CN114578740A - Software driver control method based on improved active disturbance rejection control - Google Patents
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Abstract
The invention relates to the technical field of automatic control, in particular to a software driver control method based on improved active disturbance rejection control, which determines a total disturbance item according to a control input gain estimation value and a dynamic model of a software driver, decomposes the total disturbance item into a known disturbance information part and an unknown disturbance information part, compensates a system control law according to the control input gain estimation value, time lag time and the known disturbance information part to obtain an input quantity of an Extended State Observer (ESO), controls an output state feedback control law by a PD (pulse width modulation) of the ESO, obtains the system control law according to the state feedback control law, the known disturbance information part, the output quantity of the ESO and the control input gain estimation value, compensates an input end of the ESO according to the known disturbance information part and the time lag time, and can compensate one input end of the ESO without increasing system adjustable parameters, the estimation burden of the ESO is reduced, and the noise immunity, the tracking performance and the robustness of the system are improved.
Description
Technical Field
The invention relates to the technical field of automatic control, in particular to a software driver control method based on improved active disturbance rejection control.
Background
The soft driver can better adapt to the unstructured environment and more firmly grab various objects with irregular shapes due to the inherent characteristics of flexibility, safety and the like, so that the soft driver is concerned by more and more scholars.
However, due to the characteristics of high nonlinearity, strong coupling, time variation and strong elastic effect of the soft body driver, it is difficult to establish an accurate model of the soft body driver, and further various uncertainties actually existing in the soft body driver system, such as unmodeled dynamics of the system, external interference, and disturbance of internal parameters of the system, need to be considered when designing the controller.
An Active Disturbance Rejection Control (ADRC) is a controller that does not depend on a system-accurate model, and is very effective in solving the Control problem of a nonlinear Control system having uncertainty such as Disturbance. In order to further improve the control performance of the active disturbance rejection controller, in the related art, the system disturbance is estimated by one or more extended state observers ESO, and the estimated value is compensated to the ADRC as a compensation term, so that the estimation burden of the ESO in the ADRC is reduced, and the disturbance rejection capability of the system is improved.
Disclosure of Invention
In order to solve the above technical problems, the present invention provides a software driver control method based on improved active disturbance rejection control.
The invention adopts the following technical scheme:
a software driver control method based on improved active disturbance rejection control comprises the following steps:
constructing a dynamic model of the soft driver;
acquiring a control input gain estimated value and time lag time, determining a total disturbance item of a system according to the control input gain estimated value and the dynamic model, and decomposing the total disturbance item into two parts, namely a known disturbance information part and an unknown disturbance information part;
compensating a system control law according to the control input gain estimated value, the time lag time and the known disturbance information part to obtain a first input quantity, wherein the first input quantity and the system output quantity are used as two input quantities of an extended state observer to obtain three output quantities of the extended state observer, the first output quantity and the second output quantity of the extended state observer and a system reference input signal are input to a PD controller, and a state feedback control law is output;
and obtaining the system control law according to the state feedback control law, the known disturbance information part, the third output quantity of the extended state observer and the control input gain estimation value.
Further, the compensating a system control law according to the control input gain estimation value, the time lag time and the known disturbance information part to obtain a first input quantity includes:
and performing time lag compensation on a system control law according to the time lag time to obtain a time lag compensation quantity, then multiplying the time lag compensation quantity by the control input gain estimation value to obtain a first intermediate compensation quantity, and finally summing the first intermediate compensation quantity and the known disturbance information part to obtain the first input quantity.
Further, the extended state observer is designed as follows:
wherein z is1、z2And z3Are the three outputs of the extended state observer, respectively, where z1And z2Respectively representing the observed values of the extended state observer on the bending angle and the angular velocity of the soft body driver, z3Representing an estimate of the unknown disturbance information component by the extended state observer, b0Is the control input gain estimate, tdIs the time lag, q is the soft driverBending angle, τ being the system control law, β1、β2And beta3Respectively the gain of the extended state observer.
Further, the first output quantity and the second output quantity of the extended state observer and the system reference input signal are input to a PD controller, and a state feedback control law is output, including:
law of state feedback control u0The following were used:
where r denotes the system reference input signal, kpAnd kdIs the controller gain.
Further, the obtaining the system control law according to the state feedback control law, the known disturbance information part, the third output quantity of the extended state observer, and the control input gain estimation value includes:
the system control law τ is as follows:
u0is a state feedback control law.
Further, the dynamic model of the soft body driver is as follows:
wherein M (q) is a system inertia term,
is a Crorrio term, G (q) is a gravity term, tau is a system control law, taudIncluding unmodeled dynamics of the system and internal and external disturbances of the system, q is the bending angle of the soft body driver,
in order to be the angular velocity of the object,
is the angular acceleration.
Firstly establishing a dynamic model of a soft driver, then obtaining a system control input gain estimated value and time lag time, determining a total disturbance item of a system according to the estimated value of the control input gain and the dynamic model of the soft driver, decomposing the total disturbance item of the system into two parts of known model information and unknown disturbance information, compensating a system control law according to the estimated value of the control input gain, the time lag time and the known disturbance information part to obtain a first input quantity, taking the first input quantity and the system as two input quantities of an extended state observer to obtain three output quantities of the extended state observer, inputting the first output quantity and the second output quantity of the extended state observer and a system reference input signal into a PD controller, outputting the state feedback control law, and outputting the state feedback control law according to the state feedback control law, the known disturbance information part, the unknown disturbance information part, and the unknown disturbance information part, And the third output quantity of the extended state observer and the control input gain estimated value obtain a system control law. According to the method, one input end of the extended state observer is compensated according to the known disturbance information part and the time lag time, the estimation burden of the extended state observer can be reduced under the condition that the adjustable parameters of the system are not increased, and the disturbance resistance, the tracking performance and the robustness of the system are improved.
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In order to more clearly illustrate the technical solution of the embodiment of the present invention, the drawings needed to be used in the embodiment will be briefly described as follows:
fig. 1 is a control diagram corresponding to a software driver control method based on improved active disturbance rejection control according to an embodiment of the present application;
fig. 2 is a schematic diagram of a software driver structure of a software driver control method based on improved active disturbance rejection control according to an embodiment of the present application;
FIG. 3 is a schematic output diagram of a software driver control method based on improved active disturbance rejection control according to an embodiment of the present application;
fig. 4 is a schematic diagram of an output of a monte carlo experiment of a soft driver control method based on improved active disturbance rejection control according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
In order to explain the technical means described in the present application, the following description will be given by way of specific embodiments.
Fig. 1 is a control diagram corresponding to a software driver control method based on improved active disturbance rejection control according to an embodiment of the present application.
The software driver control method based on the improved active disturbance rejection control comprises the following steps:
constructing a dynamic model of the soft driver, which comprises the following steps:
wherein M (q) is a system inertia term,
is a Crrioo term, G (q) is a gravity term, and tau is a system control law, namely a system generalized force, taudIncluding unmodeled dynamics of the system and internal and external disturbances of the system, q is the bending angle of the soft body driver,
in order to be the angular velocity of the object,
is the angular acceleration.
It should be noted that the soft body driver of the embodiment of the present invention is a pneumatic soft body driver, and compared with a rigid robot, the term g (q) in the soft body driver model includes a strain energy part in addition to a gravitational potential energy part.
Specifically, M (q),
And the expression of G (q) is as follows:
wherein, Wp,Lp,Hp1,Hp2,LpqIn order to simplify the expressions in the formula (2), the expressions are respectively as follows:
as shown in FIG. 2, W, L, H represent the width, length and height, respectively, of the pneumatic soft driver, W1,W2Respectively, the width of the front wall and the side walls, L1,L20Respectively, the length of the outer wall and the initial length between the two side walls of the chamber, H1,H2,H3Respectively representing the heights of the outer wall, the upper wall and the bottom layer, wherein N is the number of the chambers, G is the shear modulus, m is the mass of the soft driver, and G is the gravity constant. The values of the parameters can be identified by a parameter identification method.
Obtaining a control input gain estimate b0And a time lag tdBased on the control input gain estimate b0And the dynamic model determines the total disturbance term of the system
And will total the disturbance term
Decomposed into two parts, respectively known disturbance information part
And unknown disturbance information part
It can be understood that for analytical convenience, the established soft body driver dynamics model is transformed into the following form:
from this it can be seen that the total disturbance term of the system
In addition, b0For the estimated value of the system control input gain, i.e. the system inertia term, i.e. the system true control input gain M-1(q) is an adjustable parameter.
Further, to better estimate the unknown disturbance information part
Will be provided with
Expand to a new system state x3And assume that
Is present and is equal to h, i.e.
Thus, a soft drive system can be written in the form of the following equation of state:
in addition, according to an embodiment of the present invention, the estimated values b of the system control input gain can be obtained by a model identification method0Time lag tdAnd a known disturbance information part
According to an embodiment of the present invention, the software driver model can be identified by the system identification tool box in matlab, and the identified objects are:
thereby determining an estimate b of the system control input gain based on the identified object010330, time lag td0.002 and known disturbance information part
Gain estimation b based on control input0Time lag tdAnd a known disturbance information part
The second-order linear active disturbance rejection controller is designed to control the soft driver so as to improve the control performance of the system.
The method comprises the following specific steps:
gain estimation b based on control input0Time lag tdAnd a known disturbance information part
Compensating the system control law tau to obtain a first input quantity of an ESO (extended state observer), wherein the specific compensation process is as follows: according to time lag tdThe time lag compensation is carried out on the system control law tau,obtaining the time lag compensation amount tau (t-t)d) Then the skew compensation amount tau (t-t)d) And control input gain estimate b0Multiplying to obtain a first intermediate compensation amount, and adding the first intermediate compensation amount and the known disturbance information part
And the first input quantity of the ESO of the extended state observer is obtained.
Acquiring a system output quantity q as a second input quantity of the extended state observer ESO, namely, the first input quantity and the system output quantity q are taken as two input quantities of the extended state observer ESO, and after being processed by the extended state observer ESO, three output quantities of the extended state observer ESO are acquired, wherein the three output quantities are respectively z1、z2And z3。
The extended state observer, ESO, is designed as follows:
wherein z is1And z2Respectively representing the bending angle q and the angular velocity of the Extended State Observer (ESO) to the soft driver
An observed value of z3Representing ESO pairs of extended state observers on unknown disturbance information parts
Estimate of beta1、β2And beta3Respectively the gain of the extended state observer ESO. Due to z1And z2Respectively representing the bending angle q and the angular velocity of the Extended State Observer (ESO) to the soft driver
An observed value of (f) is then1(z1，z2) Also denoted as known disturbance information part.
Current observerWhen the gain is properly set, the observer outputs z1、z2And z3The closer to the bending angle q and the angular velocity of the soft actuator
And the unknown disturbance information part
An estimate of (d). The parameters can be adjusted by a bandwidth parameterization method or a multi-objective optimization method and the like.
It can be understood that the conventional ADRC (auto-disturbance controller) directly connects the control quantity τ, i.e. the system control law τ and the estimated value b of the control input gain0The product of (d) is used as an input quantity of the extended state observer ESO, however, as shown in fig. 1, the improved active disturbance rejection controller (MADRC) according to the embodiment of the present invention performs two-part compensation on the control quantity τ and inputs the control quantity τ to the ESO, wherein the first part of compensation is based on the time lag tdCompensating the control quantity tau, i.e. delaying the control quantity tau output by the controller by the time lag tdTherefore, the problem that two input quantities of the ESO, namely the control quantity tau and the output quantity q, are not synchronous due to actual system delay can be avoided, and the control performance of the control system is improved. The second part of compensation is to use the known model information
Adding the control quantity tau (t-t) compensated by the first partd) And an estimate b of the control input gain0In the product of (a). Therefore, the estimation burden of the ESO can be reduced, the observation precision of the ESO is improved, and the anti-interference capability, the rapidness and the robustness of the system are further improved.
First output z of extended state observer1And a second output quantity z2And inputting a system reference input signal r into the PD controller to output a state feedback control law u0The following are:
wherein k ispAnd kdIs the controller gain.
According to the state feedback control law u0Part of known disturbance information
Third output z of extended state observer3And controlling the input gain estimate b0Obtaining a system control law tau as follows:
therefore, the purpose of the design of the system control law τ is to compensate for the estimation of unknown disturbances, thereby improving the tracking and anti-interference capabilities of the system.
It can be understood that, as shown in fig. 1, the improved active disturbance rejection controller MADRC of the embodiment of the present invention further adds a known disturbance information part when compensating for the unknown disturbance
Law of control to be designed
Substituting into the software driver model yields:
that is, the soft driver system can be converted to an integral tandem object by compensating for the estimated unknown perturbation and the known perturbation information part.
Therefore, the control method of the PD controller, i.e., the state feedback control law u, is designed for the compensated integral cascade object0。
Thus, according to an embodiment of the present invention, the improved active disturbance rejection controller MADRC of the present invention is used to control the soft driver shown in the aforementioned step S1, and add the disturbance at the simulation time of 25S, and the conventional ADRC and PID are used as the comparison controller to obtain the simulation output diagram shown in fig. 3, and as can be seen from fig. 3, the improved active disturbance rejection controller MADRC of the present invention is superior to the conventional ADRC and PID in both tracking speed and disturbance rejection. Meanwhile, when the model parameters L, L1, L20 and m of the software driver are changed within the range of +/-20% of the value, and when W2 and H1 are changed within the range of +/-10% of the value, Monte Carlo experiments are carried out on the improved active disturbance rejection controller MADRC, the traditional ADRC and the PID control software driver respectively to obtain an experimental graph as shown in FIG. 4, and as can be seen from the experimental graph, compared with the traditional ADRC and PID controller, the value of an Integral of Time and Absolute value of Error (ITAE) index output by the improved active disturbance rejection controller MADRC of the embodiment of the invention is smaller, wherein ITAE-sp represents an ITAE index in a tracking stage before disturbance is added, and ITAE-id represents an ITAE index after disturbance is added, so that the improved active disturbance rejection controller of the embodiment of the invention is stronger in robustness.
In summary, according to the software driver control method based on the improved active-disturbance-rejection control of the embodiment of the present invention, a dynamic model of the software driver is first established, then an estimated value of a control input gain of the system and a time lag time are obtained, a total disturbance term of the system is determined according to the estimated value of the control input gain and the dynamic model of the software driver, the total disturbance term of the system is decomposed into a known disturbance information part and an unknown disturbance information part, and finally a second-order linear active-disturbance-rejection controller is designed to control the software driver according to the known disturbance information part and the time lag time. Therefore, the software driver control method based on the improved active disturbance rejection control can reduce the estimation burden of the ESO without increasing the adjustable parameters of the system, thereby improving the disturbance rejection, the tracking performance and the robustness of the system.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (6)
1. A software driver control method based on improved active disturbance rejection control is characterized by comprising the following steps:
constructing a dynamic model of the soft driver;
acquiring a control input gain estimated value and time lag time, determining a total disturbance item of a system according to the control input gain estimated value and the dynamic model, and decomposing the total disturbance item into two parts, namely a known disturbance information part and an unknown disturbance information part;
compensating a system control law according to the control input gain estimation value, the time lag time and the known disturbance information part to obtain a first input quantity, wherein the first input quantity and the system output quantity are used as two input quantities of the extended state observer to obtain three output quantities of the extended state observer, the first output quantity and the second output quantity of the extended state observer and a system reference input signal are input to a PD controller, and a state feedback control law is output;
and obtaining the system control law according to the state feedback control law, the known disturbance information part, the third output quantity of the extended state observer and the control input gain estimation value.
2. The soft body driver control method based on the modified active disturbance rejection control of claim 1, wherein the compensating the system control law according to the control input gain estimation value, the time lag time and the known disturbance information part to obtain a first input quantity comprises:
and performing time lag compensation on a system control law according to the time lag time to obtain a time lag compensation quantity, then multiplying the time lag compensation quantity by the control input gain estimation value to obtain a first intermediate compensation quantity, and finally summing the first intermediate compensation quantity and the known disturbance information part to obtain the first input quantity.
3. The soft-body driver control method based on the improved active disturbance rejection control according to claim 1, wherein the extended state observer is designed as follows:
wherein z is1、z2And z3Are the three outputs of the extended state observer, respectively, where z1And z2Respectively representing the observed values, z, of the extended state observer on the bending angle and the angular velocity of the soft body driver3Representing the estimated value of the extended state observer on the unknown disturbance information part, b0Is the control input gain estimate, tdIs the time lag, q is the bending angle of the soft driver, tau is the system control law, beta1、β2And beta3Respectively the gain of the extended state observer.
4. The soft-body driver control method based on the improved active-disturbance-rejection control of claim 3, wherein the first output quantity and the second output quantity of the extended state observer and the system reference input signal are input to a PD controller, and a state feedback control law is output, comprising:
law of state feedback control u0The following:
where r denotes the system reference input signal, kpAnd kdIs the controller gain.
5. The soft-body driver control method based on the improved active-disturbance-rejection control according to claim 4, wherein the obtaining the system control law according to the state feedback control law, the known disturbance information part, the third output quantity of the extended state observer and the control input gain estimation value comprises:
the system control law τ is as follows:
u0is a state feedback control law.
6. The soft-body driver control method based on the improved active disturbance rejection control as claimed in claim 1, wherein the dynamic model of the soft-body driver is:
wherein M (q) is a system inertia term,
is a Crorrio term, G (q) is a gravity term, tau is a system control law, taudIncluding unmodeled dynamics of the system and internal and external disturbances of the system, q is the bending angle of the soft body driver,
in order to be the angular velocity of the object,
is the angular acceleration.
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| CN116352705A (en) * | 2023-02-28 | 2023-06-30 | 南通大学 | Underwater mechanical arm disturbance rejection prediction control method based on data driving |
| CN117192726A (en) * | 2023-09-07 | 2023-12-08 | 山东科技大学 | Quick reflector control method and device based on improved active disturbance rejection control |
| CN117890835A (en) * | 2024-01-29 | 2024-04-16 | 华中科技大学 | Overshoot time lag compensation method and system for inertial links |
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