An adaptive augmented anti-disturbance load controller design method

Abstract

The application discloses a kind of self-adapting augmented anti-interference load shedding controller design methods, which comprises the following steps: first, based on pitch channel analysis, setting PD control parameters, and building PD correction network controller;Second, construct augmented adaptive controller;Then, design load shedding controller, and utilize measured overload value to carry out real-time correction and compensation to engine deflection angle;Next, design linear extended state observer;Finally, the above-mentioned PD correction network controller, augmented adaptive controller, load shedding controller and linear extended state observer are organically combined to form the final comprehensive controller.By using the application, the robustness of the control system can be significantly improved, thereby enhancing the stability of rocket flight.The application can be widely applied in the field of attitude control.

Description

Technical Field

[0001] This invention relates to the field of attitude control technology, and in particular to a design method for an adaptive augmented anti-interference load reduction controller. Background Technology

[0002] Launch vehicles face numerous uncertainties during flight, such as changes in altitude, speed, atmospheric conditions, and internal structural vibrations. These factors result in significant time-varying characteristics and uncertainties in the attitude dynamics model parameters. This uncertainty reduces the stability margin of the attitude control system and can even lead to system instability. Solving the control problem of strong coupling, high uncertainty, and complex disturbances during the powered flight phase of a launch vehicle is an extremely challenging task. Its core issues include designing advanced adaptive control methods to improve steady-state control accuracy, reduce aerodynamic bending moments under strong wind disturbances, and achieve stable elastic control under conditions of large deviations in elastic vibration frequencies.

[0003] However, traditional frequency-domain-based PD control systems employ a conservative, single-design approach, which is difficult to effectively meet these requirements in practical applications. Therefore, new methods are urgently needed to adapt to such complex and variable operating conditions. Summary of the Invention

[0004] In view of this, in order to address the challenges of existing control systems in meeting the complex requirements of high-precision attitude control, resistance to elastic vibration frequency deviations, sudden wind disturbances, and active load shedding, this invention proposes an adaptive augmented anti-interference load shedding controller design method, which includes the following steps: First, based on pitch channel analysis, the PD control parameters are tuned, and a PD correction network controller is built. Second, an augmented adaptive controller (AAC) is constructed. Then, a load reduction controller (LR) is designed to correct and compensate for the engine deflection angle in real time using measured overload values. Next, a linear extended state observer (ESO) is designed. Finally, the PD correction network controller, augmented adaptive controller, load reduction controller, and linear extended state observer are organically combined to form the final integrated controller.

[0005] In some feasible embodiments, the method further includes performing stability analysis on a controller that incorporates PD, AAC, LR, and LESO.

[0006] Based on the above scheme, this invention provides a design method for an adaptive augmented anti-interference load reduction controller. This invention can be seamlessly integrated with a traditional PD controller to form a complete control system, without affecting the operation of the PD controller under disturbance-free conditions. The added adaptive augmented control algorithm can adjust the open-loop gain according to the disturbance, the load reduction controller can compensate for strong wind disturbances during the ascent phase in high-wind areas, and the linear extended state observer can observe and compensate for disturbances. This ensures that the system maintains excellent control performance even under disturbances such as rocket body elastic vibration, liquid sloshing, structural errors, and wind interference. This composite method can significantly improve the robustness of the control system, thereby enhancing the stability of rocket flight, and has broad application prospects in the field of launch vehicle control. Attached Figure Description

[0007] Figure 1 This is a flowchart illustrating the steps of an adaptive augmented anti-interference load reduction controller design method according to the present invention. Figure 2 This is a block diagram of the pitch channel control according to a specific embodiment of the present invention; Figure 3 This is a block diagram of the adaptive augmentation control algorithm according to a specific embodiment of the present invention; Figure 4 It is a classic open-loop Nichols diagram; Figure 5 This is a schematic diagram illustrating the effect of high-pass and low-pass filters; Figure 6 This is a PD+LR control block diagram of a specific embodiment of the present invention; Figure 7 This is a control block diagram of PD+LESO+LR according to a specific embodiment of the present invention; Figure 8 This is a control block diagram of AAC+PD+LESO+LR in a specific embodiment of the present invention. Detailed Implementation

[0008] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0009] It should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0010] It should be understood that the terms "system," "apparatus," "unit," and / or "module" used in this application are a method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0011] Unless the context explicitly indicates an exception, words such as "a," "an," "a kind," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list; a method or apparatus may also include other steps or elements. An element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, product, or apparatus that includes the element.

[0012] In the description of the embodiments of this application, "a plurality of" refers to two or more. The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0013] Furthermore, flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Additionally, other operations can be added to these processes, or one or more steps can be removed from them.

[0014] A novel composite control method is proposed for attitude control during the ascent phase of a launch vehicle, capable of meeting the combined requirements of high-precision attitude control, resistance to elastic vibration frequency deviations, sudden wind disturbances, and active load reduction. (Refer to...) Figure 1 This is a flowchart illustrating an optional example of the adaptive augmented anti-interference load reduction controller design method proposed in this invention. This method can be applied to computer equipment, and the design method proposed in this embodiment may include, but is not limited to, the following steps: Step S1: Based on pitch channel control analysis, design PD control parameters and construct a PD correction network controller; Step S2: Construct an augmented adaptive controller; Step S3: Construct a load reduction controller and use the measured overload value to correct and compensate the original engine deflection angle. Step S4: Design a linearly extended state observer; Step S5: Generate the final controller based on the PD correction network controller, the augmented adaptive controller, the load reduction controller, and the linear expansion state observer; Step S6: Stability analysis.

[0015] In some feasible embodiments, step S1, designing a PD correction network controller, specifically includes: This section takes the pitch channel control analysis under elastic conditions as an example. The control block diagram of this channel is as follows: Figure 2 As shown.

[0016] The corresponding PD control parameters are designed, and the open-loop transfer function without compensation network is calculated as follows: (1) in, This represents the static magnification factor of the pitch channel. This is the dynamic amplification factor. For inertial navigation system transfer function, For the rate gyroscope transfer function, The transfer function for the servo mechanism. In the initial design of the control system, the position of the rate gyroscope (generally at the antinode of the second-order mode) needs to be determined first to ensure the stability of the second-order elastic amplitude. The transfer function can be obtained using a formula. Then, the initial determination... , For open-loop system cutoff frequencies, it is generally necessary to ensure a gain margin greater than 6dB and a phase margin greater than 30° under rigid body conditions. Finally, through analysis... Based on the Bode plot, the corresponding correction network can be designed: Format 1: Form 2: in, It is the center frequency of the notch filter. It is the damping ratio.

[0017] In some feasible embodiments, step S2, designing an augmented adaptive controller, specifically includes: The adaptive law in the adaptive augmentation controller is designed as follows: The first term in the first expression is the rate of change of the adaptive gain parameter. The first term on the right-hand side improves tracking performance, the second term improves the ability to escape unstable states, and the third term is equivalent to the stability recovery coefficient term. Error term coefficient, For the gain related to the elastic signal, The gain coefficient associated with the recovery term is typically taken between (0, 0.1). To track signal errors, It is an elastic amplitude signal. This is the upper limit of the gain parameter. This is the lower limit value of the gain parameter. For adaptive control of gain, This represents the final open-loop gain coefficient. Its control block diagram is as follows: Figure 2 As shown, it can also be observed that: This item will cause large system errors. Increase the controller's parameters to reduce system error; The item will cause the system's elasticity to be activated. Reduce the controller's control parameters to prevent system divergence; The item uses feedback to make It has the ability to restore to 1, which enables the system to function normally. Near 1.

[0018] Refer to the block diagram of the adaptive augmentation control algorithm. Figure 3 .

[0019] The detailed design methods for the remaining parts are as follows: Determine the upper and lower limits of gain: Based on the transfer function at a certain characteristic point, assuming that mass deviation, thrust deviation, aerodynamic deviation, density deviation, center of mass deviation, and moment of inertia deviation are uniformly distributed within 20%, without changing the forward gain of the controller... Monte Carlo simulations were performed on the target under normal conditions to analyze the gain margin and phase margin simulation results and obtain the minimum gain margin. Then, by reversing the equations, we can obtain the upper and lower limits of the gain.

[0020] In traditional control system design, it is generally required that ,make Then we can obtain , , , However, achieving a 6dB margin in the design of elastic rockets can be challenging. In such cases, Nichols diagrams can be used for analysis and design.

[0021] Based on the Nichols diagram of the uncorrected open-loop system, the aerodynamic gain margin point is obtained. Gauss margin point of rigid body Then we can use the equation Seeking Similarly, Then we have: For example, the Nichols diagram of an open-loop system is as follows: Figure 4 As shown, you can see Therefore, we can obtain ,because , .

[0022] Reference model design: The reference model primarily simulates the rigid-body controlled motion of a missile under nominal conditions by establishing a mathematical model. By adjusting the model parameters, it generates the desired tracking response to guidance commands. The difference between this response and the actual attitude response of the missile under disturbance is then used to form the attitude angle error. This serves as the input to the adaptive law, achieving the goal of increasing the gain of the PD controller online. Based on the PD control parameters, the reference model can be designed as follows: By introducing a delay element, the simplified reference model is obtained as follows: in , , It is the delay time constant.

[0023] High-pass and low-pass filter parameter design: The design parameters of the high-pass and low-pass filters should be determined based on the characteristics of the launch vehicle, such as the system's closed-loop cutoff frequency and the first- or second-order elastic vibration frequencies. Appropriate frequencies and damping ratios need to be selected so that the center frequency of the high-pass filter is higher than the closed-loop cutoff frequency, thereby filtering out rigid body control signals. Simultaneously, the low-pass filter can smooth the vibration signal, providing information for gain reduction. This paper uses second-order high-pass and low-pass filters to obtain smooth elastic vibration signals, and their structure is as follows: in The center frequency of the high-pass filter. It can generally be designed to be 0.9. Among them... The center frequency of the low-pass filter. It can generally be designed to be 1. The elastic vibration signal design is as follows: This formula will cause frequency folding, therefore, we can conclude that... A typical signal, after being processed by a high-pass filter and a low-pass filter, yields the following result: Figure 5 The results are shown. As can be seen, the signal becomes smooth and oscillatory after being processed by the two filters. This filtered signal can be used as input to an adaptive law for adaptive gain adjustment.

[0024] Parameter adjustment design: The core of an adaptive augmenting controller is the adaptive law, which contains multiple control parameters. However, tuning these parameters is challenging; therefore, this paper proposes an analytical method for their calculation. By setting the magnitude and distribution of the deviation associated with the disturbance, the Monte Carlo method can be used to obtain the tracking error of the reference model. With elastic vibration amplitude signal The maximum value of . Based on these values, the following result can be derived using equation (4): in express from Change to The time required reflects the rate of gain increase. for from Change to The time required also reflects the rate of gain decrease. To ensure Able to recover steadily to 1, usually Selected as the initial candidate value, which can be adjusted during testing.

[0025] In some feasible embodiments, step S3, designing a load shedding controller, specifically includes: In the design of the load shedding loop, a PI controller and correction network design method based on overload acceleration feedback are mainly used. The measured overload value is primarily utilized in the load shedding loop. The original engine deflection angle was corrected and compensated.

[0026] in, and For overload feedback coefficient, and For integral gain, and The distance between the accelerometer installation location and the center of mass.

[0027] In some feasible embodiments, step S4, designing a linearly extended state observer, specifically includes: Based on the pitch channel transfer function model described above, the linear extended state observer is designed as follows: Define the state variable as , Therefore, the state-space equations can be derived as follows: in These represent the measured values ​​of the additional attitude angle and angular rate caused by elastic vibration. The remaining variables are defined as follows: Based on the above two equations, the following extended state observer (ESO) is designed: in , , , and are respectively , , and The measured value. This refers to the observer gain, which is a key factor determining the observer's convergence. According to methods described in existing literature, this factor is determined by configuring the observer bandwidth. To determine.

[0028] Therefore, the disturbance compensation control input design is as follows: In summary, step S5, taking the pitch channel as an example, yields the final design of the adaptive augmentation anti-interference load reduction controller as shown below: It should be noted that the PD controller is the baseline controller for the entire system, ensuring closed-loop attitude control under nominal operating conditions. The other three modules (augmented adaptive controller, load shedding controller, and linear extended state observer) estimate external disturbances through measurement and calculation, make corresponding disturbance corrections, and then superimpose them onto the basic control input of the PD controller. When there are no disturbances, the corrections output by AAC, LR, and LESO approach zero, and the system is equivalent to the basic PD controller.

[0029] In some feasible embodiments, step S6 specifically includes: Based on frequency domain methods and sinusoidal function analysis, stability analysis is performed on the four designed modules to determine the system's stability margin, and the overall stability margin of the entire control system can be calculated. According to the aforementioned PD control block diagram, after adding the load shedding control loop, the following can be obtained: Figure 6 The results are shown.

[0030] The open-loop transfer function of the system is: in For the correction network of the table, and The transfer function from engine nozzle deflection angle to overload is calculated as follows: By applying the Laplace transform, when the distance deviation between the accelerometer's installation position and the center of mass is removed from the control system feedback, we have: When the angle of attack is converted into elevation and trajectory inclination, then: Substituting this into the previous open-loop transfer function, we can plot the Bode plot of the transfer function. Next, we analyze the stability of LESO.

[0031] Substituting this into the previous open-loop transfer function, we can plot the Bode plot of the transfer function. Next, we analyze the stability of LESO.

[0032] Considering the correction network at the observer's state input, a Laplace transform of equation (17) yields: In the formula, Based on the above equations, the transfer function of the Linear Extended State Observer (LESO) can be derived as follows: The specific details are as follows: The control law after compensation by the linear active disturbance rejection observer is: Controller parameters It can be determined by interpolation under nominal operating conditions. By combining the PD controller, the load shedding controller, and the linearly extended state observer, the following can be obtained: Figure 7 The block diagram shown.

[0033] according to Figure 7 The block diagram and the open-loop transfer function of the system are calculated as follows: To facilitate stability analysis of the adaptive augmented control law, the adaptive law in adaptive augmented control (AAC) is rewritten as follows: There is also an expression for the control law. The stability margin analysis of the adaptive augmented controller can be carried out by combining the sinusoidal input signal method, and the open-loop gain can be derived. The time-domain response results. First, assume the error... If the sinusoidal input condition is met, then according to the relationship between high-pass and low-pass filters, we can obtain: in For high-pass filters The phase. Furthermore, using trigonometric relationships... Similarly, we can obtain have: This is because This leads to the following: Substituting this into the preceding context, we get: Further simplification yields: in , ,error A low-pass filter can then be connected to filter out the remaining signal. Let be a relatively small constant value. Then the solution to the above equation is: in Let be the general solution coefficient, and be any constant. According to... and From the expression, we can see that ,but , , but , that is Therefore, the open-loop gain of the AAC output must be a positive number. Also, since... Then, as time increases... , ,but Then we have: if If the input frequency is relatively low, then... ,because Smaller (on the order of 0.01) Therefore When the input frequency is high, then... Then we have: when At that time, ,Right now .

[0034] In summary, we can conclude that when the input signal is low frequency, the open-loop gain of the AAC will be close to... Upper limit amplitude; while when the input signal is high frequency, the AAC gain... Less than 1, close to (That is, the minimum value). According to the expression form of (34), the open-loop gain can be known. It converges gradually and does not have a chattering problem.

[0035] Next, the amplitude and phase response curves of the AAC open-loop gain under different frequency conditions are derived using the describing function method. Considering the derivation using the describing function method, first... ,but In describing function analysis, generally only the fundamental frequency is considered. Substituting it into (33), we get: By performing a merging and transformation, we can obtain: The solution to the system is: in Let be a constant related to the initial value. If we only consider the steady-state solutions of the system at different frequencies, then we have: Then we can know the amplitude of the system and Irrelevant (not considered) (When the influence is irrelevant, it is irrelevant) when considering When, the overall open-loop gain of the system is... Then we have: Based on the results of the above equations, it can be concluded that the adaptive augmenting control law approximates as an open-loop gain in the frequency domain analysis, exhibiting only amplitude-frequency characteristics and no phase-frequency characteristics. Subsequently, the block diagram of the control system containing all four control modules is as follows: Figure 8 As shown in the diagram. Stability analysis can then be performed based on this block diagram, and a Bode plot can be generated.

[0036] A storage medium storing processor-executable instructions, which, when executed by a processor, are used to implement an adaptive augmented anti-interference load shedding controller design method as described above.

[0037] The content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0038] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A design method for an adaptive augmented anti-interference load shedding controller, characterized in that, Includes the following steps: Based on pitch channel control analysis, PD control parameters are designed and a PD correction network controller is constructed. Construct an augmented adaptive controller; Construct a load reduction controller and use the measured overload value to correct and compensate for the original engine deflection angle; Design a linearly extended state observer; The final controller is generated based on the PD correction network controller, the augmented adaptive controller, the load reduction controller, and the linear expansion state observer.

2. The adaptive augmented anti-interference load reduction controller design method according to claim 1, characterized in that, Also includes: Based on frequency domain methods and sinusoidal function analysis, stability analysis is performed on the PD correction network controller, the augmented adaptive controller, the load reduction controller, and the linear expansion state observer, and the stability margin is calculated.

3. The adaptive augmented anti-interference load reduction controller design method according to claim 1, characterized in that, The PD correction network controller is represented as follows: in, This represents the transfer function of the calibration network controller. It is the center frequency of the notch filter. It is the damping ratio.

4. The adaptive augmented anti-interference load reduction controller design method according to claim 1, characterized in that, The PD correction network controller is represented as follows: in, This represents the transfer function of the calibration network controller. It is the center frequency of the notch filter. It is the damping ratio.

5. The adaptive augmented anti-interference load reduction controller design method according to claim 4, characterized in that, The adaptive law of the augmented adaptive controller is expressed as follows: in, Indicates the adaptive control gain. express The derivative, This represents the maximum value of the adaptive control gain. For the error term coefficient, To track signal errors, It is an elastic amplitude signal. For the gain related to the elastic signal, The gain coefficient associated with the recovery term. This is the final open-loop gain coefficient. This is the lower limit value of the gain parameter.

6. The adaptive augmented anti-interference load reduction controller design method according to claim 5, characterized in that, The expression for the load reduction controller is as follows: in, , Indicates the pitch and yaw angles of the engine under load; , The overload feedback coefficients represent pitch and yaw. , Integral gain representing pitch and yaw; , Indicates the measured overload value; , This indicates the distance between the accelerometer's installation location and the center of mass; , It represents angular acceleration.

7. The adaptive augmented anti-interference load reduction controller design method according to claim 6, characterized in that, The expression for the linearly extended state observer is as follows: in, This represents the measured pitch angle value. Indicates the measured angle of attack; , , , , These represent the coefficients of the small-perturbation linearization model. This indicates the pitch direction control value.

8. The adaptive augmented anti-interference load reduction controller design method according to claim 6, characterized in that, The expression for the final controller is as follows: in, This represents the static amplification factor for attitude angle deviation; Indicates the attitude angular rate amplification factor; Indicates the apparent acceleration in the normal direction; This indicates the distance between the inertial navigation system's installation location and its center of mass; This represents the measured value of ESO.

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