CN111608808A - Input-limited aeroengine gain scheduling fault-tolerant controller - Google Patents

Input-limited aeroengine gain scheduling fault-tolerant controller Download PDF

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CN111608808A
CN111608808A CN202010544561.3A CN202010544561A CN111608808A CN 111608808 A CN111608808 A CN 111608808A CN 202010544561 A CN202010544561 A CN 202010544561A CN 111608808 A CN111608808 A CN 111608808A
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engine
fault
input
vector
tolerant
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孙楚佳
缑林峰
刘志丹
蒋宗霆
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Northwestern Polytechnical University
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02C—GAS-TURBINE PLANTS; AIR INTAKES FOR JET-PROPULSION PLANTS; CONTROLLING FUEL SUPPLY IN AIR-BREATHING JET-PROPULSION PLANTS
    • F02C9/00—Controlling gas-turbine plants; Controlling fuel supply in air- breathing jet-propulsion plants
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2260/00—Function
    • F05D2260/80—Diagnostics
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2260/00—Function
    • F05D2260/81—Modelling or simulation
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2270/00—Control
    • F05D2270/70—Type of control algorithm
    • F05D2270/706—Type of control algorithm proportional-integral-differential
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2270/00—Control
    • F05D2270/70—Type of control algorithm
    • F05D2270/71—Type of control algorithm synthesized, i.e. parameter computed by a mathematical model

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Abstract

The invention provides an input-limited aeroengine gain scheduling fault-tolerant controller, which comprises a PID controller group fault-tolerant control module, an input limit module and a gas circuit component fault diagnosis module; the fault-tolerant control module of the PID controller group generates a control vector v and outputs the control vector v to the input limiting module, the input limiting module generates a limited control input vector u and outputs the limited control input vector u to the aircraft engine body, and the sensor obtains an engine measurement parameter y; the control input vector u and the measurement parameter y are jointly input into the gas path component fault diagnosis module, the gas path component fault diagnosis module diagnoses the gas path component fault of the engine, the health parameter h of the engine is obtained through calculation, and the health parameter h is output to the PID controller group fault-tolerant control module; the fault-tolerant control module of the PID controller group is internally provided with a plurality of PID controllers, the fault-tolerant control module of the PID controller group calculates and obtains an adaptive PID controller by utilizing a plurality of internally designed PID controllers according to an input health parameter h and a scheduling parameter alpha, and the PID controller generates a control input vector u according to a difference e between a reference input r and a measurement parameter y. The invention can well control the real engine under the condition of failure of an engine gas path component on the premise of ensuring the safe operation of the engine, ensure the safe operation of the engine, give full play to the performance of the engine and improve the safety and the performance of the airplane.

Description

Input-limited aeroengine gain scheduling fault-tolerant controller
Technical Field
The invention relates to the technical field of aero-engine control, in particular to an input-limited aero-engine gain scheduling fault-tolerant controller.
Background
An aircraft engine is a complex nonlinear dynamical system, and when the aircraft engine works in a wide flight envelope, the working state of the engine continuously changes along with the change of external conditions and flight conditions. The use of a single linear controller does not provide good control of the engine within the full flight envelope, so a non-linear controller design approach has been proposed, which is however immature and very complex. For the control of the engine, gain scheduling control is used more frequently, a linearization model corresponding to each point is obtained by linearizing a plurality of stable design points in a nonlinear model, then controllers are respectively designed for each linearization model, and the controllers are connected by a fitting or interpolation method, so that the linear controller is used for effectively controlling the nonlinear engine.
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.
In addition, excessive control inputs can cause engine damage, and therefore we need to consider the design of controllers with limited control inputs.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides an input-limited gain scheduling fault-tolerant controller for an aircraft engine, which can well control a real engine under the condition of failure of an engine air path component, ensure the safe work of the engine, give full play to the performance of the engine and improve the safety and the performance of an aircraft. And the control input limit is considered, so that the safe operation of the engine is ensured.
The technical scheme of the invention is as follows:
the input-limited aeroengine gain scheduling fault-tolerant controller is characterized in that: the system comprises a PID controller group fault-tolerant control module, an input limit module and a gas circuit component fault diagnosis module;
the fault-tolerant control module, the input limit module, 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 PID controller group fault-tolerant control module generates a control vector v and outputs the control vector v to the input limiting module, the input limiting module generates a limited control input vector u and outputs the limited control input vector u to the aircraft engine body, and the sensor obtains an aircraft engine measurement parameter y; the control input vector u and the measurement parameter y are jointly input into the gas circuit component fault diagnosis module, and 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 PID controller group fault-tolerant control module;
the PID controller group fault-tolerant control module, the input limit module, the aircraft engine body and a plurality of sensors on the aircraft engine also form a scheduling parameter scheduling control loop; the sensor outputs a scheduling parameter alpha to a PID controller group fault-tolerant control module;
the input limiting module limits the amplitude of the control input vector and avoids damage to the engine caused by excessive control input to the engine;
the fault-tolerant control module of the PID controller group is internally provided with a plurality of PID controllers which are respectively designed by utilizing a plurality of linearization models, and the linearization models are obtained by linearizing nonlinear models of the aircraft engine under different set working points and different gas circuit component faults of the aircraft engine;
the fault-tolerant control module of the PID controller group calculates and obtains an adaptive PID controller by utilizing a plurality of PID controllers designed in the PID controller according to the input health parameter h and the scheduling parameter alpha, and the PID controller generates a control vector v according to a difference value e between a reference input r and a measurement parameter y.
Further, the process of designing a plurality of PID controllers in the PID controller group fault-tolerant control module is as follows: selecting q working points in the full flight envelope according to the scheduling parameter alpha to linearize the engine nonlinear model containing the health parameters to obtain q linearized models containing the health parameters, obtaining 11q linearized models at the positions of the engine without air channel component failure and the specific air channel component failure by adjusting the values of the health parameters, and designing corresponding PID controllers for the 11q linearized models respectively to form a PID controller group.
Further, the gas path component fault diagnosis module comprises a nonlinear onboard engine model and a piecewise linearization Kalman filter;
the nonlinear airborne engine model is an engine nonlinear model with health parameters:
Figure BDA0002540106730000031
y＝g(x,u,h)
wherein
Figure BDA0002540106730000032
In order to control the input vector,
Figure BDA0002540106730000033
in the form of a state vector, the state vector,
Figure BDA0002540106730000034
in order to output the vector, the vector is,
Figure BDA0002540106730000035
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 as an estimated initial value of a piecewise linearization Kalman filter;
the inputs of the piecewise linearization Kalman filter are 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 BDA0002540106730000036
Calculating to obtain a health parameter h of the engine in the current period; wherein
Figure BDA0002540106730000037
K is the gain of Kalman filtering
Figure BDA0002540106730000038
P is the Ricini equation
Figure BDA0002540106730000039
The solution of (1); coefficient AaugAnd CaugAccording to the formula
Figure BDA00025401067300000310
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 BDA0002540106730000041
Coefficient (c):
Figure BDA0002540106730000042
Figure BDA0002540106730000043
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 PID controller group obtains the adaptive PID controller according to the interpolation of the input health parameter h and the scheduling parameter alpha.
Further, the fault-tolerant control module of the PID controller group selects two set working points α which are adjacent to each other in front and back according to the current scheduling parameter α of the aircraft engineiAnd αi+1And obtains two set operating points αiAnd αi+1Controller K for engine without component failureiAnd Ki+1Various typical component failures Δ hbase_jController (2)
Figure BDA0002540106730000044
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 BDA0002540106730000045
Figure BDA0002540106730000046
The selected operating point α of the aircraft engine is calculatediAnd αi+1PID controller K under the current component fault degree (health parameter is h) of the engineiAnd Ki+1(wherein. DELTA.hjIs 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); according to the formula
Figure BDA0002540106730000047
And calculating to obtain the current adaptive fault-tolerant PID controller K (alpha) of the aero-engine.
Further, the input limiting module adopts a multidimensional rectangular saturation function, and controls an input vector u to be:
Figure BDA0002540106730000051
Figure BDA0002540106730000052
wherein v is1And vmTo control the elements of a vector v, v1，maxAnd vm,maxIs the clipping value of the corresponding element of the control vector v.
Further, the scheduling parameter α includes a fan rotation speed or a compressor rotation speed of the aircraft engine.
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 gain scheduling fault-tolerant controller of the input-limited aero-engine utilizes the inherent modules in the traditional gain scheduling controller, improves the fault-tolerant control module of the PID controller group by additionally arranging the gas circuit component fault diagnosis module and the input limit module, and additionally arranging a plurality of groups of PID controllers under the faults of different gas circuit components of the engine. The gas circuit component fault diagnosis module realizes accurate judgment of gas circuit component faults through reliable estimation of health parameters, and further combines the traditional scheduling parameters, on the premise of ensuring safe work of an engine, gain scheduling control during the engine gas circuit component faults is realized, the safe work of the engine when the gas circuit component faults occur is ensured, the control precision of the gain scheduling during the engine gas circuit component faults is improved to the maximum extent, the transition time of a control system is shortened, and the dynamic deviation and the static deviation of the control system are reduced. The nonlinear controlled system is controlled by the controller, so that the system can obtain ideal dynamic and static control quality in the whole working range.
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.
Drawings
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 diagram of an input-limited aero-engine gain-scheduled fault-tolerant controller according to the present 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 schematic representation of a non-linear engine model of the present invention.
Detailed Description
The performance of gas circuit components can be degraded due to factors such as natural wear, corrosion, scale deposit, thermal creep and the like in the operation process of the aero-engine, and faults can be caused when the performance is 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, the safe operation of the engine can not be ensured, and the damage of the engine can be caused by overlarge control input. 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 BDA0002540106730000071
y＝g(x,u,h)
Wherein
Figure BDA0002540106730000072
In order to control the input vector,
Figure BDA0002540106730000073
in the form of a state vector, the state vector,
Figure BDA0002540106730000074
in order to output the vector, the vector is,
Figure BDA0002540106730000075
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 BDA0002540106730000076
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 BDA0002540106730000077
Wherein the coefficient matrix is obtained by:
Figure BDA0002540106730000078
Figure BDA0002540106730000079
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 BDA0002540106730000081
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 BDA0002540106730000082
Further converting the health parameters into state variables to obtain
Figure BDA0002540106730000083
Wherein
Figure BDA0002540106730000084
Figure BDA0002540106730000085
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 BDA0002540106730000086
k is the gain of Kalman filtering
Figure BDA0002540106730000087
P is the Ricini equation
Figure BDA0002540106730000088
The solution of (1); healthy steady-state reference value (x) output by using nonlinear airborne modelaug,NOBEM,yNOBEM) As formula
Figure BDA0002540106730000091
The initial value of (a) can be obtained by the following calculation formula:
Figure BDA0002540106730000092
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. Gain scheduling fault tolerant control design
The essence of gain scheduling control is to design a set of linearized controllers, which are then regularly combined to be able to control a non-linear system. The basic principle of the gain scheduling fault-tolerant control is to select a series of working points, obtain engine linearization models under different set working points and different gas circuit component faults and respectively design corresponding PID controllers to obtain the PID controller group in FIG. 1.
Referring to FIG. 4, a set of scheduling parameter values α is selectedi1, 2.. q, representing the dynamic range of the system, and dividing the flight envelope into several subintervals and using these points as operating points. At the operating point, there are these equations
Figure BDA0002540106730000093
Figure BDA0002540106730000094
Wherein
Figure BDA0002540106730000095
For the selected i-th operating point, udiTo be at the moment of time
Figure BDA0002540106730000096
Steady state control input required to maintain equilibrium, hdiIs a time of day
Figure BDA0002540106730000097
The health parameter of (1).
By using a small disturbance method, a linear model of the health parameters of each working condition point can be obtained, and a linear model of the engine in a normal state and a performance degradation h state is obtained.
Referring to fig. 4, the upper and lower solid lines represent non-linear models of no-air path component failure and air path component failure h, respectively, of the engine. A series of small black dots represent different working points of the engine, and linearization is carried out at each working point to obtain a linear model. Aiming at linear models of an engine in a normal state and different gas circuit component fault states, a series of PID controllers are respectively designed to obtain the PID controller group in the figure 1. The controller gain is then linearly interpolated between the selected operating points so that the closed loop system is stable and has good performance for all fixed parameter values. The parameter α is a scheduling parameter, which may be defined herein as a fan speed or a compressor speed of the aircraft engine, and may be measured in real time. Another scheduling variable of the control system is a health parameter h reflecting the degree of failure of engine gas path components. The working principle is that the fault-tolerant control module of the PID controller group in the figure 1 carries out linear interpolation according to the scheduling parameter and the health parameter to obtain a corresponding PID controller to control the system.
3. Interpolation of controller
This section illustrates the scheduling calculation principle of the PID controller group fault-tolerant control module in fig. 1 that obtains the corresponding PID controller by scheduling linear interpolation of the scheduling parameter and the health parameter.
Respectively in the normal state of the engine and various typical component faults delta hbase_jA series of linear PID controllers are designed under the state of each selected operating point αiAnd (5) controlling. This will result in the controller in the fault tolerant control module of the PID controller set of FIG. 1
Ki，
Figure BDA0002540106730000101
And then interpolating the controller according to the scheduling parameter alpha and the health parameter h, and then controlling the system by using the obtained interpolated controller.
Two adjacent surrounding operating points α are selected based on the current engine schedule αiAnd αi+1And obtains two set operating points αiAnd αi+1Controller K for engine without component failureiAnd Ki+1Various typical component failures Δ hbase_jController (2)
Figure BDA0002540106730000102
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 hbaseLinear interpolation can result in α at the operating pointiController for gas circuit component fault h
Figure BDA0002540106730000103
Likewise, operating point α may be obtainedi+1Controller for gas circuit component fault h
Figure BDA0002540106730000104
We use the piecewise linear interpolation method to derive K from the PID controller set1,K2,...,KqLinear interpolation between each pair of controllers, the linear interpolation controller K (α) at the current degradation degree h of the current scheduling parameter α is obtained, i is 1,2
Figure BDA0002540106730000111
According to the formula, a corresponding controller under the condition that a certain air path component has a fault at a certain working point can be obtained, and the engine is effectively controlled.
4. Input restriction of a system
Referring to fig. 1, the input limit module in fig. 1 uses a multidimensional rectangular saturation function to model the physical limit on the control input of the system. Limiting inputs to aircraft engine controls, particularly for fuel flow inputs. The multidimensional saturation function may also handle other control input constraints including the throat area of the aft nozzle. The function is a multi-dimensional rectangular saturation function defined as
Figure BDA0002540106730000112
Wherein v is1And vmTo control the elements of a vector v, v1，maxAnd vm,maxIs the clipping value of the corresponding element of the control vector v. For all
Figure BDA0002540106730000113
The following formula gives sat (·)
Figure BDA0002540106730000114
Based on the above process, the following provides an input-limited aero-engine gain scheduling fault-tolerant controller proposed in this embodiment, as shown in fig. 1, which mainly includes a PID controller group fault-tolerant control module, an input-limited module, and a gas path component fault diagnosis module.
Wherein, the fault-tolerant control module, the input limit module, 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 PID controller group fault-tolerant control module generates a control vector v and outputs the control vector v to the input limiting module, the input limiting module generates a limited control input vector u and outputs the limited control input vector u to the aircraft engine body, and the sensor obtains an aircraft engine 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 PID controller group fault-tolerant control module.
The PID controller group fault-tolerant control module, the input limit module, the aircraft engine body and a plurality of sensors on the aircraft engine also form a scheduling parameter scheduling control loop 20; and outputting the scheduling parameter alpha to a PID controller group fault-tolerant control module by a sensor.
The input limit module limits the magnitude of the control input vector to avoid engine damage caused by excessive control input to the engine.
In a preferred specific implementation manner, the input limiting module adopts a multidimensional rectangular saturation function, and controls an input vector u to be:
Figure BDA0002540106730000121
Figure BDA0002540106730000122
wherein v is1And vmTo control the elements of a vector v, v1，maxAnd vm,maxIs the clipping value of the corresponding element of the control vector v.
The fault-tolerant control module of the PID controller group is internally provided with a plurality of PID controllers, the PID controllers are respectively designed by utilizing a plurality of linearization models, and the linearization models are obtained by linearizing nonlinear models of the aircraft engine under different set working points and different gas circuit component faults.
In a preferred embodiment, the PID controllers are designed by the following process: selecting q working points in the full flight envelope according to the scheduling parameter alpha to linearize the engine nonlinear model containing the health parameters to obtain q linearized models containing the health parameters, obtaining 11q linearized models at the positions of the engine without air channel component failure and the specific air channel component failure by adjusting the values of the health parameters, and designing corresponding PID controllers for the 11q linearized models respectively to form a PID controller group.
The fault-tolerant control module of the PID controller group calculates and obtains an adaptive PID controller by utilizing a plurality of PID controllers designed in the PID controller according to the input health parameter h and the scheduling parameter alpha, and the PID controller generates a control input vector u according to a difference value e between a reference input r and a measurement parameter y.
In a preferred specific implementation manner, the adaptive PID controller may be obtained by interpolation according to the input health parameter h and the scheduling parameter α:
firstly, according to the current scheduling parameter α of the aeroengine, the front and the back adjacent are selectedTwo set operating points αiAnd αi+1And obtains two set operating points αiAnd αi+1Controller K for engine without component failureiAnd Ki+1Various typical component failures Δ hbase_jController (2)
Figure BDA0002540106730000131
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 BDA0002540106730000132
Figure BDA0002540106730000133
The selected operating point α of the aircraft engine is calculatediAnd αi+1PID controller K under the current component fault degree (health parameter is h) of the engineiAnd Ki+1(wherein. DELTA.hjIs 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); according to the formula
Figure BDA0002540106730000134
And calculating to obtain the current adaptive fault-tolerant PID controller K (alpha) of the aero-engine.
The gas circuit component fault diagnosis module comprises a nonlinear onboard engine model and a piecewise linearization Kalman filter.
The nonlinear airborne engine model is an engine nonlinear model with health parameters:
Figure BDA0002540106730000135
y＝g(x,u,h)
wherein
Figure BDA0002540106730000136
In order to control the input vector,
Figure BDA0002540106730000137
in the form of a state vector, the state vector,
Figure BDA0002540106730000138
in order to output the vector, the vector is,
Figure BDA0002540106730000139
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 the estimated initial value of the current period of the piecewise linearization Kalman filter.
The inputs of the piecewise linearization Kalman filter are 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 BDA0002540106730000141
And calculating to obtain the health parameter h of the engine in the current period.
Wherein
Figure BDA0002540106730000142
K is the gain of Kalman filtering
Figure BDA0002540106730000143
P is the Ricini equation
Figure BDA0002540106730000144
The solution of (1); coefficient AaugAnd CaugAccording to the formula
Figure BDA0002540106730000145
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 BDA0002540106730000146
Coefficient (c):
Figure BDA0002540106730000147
Figure BDA0002540106730000148
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 (7)

1. An input-limited aeroengine gain scheduling fault-tolerant controller is characterized in that: the system comprises a PID controller group fault-tolerant control module, an input limit module and a gas circuit component fault diagnosis module;
the fault-tolerant control module, the input limit module, 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 PID controller group fault-tolerant control module generates a control vector v and outputs the control vector v to the input limiting module, the input limiting module generates a limited control input vector u and outputs the limited control input vector u to the aircraft engine body, and the sensor obtains an aircraft engine measurement parameter y; the control input vector u and the measurement parameter y are jointly input into the gas circuit component fault diagnosis module, and 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 PID controller group fault-tolerant control module;
the PID controller group fault-tolerant control module, the input limit module, the aircraft engine body and a plurality of sensors on the aircraft engine also form a scheduling parameter scheduling control loop; the sensor outputs a scheduling parameter alpha to a PID controller group fault-tolerant control module;
the input limiting module limits the amplitude of the control input vector and avoids damage to the engine caused by excessive control input to the engine;
the fault-tolerant control module of the PID controller group is internally provided with a plurality of PID controllers which are respectively designed by utilizing a plurality of linearization models, and the linearization models are obtained by linearizing nonlinear models of the aircraft engine under different set working points and different gas circuit component faults of the aircraft engine;
the fault-tolerant control module of the PID controller group calculates and obtains an adaptive PID controller by utilizing a plurality of PID controllers designed in the PID controller according to the input health parameter h and the scheduling parameter alpha, and the PID controller generates a control input vector u according to a difference value e between a reference input r and a measurement parameter y.
2. The input-limited aero-engine gain-scheduled fault-tolerant controller of claim 1, wherein: the process of designing a plurality of PID controllers in the PID controller group fault-tolerant control module is as follows: selecting q working points in the full flight envelope according to the scheduling parameter alpha to linearize the engine nonlinear model containing the health parameters to obtain q linearized models containing the health parameters, obtaining 11q linearized models at the positions of the engine without air channel component failure and the specific air channel component failure by adjusting the values of the health parameters, and designing corresponding PID controllers for the 11q linearized models respectively to form a PID controller group.
3. The input-limited aero-engine gain-scheduled fault-tolerant controller as claimed in claim 1 or 2, wherein: and the PID controller group fault-tolerant control module obtains an adaptive PID controller according to the input health parameter h and the scheduling parameter alpha by interpolation.
The input-limited aero-engine gain scheduling fault-tolerant controller as claimed in claim 3, wherein the PID controller set fault-tolerant control module selects two set working points α which are adjacent to each other in front and back according to the current scheduling parameter α of the aero-engineiAnd αi+1And obtains two set operating points αiAnd αi+1Controller K for engine without component failureiAnd Ki+1Various typical component failures Δ hbase_jController (2)
Figure FDA0002540106720000021
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 FDA0002540106720000022
Figure FDA0002540106720000023
The selected operating point α of the aircraft engine is calculatediAnd αi+1PID controller K under the current component fault degree (health parameter is h) of the engineiAnd Ki+1(wherein. DELTA.hjIs 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); according to the formula
Figure FDA0002540106720000024
And calculating to obtain the current adaptive fault-tolerant PID controller K (alpha) of the aero-engine.
4. The input-limited aero-engine gain-scheduled fault-tolerant controller of claim 1, wherein: the gas circuit component fault diagnosis module comprises a nonlinear onboard engine model and a piecewise linearization Kalman filter;
the nonlinear airborne engine model is an engine nonlinear model with health parameters:
Figure FDA0002540106720000025
y＝g(x,u,h)
wherein
Figure FDA0002540106720000031
In order to control the input vector,
Figure FDA0002540106720000032
in the form of a state vector, the state vector,
Figure FDA0002540106720000033
in order to output the vector, the vector is,
Figure FDA0002540106720000034
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 airborne engine model is input as a control input vector u and the last weekHealth parameter h of period, health steady state reference value (x) of its outputaug,NOBEM,yNOBEM) The method comprises the steps of taking the current period as an estimated initial value of a piecewise linearization Kalman filter;
the inputs of the piecewise linearization Kalman filter are 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 FDA0002540106720000035
Calculating to obtain a health parameter h of the engine in the current period; wherein
Figure FDA0002540106720000036
K is the gain of Kalman filtering
Figure FDA0002540106720000037
P is the Ricini equation
Figure FDA0002540106720000038
The solution of (1); coefficient AaugAnd CaugAccording to the formula
Figure FDA0002540106720000039
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 FDA00025401067200000310
Coefficient (c):
Figure FDA00025401067200000311
Figure FDA00025401067200000312
w is the system noise, v is the measurement noise, and the corresponding covariance matrices are the diagonal matrices Q and R.
5. The input-limited aero-engine gain-scheduled fault-tolerant controller of claim 1, wherein:
the input limiting module adopts a multidimensional rectangular saturation function, and controls an input vector u to be:
Figure FDA0002540106720000041
Figure FDA0002540106720000042
wherein v is1And vmTo control the elements of a vector v, v1，maxAnd vm,maxIs the clipping value of the corresponding element of the control vector v.
6. The input-limited aero-engine gain-scheduled fault-tolerant controller of claim 1, wherein: the scheduling parameter alpha comprises the fan rotating speed or the compressor rotating speed of the aircraft engine.
7. The input-limited aero-engine gain-scheduled fault-tolerant controller of claim 1, wherein: 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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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112879165A (en) * 2021-01-14 2021-06-01 西北工业大学 Optimal control method for acceleration process of aircraft engine considering gas circuit component faults
CN112904881A (en) * 2021-01-19 2021-06-04 杭州电子科技大学 Design method for dynamic gain scheduling controller of hypersonic aircraft
CN112949161A (en) * 2021-01-21 2021-06-11 西北工业大学 IGA-based engine minimum oil consumption control optimization method under gas circuit component fault
CN112949160A (en) * 2021-01-21 2021-06-11 西北工业大学 IPSO-based engine acceleration process optimal control method under gas path component failure
CN112947064A (en) * 2021-01-21 2021-06-11 西北工业大学 Aero-engine maximum thrust control optimization method considering gas circuit component faults

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109358491A (en) * 2018-10-25 2019-02-19 中国电子科技集团公司第五十四研究所 Fault tolerant control method is determined based on the fuzzy failure of Kalman filtering
CN110118128A (en) * 2019-05-28 2019-08-13 南京航空航天大学 Miniature gas turbine sensor fault diagnosis and fault tolerant control method
US20190383221A1 (en) * 2018-06-15 2019-12-19 Dalian University Of Technology Design method of aero-engine on-line optimization and multivariable control based on model prediction
CN111271181A (en) * 2020-04-04 2020-06-12 西北工业大学 Two-degree-of-freedom [ mu ] controller for conservative gain reduction scheduling of aero-engine

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190383221A1 (en) * 2018-06-15 2019-12-19 Dalian University Of Technology Design method of aero-engine on-line optimization and multivariable control based on model prediction
CN109358491A (en) * 2018-10-25 2019-02-19 中国电子科技集团公司第五十四研究所 Fault tolerant control method is determined based on the fuzzy failure of Kalman filtering
CN110118128A (en) * 2019-05-28 2019-08-13 南京航空航天大学 Miniature gas turbine sensor fault diagnosis and fault tolerant control method
CN111271181A (en) * 2020-04-04 2020-06-12 西北工业大学 Two-degree-of-freedom [ mu ] controller for conservative gain reduction scheduling of aero-engine

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
MEHRDAD PAKMEHR .ETAL: "Gain Scheduled Control of Gas Turbine Engines: Stability and Verification", 《JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER》 *
吴贞等: "一种航空发动机加速控制参数优化新方法", 《计算机仿真》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112879165A (en) * 2021-01-14 2021-06-01 西北工业大学 Optimal control method for acceleration process of aircraft engine considering gas circuit component faults
CN112904881A (en) * 2021-01-19 2021-06-04 杭州电子科技大学 Design method for dynamic gain scheduling controller of hypersonic aircraft
CN112949161A (en) * 2021-01-21 2021-06-11 西北工业大学 IGA-based engine minimum oil consumption control optimization method under gas circuit component fault
CN112949160A (en) * 2021-01-21 2021-06-11 西北工业大学 IPSO-based engine acceleration process optimal control method under gas path component failure
CN112947064A (en) * 2021-01-21 2021-06-11 西北工业大学 Aero-engine maximum thrust control optimization method considering gas circuit component faults

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