Rocket simulation system and adaptive augmentation control method

Abstract

The invention discloses a rocket simulation system and an adaptive augmentation control method, and the method comprises the steps: describing the controlled motion of a rigid body of a carrier rocket under a nominal condition, forming an expected tracking instruction through the design of model parameters, carrying out the difference between the expected tracking instruction and the attitude response of the actual disturbed motion of the carrier rocket, and generating an attitude angle deviation; the method comprises the following steps: establishing a flight control computer module as the input of a self-adaptive law to achieve the purpose of changing the gain of a PID controller in real time, establishing a rocket simulation system, embedding a rocket control strategy based on a self-adaptive augmentation control method in the flight control computer module, obtaining real-time data of a motion measurement module and real-time attitude information of a rocket calculated by a six-degree-of-freedom model module, and calculating the real-time attitude information of the rocket. And a control signal is output to the six-degree-of-freedom model module through a rocket control strategy. By adjusting the control parameters in real time, dynamic changes in the rocket flight process can be responded in real time, the control precision and adaptability of the rocket simulation system are improved, and an efficient and reliable solution is provided for rocket simulation and control.

Description

Technical Field

[0001] The invention relates to the technical field of rocket simulation and control, and in particular to a rocket simulation system and an adaptive augmented control method. Background Art

[0002] With the development of aerospace technology, the precise control of rocket launch and flight has become an important research topic. During the flight, the rocket faces a complex nonlinear dynamic environment and multiple interference factors, such as airflow disturbance, structural vibration, fuel consumption, etc. These factors put forward higher requirements on the stability and precision of the rocket.

[0003] At present, attitude control is a hot topic in the research of aircraft motion simulation systems at home and abroad, including rockets. Gain scheduling, adaptive control, pseudo-inverse method, nonlinear dynamic inversion, model predictive control, etc. have been widely used. At present, the combination of fuzzy adaptive control system and machine learning has made the adaptive control theory based on various intelligent algorithms develop rapidly. The main goal is to reduce assumptions, remove augmented error signals, reduce adjustable parameters, improve system robustness, overcome external interference, etc. Designers generally assume that the parameters of the controlled object or process are known and fixed quantities. This mathematical model is too idealized. In actual engineering, the parameters of the system will change over time, and its performance will deteriorate over time. In addition, external interference, loss in signal transmission and noise will increase the error of the control system and make the system unstable.

[0004] Existing rocket simulation systems mostly use fixed parameter control methods, which cannot effectively deal with parameter changes and external disturbances that occur during flight. Although advanced control algorithms (such as fuzzy control, neural network control, etc.) can improve control accuracy and adaptability in theory, they face problems such as complex parameter adjustment, difficult algorithm design, and high computing resource consumption in actual applications, which increases the complexity of system implementation and maintenance, resulting in a large gap between simulation results and actual flight conditions.

[0005] Most of the current research results focus on the conclusions drawn from a certain characteristic of the launch vehicle during flight, and they are not universal. When faced with multiple complex influences such as strong interference, large uncertainty, and multiple constraints, it is impossible to guarantee that the established requirements can be met.

[0006] Most existing simulation hardware systems are based on single-degree-of-freedom or low-degree-of-freedom motion platforms, which generally move in certain specific directions and cannot fully reproduce the complex attitude changes and multi-axis linkage states of the rocket during flight, limiting the authenticity and accuracy of the simulation results. In addition, the rocket control system requires data processing and control command execution to be completed in a very short time. The traditional simulation system is insufficient in terms of high-precision modeling and real-time performance, and it is difficult to meet the response requirements of high-frequency dynamic changes and calculations in complex environments.

[0007] Therefore, how to provide a rocket simulation system and an adaptive augmented control method that can improve the accuracy and adaptability of rocket simulation control is a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0008] In view of the above research status and existing problems, the present invention provides a rocket simulation system and an adaptive augmented control method, which can respond to dynamic changes in the rocket flight process in real time by adjusting control parameters in real time, thereby improving the control accuracy and adaptability of the rocket simulation system, providing an efficient and reliable solution for rocket simulation and control, and has broad application prospects.

[0009] The present invention first provides a rocket model adaptive augmentation control method, comprising the following steps:

[0010] A rigid body controlled motion model of a rocket entity model under nominal conditions is established as a reference model to describe the motion state of the rocket in a preset interference-free flight environment; by setting the reference model parameters, an expected tracking instruction is generated, that is, an expected attitude angle that the rocket entity model should achieve in an interference-free state;

[0011] Using the real-time data of inertial measurement information and navigation information and the six-degree-of-freedom equation during the movement of the rocket physical model, the actual motion state of the rocket physical model, including the actual attitude angle, is calculated;

[0012] Calculating the difference between the desired attitude angle and the actual attitude angle to obtain an attitude angle deviation;

[0013] The elastic vibration response in the output control command of the PID controller is subjected to high-pass and low-pass filtering to separate the elastic vibration signal, which is used to characterize the control signal error caused by the elastic vibration;

[0014] According to the attitude angle deviation and the elastic vibration signal, as inputs of the adaptive law, the gain of the PID controller is adjusted in real time to obtain the PID control parameters updated in real time;

[0015] Based on the updated PID controller parameters and the attitude angle deviation, a control instruction is calculated to control the attitude of the rocket.

[0016] Preferably, the calculating the actual motion state of the rocket entity model comprises the step of performing attitude calculation using an improved adaptive Mahony complementary filtering algorithm:

[0017] Calculate the relative rotation error between the accelerometer measurement and the attitude angle estimate of the previous time interval;

[0018] Based on the relative rotation error, PI adjustment parameter k p and k i Calculate the new information generated by the PI regulator, where k p Used to control the crossover frequency between the accelerometer and the gyroscope, k i Used to correct gyroscope errors;

[0019] Calculate a compensated gyroscope value based on the gyroscope measurement value and the new information;

[0020] Using the quaternion at the previous moment and the compensated gyroscope value, the quaternion is updated to calculate the predicted quaternion value at the current moment;

[0021] The estimated value of the attitude angle at the current moment is calculated using the quaternion prediction value at the current moment.

[0022] Preferably, performing high-pass and low-pass filtering on the elastic vibration response in the control instruction comprises the following steps:

[0023] The output of high-pass and low-pass filtering s The expression is as follows:

[0024]

[0025] Where: G hp (s) is the transfer function of the high-pass filter, G lp (s) is the transfer function of the low-pass filter, The control instructions output by the reference model, It is the control instruction output by the PID controller;

[0026] The transfer function of the high-pass filter is:

[0027]

[0028] The transfer function of the low-pass filter is:

[0029]

[0030] Where: hp and ω lp are the cutoff frequencies of the high-pass filter and the low-pass filter respectively.

[0031] Preferably, adjusting the gain of the PID controller in real time based on the attitude angle deviation and the elastic vibration signal as inputs of the adaptive law comprises the following steps:

[0032]

[0033] k T ∈[k Tmin ,k Tmax ],k α ∈[0,k αmax ]

[0034] k T =k α +k Tmin

[0035] Where: k α is the adaptive gain, k αmax is the adaptive maximum gain, k T is the forward gain, k Tmax and k Tmin are the maximum and minimum forward gain respectively, K s is the control command suppression gain, K β is the adaptive gain convergence coefficient, K e is the error amplification factor, which is the effect of amplifying or reducing the signal on the system gain. r is the error between the reference model and the actual model output attitude angle, y s is the output of high-pass and low-pass filtering, k T is the total forward gain.

[0036] Preferably, it also includes:

[0037] When the output of high-pass and low-pass filtering y s When the deviation of the attitude angle between the reference model and the actual model is less than the set threshold, r When not 0, the adaptive gain convergence coefficient K is ignored. β , adaptive gain k α gradually increases and eventually converges to k αmax ;

[0038] With the high-pass and low-pass filtered output y s The increase eventually Approaching 0, the control command's response to the elastic vibration is weakened to a self-oscillation state with an amplitude less than the specified value;

[0039] When the control command's response to the elastic vibration is weakened to a self-oscillation state with an amplitude less than the specified value, the attitude angle deviation e r And the output y of high-pass and low-pass filtering s approaches 0. When t→∞, k T=k α +k T min =1.

[0040] The present invention further provides a rocket simulation system, comprising a flight control computer module, an actuator module, a six-degree-of-freedom module, a motion measurement module and a rocket entity model; wherein:

[0041] The flight control computer module is embedded with a rocket control strategy, which obtains the real-time data of the motion measurement module and the real-time attitude information of the rocket solved by the six-degree-of-freedom model module, and outputs a control signal to the actuator and the six-degree-of-freedom model module through the rocket control strategy; the rocket control strategy is the rocket model adaptive augmented control method;

[0042] The actuator includes a steering gear for controlling the rocket entity model, and is used to receive the control signal to control the action of the steering gear;

[0043] The six-degree-of-freedom model module includes an attitude solving industrial computer and a six-degree-of-freedom platform; the rocket entity model is fixed on the six-degree-of-freedom platform, and the attitude solving industrial computer is embedded with an attitude solving algorithm and a rocket six-degree-of-freedom equation. The attitude solving algorithm is used to solve the attitude according to the real-time data of the motion measurement module, and the six-degree-of-freedom equation model is updated in combination with the control signal and the attitude solving result. The updated rocket six-degree-of-freedom equation is used to calculate the real-time attitude information of the rocket, and the position inverse solution algorithm is used based on the real-time attitude information of the rocket to calculate the motion position of the six-degree-of-freedom platform, so as to reproduce the motion state of the rocket entity model under the control signal;

[0044] The motion measurement module is installed in the rocket entity model and is used to monitor the real-time data of the inertial measurement information and navigation information of the rocket entity model in real time.

[0045] Preferably, the flight control computer module includes a PID controller, an adaptive gain adjustment module, an interference compensation module, and an active load reduction module; wherein,

[0046] The PID controller module is used to receive guidance instructions and output control signals to the rocket entity model;

[0047] The adaptive gain adjustment module adjusts the gain of the PID controller in real time according to the adaptive law;

[0048] The disturbance compensation module is used to provide disturbance error compensation to the PID controller module and the adaptive gain adjustment module to reduce the control error of the attitude angle when the PID controller gain is reduced;

[0049] The active load reduction module uses the active load reduction control algorithm to ensure that the lateral and side loads on the launch vehicle in the large dynamic pressure area are lower than the set threshold.

[0050] Preferably, the six-degree-of-freedom platform comprises: six servo electric cylinders, an upper platform and a lower platform arranged in parallel; the rocket entity model is fixed on the upper platform;

[0051] The six servo electric cylinders connect the upper platform and the lower platform through Hooke hinges and ball cage universal joint couplings, and the lower platform is fixed on the base; the attitude solving industrial computer controls the telescopic movement of the six servo electric cylinders to complete the movement of the upper platform with six degrees of freedom in three-dimensional space, so that the rocket entity model simulates the three attitudes of roll, yaw and pitch and the movement of X, Y and Z axis translation.

[0052] Preferably, the attitude solving industrial computer is connected to a servo motor via a servo drive, and the servo motor is connected to the servo electric cylinder;

[0053] An encoder is provided at the tail end of the servo motor; the encoder data is sent to the host computer through the servo drive, and the current positions of the six servo electric cylinders are obtained by solving the encoder data; the resistance scale judges the stroke of the servo electric cylinder and is used for the electrical limit of the absolute position of the servo electric cylinder.

[0054] Preferably, it also includes an interactive machine, which has a built-in rocket simulation program for receiving initial conditions of a simulated rocket body input by a user, and displaying data and image animation; the data includes real-time data of a motion measurement module, and the image animation includes a simulated rocket body.

[0055] Compared with the prior art, it has the following beneficial effects:

[0056] The present invention proposes an adaptive augmented control method, which can actively compensate for unpredictable changes in model order, parameters and input signals according to feedback signals. Compared with the fixed structure and parameters of conventional feedback controllers, the controller of the adaptive control system follows certain adaptive rules during the control process and continuously adjusts its own parameters. Correspondingly, the adaptive control system adds an adaptive loop, which enables it to automatically adjust the controller parameters according to the system operation conditions to adapt to the changes in the characteristics of the controlled object and the external environment.

[0057] The present invention establishes a six-degree-of-freedom motion platform to simulate the forward and backward, left and right, up and down translation and rotation around three axes of the rocket during flight. The motion platform hardware system is controlled by a servo motor and integrates a variety of high-precision sensors, including accelerometers, gyroscopes, position sensors, etc., to collect real-time data such as displacement, velocity, acceleration and angular velocity of the motion platform to ensure data accuracy during the simulation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without creative work.

[0059] Figure 1 A schematic diagram of a rocket model adaptive augmented control method provided by an embodiment of the present invention;

[0060] Figure 2 A schematic diagram of the structure of a PID controller provided in an embodiment of the present invention;

[0061] Figure 3 A schematic diagram of the structure of an adaptive gain adjustment module provided in an embodiment of the present invention;

[0062] Figure 4 A schematic diagram of a reference model structure provided by an embodiment of the present invention;

[0063] Figure 5 A schematic diagram of the structure of a high-pass and low-pass filter provided in an embodiment of the present invention;

[0064] Figure 6 A flow chart of attitude calculation provided by an embodiment of the present invention;

[0065] Figure 7 A schematic diagram of the connection structure of a rocket simulation system provided by an embodiment of the present invention;

[0066] Figure 8 A schematic diagram of a motion measurement module provided by an embodiment of the present invention;

[0067] Fig. 9 A schematic diagram of the mechanical structure of a six-degree-of-freedom motion platform provided in an embodiment of the present invention;

[0068] Fig.10 A control block diagram of a six-degree-of-freedom motion platform provided in an embodiment of the present invention;

[0069] Fig.11 A flow chart of attitude calculation performed by a rocket simulation system provided by an embodiment of the present invention;

[0070] Fig.12 A flowchart of initializing a rocket simulation system provided by an embodiment of the present invention;

[0071] Fig.13 A schematic diagram of a user console for a rocket simulation system provided by an embodiment of the present invention;

[0072] Fig.14A schematic diagram of a user operation start interface of a rocket simulation system provided by an embodiment of the present invention;

[0073] Fig.15 A schematic diagram of a sensor setting window for a rocket simulation system provided by an embodiment of the present invention;

[0074] Fig.16 A schematic diagram of an initial condition setting window for a rocket simulation system provided by an embodiment of the present invention;

[0075] Fig.17 A schematic diagram of an animation display interface of a rocket simulation system provided by an embodiment of the present invention;

[0076] Fig.18 A schematic diagram of a data display interface for a rocket simulation system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] A first aspect of an embodiment of the present invention discloses a rocket model adaptive augmentation control method, comprising the following steps:

[0079] A rigid body controlled motion model of the rocket entity model under nominal conditions is established as a reference model to describe the motion state of the rocket in a preset interference-free flight environment; by setting the reference model parameters, the expected tracking instructions are generated, that is, the expected attitude angle that the rocket entity model should achieve under interference-free conditions;

[0080] Using the real-time data of inertial measurement information and navigation information and the six-degree-of-freedom equation during the movement of the rocket physical model, the actual motion state of the rocket physical model, including the actual attitude angle, is calculated;

[0081] Calculate the difference between the expected attitude angle and the actual attitude angle to obtain the attitude angle deviation;

[0082] The elastic vibration response in the output control command of the PID controller is subjected to high-pass and low-pass filtering to separate the elastic vibration signal, which is used to characterize the control signal error caused by the elastic vibration;

[0083] According to the attitude angle deviation and elastic vibration signal, as the input of the adaptive law, the gain of the PID controller is adjusted in real time to obtain the real-time updated PID control parameters;

[0084] Based on the updated PID controller parameters and attitude angle deviation, the control instructions are calculated to control the attitude of the rocket.

[0085] like Figure 1 As shown, the adaptive augmented control algorithm designed in the present invention can be divided into a PID controller module, a digital filter module, an adaptive gain adjustment module, an interference compensation module, and an active load reduction module, that is, a modular augmented design concept is adopted.

[0086] The PID controller module mainly realizes stable control in the assumed flight environment based on the nominal model of the launch vehicle, and comprehensively considers stability, accuracy and speed;

[0087] The digital filter module mainly suppresses elastic vibration interference through phase stability and amplitude stability;

[0088] The adaptive gain adjustment module mainly adjusts the controller gain in real time according to the comprehensive adaptive control rate, thereby improving the attitude control accuracy in strong interference and uncertainty environments;

[0089] The disturbance compensation module is mainly used to compensate for the error caused by the disturbance to reduce the control error of the attitude angle when the controller gain is reduced;

[0090] The active load reduction module mainly reduces the lateral and side loads on the launch vehicle in the large dynamic pressure area through the active load reduction control algorithm, such as Figure 1 The figure shows the adaptive augmented control system designed by the present invention.

[0091] The following is a detailed description of the algorithm functions:

[0092] In one embodiment, the PID controller is designed using the classical frequency domain method, and a digital filter is added to suppress the influence of elastic vibration. The PID controller structure is as follows: Figure 2 As shown:

[0093] By adjusting KP, KI, and KD, the control system has a certain amplitude margin and phase margin under ideal conditions. The digital filter is mainly aimed at the problem of large-scale changes in elastic vibration frequency during rocket flight. Considering that the design of traditional fixed parameter filters cannot meet the needs of elastic vibration control throughout the flight, the launch vehicle flight segment is divided into multiple intervals according to time, and the filter is optimized and designed in each interval. In the jth interval [t j ,t j+1 ], for the i-th order elastic vibration, a filter with the following transfer function form can be used for control:

[0094]

[0095] The corresponding filter optimization design method will be studied by taking the control of third-order elastic vibration as an example:

[0096] For the first-order elastic vibration, its frequency is close to the rigid body control frequency of the launch vehicle, so a filter needs to be designed to achieve phase stability control; for the second and third-order elastic vibrations, their frequencies are much larger than the rigid body control frequency, but the vibration amplitude is large, so a filter can be designed to achieve amplitude stability. The filter transfer function for the third-order elastic vibration is as follows:

[0097]

[0098] Among them, ω i1 ,ω i2 , i1 , i2 , k f are the parameters to be designed (i=1, 2, 3).

[0099] In one embodiment, in order to solve the problems that the active section of the launch vehicle is subject to large-scale interference and uncertainty, and the elastic vibration during the switching process of the digital filter is significantly affected, the adaptive gain is adjusted in real time to give full play to the control system's ability to cope with complex flight conditions. The schematic diagram of the adaptive gain adjustment algorithm designed in this embodiment is as follows: Figure 3 shown.

[0100] The adaptive gain adjustment algorithm is expressed as:

[0101]

[0102] In the formula, e r is the error between the reference model and the actual model output attitude angle, y s Characterize the influence of elastic vibration signal on the control system, k T is the total forward gain. The adaptive gain online adjustment system mainly consists of three parts: reference model, high-pass and low-pass filters, and adaptive law.

[0103] In this embodiment, the reference model mainly describes the rigid body controlled motion of the launch vehicle under nominal conditions, and forms the expected tracking instructions by designing model parameters, and then generates the attitude angle deviation by subtracting it from the attitude response of the actual launch vehicle under disturbed motion as the input of the adaptive law to achieve the purpose of changing the gain of the PID controller in real time. The reference model structure is as follows: Figure 4 shown.

[0104] Without considering the delay effect, the guidance command ω C and expected movement ω g Output control instructions with reference model The relationship between them can be expressed as follows:

[0105]

[0106] Then we can get:

[0107]

[0108] The reference model can be described by the second-order system transfer function form:

[0109]

[0110] Where: The design can be performed according to the expected response of each section of the nominal trajectory.

[0111] Taking into account the phase lag caused by the guidance command delay, actuators and sensors and other parasitic dynamic links, a delay link is introduced e -τs , the final reference model is as follows:

[0112]

[0113] Where: The delay time τ needs to be designed according to the specific characteristics of the actuator, sensor, and guidance command delay in the actual system to match the phase delay between the reference model and the actual model caused by the additional dynamics.

[0114] In one embodiment, high-pass and low-pass filtering is performed between the PID output and the adaptive gain adjustment algorithm. The functions of the high-pass filter and the low-pass filter are to extract and process the additional signal generated by the elastic vibration excitation in the control instruction and use it to reduce the controller gain. Its structure is as follows Figure 5 As shown in the figure, Output control instructions for the reference model, The PID controller outputs the control instruction. The difference between the two items can be The rigid body control signal in the output is eliminated and the remaining value is mainly the elastic vibration response. The function of the high-pass filter is to further reduce the amplitude of the low-frequency rigid body control signal, thereby ensuring that the adaptive law only accepts the elastic body vibration response. 2 The meaning of is to take the amplitude of the elastic vibration response, and the role of the low-pass filter is to convert y 2 The high-frequency vibration signal in the link output signal is eliminated.

[0115] Low pass filter output y s The expression is as follows:

[0116]

[0117] Where: G hp(s) is the transfer function of the high-pass filter, G lp (s) is the transfer function of the low-pass filter.

[0118] The transfer function of the high-pass filter is:

[0119]

[0120] The transfer function of the low-pass filter is:

[0121]

[0122] Where: hp and ω lp are the cutoff frequencies of the high-pass filter and the low-pass filter respectively.

[0123] Since it is necessary to obtain the elastic vibration excitation signal in the control command signal, ω hp The value should be slightly higher than the rigid body control frequency of the launch vehicle. After the signal is squared, it is passed through a low-pass filter to obtain the low-frequency component in the signal. Therefore, the cutoff frequency of the low-pass filter is ω lp It should be near the rigid body control frequency.

[0124] In summary, the main factors to be considered in the adaptive law design process are the deviation between the actual output and the reference model output, as well as the influence of elastic vibration, which are in the following specific forms:

[0125]

[0126] k T ∈[k T min ,k T max ],k α ∈[0,k αmax ]

[0127] k T =k α +k T min (11)

[0128] In the formula, k α is the adaptive gain, k αmax is the adaptive maximum gain, k T is the forward gain, k T max and k T min are the maximum and minimum forward gain, respectively, K s is the control command suppression gain, K β is the adaptive gain convergence coefficient, K e is the error amplification factor, which is the effect of amplifying or reducing the signal on the system gain. r is the error between the reference model and the actual model output attitude angle, y sis the output of high-pass and low-pass filtering, k T is the total forward gain.

[0129] In this embodiment, when the nominal controller is stable, the adaptive law will appear in the following three working states when it is applied to the ascent phase of the launch vehicle:

[0130] (1) When the elastic vibration has a small influence, that is, the digital filter has a good effect on suppressing the elastic vibration in each flight segment, and considering K β is very small and can be ignored, then the adaptive law becomes:

[0131]

[0132] By performing a pull-type transformation on the above formula, we can know that:

[0133]

[0134] From the final value theorem we know that:

[0135]

[0136] From the above formula, we can see that when the error e between the reference model and the actual model output attitude angle is r When it is not 0, the adaptive gain k α will gradually increase and eventually converge to k αmax .

[0137] (2) When the elastic vibration has a significant effect, which mainly occurs when the launch vehicle enters the large dynamic pressure area, the lateral load is large, the booster separation, stage separation and other structural changes are obvious, or the digital filters of each flight segment are switched, K in formula (11) is also ignored. β , then the adaptive law becomes:

[0138]

[0139] As the filter output signal y s The increase of Decreases to negative, then k T will also decrease, which is equivalent to controlling the amplitude of elastic vibration stably. If k is negative, α Reduce, the The term increases, K s k a y s The term decreases, which leads to the following result as shown in Equation 16 Increase, and eventually Approaches 0. At this time, the response of the control command to the elastic vibration is weakened to a self-oscillation state with a smaller amplitude.

[0140] (3) When the launch vehicle attitude enters a stable state, that is, when stable control is obtained and the influence of elastic vibration is small, the attitude angle deviation e between the actual model and the reference model is r and the control signal error y caused by elastic vibration s Close to 0, then:

[0141]

[0142] From formula (16), we can see that when t→∞, we have:

[0143]

[0144] From formula (17), we can see that when t→∞, k T =k α +k Tmin =1, indicating that the nominal PID controller can control the launch vehicle well at this time, so the adaptive law has no effect on the nominal controller.

[0145] In one embodiment, Mahony complementary filtering is often used in the attitude solution of UAVs, which is to add adaptive PI adjustment on the basis of complementary filtering. Calculating the actual motion state of the rocket entity model includes the steps of using the improved adaptive Mahony complementary filtering algorithm to perform attitude solution, mainly performing data fusion on the six-axis IMU (three-axis accelerometer, three-axis gyroscope), using high-pass filtering for the gyroscope (low-frequency noise), and using low-frequency filtering for the accelerometer (high noise), such as Figure 6 As shown:

[0146] Calculate the relative rotation error between the accelerometer measurement and the attitude angle estimate of the previous time interval;

[0147] Based on the relative rotation error, PI adjustment parameter k p and k i Calculate the new information generated by the PI regulator, where k p Used to control the crossover frequency between the accelerometer and the gyroscope, k i Used to correct gyroscope errors;

[0148] The compensated gyroscope value is calculated based on the gyroscope measurement value and the new information;

[0149] Using the quaternion at the previous moment and the compensated gyroscope value, the quaternion is updated to calculate the predicted quaternion value at the current moment;

[0150] The estimated value of the attitude angle at the current moment is calculated using the quaternion prediction value at the current moment.

[0151] When this embodiment is specifically implemented, the main filtering process is:

[0152]

[0153] δ=k p e+k i ·∫e

[0154] e=f×d (18)

[0155] In the formula, The quaternion represents the system attitude estimation, P(·) represents the rotation vector, δ represents the new information generated by the PI regulator, w represents the gyroscope measurement value, e represents the relative rotation error between the accelerometer measurement value f and the predicted inertia vector d, and the PI adjustment parameter k p Used to control the crossover frequency between the accelerometer and the gyroscope, k i Used to correct gyroscope errors.

[0156] The filtering process is divided into two parts: prediction and correction. In the prediction part, the quaternion attitude prediction is obtained by the angular velocity measured by the three-axis gyroscope. In the correction part, the quaternion attitude prediction is corrected by the value of the accelerometer.

[0157] The average value of the accelerometer value in the recent short period of time is used to adjust the parameters of the PI regulator. The specific design ideas are as follows:

[0158] Step 1: Get the gyroscope measurement value w, the accelerometer measurement value f, and the quaternion qn-1 at the previous moment;

[0159] Step 2: Use the most recent 20 acceleration measurements f to determine k p , k i value;

[0160] Step 3: Normalize f;

[0161] Step 4: Get the gravity field vector estimate from the quaternion attitude matrix q

[0162]

[0163] Step 5: Calculate the error vector e = f × d;

[0164] Step 6: Use the integral term I of the previous filter n-1 And this time the error vector e, calculate the integral term I n =I n-1 +k i ·Δt·e (Δt is the sampling period);

[0165] Step 7: Calculate the new information δ = k p e+I n ;

[0166] Step 8: Get the compensated gyroscope value w'=w+δ;

[0167] Step 9: Use the quaternion q at the previous moment n-1 And the compensated gyroscope value w′, update the quaternion:

[0168]

[0169] Step 10: q n Normalization.

[0170] Each attitude calculation goes through these 10 steps, using the quaternion attitude matrix above to calculate the attitude angle of the vehicle.

[0171] The second aspect of the embodiment of the present invention discloses a rocket simulation system, including a flight control computer module, an actuator module, a six-degree-of-freedom module, a motion measurement module and a rocket entity model; wherein:

[0172] The flight control computer module is embedded with a rocket control strategy, which obtains the real-time data of the motion measurement module and the real-time attitude information of the rocket solved by the six-degree-of-freedom model module, and outputs a control signal to the actuator and the six-degree-of-freedom model module through the rocket control strategy; the rocket control strategy is the rocket model adaptive augmented control method according to the first aspect of the embodiment;

[0173] The actuator includes a steering gear for controlling the rocket entity model, and is used for receiving a control signal to control the action of the steering gear;

[0174] The six-degree-of-freedom model module includes an attitude solving industrial computer and a six-degree-of-freedom platform; the rocket entity model is fixed on the six-degree-of-freedom platform, and the attitude solving industrial computer is embedded with an attitude solving algorithm and a rocket six-degree-of-freedom equation. The attitude solving algorithm is used to solve the attitude according to the real-time data of the motion measurement module, and the six-degree-of-freedom equation model is updated in combination with the control signal and the attitude solving result. The updated rocket six-degree-of-freedom equation is used to calculate the real-time attitude information of the rocket, and the position inverse solution algorithm is used based on the real-time attitude information of the rocket to calculate the motion position of the six-degree-of-freedom platform, so as to reproduce the motion state of the rocket entity model under the control signal;

[0175] The motion measurement module is installed in the rocket physical model to monitor the real-time data of the inertial measurement information and navigation information of the rocket physical model.

[0176] like Figure 7 As shown, an industrial computer or touch screen is used as a human-machine interface to input attitude signals, set motion commands and conduct real-time monitoring. The controller (attitude solving industrial computer) uses a motion control card or motion controller as the control core to perform kinematic inverse calculations. At the same time, 6 servo drivers generate drive signals to drive the electric cylinder to extend and retract to complete the motion command action, thereby realizing real-time closed-loop control.

[0177] In one embodiment, the motion measurement module uses a VG467 motion measurement system, which is installed in the simulated rocket body and can monitor the attitude information of the simulated rocket body in real time, and transmit the collected attitude information to the flight control computer to form an attitude control loop, such as Figure 8 It integrates a three-dimensional orthogonal accelerometer, a three-dimensional orthogonal gyroscope and a temperature sensor, and has excellent performance. It can measure the attitude (roll and pitch angles), angular velocity and acceleration information of the moving carrier, and is suitable for the navigation and control of the aircraft.

[0178] In one embodiment, Fig. 9 As shown, the six-degree-of-freedom platform is driven by six servo electric cylinders arranged in parallel. Its parallel mechanism is a multi-variable strongly coupled servo system, and each servo electric cylinder needs to move in a coordinated manner.

[0179] The six-degree-of-freedom platform includes: six servo electric cylinders arranged in parallel, an upper platform and a lower platform; the rocket entity model is fixed on the upper platform;

[0180] Six servo electric cylinders connect the upper platform and the lower platform through Hooke hinges and ball cage universal joint couplings, and the lower platform is fixed on the base; the attitude solving industrial computer controls the extension and retraction movement of the six servo electric cylinders to complete the movement of the upper platform with six degrees of freedom in three-dimensional space, so that the rocket physical model can simulate the three attitudes of roll, yaw and pitch and the translation movement of X, Y and Z axes.

[0181] In one embodiment, Fig.10 As shown, the attitude solving industrial computer is connected to the servo motor through the servo drive, and the servo motor is connected to the servo electric cylinder;

[0182] An encoder is provided at the tail end of the servo motor; the encoder data is sent to the host computer through the servo drive, and the current positions of the six servo electric cylinders are obtained by solving the encoder data; the resistance scale judges the stroke of the servo electric cylinder and is used for the absolute position electrical limit of the servo electric cylinder.

[0183] The function of the electronic control part is to receive the command data output by the flight control computer module and transmit it to the servo driver. The driver amplifies the signal and controls the motor movement, thereby driving the electric cylinder to move, and finally enables the platform to achieve various postures. The electronic control system is mainly used to receive user control commands, process various feedback signals, generate control signals, control the servo actuator to work, and finally drive the motion platform to complete various degrees of freedom.

[0184] In one embodiment, a position inverse algorithm is used to calculate the length of each electric cylinder through the platform position, and a motion control card is used as the instruction sending device of the motion platform. According to the calculated results, a 6-channel pulse + direction instruction is sent to control the movement of the 6 electric cylinders; the position inverse algorithm is:

[0185]

[0186] Where α, β, and γ correspond to the rotation angles of the moving platform around the X-axis, Y-axis, and Z-axis.

[0187] In one embodiment, the flight control computer module includes a PID controller, an adaptive gain adjustment module, an interference compensation module, and an active load reduction module; wherein,

[0188] The PID controller module is used to receive guidance instructions and output control signals to the rocket entity model;

[0189] The adaptive gain adjustment module adjusts the gain of the PID controller in real time according to the adaptive law;

[0190] The interference compensation module is used to provide interference error compensation to the PID controller module and the adaptive gain adjustment module to reduce the control error of the attitude angle when the PID controller gain is reduced to be lower than the set threshold;

[0191] The active load reduction module uses the active load reduction control algorithm to ensure that the lateral and side loads on the launch vehicle in the large dynamic pressure area are lower than the set threshold.

[0192] In one embodiment, Fig.11 The overall software design process of the rocket simulation system shown in the figure mainly includes system initialization, IMU data collection and calibration, attitude solution and data transmission. The main task is to configure the functions of each device in the system, collect IMU data, and finally send the calculated attitude angle to the aircraft controller through the serial port, while also sending the analog information of the attitude angle to the outside.

[0193] The system initialization is as follows: Fig.12 As shown. First, configure the system clock and multiply the 8MHz external clock to 168MHz. The difference between the STM32F4 chip and the STM32F1 chip is that the system clock has been set by default. You only need to call the startup_stm32f4xx.s file in the official library to set the external clock to 8MHz. Initialize the delay function and timer

[0194] In order to complete the control of the main control chip peripherals, a relatively accurate delay program should be provided. In this software project, the system tick timer is used to design two delay functions of microseconds and milliseconds. The timer is the general timer 3, and the timing time of this timer is configured to be 10ms, which meets the data transmission frequency of 100Hz of the horizon system. Both IMU and DAC8562 need SPI port driver, and the SPI port needs to be configured, and then the IMU and DAC8562 are written and read through the SPI port. In addition, the USART1 serial port needs to be initialized and configured. In order to transmit data quickly without occupying the CPU, the DMA function of USART1_TX is configured, and the DAM data transmission method is adopted.

[0195] In one embodiment, an interactive machine is also included, in which a rocket simulation program is embedded, and is used to receive the initial conditions of the simulated rocket body input by the user, and to display data and image animations; the data includes real-time data of the motion measurement module, and the image animation includes the simulated rocket body, such as Figure 13-18 As shown, users can intuitively see the input and output status of the sensor and adjust it to the data they want through settings. The system displays real-time animation, which is more intuitive.

[0196] The simulation system can accurately simulate the translation and rotation of the rocket. The simulation results show that the system can truly reflect the movement speed and attitude of the rocket under different conditions, record the flight altitude in real time, and fully display the entire process of the rocket's takeoff and landing. The implementation and integration of the dynamic model, sensor model, and actuator model designed in the system make the entire system have good scalability and flexibility, and can adapt to different simulation needs.

[0197] The rocket simulation system provided by the present invention is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

[0198] In this article, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

Claims

1. A rocket model adaptive augmented control method, characterized in that: The steps include: A rigid body controlled motion model of a rocket entity model under nominal conditions is established as a reference model to describe the motion state of the rocket in a preset interference-free flight environment; by setting the reference model parameters, an expected tracking instruction is generated, that is, an expected attitude angle that the rocket entity model should achieve in an interference-free state; Using the real-time data of inertial measurement information and navigation information and the six-degree-of-freedom equation during the movement of the rocket physical model, the actual motion state of the rocket physical model, including the actual attitude angle, is calculated; Calculating the difference between the desired attitude angle and the actual attitude angle to obtain an attitude angle deviation; The elastic vibration response in the output control command of the PID controller is subjected to high-pass and low-pass filtering to separate the elastic vibration signal, which is used to characterize the control signal error caused by the elastic vibration; According to the attitude angle deviation and the elastic vibration signal, as inputs of the adaptive law, the gain of the PID controller is adjusted in real time to obtain the PID control parameters updated in real time; Based on the updated PID controller parameters and the attitude angle deviation, a control instruction is calculated to control the attitude of the rocket.

2. The rocket model adaptive augmentation control method according to claim 1, characterized in that: The calculation of the actual motion state of the rocket entity model includes the steps of performing attitude calculation using an improved adaptive Mahony complementary filtering algorithm: Calculate the relative rotation error between the accelerometer measurement and the attitude angle estimate of the previous time interval; Based on the relative rotation error, PI adjustment parameter k p and k i Calculate the new information generated by the PI regulator, where k p Used to control the crossover frequency between the accelerometer and the gyroscope, k i Used to correct gyroscope errors; Calculate a compensated gyroscope value based on the gyroscope measurement value and the new information; Using the quaternion at the previous moment and the compensated gyroscope value, the quaternion is updated to calculate the predicted quaternion value at the current moment; The estimated value of the attitude angle at the current moment is calculated using the quaternion prediction value at the current moment.

3. The rocket model adaptive augmentation control method according to claim 1, characterized in that: The high-pass and low-pass filtering of the elastic vibration response in the control command includes the following steps: The output of high-pass and low-pass filtering s The expression is as follows: Where: G hp (s) is the transfer function of the high-pass filter, G lp (s) is the transfer function of the low-pass filter, The control instructions output by the reference model, It is the control instruction output by the PID controller; The transfer function of the high-pass filter is: The transfer function of the low-pass filter is: Where: hp and ω lp are the cutoff frequencies of the high-pass filter and the low-pass filter respectively.

4. The rocket model adaptive augmentation control method according to claim 1, characterized in that: According to the attitude angle deviation and the elastic vibration signal, as inputs of the adaptive law, real-time adjustment of the gain of the PID controller comprises the following steps: k T ∈[k Tmin ,k Tmax ],k α ∈[0,k αmax ] k T =k α +k Tmin Where: k α is the adaptive gain, k αmax is the adaptive maximum gain, k T is the forward gain, k Tmax and k Tmin are the maximum and minimum forward gain respectively, K s is the control command suppression gain, K β is the adaptive gain convergence coefficient, K e is the error amplification factor, which is the effect of amplifying or reducing the signal on the system gain. r is the error between the reference model and the actual model output attitude angle, y s is the output of high-pass and low-pass filtering, k T is the total forward gain.

5. The rocket model adaptive augmentation control method according to claim 4, characterized in that: Also includes: When the output of high-pass and low-pass filtering y s When the deviation of the attitude angle between the reference model and the actual model is less than the set threshold, r When not 0, the adaptive gain convergence coefficient K is ignored. β , adaptive gain k α gradually increases and eventually converges to k αmax ; With the high-pass and low-pass filtered output y s The increase eventually Approaching 0, the control command's response to the elastic vibration is weakened to a self-oscillation state with an amplitude less than the specified value; When the control command's response to the elastic vibration is weakened to a self-oscillation state with an amplitude less than the specified value, the attitude angle deviation e r And the output y of high-pass and low-pass filtering s approaches 0. When t→∞, k T =k α +k Tmin =1.

6. A rocket simulation system, characterized in that: It includes flight control computer module, actuator module, six-degree-of-freedom module, motion measurement module and rocket entity model; among them, The flight control computer module is embedded with a rocket control strategy, which obtains the real-time data of the motion measurement module and the real-time attitude information of the rocket solved by the six-degree-of-freedom model module, and outputs a control signal to the actuator and the six-degree-of-freedom model module through the rocket control strategy; the rocket control strategy is a rocket model adaptive augmented control method according to any one of claims 1 to 5; The actuator includes a steering gear for controlling the rocket entity model, and is used to receive the control signal to control the action of the steering gear; The six-degree-of-freedom model module includes an attitude solving industrial computer and a six-degree-of-freedom platform; the rocket entity model is fixed on the six-degree-of-freedom platform, and the attitude solving industrial computer is embedded with an attitude solving algorithm and a rocket six-degree-of-freedom equation. The attitude solving algorithm is used to solve the attitude according to the real-time data of the motion measurement module, and the six-degree-of-freedom equation model is updated in combination with the control signal and the attitude solving result. The updated rocket six-degree-of-freedom equation is used to calculate the real-time attitude information of the rocket, and the position inverse solution algorithm is used based on the real-time attitude information of the rocket to calculate the motion position of the six-degree-of-freedom platform, so as to reproduce the motion state of the rocket entity model under the control signal; The motion measurement module is installed in the rocket entity model and is used to monitor the real-time data of the inertial measurement information and navigation information of the rocket entity model in real time.

7. A rocket simulation system according to claim 6, characterized in that: The flight control computer module includes a PID controller, an adaptive gain adjustment module, an interference compensation module, and an active load reduction module; wherein, The PID controller module is used to receive guidance instructions and output control signals to the rocket entity model; The adaptive gain adjustment module adjusts the gain of the PID controller in real time according to the adaptive law; The disturbance compensation module is used to provide disturbance error compensation to the PID controller module and the adaptive gain adjustment module to reduce the control error of the attitude angle when the PID controller gain is reduced; The active load reduction module uses the active load reduction control algorithm to ensure that the lateral and side loads on the launch vehicle in the large dynamic pressure area are lower than the set threshold.

8. A rocket simulation system according to claim 6, characterized in that: The six-degree-of-freedom platform comprises: six servo electric cylinders arranged in parallel, an upper platform and a lower platform; the rocket entity model is fixed on the upper platform; The six servo electric cylinders connect the upper platform and the lower platform through Hooke hinges and ball cage universal joint couplings, and the lower platform is fixed on the base; the attitude solving industrial computer controls the telescopic movement of the six servo electric cylinders to complete the movement of the upper platform with six degrees of freedom in three-dimensional space, so that the rocket entity model simulates the three attitudes of roll, yaw and pitch and the movement of X, Y and Z axis translation.

9. A rocket simulation system according to claim 8, characterized in that: The attitude solving industrial computer is connected to the servo motor via a servo drive, and the servo motor is connected to the servo electric cylinder; An encoder is provided at the tail end of the servo motor; the encoder data is sent to the host computer through the servo drive, and the current positions of the six servo electric cylinders are obtained by solving the encoder data; the resistance scale judges the stroke of the servo electric cylinder and is used for the electrical limit of the absolute position of the servo electric cylinder.

10. A rocket simulation system according to claim 6, characterized in that: It also includes an interactive machine, which has a built-in rocket simulation program for receiving initial conditions of a simulated rocket body input by a user and displaying data and image animations; the data includes real-time data from a motion measurement module, and the image animation includes a simulated rocket body.

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