when the voltage jumps back from 7V to 5V, respectively. V in During transitions, a two-degree-of-freedom internal model control strategy can enable... vo It is stabilized at 8.5V, 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 a two-degree-of-freedom internal model control method for three-state Boost converters. First, a state-space averaging method is used to establish the system's mathematical model. Then, precise feedback linearization technology is employed to linearize the original nonlinear system. A two-degree-of-freedom internal model 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.

[0041] 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. A two-degree-of-freedom internal model control method based on a three-state Boost converter, 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 the three-state Boost converter; S2. Based on differential geometry theory, the nonlinear mathematical model of the converter is transformed into the Brunofsky canonical form by using the exact feedback linearization method, which is equivalent to decoupling into a linear integral system. S3. Construct a two-degree-of-freedom internal model control structure, set up a tracking controller and an anti-disturbance controller, and independently adjust the system's reference tracking performance and anti-disturbance robustness performance respectively; S4. Design low-pass filters that enable the controller to function, and tune the filter parameters to obtain the transfer functions of the tracking controller and the disturbance rejection controller. S5. Under both model matching and mismatch conditions, robust stability analysis is performed to suppress input voltage fluctuations and load step disturbances, thereby achieving high-precision and stable control of the output voltage.

2. The two-degree-of-freedom internal model control method based on a three-state Boost converter according to claim 1, characterized in that: In step S1, the three-state Boost converter operates in three modes: capacitor charging, capacitor discharging, and freewheeling, with corresponding duty cycles... d c , d a , d f satisfy: d c + d a + d f = 1. The duty cycle ranges from (0,1). The state equations for these three modes are obtained using the KCL and KVL laws.

3. The two-degree-of-freedom internal model control method based on a three-state Boost converter according to claim 1, characterized in that: In step S2, the mathematical model is transformed into an affine nonlinear form. The sum of the relative orders is verified to be equal to the system dimension by calculating the Lie derivative, thus satisfying the exact feedback linearization condition. The linearized matrix is ​​constructed and the control law is solved to complete the linearization and decoupling of the nonlinear system.

4. The two-degree-of-freedom internal model control method based on a three-state Boost converter according to claim 1, characterized in that: In step S3, the two-degree-of-freedom internal model controller is controlled by a tracking controller. Q r ( s ) and disturbance rejection controller Q d ( s The system consists of a tracking controller to adjust the dynamic tracking performance of the system reference input and an anti-disturbance controller to suppress external disturbances and model mismatch.

5. The two-degree-of-freedom internal model control method based on a three-state Boost converter according to claim 1, characterized in that: In step S4, filters that enable the controller to function are constructed, resulting in the transfer functions of the tracking controller and the disturbance rejection controller; wherein, the filter parameters... λ 1. λ 2>0, through tuning λ 1. λ 2. This allows for independent adjustment of the system's reference input tracking performance and anti-interference capability.

6. The two-degree-of-freedom internal model control method based on a three-state Boost converter according to claim 1, characterized in that: In step S5, when the model matches, the filter parameters are adjusted. λ When 1 is positive, all eigenvalues ​​lie in the left half of the complex plane, and the system is asymptotically stable. When model mismatch exists, by establishing the necessary and sufficient condition for closed-loop stability, it is known that adjusting the disturbance rejection controller parameters... Q d ( s This ensures that the system has good robust stability.

7. The two-degree-of-freedom internal model control method based on a three-state Boost converter according to claim 1, characterized in that: This two-degree-of-freedom internal mode control method can be extended to various non-minimum phase DC-DC converter topologies.

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