CN115657473A - Control system for adaptive adjustment of carrier rocket gain and network parameters - Google Patents
Control system for adaptive adjustment of carrier rocket gain and network parameters Download PDFInfo
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Abstract
The application relates to the field of carrier rockets, and particularly discloses a control method and a system for adaptive adjustment of carrier rocket gain and network parameters. The control method comprises the following steps: acquiring a first arrow posture deviation signal, wherein the first arrow posture deviation signal is used for indicating the deviation between the actual arrow posture and the theoretical arrow posture; executing self-adaptive law operation according to the first rocket body attitude deviation signal to obtain an adjusting coefficient; adjusting the second arrow posture deviation signal according to the adjusting coefficient to obtain an arrow command signal; and controlling the attitude angle and/or the angular speed of the arrow body according to the arrow body command signal. The scheme of the application adopts stable amplitude control to the elastic vibration, so that the amplitude of the elastic vibration is reduced until the self-adaptation law reaches the latest equilibrium state.
Description
Technical Field
The application relates to the technical field of carrier rockets, in particular to a control system for adaptive adjustment of carrier rocket gain and network parameters.
Background
Along with the improvement of the carrying capacity of the carrier rocket, the mass, the thrust and the slenderness ratio of the carrier rocket are increased, the booster and the core-class engine are adopted to jointly swing to participate in attitude control, and meanwhile, due to the action of complex pneumatic load, the whole rocket presents the characteristics of elastic low-frequency dense-frequency mode, strong coupling vibration, complex local deformation and the like, so that the time-varying property and uncertainty of rocket model parameters to a great extent exist, and the stability margin of a rocket attitude control system is reduced, even the instability probability is greatly improved. The traditional attitude control design carries out ultimate deviation on model parameters according to selected characteristic second points, and a set of fixed parameters is designed to be suitable for rated and deviation states at multiple flight moments. This bias-based design is widely used in engineering, but is more conservative. And for the condition that the deviation of the model parameters is large, the parameters designed based on the mode are difficult to adapt to different flight moments.
Disclosure of Invention
The application provides a control method and a control system for self-adaptive adjustment, aiming at stably controlling the amplitude of elastic vibration to reduce the amplitude of the elastic vibration until the self-adaptive law reaches the latest equilibrium state.
In a first aspect, a method for controlling adaptive adjustment is provided, which includes:
acquiring a first arrow posture deviation signal, wherein the first arrow posture deviation signal is used for indicating the deviation between the actual arrow posture and the theoretical arrow posture;
executing self-adaptation law operation according to the first arrow posture deviation signal to obtain an adjusting coefficient;
adjusting a second arrow posture deviation signal according to the adjusting coefficient to obtain an arrow command signal;
and controlling the attitude angle and/or the angular speed of the arrow body according to the arrow body command signal.
The adjustment coefficients include gain adjustment coefficients and/or network adjustment coefficients.
On the basis of traditional PID control, a gain and network parameter self-adaptive adjusting module is added. Real-time high-order elastic vibration energy signals are extracted from the instruction signals through a high-pass filter and a low-pass filter, then gain and network adjustment coefficients are obtained through self-adaptive law and amplitude limiting processing, and the adjustment coefficients are fed back to the original gain and network, so that online self-adaptive adjustment of attitude angle gain parameters and network parameters is achieved.
Compared with the prior art, the scheme provided by the application at least comprises the following beneficial technical effects:
(1) The control parameters are adaptively adjusted according to the strength of the elastic signal flying in real time, the conservatism of the design of the ground fixed parameters is overcome, and the adaptability of the control system is greatly improved.
(2) The adjusted gain and/or network parameters are used for controlling, the influence of high-order elasticity on attitude angle control can be effectively inhibited, and the robustness and reliability of a control system are enhanced.
(3) The scheme provided by the invention is simple and reliable, and is easy for engineering realization.
With reference to the first aspect, in certain implementations of the first aspect, the second arrow attitude deviation signal and the first arrow attitude deviation signal are the same information.
The posture deviation of the arrow body in the current period can be regulated and controlled in real time.
With reference to the first aspect, in certain implementations of the first aspect, a period to which the first arrow attitude deviation signal corresponds precedes a period to which the second arrow attitude deviation signal corresponds.
The arrow attitude deviation signals can be processed in parallel, and the method is convenient to apply to high-frequency scenes.
With reference to the first aspect, in certain implementations of the first aspect, the performing an adaptive law operation according to the first arrow posture deviation signal to obtain an adjustment coefficient includes:
carrying out high-pass filtering processing on the first arrow body attitude deviation signal to obtain a first elastic energy signal;
carrying out low-pass filtering processing on the first elastic energy signal to obtain a second elastic energy signal;
and executing self-adaptation law operation according to the second elastic energy signal to obtain the adjusting coefficient.
The adaptive modulation design of gain and network parameters needs to use the elastic energy signal extracted by the low-pass filter as input, when the control parameters are reasonably designed, namely the correction network has good suppression on elastic vibration in each flight segment, the elastic signal in the instruction approaches to zero, so that the change rate of the adjustment coefficient is 0, and the adjustment coefficient is always kept about 1 as an initial value. If the elastic signal suddenly increases in the flying process, a high-frequency elastic vibration signal occurs in the attitude angle control command, the elastic energy of the attitude angle command after high-low pass filtering is increased, and the gain adjusting coefficient and the network adjusting coefficient are gradually reduced. The adjustment factor reduces the effect in two ways: firstly, the reduction of the gain is controlled, and secondly, the network parameters are adjusted to enhance the filtering effect of the elastic amplitude. The two measures are equivalent to adopting amplitude stability to control the elastic vibration, so that the amplitude of the elastic vibration is reduced until the self-adaptive law reaches the latest equilibrium state.
With reference to the first aspect, in certain implementations of the first aspect, the performing an adaptive law operation according to the first arrow posture deviation signal to obtain an adjustment coefficient includes:
executing self-adaptation law operation according to the first arrow posture deviation signal to obtain an initial value of an adjusting coefficient;
when the initial value of the adjusting coefficient is larger than the maximum preset adjusting coefficient, the adjusting coefficient is the maximum preset adjusting coefficient;
when the initial value of the adjusting coefficient is smaller than a minimum preset adjusting coefficient, the adjusting coefficient is the minimum preset adjusting coefficient;
and when the initial value of the adjusting coefficient is between the minimum preset adjusting coefficient and the maximum preset adjusting coefficient, the adjusting coefficient is the initial value of the adjusting coefficient.
And carrying out amplitude limiting processing on the adjustment coefficient to enable the adjustment coefficient to be in a reasonable range. In order to ensure that the adaptive gain and the network regulation range are within the design envelope range, margin analysis is carried out when the upper and lower limits of the gain are biased by 20% during normal frequency domain design. Meanwhile, enough stability margin is still reserved at the first-order elastic frequency after the time-varying network link on the first-order flight section main channel network string.
With reference to the first aspect, in certain implementations of the first aspect, the first elastic energy signal satisfies:
y hp ＝G hp (s)δ c ，G hp (s) represents the high-pass filtering process, δ c Representing the arrow command signal.
With reference to the first aspect, in certain implementations of the first aspect, the second elastic energy signal satisfies:
With reference to the first aspect, in certain implementations of the first aspect, the performing an adaptive law operation according to the first arrow pose deviation signal includes:
according to
Determining the adjustment coefficient k, y s ＝D aL (z)·(D aH (z)·L zl ) 2 Alpha and beta are adaptive constant coefficients greater than zero, D aH (z)、D aL (z) high-pass filter network and low-pass filter network, respectively, L zl In order to control the instructions, the control unit is provided with a control unit,
the adaptive law operation may take into account elastic effects, embodied in-p hi (y s ) A.k, realizationAnd controlling the amplitude stability caused by the elastic vibration.
With reference to the first aspect, in certain implementations of the first aspect, the activation function satisfies:
a. b and m are constant coefficients larger than zero.
The activation function being an elastic energy signal y s The function of (2) can be changed according to the strength of high-frequency elasticity contained in the attitude angle channel control command, and can be flexibly designed according to the actual situation.
With reference to the first aspect, in certain implementations of the first aspect,
and the lower limit design of attitude control design is combined, so that the rationality of self-adaptation law design is improved.
In a second aspect, there is provided an adaptive control system for performing the method as described in any one of the implementations of the first aspect.
Drawings
Fig. 1 is a schematic flowchart of a control method for adaptive adjustment according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of a control system for adaptive adjustment according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of another adaptive adjustment control system provided in an embodiment of the present application.
FIG. 4 shows the activation function p for different b/a hi (y s ) Schematic representation of (a).
Detailed Description
The present application is described in further detail below with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a schematic flowchart of a control method for adaptive adjustment according to an embodiment of the present application.
110, a first arrow attitude deviation signal is acquired.
And 120, executing self-adaptation law operation according to the first arrow posture deviation signal to obtain an adjusting coefficient.
And 130, adjusting the second arrow posture deviation signal according to the adjusting coefficient to obtain an arrow command signal.
And 140, controlling the attitude angle and/or the angular speed of the arrow body according to the arrow body command signal.
In the embodiment of the present application, the adjustment coefficient may include a gain adjustment coefficient and/or a network adjustment coefficient.
Fig. 2 is a schematic structural diagram of a control system for adaptive adjustment according to an embodiment of the present application. A control method for adaptive adjustment provided in the embodiment of the present application is described below with reference to fig. 2.
The control system may include a high pass filter, a low pass filter, an adaptation law 1, an adaptation law 2, a clipping process 1, a clipping process 2.
In period 1, the theoretical attitude angle 1 of the arrow body is assumed to be
Theoretical angular velocity 1 is ω c1 The actual attitude angle 1 of the arrow body is
The actual angular velocity 1 is ω 1 (the actual attitude angle and actual angular velocity can be detected by inertial components and rate gyros). According to
And
deviation of (a), and ω c1 And ω 1 The arrow posture deviation signal 1 can be obtained.
Network adjustment factor k according to cycle 1 w1 (e.g. for initial network adjustment factors, or δ from the previous cycle of cycle 1 c0 Determine) and the gain adjustment coefficient k for period 1 a1 (e.g. initial gain adjustment factor, or from a previous cycle of cycle 1δ c0 Determining), adjusting the arrow posture deviation signal 1 to obtain an adjusted arrow posture deviation signal 2. The arrow instruction signal delta can be determined according to the arrow attitude deviation signal 2 c1 . The arrow body command signal may be used to instruct the servo mechanism to control the state of the engine to reduce a deviation between the theoretical attitude angle and the actual attitude angle of the arrow body, and a deviation between the theoretical angular velocity and the actual angular velocity of the arrow body.
In particular, for the adjustment of the gain, it can be considered to directly adjust the static gain a of the main channel 0 Multiplying by an adjustment factor k 1 I.e. a 0 ＝k 1 ·a 0 (ii) a Network adjustments may be considered for, for example, second-order network elements
Molecular damping term xi of 1 Is adjusted by k 2 The variation of (c) completing the adjustment of the elastic high-frequency filtering, i.e. ξ 1 ＝k 2 ·ξ 2 。
In some embodiments, δ c1 Network adjustment coefficient k, which may also be used to indicate period 2 w2 And a gain adjustment coefficient k a2 . Network adjustment factor k w2 And a gain adjustment coefficient k a2 The method can be used for adjusting the arrow posture deviation signal 3 of the period 2 in the period 2, and obtaining an adjusted arrow posture deviation signal 4 in the period 2.
The specific process is as follows:
in period 2, the theoretical attitude angle 2 of the arrow body is assumed to be
Theoretical angular velocity 2 is ω c2 The actual attitude angle 2 of the arrow body is
The actual angular velocity 2 is ω 2 . According to
And
deviation of (a), and ω c2 And omega 2 The arrow posture deviation signal 3 can be obtained.
Network adjustment factor k according to cycle 2 w2 And the gain adjustment coefficient k of period 2 a2 And adjusting the arrow posture deviation signal 3 to obtain an adjusted arrow posture deviation signal 4. The arrow instruction signal delta can be determined according to the arrow attitude deviation signal 4 c2 。δ c2 Can be used for instructing the servo mechanism to control the state of the engine so as to reduce the deviation between the theoretical attitude angle and the actual attitude angle of the arrow body and the deviation between the theoretical angular velocity and the actual angular velocity of the arrow body.
In other embodiments, δ c1 It can also be used to modify the network regulation factor k of cycle 1 w1 And a gain adjustment coefficient k a1 Obtaining the corrected network regulation coefficient k w1’ And a gain adjustment coefficient k a1’ . Network adjustment factor k w1’ And a gain adjustment coefficient k a1’ The method can be used for adjusting the arrow posture deviation signal 1 of the period 1 in the period 1, and obtaining the adjusted arrow posture deviation signal 5 in the period 1. The arrow instruction signal delta can be determined according to the arrow attitude deviation signal 5 c1’ 。δ c1’ Can be used for instructing the servo mechanism to control the state of the engine to reduce the deviation between the theoretical attitude angle and the actual attitude angle of the arrow body, and the deviation between the theoretical angular velocity and the actual angular velocity of the arrow body.
Fig. 3 is another adaptive control system provided in an embodiment of the present application. A control method for adaptive adjustment provided in the embodiment of the present application is described below with reference to fig. 3.
The control system may include a high pass filter, a low pass filter, an adaptation law 1, an adaptation law 2, a clipping process 1, a clipping process 2.
In period 1, the theoretical attitude angle 1 of the arrow body is assumed to be
Theory of the inventionAngular velocity 1 is ω c1 The actual attitude angle 1 of the arrow body is
The actual angular velocity 1 is ω 1 . According to
And
deviation of (a), and ω c1 And ω 1 The arrow posture deviation signal 1 can be obtained. The rocket attitude deviation signal 1 can be used for indicating the network adjustment coefficient k of the period 1 w1 And a gain adjustment coefficient k a1 . Network adjustment factor k according to cycle 1 w1 And the gain adjustment coefficient k of period 1 a1 And adjusting the arrow body posture deviation signal 1 to obtain an adjusted arrow body posture deviation signal 2. The arrow instruction signal delta can be determined according to the arrow attitude deviation signal 2 c1 。
The flow of determining the adjustment coefficient is described below.
δ c May be passed through a high pass filter. Designing a high-pass filter G by combining the arrow high-order elastic frequency deviation range hp (s) calculating the high-order elasticity information y in the control command obtained through the network and the gain hp Extracted, comprising the following steps: y is hp ＝G hp (s)δ c . The extracted elastic information is squared to obtain an elastic energy signal
Elastic energy signal
May be passed through a low pass filter. Designing a low-pass filter G according to the arrow body response capability lp The frequency band of(s) is within the rigid body cutoff frequency, ensuring that the elastic signal entering the adaptive law changes smoothly. The low-pass filtering processing is carried out on the elastic energy signal, and the method comprises the following steps:
the elastic vibration signal is processed by a high-low pass filter and then is input into an adaptive law. Generally, the adaptive law is designed as a differential function form of an adjusting coefficient k, can be changed according to the strength of high-frequency elasticity contained in an attitude angle channel control command, and can be flexibly designed according to actual conditions.
In some embodiments provided by the present application, the gain and the adaptation law of the network are both designed as a differential function form of the adjustment coefficient k:
in the formula p hi (y s ) The function is an activation function, the activation function changes within the range of 0-1 according to the strength of high-frequency elasticity contained in the attitude angle channel control command, and alpha and beta are self-adaptive constant coefficients larger than zero.
The activation function may satisfy:
y s ＝D aL (z)·(D aH (z)·L zl ) 2 ，D aH (z)、D aL (z) high-pass and low-pass filter networks, respectively, L zl For control commands, a, b, m are constant coefficients greater than zero.
Elastic energy y in the command s Very small, the activation function is approximately 0, the elastic contribution part-p in the adaptation law hi (y s ) α · k is 0, in which case elasticity does not contribute to the gain adjustment. When y is s When the value is increased to a certain value, the activation function is gradually increased to 1, and the effect of elasticity on gain adjustment is gradually enhanced. Where m is the elastic energy signal y s The magnification of (2).
a and b determine the activation function p hi (y s ) B/a determines the threshold of activation, which is lower the smaller the threshold of activation, as shown in fig. 4. b determines a functionThe speed of rise, the faster the speed of rise, means the faster the gain and speed of network adjustment, the more sensitive to changes in resilience. From the perspective of engineering practice, it is desirable to avoid excessive tuning while combining simulation and actual flight result analysis.
In some embodiments, the adjustment coefficient output by the adaptive law may be an initial adjustment coefficient value. The initial value of the adjustment coefficient may be subjected to a clipping operation. Specifically, the adjustment coefficient calculated by the adaptive law is subjected to amplitude limiting processing by combining with frequency domain stability analysis, so as to output an adjustment coefficient final value.
Gain adjustment coefficient k a Network regulation factor k w The amplitude limiting value needs to be comprehensively considered according to the actual frequency domain stability design envelope range and the actual deviation range. k is a radical of formula a 、k w All initial values of (1.0) are carried out, and amplitude limiting treatment is carried out:
1) Clipping for gain adjustment
Is limited at
Within the range of, i.e.
2) Amplitude limiting for time-varying network regulation
Is limited at
Within the range of, i.e.
Then there is an adjusted control gain: a is 0 ＝k a ·a 0 And the adjusted time-varying network damping: xi 1 ＝k w ·ξ 1 。
For the design of the adaptive law parameters α and β, the balance point of the adaptive law, i.e. the
Comprises the following steps:
designing upper and lower limit ranges according to attitude control, and combining upper and lower limit ranges of gain deviation
When the gain reaches the lower limit amplitude
In time, there are:
for the adjustment of network parameters, the damping parameters of a second-order filter network at a fixed elastic frequency are considered to be adjusted, and a molecular damping parameter xi is set 1 In a regulation range of
When xi 1 Reach the lower limit amplitude
In time, there are:
the parameter selection principle is as follows:
1) If it is desired to activate the function p hi (y s ) If the gain adjustment coefficient reaches the amplitude limit value, =1
In this case, the gain does not easily reach the amplitude limit value, and the adjustment speed is not fast;
2) If desired at the activation functionIn the rising section p hi (y s ) When the gain adjustment coefficient reaches the amplitude limiting value, then
Therefore, the whole self-adaptive law is more sensitive to the reflection of elasticity, and the effect of reducing the elastic vibration by reducing the gain is better;
3) If desired activating the function p hi (y s ) If the network regulation coefficient reaches the amplitude limit value in the time of =1, the network regulation coefficient reaches the amplitude limit value
Under the condition, the parameters cannot easily reach the amplitude limit value, and the adjusting speed is not high;
4) If desired in the rising part p of the activation function hi (y s ) When the frequency is less than 1, the network regulation coefficient reaches the amplitude limit value, then
Therefore, the whole self-adaptive law is more sensitive to the reflection of elasticity, and the effect of reducing the elastic vibration by adjusting network parameters is better.
For inhibiting the crossing of large elastic deviation amplitude, the upper limit value of the regulating coefficient is regulated
Are all 1.
The adaptive adjustment control systems shown in fig. 2 and 3 can control the command δ at the attitude angle c For input, the static gain adjusts the coefficient k 1 Network adjustment factor k 2 For output, on the basis of a PID-based controller + correction network, the following two functions are realized through adaptive adjustment of gain and network adjustment coefficients:
(1) When the elastic signal is coupled with the control signal due to uncertain elastic vibration, the influence of the elastic vibration is weakened by adjusting the attitude angle channel gain and adjusting the network parameter on line to enhance the filtering;
(2) When the original controller can better realize stable control of the attitude angle, the gain and the network parameters are not changed as much as possible.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that the invention is not limited thereto, and that various changes and modifications may be made by those skilled in the art without departing from the spirit and scope of the invention.
Claims (12)
1. A control method for adaptive adjustment is characterized by comprising the following steps:
acquiring a first arrow posture deviation signal, wherein the first arrow posture deviation signal is used for indicating the deviation between the actual arrow posture and the theoretical arrow posture;
executing self-adaptation law operation according to the first arrow posture deviation signal to obtain an adjusting coefficient;
adjusting a second arrow posture deviation signal according to the adjusting coefficient to obtain an arrow command signal;
and controlling the attitude angle and/or the angular speed of the arrow body according to the arrow body command signal.
2. The method of claim 1, wherein the second arrow pose deviation signal and the first arrow pose deviation signal are the same.
3. The method of claim 1, wherein the first arrow pose deviation signal corresponds to a period that precedes a period that corresponds to the second arrow pose deviation signal.
4. The method of claim 1, wherein said performing an adaptive law operation based on said first arrow pose bias signal to obtain an adjustment coefficient comprises:
carrying out high-pass filtering processing on the first arrow body attitude deviation signal to obtain a first elastic energy signal;
carrying out low-pass filtering processing on the first elastic energy signal to obtain a second elastic energy signal;
and executing self-adaptation law operation according to the second elastic energy signal to obtain the adjusting coefficient.
5. The method of claim 4, wherein said performing an adaptive law operation based on said first arrow pose bias signal to obtain an adjustment coefficient comprises:
executing self-adaptation law operation according to the first arrow posture deviation signal to obtain an initial value of an adjusting coefficient;
when the initial value of the adjusting coefficient is larger than a maximum preset adjusting coefficient, the adjusting coefficient is the maximum preset adjusting coefficient;
when the initial value of the adjusting coefficient is smaller than a minimum preset adjusting coefficient, the adjusting coefficient is the minimum preset adjusting coefficient;
and when the initial value of the adjusting coefficient is between the minimum preset adjusting coefficient and the maximum preset adjusting coefficient, the adjusting coefficient is the initial value of the adjusting coefficient.
6. The method of claim 4, wherein the first elastic energy signal satisfies: y is hp ＝G hp (s)δ c ，G hp (s) represents the high-pass filtering process, δ c Representing the arrow command signal.
7. The method of claim 4, wherein the second elastic energy signal satisfies:
G lp (s) represents the low-pass filtering process, y hp Representing the first elastic energy signal.
8. The method of claim 4, wherein performing an adaptive law operation based on the first arrow pose bias signal comprises:
according to
Determining the adjustment coefficient k, y s ＝D aL (z)·(D aH (z)·L zl ) 2 Alpha and beta are adaptive constant coefficients greater than zero, D aH (z)、D aL (z) high-pass and low-pass filter networks, respectively, L zl In order to control the instructions, the control unit is provided with a control unit,
9. the method of claim 8, wherein the activation function satisfies:
a. b and m are constant coefficients larger than zero.
10. The method of claim 8,
11. the method according to any of claims 1 to 10, wherein the adjustment coefficients comprise gain adjustment coefficients and/or network adjustment coefficients.
12. An adaptive control system, characterized in that the system is adapted to perform the method according to any of claims 1 to 11.
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