CN107632531B - Method for establishing model for longitudinal movement of high-speed train with interference - Google Patents

Method for establishing model for longitudinal movement of high-speed train with interference Download PDF

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CN107632531B
CN107632531B CN201710826103.7A CN201710826103A CN107632531B CN 107632531 B CN107632531 B CN 107632531B CN 201710826103 A CN201710826103 A CN 201710826103A CN 107632531 B CN107632531 B CN 107632531B
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CN107632531A (en
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冒泽慧
李文凯
陶钢
姜斌
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Nanjing University of Aeronautics and Astronautics
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Abstract

The embodiment of the invention discloses a method for establishing a model for longitudinal movement of a high-speed train containing interference, which relates to the technical field of train control, can completely reflect the dynamic characteristics of a system and realizes the description of the longitudinal movement of the train through the model. The invention comprises the following steps: establishing a segmented dynamic model of the train, wherein the segmented dynamic model is used for representing: the longitudinal motion state of the healthy traction system of the train under the condition of containing interference; establishing an actuator fault model, wherein the actuator fault model comprises a parameterized fault model and a non-parameterized fault model and is used for analyzing actuator faults in the running process of the train; and correcting the segmented dynamic model through the actuator fault model. The invention is suitable for a train traction system.

Description

Method for establishing model for longitudinal movement of high-speed train with interference
Technical Field
The invention relates to the technical field of train control, in particular to a method for establishing a model of longitudinal movement of a high-speed train containing interference.
Background
After the sixth railway of the China railway has greatly accelerated, the train of the motor train unit which runs as the main force is basically changed into a CRH type train. And up to now, the expressway network with the largest scale and the fastest operation speed in the world has been built.
The actuator in the motor train unit train plays an extremely important role in the whole traction system of the train and is responsible for providing power required by normal operation of the train, so that the actuator has high reliability requirement on the train. With the acceleration of high-speed trains, the problem of actuator failure of train traction systems is more and more emphasized. In order to improve the safety of high-speed rail operation in China, the research on the faults of the actuator of the traction system of the high-speed train is imperative. In the field of research on faults of actuators of a traction system of a high-speed train, no matter fault diagnosis and positioning or fault compensation technology, longitudinal motion of the high-speed train needs to be modeled.
At present, almost all existing research results describe the longitudinal dynamic model parameters of the train by using known constant and time-varying bounded functions. In practice, these train longitudinal dynamics parameters are time-varying and no specific values can be obtained. In order to fully embody the dynamic characteristics of the system, a new model is required to describe the longitudinal movement of the train.
Disclosure of Invention
The embodiment of the invention provides a method for establishing a model for longitudinal movement of a high-speed train with interference, which can completely reflect the dynamic characteristics of a system and realize that the longitudinal movement of the train is described through the model.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
establishing a segmented dynamic model of the train, wherein the segmented dynamic model is used for representing: the longitudinal motion state of the healthy traction system of the train under the condition of containing interference;
establishing an actuator fault model, wherein the actuator fault model comprises a parameterized fault model and a non-parameterized fault model and is used for analyzing actuator faults in the running process of the train;
and correcting the segmented dynamic model through the actuator fault model.
The establishing of the segmental dynamic model of the train further comprises the following steps:
establishing a common resistance model F according to the acquired time-varying parametersr(t) wherein Fr(t) is expressed by the davis equation as:
Figure GDA0002590417420000021
Figure GDA0002590417420000022
representing the operating speed of the train, the time-varying parameters including: a (t) represents a drag component independent of the speed of travel of the train, b (t) represents a linear drag related to speed of travel, c (t) represents a non-linear drag related to speed of travel;
establishing a slope resistance model Fg(t) and Curve resistance model Fc(t) wherein Fg(t)＝M(t)gsinθ(t)，Fc(t) 0.004d (t) m (t), θ (t) represents the track inclination angle, d (t) represents the curvature of the curved track, and d (t) represents the curvature of the curved trackwThe representation indicates the distance between the front and rear wheels of the train, and R (t) indicates the radius of curvature of the curved track.
Further comprising:
updating the segmental dynamic model according to the acquired parameters, wherein the updated segmental dynamic modelThe method comprises the following steps:
Figure GDA0002590417420000023
wherein,
Figure GDA0002590417420000024
x1(t)＝x(t)，
Figure GDA00025904174200000213
and the space state equation of the longitudinal motion of the train is expressed as
Figure GDA0002590417420000026
Figure GDA0002590417420000027
Displacement x (t) and speed of the train
Figure GDA0002590417420000028
Obtaining from a GPS and onboard sensors of the train; m (t), a (t), b (t), c (t),
Figure GDA0002590417420000029
d (t) and
Figure GDA00025904174200000210
respectively, an unknown time-varying parameter, m (t), a (t), b (t), c (t),
Figure GDA00025904174200000211
d (t) and
Figure GDA00025904174200000212
is expressed as an indicative function χi：
Figure GDA0002590417420000031
Figure GDA0002590417420000032
Wherein Ω represents all possible system states in the train operation
Figure GDA0002590417420000033
Is divided into l partitions omegaiI 1.. l, the piecewise equation for each parameter is identified as:
Figure GDA0002590417420000034
Figure GDA0002590417420000035
Figure GDA0002590417420000036
the establishing of the actuator fault model comprises the following steps:
establishing a parameterized fault model of the actuator, wherein:
obtaining the sum of the traction force provided by all actuators when the train operates
Figure GDA0002590417420000037
Wherein n is the number of actuators, Fj(t) is the tractive effort produced by the jth of the n actuators;
establishing an actuator parameterized fault model:
Figure GDA0002590417420000038
wherein,
Figure GDA0002590417420000039
is the force, s, generated when the jth actuator failsjIs the number of fault base signals of the jth actuator, tjIt indicates the time at which the fault occurred,
Figure GDA00025904174200000310
all represent calculation constants, fjρRepresenting the underlying signal.
Acquiring system input when an actuator fails:
Figure GDA00025904174200000311
wherein v isj(t) represents a control signal of an actuator,. sigma.)jA parameter representing the fault type of the actuator;
and is
Figure GDA00025904174200000312
Wherein when σjWhen 0, the actuator fails, when σ isjWhen the value is 1, the actuating mechanism is in a healthy state;
since all of the actuators in the traction system use the same control signal, the system inputs can be written as:
Figure GDA0002590417420000041
Figure GDA0002590417420000042
Figure GDA0002590417420000043
Figure GDA0002590417420000044
wherein,
Figure GDA0002590417420000045
is a vector composed of the basis signals, vo(t) is the designed control signal, kvIs the failure mode parameter, and xi and
Figure GDA0002590417420000046
determining which actuators have failed and what type of failure occurred, k when an actuator has failedvξ is an unknown constant and occursK before failurev＝n，ξ＝0；
Establishing a parameterized fault model of an actuator:
Figure GDA0002590417420000047
Figure GDA0002590417420000048
the establishing of the actuator fault model comprises the following steps:
establishing non-parametric fault model of actuator
Figure GDA0002590417420000049
Figure GDA00025904174200000410
Wherein,
Figure GDA00025904174200000411
Figure GDA00025904174200000412
is an unknown bounded unparameterized term, and the system input is represented as:
Figure GDA00025904174200000413
vo(t) is the control signal for the design.
The invention provides a method for establishing a model for longitudinal motion of a high-speed train with interference, and relates to establishment of a segmented model based on the longitudinal motion of the high-speed train with interference and based on unknown system parameters, wherein the segmented model comprises a healthy segmented model and a fault segmented model. The fault segmentation model can be divided into an actuator parameterized fault model and an actuator non-parameterized fault model according to the type of the fault. The method specifically provides a method for establishing a segmented model based on unknown system parameters based on the longitudinal movement of a high-speed train containing interference, and under the multi-working-condition operation of the high-speed train, the unknown parameter segmented model is introduced to describe the longitudinal movement of the train, including a health model and a fault model. And aiming at the type of the fault, an actuator parameterized fault model and a non-parameterized fault model are respectively established, so that the dynamic characteristics of the system are completely reflected, and the longitudinal motion of the train is described through the models.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic view of the operation principle of the traction system according to the embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention. As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, 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 will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The embodiment of the invention provides a method for establishing a model of longitudinal movement of a high-speed train with interference, which is particularly applied to a traction system of the train shown in figure 1, and the method particularly comprises the following steps:
s1, establishing a segmented dynamic model of the train, wherein the segmented dynamic model is used for expressing: the longitudinal motion state of the healthy traction system of the train under the condition of containing interference;
s2, establishing an actuator fault model, wherein the actuator fault model comprises a parameterized fault model and a non-parameterized fault model and is used for analyzing actuator faults in the running process of the train;
and S3, correcting the segmented dynamic model through the actuator fault model.
S1, establishing a dynamic model of the train section, comprising:
establishing an initial model of longitudinal movement of the train
Figure GDA0002590417420000061
Wherein:
Figure GDA0002590417420000062
x (t) represents the displacement of the train, M (t) represents the mass of the train, F (t) represents the tractive effort of the trainr(t) common drag, Fg(t) represents the resistance generated by the inclined track, Fc(t) watchShowing the drag produced by the curved trajectory, d (t) showing the unmodeled disturbance component,
Figure GDA0002590417420000063
the representation represents the operating acceleration of the train.
Wherein, aiming at the parameters required in the establishment of the dynamic model of the train section, the method further comprises the following steps:
establishing a common resistance model F according to the acquired time-varying parametersr(t) wherein Fr(t) is expressed by the davis equation as:
Figure GDA0002590417420000071
Figure GDA0002590417420000072
representing the operating speed of the train, the time-varying parameters including: a (t) represents a resistance component independent of the running speed of the train, such as sliding resistance, track resistance, etc., b (t) represents a linear resistance related to the running speed, such as resistance generated by rim friction, rim impact, and inter-wheel rolling, etc., c (t) represents a non-linear resistance related to the running speed; such as drag caused by head end wind pressure, surface friction on the sides of the train, in-train turbulence, wind tunnel yaw, etc. During the train operation, the parameters a (t), b (t), c (t) are time-varying and unknown.
Establishing a slope resistance model Fg(t) and Curve resistance model Fc(t) wherein Fg(t)＝M(t)gsinθ(t)，Fc(t) 0.004d (t) m (t), θ (t) represents the track inclination angle, d (t) represents the curvature of the curved track, and the curvature can be represented by d (t) 0.5dwCalculated as/R (t), dwThe representation indicates the distance between the front and rear wheels of the train (for a train, the wheelbase length is a constant value), and r (t) indicates the radius of curvature of the curved track (for a curved track, its radius of curvature is a constant value).
Correcting the segmented dynamic model through the actuator fault model specifically comprises:
updating the institute according to the collected parametersThe segmented dynamic model after updating comprises:
Figure GDA0002590417420000073
wherein,
Figure GDA0002590417420000074
x1(t)＝x(t)，
Figure GDA00025904174200000711
and the space state equation of the longitudinal motion of the train is expressed as
Figure GDA0002590417420000076
Figure GDA0002590417420000077
x1(t) represents the displacement of the train,
Figure GDA0002590417420000078
is representative of the speed of the train or trains,
Figure GDA0002590417420000079
representing the acceleration, x, of said train1(t) and
Figure GDA00025904174200000710
obtaining from a GPS and onboard sensors of the train;
m(t)，a(t)，b(t)，c(t)，
Figure GDA0002590417420000081
d (t) and
Figure GDA0002590417420000082
respectively, an unknown time-varying parameter, m (t), a (t), b (t), c (t),
Figure GDA0002590417420000083
d (t) and
Figure GDA0002590417420000084
is expressed as an indicative function χi：
Figure GDA0002590417420000085
Figure GDA0002590417420000086
Wherein Ω represents all possible system states in the train operation
Figure GDA0002590417420000087
Is divided into l partitions omegaiI 1.. l, the piecewise equation for each parameter is identified as:
Figure GDA0002590417420000088
Figure GDA0002590417420000089
Figure GDA00025904174200000810
when the train is in a certain system shape omegaiIn operation, the system parameters (m (t), a (t), b (t), c (t),
Figure GDA00025904174200000811
D(t)，
Figure GDA00025904174200000812
) Has a value of (m)i，ai，bi，ci，
Figure GDA00025904174200000813
Di，
Figure GDA00025904174200000818
) But the specific numerical value is unknown. Due to system states x (t) and
Figure GDA00025904174200000815
is measurable in real time and the time t at which the change from one partition to another is known. Thus, the indicator number i can represent all the different operating conditions of the train.
In this embodiment, the establishing an actuator fault model includes:
establishing a parameterized fault model of the actuator, wherein:
obtaining the sum of the traction force provided by all actuators when the train operates
Figure GDA00025904174200000816
Wherein n is the number of actuators, Fj(t) is the tractive effort produced by the jth of the n actuators; when one or some of the actuators fails, the remaining actuators can still meet the desired control requirements.
Establishing an actuator parameterized fault model:
Figure GDA00025904174200000817
wherein,
Figure GDA0002590417420000091
is the force, s, generated when the jth actuator failsjIs the number of fault base signals of the jth actuator, tjIndicating the time of occurrence of the fault, Fj0、FjρAll represent calculation constants, fjρRepresenting the underlying signal.
Acquiring system input when an actuator fails:
Figure GDA0002590417420000092
wherein vj(t) represents a control signal of an actuator,. sigma.)jA parameter representing the fault type of the actuator;
and is
Figure GDA0002590417420000093
Wherein when σjWhen 0, the actuator fails, whenσjWhen the value is 1, the actuating mechanism is in a healthy state;
since all of the actuators in the traction system use the same control signal, the system inputs can be written as:
Figure GDA0002590417420000094
Figure GDA0002590417420000095
Figure GDA0002590417420000096
Figure GDA0002590417420000097
wherein,
Figure GDA0002590417420000098
is a vector composed of basic signals, vo(t) is the designed control signal, kvIs the failure mode parameter, and xi and
Figure GDA0002590417420000099
determining which actuators have failed and what type of failure occurred, k when an actuator has failedvξ is an unknown constant and k is before failureν＝n，ξ＝0；
Establishing a parameterized fault model of the actuator, which can be specifically understood as: according to an actuator parameterized fault model and a system input equation when the actuator of the traction system fails, a train fault system is rebuilt with an interference-containing vertical section dynamic model:
Figure GDA00025904174200000910
Figure GDA0002590417420000101
in parallel, the establishing of the actuator fault model further includes a process of reconstructing a dynamic model of a vertical section containing interference for a train fault system according to the non-parametric fault model of the actuator and a system input equation when the actuator of the traction system fails, namely, the establishing of the non-parametric fault model of the actuator includes:
Figure GDA0002590417420000102
Figure GDA0002590417420000103
wherein,
Figure GDA0002590417420000104
Fj0、Fjρ、fjρthere has been a definition as set forth above,
Figure GDA0002590417420000105
is an unknown bounded unparameterized term, and the system input is represented as:
Figure GDA0002590417420000106
νo(t) is the control signal of the design, parameter kv、ξ、
Figure GDA0002590417420000107
As defined above.
The invention relates to establishment of a segmentation model based on longitudinal movement of a high-speed train containing interference and based on unknown system parameters, which comprises a healthy segmentation model and a fault segmentation model. The fault segmentation model can be divided into an actuator parameterized fault model and an actuator non-parameterized fault model according to the type of the fault. The method specifically provides a method for establishing a segmented model based on unknown system parameters based on the longitudinal movement of a high-speed train containing interference, and under the multi-working-condition operation of the high-speed train, the unknown parameter segmented model is introduced to describe the longitudinal movement of the train, including a health model and a fault model. And respectively establishing parameterized and unparameterized fault models of the actuator according to the types of the faults. The method can be mainly divided into 2 stages: establishing a longitudinal motion segmental dynamic model containing interference under the condition of a train health traction system; when the actuator fault occurs in the running process of the train, the actuator fault model is divided into a parameterized fault model and a non-parameterized fault model, the actuator fault is designed according to the two models, and a segmented dynamic model containing interference under the system fault is described.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, it is relatively simple to describe, and reference may be made to some descriptions of the method embodiment for relevant points. The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (1)

1. A method for establishing a model of longitudinal movement of a high-speed train with interference is characterized by comprising the following steps:
establishing a segmented dynamic model of the train, wherein the segmented dynamic model is used for representing: the longitudinal motion state of the healthy traction system of the train under the condition of containing interference;
establishing an actuator fault model, wherein the actuator fault model comprises a parameterized fault model and a non-parameterized fault model and is used for analyzing actuator faults in the running process of the train;
correcting the segmented dynamic model through the actuator fault model;
the establishing of the segmental dynamic model of the train comprises the following steps:
establishing an initial model of longitudinal movement of the train
Figure FDA0002630988630000011
Wherein:
Figure FDA0002630988630000012
x (t) represents the displacement of the train, M (t) represents the mass of the train, F (t) represents the tractive effort of the trainr(t) common drag, Fg(t) represents the resistance generated by the inclined track, Fc(t) represents the drag produced by the curved trajectory, d (t) represents the unmodeled disturbance component,
Figure FDA0002630988630000013
representing the running acceleration of the train;
the establishing of the segmental dynamic model of the train further comprises the following steps:
establishing a common resistance model F according to the acquired time-varying parametersr(t) wherein Fr(t) is expressed by the davis equation as:
Figure FDA0002630988630000014
Figure FDA0002630988630000015
representing the operating speed of the train, the time-varying parameters including: a (t) represents a resistance component independent of the train operating speed, b (t) represents a linear resistance related to the operating speed, c (t) represents a non-linear resistance related to the operating speed;
establishing a slope resistance model Fg(t) and Curve resistance model Fc(t) wherein Fg(t)＝M(t)gsinθ(t)，Fc(t) 0.004d (t) m (t), θ (t) represents the track inclination angle, and d (t) represents the curvature of the curved track;
further comprising:
according to the collectedThe segmented dynamic model is updated with the parameters, and the updated segmented dynamic model includes:
Figure FDA0002630988630000021
wherein,
Figure FDA0002630988630000022
x1(t)＝x(t)，
Figure FDA0002630988630000023
and the space state equation of the longitudinal motion of the train is expressed as
Figure FDA0002630988630000024
Figure FDA0002630988630000025
x1(t) represents the displacement of the train,
Figure FDA0002630988630000026
representing the acceleration, x, of said train1(t) and
Figure FDA0002630988630000027
obtaining from a GPS and onboard sensors of the train;
m(t)，a(t)，b(t)，c(t)，
Figure FDA00026309886300000217
d (t) and
Figure FDA0002630988630000028
respectively, an unknown time-varying parameter, m (t), a (t), b (t), c (t),
Figure FDA00026309886300000218
d (t) and
Figure FDA0002630988630000029
is expressed as an indicative function χi：
Figure FDA00026309886300000210
Figure FDA00026309886300000211
Wherein Ω represents all possible system states in the train operation
Figure FDA00026309886300000212
Is divided into l partitions omegaiI 1.. l, the piecewise equation for each parameter is identified as:
Figure FDA00026309886300000213
Figure FDA00026309886300000214
Figure FDA00026309886300000215
the establishing of the actuator fault model comprises the following steps:
establishing a parameterized fault model of the actuator, wherein:
obtaining the sum of the traction force provided by all actuators when the train operates
Figure FDA00026309886300000216
Wherein n is the number of actuators, Fj(t) is the tractive effort produced by the jth of the n actuators;
establishing an actuator parameterized fault model:
Figure FDA0002630988630000031
wherein,
Figure FDA0002630988630000032
is the force, s, generated when the jth actuator failsjIs the number of fault base signals of the jth actuator, tjIt indicates the time at which the fault occurred,
Figure FDA0002630988630000033
all represent calculation constants, fjρRepresenting a base signal;
acquiring system input when an actuator fails:
Figure FDA0002630988630000034
wherein v isj(t) represents a control signal of an actuator,. sigma.)jA parameter representing the fault type of the actuator;
and is
Figure FDA0002630988630000035
Wherein when σjWhen 0, the actuator fails, when σ isjWhen the value is 1, the actuating mechanism is in a healthy state;
since all of the actuators in the traction system use the same control signal, the system inputs can be written as:
Figure FDA0002630988630000036
Figure FDA0002630988630000037
Figure FDA0002630988630000038
Figure FDA0002630988630000039
wherein,
Figure FDA00026309886300000310
is a vector composed of basic signals, vo(t) is the designed control signal, kνIs the failure mode parameter, and xi and
Figure FDA00026309886300000311
determining which actuators have failed and what type of failure occurred, k when an actuator has failedνξ is an unknown constant and k is before failureν＝n，ξ＝0；
Reestablishing a segmented dynamic model containing interference for a train fault system:
Figure FDA00026309886300000312
Figure FDA00026309886300000313
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CN106970528B (en) * 2017-04-06 2019-06-04 北京交通大学 A kind of adaptive contragradience fault tolerant control method for train Actuators Failures failure

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