CN111880403A - Fault-tolerant two-degree-of-freedom [ mu ] controller for maximum thrust state of aircraft engine - Google Patents

Fault-tolerant two-degree-of-freedom [ mu ] controller for maximum thrust state of aircraft engine Download PDF

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CN111880403A
CN111880403A CN202010546308.1A CN202010546308A CN111880403A CN 111880403 A CN111880403 A CN 111880403A CN 202010546308 A CN202010546308 A CN 202010546308A CN 111880403 A CN111880403 A CN 111880403A
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freedom
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缑林峰
张猛
刘志丹
蒋宗霆
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Northwestern Polytechnical University
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    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
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Abstract

The invention provides a fault-tolerant two-degree-of-freedom [ mu ] controller for a maximum thrust state of an aircraft engine, which mainly comprises a fault-tolerant control module for the two-degree-of-freedom [ mu ] controller group in the maximum thrust state and a fault diagnosis module for a gas circuit component; the fault-tolerant control module of the maximum thrust state two-degree-of-freedom mu controller group generates a control input vector u and outputs the control input vector u to the engine body, and the gas circuit component fault diagnosis module diagnoses the fault of the gas circuit component of the engine, calculates the health parameter h of the engine and outputs the health parameter h to the fault-tolerant control module of the maximum thrust state two-degree-of-freedom mu controller group. The invention not only has stronger robustness and low conservation, but also can well control the real engine in the maximum thrust state under the condition of the fault of the air passage component of the engine, improve the performance of the engine in the maximum thrust state to the maximum extent, ensure that the air passage component of the engine stably works in the maximum thrust state when the fault occurs, have optimal performance and improve the maneuvering performance of the fighter.

Description

Fault-tolerant two-degree-of-freedom [ mu ] controller for maximum thrust state of aircraft engine
Technical Field
The invention relates to the technical field of control of aero-engines, in particular to a fault-tolerant two-degree-of-freedom [ mu ] controller for a maximum thrust state of an aero-engine.
Background
An aircraft engine is a complex nonlinear dynamical system whose control system is susceptible to operating conditions, engine degradation, changes in environmental conditions, and it is difficult to know in advance the effects of external disturbances and measurement noise. Because the working process of the aircraft engine is very complicated and an accurate mathematical model is difficult to establish, the mathematical model always has a difference from an actual system. Therefore, there is a need for a robust controller for stabilizing an aircraft engine control system with good performance in the presence of external disturbance signals, noise disturbances, unmodeled dynamics and parameter variations. The method aims at the problem that the traditional single-degree-of-freedom controller cannot simultaneously give consideration to the robust stability and the robust performance of an aero-engine control system, and the design conservatism of the two-degree-of-freedom H-infinity controller design method is enhanced due to the fact that a perturbation structure is not considered. The design method of the two-degree-of-freedom mu controller adds a pre-filter and a feedback controller on the basis of the traditional mu controller, and the disturbance suppression capability is optimized by adjusting the feedback controller, and the instruction tracking capability of the system is optimized by adjusting the pre-filter on the basis.
The fighter plane needs to realize high maneuverability, and the performance and the safety of the maximum thrust state of an engine are very important. The traditional two-degree-of-freedom mu controller can realize stable control on the engine in the maximum thrust state. However, the requirements of modern warplanes on the performance of aircraft engines are continuously increased, the structures of the aircraft engines are more and more complex, and the engine faults account for 1/3 of the total faults of the aircraft due to the severe and variable operating environments of the engines. Wherein, the gas circuit part failure accounts for more than 90% of the total failure of the engine, and the maintenance cost accounts for 60% of the total maintenance cost of the engine. In order to ensure the safe operation of the engine and to make the failed engine provide sufficient performance to ensure the safe flight of the aircraft or have high maneuverability, the performance of the failed engine must be recovered, and the fault-tolerant control of the engine is performed to ensure the normal and stable operation of the control system and good performance. Therefore, the research on the fault tolerance control method of the gas circuit component of the engine is of great significance.
According to the traditional fault-tolerant control method for the gas circuit component, when the gas circuit component of the aeroengine fails, the control rule is corrected, so that the thrust of the engine is always matched with the throttle lever, and the thrust of the engine is effectively guaranteed. However, these design methods do not address the issue of current controller and engine model mismatches that result in degraded or even unstable control system performance. When the engine has a gas path component fault, the linear model of the engine at the same working point is also changed greatly. Therefore, a controller designed according to an engine model in a normal state generally cannot guarantee the performance of the engine when a gas path component fails, or even cannot guarantee the closed loop stability of a control system.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of an aero-engine, simultaneously gives consideration to the robust stability and the robust performance of an aero-engine control system, can still well control a real engine under the condition that an engine air path component has a fault in the maximum thrust state, ensures the safe work of the engine, gives full play to the performance of the maximum thrust state of the engine, improves the safety and the performance of an airplane, and improves the maneuverability of a fighter plane.
The technical scheme of the invention is as follows:
the fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of the aircraft engine is characterized in that: the device comprises a fault-tolerant control module of a two-degree-of-freedom [ mu ] controller group in a maximum thrust state and a fault diagnosis module of a gas path component;
the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state, the gas circuit component fault diagnosis module, the aircraft engine body and a plurality of sensors on the aircraft engine form a gas circuit component fault scheduling control loop;
the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state generates a control input vector u and outputs the control input vector u to the aeroengine body, and the sensor obtains an aeroengine measurement parameter y; the control input vector u and the measurement parameter y are jointly input into the gas circuit component fault diagnosis module, the gas circuit component fault diagnosis module diagnoses the fault condition of the gas circuit component of the engine to obtain a health parameter h of the aircraft engine, and outputs the health parameter h to the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state;
the fault-tolerant control module of the maximum thrust state two-degree-of-freedom mu controller group is internally provided with a plurality of two-degree-of-freedom mu controllers, the two-degree-of-freedom mu controllers are respectively designed and obtained by utilizing a plurality of linear uncertainty engine models, and the linear uncertainty engine models are obtained by adding the camera block after linearization is carried out on the nonlinear models of the aero-engine under the maximum thrust state and different gas path component faults of the aero-engine;
the fault-tolerant control module of the maximum thrust state two-degree-of-freedom mu controller group calculates and obtains an adaptive two-degree-of-freedom mu controller by utilizing a plurality of internally designed two-degree-of-freedom mu controllers according to an input health parameter h, and the two-degree-of-freedom mu controller generates a control input vector u according to a difference e between a reference input r and a measurement parameter y.
Further, the process of designing a plurality of two-degree-of-freedom μ controllers in the maximum thrust state two-degree-of-freedom μ controller group fault-tolerant control module is as follows: the method comprises the steps of linearizing an engine nonlinear model containing health parameters in the maximum thrust state of the aircraft engine to obtain a linearized model containing the health parameters, adjusting the values of the health parameters to obtain 11 linearized models respectively at the positions where the engine has no gas path component fault and a specific gas path component fault, adding a camera block to obtain 11 linear uncertainty engine models, and designing corresponding two-degree-of-freedom mu controllers for the 11 linear uncertainty engine models respectively to form a two-degree-of-freedom mu controller group in the maximum thrust state.
Further, the gas path component fault diagnosis module comprises a nonlinear airborne engine model and a linearization Kalman filter;
the nonlinear airborne engine model is an engine nonlinear model with health parameters:
Figure BDA0002539955960000031
y＝g(x,u,h)
wherein
Figure BDA0002539955960000032
In order to control the input vector,
Figure BDA0002539955960000033
in the form of a state vector, the state vector,
Figure BDA0002539955960000034
in order to output the vector, the vector is,
Figure BDA0002539955960000035
for the health parameter vector, f (-) is an n-dimensional differentiable nonlinear vector function representing the system dynamics, and g (-) is an m-dimensional differentiable nonlinear vector function producing the system output; the nonlinear onboard engine model is input into a control input vector u and a health parameter h of the previous period, and the output health steady-state reference value (x) of the nonlinear onboard engine modelaug,NOBEM,yNOBEM) The method comprises the steps of taking the current period of the linear Kalman filter as an estimated initial value;
the input of the linearized Kalman filter is a measurement parameter y and a healthy steady-state reference value (x) output by a nonlinear airborne engine modelaug,NOBEM,yNOBEM) According to the formula
Figure BDA0002539955960000036
Calculating to obtain a health parameter h of the engine in the current period; wherein
Figure BDA0002539955960000037
K is the gain of Kalman filtering
Figure BDA0002539955960000038
P is the Ricini equation
Figure BDA0002539955960000039
The solution of (1); coefficient AaugAnd CaugAccording to the formula
Figure BDA00025399559600000310
Determining, and A, C, L, M is an augmented linear state variable model reflecting engine performance degradation obtained by regarding the health parameter h as the control input of the engine and linearizing the nonlinear on-board engine model at a healthy steady-state reference point
Figure BDA0002539955960000041
Coefficient (c):
Figure BDA0002539955960000042
Figure BDA0002539955960000043
w is the system noise, v is the measurement noise, and the corresponding covariance matrices are the diagonal matrices Q and R.
Furthermore, the fault-tolerant control module of the maximum thrust state two-degree-of-freedom mu controller group obtains an adaptive two-degree-of-freedom mu controller according to the interpolation of the input health parameter h.
Furthermore, the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state corresponds to a controller K of the engine without component faults according to the maximum thrust state of the aircraft engine0Various typical component failures Δ hbase_jController (2)
Figure BDA0002539955960000045
(j＝1,2,...10)。Δhbase_jThe value of the jth element representing the vector Δ h is Δ hbaseThe value of the other element is 0, i.e. Δ hbase_jIndicating 10 different component failures, e.g. Δ hbase_1Indicates that the fan has failed and the amount of change in fan efficiency is Δ hbase. According to the formula
Figure BDA0002539955960000044
Calculating to obtain the second self of the fault degree (health parameter is h) of the current component of the engine at the maximum thrust state of the aircraft engineA degree mu controller K (in the formula,. DELTA.h)jIs the jth element of the vector Δ h; only if the | | delta h | | | is less than or equal to | | | delta hmaxFault condition of engine gas path component, when | | | delta h | | non-woven hair>||ΔhmaxThe engine has failed).
Further, the measurement parameters include the temperature and pressure at the outlet of the air inlet, the outlet of the fan, the outlet of the air compressor, the rear of the high-pressure turbine and the rear of the low-pressure turbine, the rotating speed of the fan and the rotating speed of the air compressor.
Advantageous effects
Compared with the prior art, the fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of the aircraft engine utilizes the inherent modules in the traditional gain scheduling controller, improves the fault-tolerant control module of the two-degree-of-freedom [ mu ] controller group for the maximum thrust state by additionally arranging a gas circuit component fault diagnosis module, and additionally arranges a plurality of groups of two-degree-of-freedom [ mu ] controllers under different gas circuit component faults of the engine. The gas circuit component fault diagnosis module realizes accurate judgment of gas circuit component faults through reliable estimation of health parameters, realizes robust fault-tolerant control of the engine in the maximum thrust state when the gas circuit component faults, has strong robustness and low conservation, improves the performance of the engine in the maximum thrust state to the maximum extent, ensures that the engine not only stably works in the maximum thrust state when the gas circuit component faults, but also has optimal performance, and improves the maneuvering performance of the fighter.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic structural diagram of a fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of an aircraft engine according to the invention;
fig. 2 is a schematic structural diagram of a fault diagnosis module of the gas circuit component in the gas circuit component fault scheduling control circuit according to the embodiment;
fig. 3 is a schematic structural diagram of a kalman filter in the fault diagnosis module of the gas path component according to the embodiment;
FIG. 4 is a diagram of a closed loop system architecture for a two degree-of-freedom controller;
FIG. 5 is a standard block diagram of a closed loop system of a two degree of freedom controller;
FIG. 6 is a diagram of a standard M- Δ structure;
FIG. 7 is a block diagram of a closed loop system;
FIG. 8 is a view of a μ -complex structure.
Detailed Description
The performance of the maximum thrust state of the engine is of great importance due to the need to achieve high maneuverability of the fighter. Although the traditional two-degree-of-freedom [ mu ] controller can realize stable control on the engine in the maximum thrust state, the properties of gas path components can be degraded due to factors such as natural abrasion, corrosion, fouling, thermal creep and the like in the running process of the aero-engine, and faults can be caused when the properties are degraded to a certain degree; in addition, the gas path member may also be damaged by foreign matter inhalation, mechanical fatigue fracture, or the like. The former failure occurs slowly, while the latter failure occurs rapidly. When the air path component of the engine fails and does not fail, part of the performance of the engine at the moment can seriously deviate from the rated state. Taking a turbine part as an example, when the turbine part fails, the working efficiency of the turbine part will be reduced, that is, the capability of converting the fuel gas with high temperature and high pressure into mechanical energy will be reduced, and corresponding power can be provided for a fan or a compressor part to enable the turbine part to work in a new balance state. At this time, the engine also deviates greatly from the original state. The failure of the gas circuit component can cause that a nonlinear model established during the design of the engine is seriously mismatched with a real engine during the failure of the gas circuit component, so that a gain scheduling controller designed according to the nonlinear model can not well control the engine with the failed gas circuit component, the performance of the engine is seriously reduced, the stability of a control system can not be even ensured, and the safe operation of the engine can not be ensured. The analytical study procedure of the present invention is given below in view of this problem.
1. Engine gas path component fault diagnosis
The failure of the gas path component can cause the corresponding characteristic parameter of the component to change. The engine gas circuit component faults are finally characterized on the changes of the working efficiency and the flow rate of different rotor components, namely the engine fault position and the fault degree can be revealed from the changes of the efficiency coefficients or the flow rate coefficients of the wind fan, the compressor, the main combustion, the high-pressure turbine and the low-pressure turbine components, and the efficiency coefficients or the flow rate coefficients of the fan, the compressor, the main combustion chamber, the high-pressure turbine and the low-pressure turbine components are called as health parameters.
Establishing engine nonlinear model with health parameters based on component method
Figure BDA0002539955960000061
y＝g(x,u,h)
Wherein
Figure BDA0002539955960000062
In order to control the input vector,
Figure BDA0002539955960000063
in the form of a state vector, the state vector,
Figure BDA0002539955960000064
in order to output the vector, the vector is,
Figure BDA0002539955960000065
for the health parameter vector, f (-) is an n-dimensional differentiable nonlinear vector function representing the system dynamics, and g (-) is an m-dimensional differentiable nonlinear vector function producing the system output.
And (3) regarding the health parameter h as the control input of the engine, and linearizing the nonlinear model of the engine at a healthy steady-state reference point by adopting a small perturbation method or a fitting method.
Figure BDA0002539955960000066
Wherein
A′＝A,B′＝(B L),C′＝C,
D′＝(D M),Δu′＝(Δu Δh)T
w is system noise, v is measurement noise, h is a health parameter, Δ h ═ h-h0(ii) a W and v are uncorrelated white gaussian noise, the mean value is 0, and the covariance matrix is diagonal matrices Q and R, which satisfies the following conditions:
E(w)＝0 E[wwT]＝Q
E(v)＝0 E[vvT]＝R
Δ represents the amount of change of the parameter, h0Representing an engine initial state health parameter.
Further obtains an augmented linear state variable model reflecting the performance degradation of the engine
Figure BDA0002539955960000071
Wherein the coefficient matrix is obtained by:
Figure BDA0002539955960000072
Figure BDA0002539955960000073
these coefficients have different values at different operating states of the engine.
In fact, the health parameters are difficult or even impossible to measure, and the pressure, temperature, speed, etc. of each part of the engine are easy to obtain by measurement, and are generally called "measurement parameters", mainly including the temperature and pressure at the outlet of the air inlet, the outlet of the fan, the outlet of the compressor, the temperature and pressure after the high-pressure turbine and the low-pressure turbine, the speed of the fan and the speed of the compressor. When the working environment of the engine does not change, the change of the health parameter can cause the corresponding change of the measured parameter, and an aerodynamic thermodynamic relation exists between the health parameter and the measured parameter. Thus, an optimal estimation filter can be designed to achieve optimal estimation of the health parameter by measuring the parameter.
For a graded component failure, the corresponding failed component health parameter changes slowly, so over the time period in which a single failure diagnosis is performed, it can be considered that the requirements are met
Figure BDA0002539955960000074
For the mutant component failure, the severity of the component failure is more concerned when the engine works stably again after the failure occurs, and the health parameter change of the failed component is still satisfied after the engine works stably again
Figure BDA0002539955960000075
Further converting the health parameters into state variables to obtain
Figure BDA0002539955960000081
Wherein
Figure BDA0002539955960000082
Figure BDA0002539955960000083
The established gas path component fault diagnosis module mainly comprises two parts, wherein one part is a nonlinear airborne engine model based on health parameters, and the other part is a piecewise linear Kalman filter. The basic working principle is that the output of the nonlinear airborne engine model is used as a steady-state reference value of the piecewise linear Kalman filter, health parameters are expanded, online real-time estimation is carried out through the piecewise linear Kalman filter, and finally the online real-time update is fed back to the nonlinear airborne engine model, so that the real-time tracking of an actual engine is realized.
The kalman estimation equation is:
Figure BDA0002539955960000084
k is the gain of Kalman filtering
Figure BDA0002539955960000085
P is the Ricini equation
Figure BDA0002539955960000086
The solution of (1); healthy steady-state reference value (x) output by using nonlinear airborne modelaug,NOBEM,yNOBEM) As formula
Figure BDA0002539955960000087
The initial value of (a) can be obtained by the following calculation formula:
Figure BDA0002539955960000088
the health parameter h of the engine can be obtained according to the calculation formula, and the fault diagnosis of the gas circuit component of the engine is realized.
2. Two-degree-of-freedom mu controller design with uncertain model of health parameters
Uncertainty inevitably exists in any practical system, and can be divided into two categories, disturbance signal and model uncertainty. The disturbing signal includes interference, noise, and the like. The uncertainty of the model represents the difference between the mathematical model and the actual object.
Model uncertainty may have several reasons, some parameters in the linear model are always in error; parameters in the linear model may change due to non-linearity or changes in operating conditions; artificial simplification during modeling; degradation of engine performance due to wear and the like.
The uncertainty may adversely affect the stability and performance of the control system.
The error between the actual engine and the nominal model (which is a conventional non-linear model of the engine without healthy parameters) can be expressed as a shot block Δ. Adding a camera block into a nominal model to establish an uncertain model of an engine
Figure BDA0002539955960000091
Figure BDA0002539955960000092
It can also be represented as
G(s)＝[I+Δ(s)]Gnom(s)
And finally, designing the two-degree-of-freedom mu controller by utilizing a traditional two-degree-of-freedom mu controller design method according to the uncertain model.
3. Two degree of freedom mu controller design
A block diagram of a closed loop system with a two degree of freedom controller is shown in fig. 4. The system has a reference input (r), an output disturbance (d) and two output errors (z)1) And (z)2). System M0 is an ideal model that the closed loop system should match. In this configuration, the two signals e and u will be minimized, in addition to the internal stability requirements. Signal e shows the difference between the system output and the reference model output. u is a control signal and also relates to robust stability in panning. In fig. 4, two weighting functions are included to reflect the characteristics between the two penalty signals.
The two-degree-of-freedom control is a control in which a parameter for optimizing the target tracking characteristic and a parameter for optimizing the disturbance rejection characteristic are independently set, and a feedback controller (K) is usedy) To achieve internal stability, robust stability, interference suppression, etc., and designing another controller (K) on the feed-forward pathr) To meet the tracking requirements and minimize the difference between the output of the entire system and the output of the reference model M, so that both characteristics are optimized simultaneously.
The structure of figure 4 can be determined by defining w-r,
Figure BDA0002539955960000101
to rearrange into the standard configuration of figure 5. The controller K is composed of a feedback controller K for interference attenuationyAnd a pre-filter KrIs composed ofThe desired closed loop performance is now expressed as
K＝[KrKy]
The difference between the design of the two-degree-of-freedom [ mu ] controller and the design of the two-degree-of-freedom H [ infinity ] controller is that the latter is a solving controller K which enables the norm of a system to be minimized, the former is a solving controller K which enables the structure singular value of the system to be minimized, if perturbation of an uncertainty system is unstructured, the norm minimum and the structure singular value are equivalent, if perturbation of the uncertainty system is structured, the controller designed is conservative by enabling the system norm to be minimized, and the condition of a known diagonal structure of perturbation is not considered, so that the robustness stability and the robustness performance of the control system cannot be fully played, and the defect is overcome by the controller K which is designed by enabling the structure singular value of the system to be minimized.
In an aircraft engine two-degree-of-freedom mu-controller design problem, the uncertainties considered will include non-structural uncertainties (e.g., unmodeled dynamics) and parameter variations. All these uncertainties can still be extracted from the dynamics, the whole system can be rearranged in a standard structure of (upper) linear fractional transforms F (M, Δ), and the relationship between the uncertainty blocks and the nominal model can be summarized as a standard structure, as shown in fig. 6, to show how the uncertainty affects the input/output relationships of the control system under study. The uncertainty block Δ will have the general form:
Figure BDA0002539955960000102
wherein
Figure BDA0002539955960000103
n is the dimension of the block delta. We also assume that the deltaset is bounded. Moreover, we can define a set of normalized structural uncertainties from this
Figure BDA0002539955960000104
For M ∈ Cn×nPhase of changeStructural singular value μ of M for ΔΔ(M) is a number defined such that μΔ -1(M) is equal to the minimum of singularities (I-M Delta)
Figure BDA0002539955960000105
Namely, it is
Figure BDA0002539955960000106
If there is no Δ ∈ Δ such that det (I-M Δ) ═ 0, then μΔ(M)：＝0。
When M is the interconnection transfer matrix as shown in FIG. 6, the structural singular values for Δ are defined as
Figure BDA0002539955960000107
Accordingly, the uncertainty set may be defined as
Figure BDA0002539955960000111
When the uncertainty structure is fixed, we can omit μ for simplicityΔSubscript Δ of (M).
The inverse of the structure singular value represents the frequency dependent stability margin. Robust stability results with respect to structural uncertainty are given below.
Make the nominal feedback system (M (s)) stable and let beta > 0 be an uncertain boundary, i.e., | | Δ | non-calculation∞＜β,
Figure BDA0002539955960000112
If and only if
Figure BDA0002539955960000113
The perturbation system is robust stable with respect to delta.
It is clear that if uncertainty is present in the unit sphere B Δ, then the robust stability condition is μΔ(M(s))≤1。μΔ(M (s)) depends on frequency and, in practical applicationsCalculated at "every" frequency within a reasonable range.
Consider the control problem in the Linear Fractional Transform (LFT) shown in fig. 7.
The system denoted by P is an open-loop connection and represents all known elements, including the nominal system model and the performance weighting function, as well as the uncertainty weighting function. The block Δ is an uncertainty element from the set Δ that parameterizes the model uncertainty for all assumptions. The controller is denoted by K. The inputs to P are three sets of signals: input u caused by uncertaintyΔReference input and disturbance w and control u. Three sets of outputs are generated: from the uncertainty, error or controlled output z and the measured value yΔ。
LFT describes a set of systems to be controlled
Figure BDA0002539955960000114
The design objective is to define a controller K that stabilizes the nominal system; for all Δ ∈ Δ, max ω σ Δ (j ω) ] ≦ 1, the closed-loop system is stable and satisfies
||FU[FL(P,K),Δ]||∞＜1
For any given K, a pair-linear fractional transform F can be usedLRobust performance testing of (P, K) to test the performance criteria. Robust performance testing should be performed on extended uncertain structures
Figure BDA0002539955960000115
Wherein ΔFIs an imaginary unstructured camera block. The system with the controller K can achieve reliable performance, if and only if
Figure BDA0002539955960000121
The purpose of the mu-integration is to make the closed-loop transfer function matrix F in the set of all stabilizing controllers KLStructural singular value of (P, K)
Figure BDA0002539955960000122
The peak of (a) is minimized. This is written as
Figure BDA0002539955960000123
As shown in fig. 8. Finally, the controller K can be obtained by carrying out mu-integration through a D-K iteration method.
4. Interpolation of controller
This section illustrates the scheduling calculation principle of the maximum thrust state two-degree-of-freedom mu controller group fault-tolerant control module in fig. 1 for obtaining the corresponding two-degree-of-freedom mu controller through the health parameter scheduling linear interpolation.
At the maximum thrust state of the engine, at the normal state of the engine and various typical component faults deltahbase_jA series of linear two-degree-of-freedom mu controllers are designed under the state to control the engine. This will result in the controller in the fault tolerant control module of the two degree of freedom mu-controller group in the maximum thrust state of fig. 1
Figure BDA0002539955960000124
The controller is then interpolated according to the health parameter h, and the resulting interpolated controller is then used to control the system.
Controller K corresponding to engine no-component fault according to maximum thrust state of engine0Various typical component failures Δ hbase_jController (2)
Figure BDA0002539955960000125
Δhbase_jThe value of the jth element representing the vector Δ h is Δ hbaseThe value of the other element is 0, i.e. Δ hbase_jIndicating 10 different component failures, e.g. Δ hbase_1Indicates that the fan has failed and the amount of change in fan efficiency is Δ hbase. Controller capable of obtaining gas circuit component fault h at maximum thrust state of engine through linear interpolation
Figure BDA0002539955960000126
And the engine is effectively controlled.
Based on the above process, the following provides a fault-tolerant two-degree-of-freedom μ controller for the maximum thrust state of an aircraft engine, which mainly includes a fault-tolerant control module for the maximum thrust state two-degree-of-freedom μ controller group and a fault diagnosis module for a gas circuit component, as shown in fig. 1.
The fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state, the gas circuit component fault diagnosis module, the aircraft engine body and a plurality of sensors on the aircraft engine form a gas circuit component fault scheduling control loop 10.
The fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state generates a control input vector u and outputs the control input vector u to the aeroengine body, and the sensor obtains an aeroengine measurement parameter y; the control input vector u and the measurement parameter y are jointly input into the gas circuit component fault diagnosis module, the gas circuit component fault diagnosis module calculates to obtain a health parameter h of the aircraft engine, and outputs the health parameter h to the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state.
The maximum thrust state two-degree-of-freedom mu controller group fault-tolerant control module is internally designed with a plurality of two-degree-of-freedom mu controllers, each two-degree-of-freedom mu controller comprises a pre-filter and a feedback controller, and the two-degree-of-freedom mu controllers are respectively designed by a mu comprehensive method for a plurality of uncertain engine models.
The uncertain engine model is obtained by adding a camera block after linearization is carried out on the nonlinear model of the aero-engine under the maximum thrust state and different gas path component faults of the aero-engine.
In a preferred embodiment, the design of the two-degree-of-freedom μ controller can be achieved by the following process: the method comprises the steps of linearizing an engine nonlinear model containing health parameters in the maximum thrust state of the aircraft engine to obtain a linearized model containing the health parameters, adjusting the values of the health parameters to obtain 11 linearized models respectively at the positions where the engine has no gas path component fault and a specific gas path component fault, adding a camera block to obtain 11 linear uncertainty engine models, and designing corresponding two-degree-of-freedom mu controllers for the 11 linear uncertainty engine models respectively to form a two-degree-of-freedom mu controller group in the maximum thrust state.
The fault-tolerant control module of the maximum thrust state two-degree-of-freedom mu controller group calculates and obtains an adaptive two-degree-of-freedom mu controller by utilizing a plurality of internally designed two-degree-of-freedom mu controllers according to an input health parameter h, and the two-degree-of-freedom mu controller generates a control input vector u according to a difference e between a reference input r and a measurement parameter y.
In a preferred embodiment, the adaptive two-degree-of-freedom μ controller may be obtained by interpolation according to the input health parameter h:
controller K corresponding to engine no-component fault according to maximum thrust state of engine0Various typical component failures Δ hbase_jController (2)
Figure BDA0002539955960000131
Δhbase_jThe value of the jth element representing the vector Δ h is Δ hbaseThe value of the other element is 0, i.e. Δ hbase_jIndicating 10 different component failures, e.g. Δ hbase_1Indicates that the fan has failed and the amount of change in fan efficiency is Δ hbase. Controller capable of obtaining gas circuit component fault h at maximum thrust state of engine through linear interpolation
Figure BDA0002539955960000141
And the engine is effectively controlled.
The gas circuit component fault diagnosis module comprises a nonlinear airborne engine model and a linearization Kalman filter.
The nonlinear airborne engine model is an engine nonlinear model with health parameters:
Figure BDA0002539955960000142
y＝g(x,u,h)
wherein
Figure BDA0002539955960000143
In order to control the input vector,
Figure BDA0002539955960000144
in the form of a state vector, the state vector,
Figure BDA0002539955960000145
in order to output the vector, the vector is,
Figure BDA0002539955960000146
for the health parameter vector, f (-) is an n-dimensional differentiable nonlinear vector function representing the system dynamics, and g (-) is an m-dimensional differentiable nonlinear vector function producing the system output; the nonlinear onboard engine model is input into a control input vector u and a health parameter h of the previous period, and the output health steady-state reference value (x) of the nonlinear onboard engine modelaug,NOBEM,yNOBEM) As an estimated initial value of the current period of the linearized kalman filter.
The input of the linearized Kalman filter is a measurement parameter y and a healthy steady-state reference value (x) output by a nonlinear airborne engine modelaug,NOBEM,yNOBEM) According to the formula
Figure BDA0002539955960000147
And calculating to obtain the health parameter h of the engine in the current period.
Wherein
Figure BDA0002539955960000148
K is the gain of Kalman filtering
Figure BDA0002539955960000149
P is the Ricini equation
Figure BDA00025399559600001410
The solution of (1); coefficient AaugAnd CaugAccording to the formula
Figure BDA00025399559600001411
Determining, and A, C, L, M is an augmented linear state variable model reflecting engine performance degradation obtained by regarding the health parameter h as the control input of the engine and linearizing the nonlinear on-board engine model at a healthy steady-state reference point
Figure BDA0002539955960000151
Coefficient (c):
Figure BDA0002539955960000152
Figure BDA0002539955960000153
w is the system noise, v is the measurement noise, and the corresponding covariance matrices are the diagonal matrices Q and R.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made in the above embodiments by those of ordinary skill in the art without departing from the principle and spirit of the present invention.

Claims (6)

1. The utility model provides an aeroengine maximum thrust state fault-tolerant two degree of freedom mu controller which characterized in that: the device comprises a fault-tolerant control module of a two-degree-of-freedom [ mu ] controller group in a maximum thrust state and a fault diagnosis module of a gas path component;
the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state, the gas circuit component fault diagnosis module, the aircraft engine body and a plurality of sensors on the aircraft engine form a gas circuit component fault scheduling control loop;
the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state generates a control input vector u and outputs the control input vector u to the aeroengine body, and the sensor obtains an aeroengine measurement parameter y; the control input vector u and the measurement parameter y are jointly input into the gas circuit component fault diagnosis module, the gas circuit component fault diagnosis module resolves to obtain a health parameter h of the aircraft engine and outputs the health parameter h to the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state;
a plurality of two-degree-of-freedom mu controllers are designed in the fault-tolerant control module of the two-degree-of-freedom mu controller group in the maximum thrust state; the two-degree-of-freedom mu controller comprises a pre-filter and a feedback controller, and is obtained by respectively designing a plurality of uncertain engine models by a mu comprehensive method;
the uncertain engine model is obtained by linearizing a nonlinear model of the aero-engine under the maximum thrust state of the aero-engine and under the faults of different gas path components and adding a camera block;
the fault-tolerant control module of the maximum thrust state two-degree-of-freedom mu controller group calculates and obtains an adaptive two-degree-of-freedom mu controller by utilizing a plurality of internally designed two-degree-of-freedom mu controllers according to an input health parameter h, and the two-degree-of-freedom mu controller generates a control input vector u according to a difference e between a reference input r and a measurement parameter y.
2. The fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of an aircraft engine according to claim 1, characterized in that: the process of designing a plurality of two-degree-of-freedom mu controllers in the maximum thrust state two-degree-of-freedom mu controller group fault-tolerant control module is as follows: the method comprises the steps of linearizing an engine nonlinear model containing health parameters in the maximum thrust state of the aircraft engine to obtain a linearized model containing the health parameters, adjusting the values of the health parameters to obtain 11 linearized models respectively at the positions where the engine has no gas path component fault and a specific gas path component fault, adding a camera block to obtain 11 linear uncertainty engine models, and designing corresponding two-degree-of-freedom mu controllers for the 11 linear uncertainty engine models respectively to form a two-degree-of-freedom mu controller group in the maximum thrust state.
3. The fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of an aircraft engine according to claim 1 or 2, characterized in that: and the fault-tolerant control module of the maximum thrust state two-degree-of-freedom mu controller group interpolates the input health parameter h to obtain an adaptive two-degree-of-freedom mu controller.
4. The fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of an aircraft engine according to claim 3, characterized in that: controller K corresponding to engine no-component fault according to maximum thrust state of engine0Various typical component failures Δ hbase_jController (2)
Figure RE-FDA0002688134910000021
Δhbase_jThe value of the jth element representing the vector Δ h is Δ hbaseThe value of the other element is 0, i.e. Δ hbase_jIndicating 10 different component failures, e.g. Δ hbase_1Indicates that the fan has failed and the amount of change in fan efficiency is Δ hbase. Controller capable of obtaining gas circuit component fault h at maximum thrust state of engine through linear interpolation
Figure RE-FDA0002688134910000022
And the engine is effectively controlled.
5. The fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of an aircraft engine according to claim 1, characterized in that: the gas circuit component fault diagnosis module comprises a nonlinear airborne engine model and a linearization Kalman filter;
the nonlinear airborne engine model is an engine nonlinear model with health parameters:
Figure RE-FDA0002688134910000023
y＝g(x,u,h)
wherein
Figure RE-FDA0002688134910000024
In order to control the input vector,
Figure RE-FDA0002688134910000025
in the form of a state vector, the state vector,
Figure RE-FDA0002688134910000026
in order to output the vector, the vector is,
Figure RE-FDA0002688134910000027
for the health parameter vector, f (-) is an n-dimensional differentiable nonlinear vector function representing the system dynamics, and g (-) is an m-dimensional differentiable nonlinear vector function producing the system output; the nonlinear onboard engine model is input into a control input vector u and a health parameter h of the previous period, and the output health steady-state reference value (x) of the nonlinear onboard engine modelaug,NOBEM,yNOBEM) The method comprises the steps of taking the current period of the linear Kalman filter as an estimated initial value;
the input of the linearized Kalman filter is a measurement parameter y and a healthy steady-state reference value (x) output by a nonlinear airborne engine modelaug,NOBEM,yNOBEM) According to the formula
Figure RE-FDA0002688134910000028
Calculating to obtain a health parameter h of the engine in the current period; wherein
Figure RE-FDA0002688134910000031
K is the gain of Kalman filtering
Figure RE-FDA0002688134910000032
P is the Ricini equation
Figure RE-FDA0002688134910000033
The solution of (1); coefficient AaugAnd CaugAccording to the formula
Figure RE-FDA0002688134910000034
Caug＝(C M)
Determining, and A, C, L, M is an augmented linear state variable model reflecting engine performance degradation obtained by regarding the health parameter h as the control input of the engine and linearizing the nonlinear on-board engine model at a healthy steady-state reference point
Figure RE-FDA0002688134910000035
Coefficient (c):
Figure RE-FDA0002688134910000036
Figure RE-FDA0002688134910000037
w is the system noise, v is the measurement noise, and the corresponding covariance matrices are the diagonal matrices Q and R.
6. The fault-tolerant two-degree-of-freedom [ mu ] controller for the maximum thrust state of an aircraft engine according to claim 1, characterized in that: the measurement parameters comprise the temperature and pressure of an air inlet outlet, a fan outlet, a gas compressor outlet, a high-pressure turbine rear part and a low-pressure turbine rear part, the fan rotating speed and the gas compressor rotating speed.
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