CN111305954B - Input-limited aero-engine conservative robust gain reduction scheduling controller - Google Patents
Input-limited aero-engine conservative robust gain reduction scheduling controller Download PDFInfo
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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
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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Abstract
The invention provides an input-limited aero-engine conservative robust gain reduction scheduling controller which comprises a linear conservative robust controller group resolving module, an input limiting module and a degradation parameter estimation loop. The linear degradation conservative robust controller designed by the invention adopts a small perturbation uncertainty engine model, eliminates a degradation item in the uncertainty of the engine, reduces the perturbation range of the uncertainty model, and reduces the conservative property of the robust gain scheduling controller. The degradation parameter estimation loop realizes the reliable estimation of the degradation parameters, realizes the gain scheduling control during the degradation of the engine performance on the premise of ensuring the safe work of the engine, improves the control precision of the gain scheduling during the degradation of the engine performance to the maximum extent, shortens the transition time of a control system, reduces the dynamic deviation and the static deviation of the control system, has stronger robustness and low conservation, and fully exerts the performance of the engine.
Description
Technical Field
The invention relates to the technical field of aero-engine control, in particular to an input-limited aero-engine conservative robust gain reduction scheduling 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. Aiming at strong nonlinearity of an aircraft engine and uncertainty of a model, a robust gain scheduling control method is provided in the prior art, the engine is divided into a series of working points, a robust controller is designed at each working point, and finally a proper robust controller is selected to control the engine by adopting the gain scheduling method.
The robust gain scheduling control method for the aero-engine can control the aero-engine. However, they are very conservative, as they consider engine degradation as an uncertainty in the engine model for robust controller design. In fact, the performance degradation degree of the engine can be estimated by measuring parameters, so that the degradation term in the uncertainty model is eliminated, the range of the uncertainty model is narrowed, the conservatism of the robust gain scheduling controller is reduced, and the performance of the engine is improved.
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 aero-engine conservative robust gain reduction scheduling controller, which has stronger robustness and low conservative property, the performance degradation degree of an engine is estimated through measuring parameters, so that the degradation item in an uncertain model is eliminated, the range of the uncertain model is reduced, the conservative property of the robust gain scheduling controller is reduced, the real engine can be still well controlled under the condition that the performance of the engine is degraded, the performance of the engine is fully exerted, and the full-life efficiency of an airplane is improved. 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 aero-engine conservative robust gain reduction scheduling controller is characterized in that: the system comprises a linear reduction conservative robust controller group resolving module, an input limiting module and a degradation parameter estimation loop;
wherein the linear degradation conservative robust controller group resolving module, the input limiting module, the degradation parameter estimation loop, the aircraft engine body and a plurality of sensors on the aircraft engine form a degradation parameter scheduling control loop;
the linear degradation conservative robust controller group resolving 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 aeroengine body, and the sensor obtains an aeroengine measurement parameter y; the control input vector u and the measurement parameter y are input into a degradation parameter estimation loop together, the degradation parameter estimation loop obtains a degradation parameter h of the aero-engine through calculation and outputs the degradation parameter h to a linear degradation conservative robust controller group calculation module;
the linear reduction conservative robust controller group resolving module, the input limiting module, the aircraft engine body and a plurality of sensors on the aircraft engine also form a scheduling parameter scheduling control loop; a sensor outputs a scheduling parameter alpha to a linear reduction conservative robust controller group resolving 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 linear degradation conservative robust controller group calculation module is internally designed with a plurality of linear degradation conservative robust controllers which are respectively designed by utilizing a plurality of small perturbation uncertainty engine models, and the small perturbation uncertainty engine models are obtained by linearizing aero-engine nonlinear models which are under different set working points of an aero-engine and contain degradation parameters and then adding perturbation blocks which do not contain engine performance degradation; aiming at the nonlinear model of the aero-engine in a certain degradation state, the added pickup block without engine performance degradation is the minimum pickup radius pickup block capable of covering all uncertainties of the aero-engine except degradation;
the linear degradation conservative robust controller group resolving module calculates and obtains an adaptive linear degradation conservative robust controller by utilizing a plurality of linear degradation conservative robust controllers designed in the linear degradation conservative robust controller group according to an input degradation parameter h and a scheduling parameter alpha, and the linear degradation conservative robust controller generates a control vector v according to a difference e between a reference input r and a measurement parameter y.
Further, the process of designing a plurality of linear degradation conservative robust controllers in the linear degradation conservative robust controller group calculation module is as follows: respectively in the normal state h of the engine 1 And setting the degree of degradation h base Selecting n working points in the full flight envelope according to the scheduling parameter alpha to linearize the nonlinear engine model containing the degradation parameter to obtain 2n linearized models, and adding a perturbation block not containing the performance degradation of the engine to the linearized models to obtain the small perturbation uncertainty engineAnd respectively designing robust controllers for the 2n small perturbation uncertainty engine models to serve as corresponding linear degradation conservative robust controllers, and forming a linear degradation conservative robust controller group.
Further, the degradation parameter estimation loop comprises a nonlinear airborne engine model and a piecewise linearization Kalman filter;
the nonlinear airborne engine model is an engine nonlinear model with degradation parameters:
y＝g(x,u,h)
wherein
In order to control the input vector,
in the form of a state vector, the state vector,
in order to output the vector, the vector is,
for the degenerate 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 degradation parameter h of a previous period, and the output healthy steady-state reference value (x) of the nonlinear onboard engine model aug,NOBEM ,y NOBEM ) 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 model aug,NOBEM ,y NOBEM ) According to the formula
Calculating to obtain a degradation parameter h of the engine in the current period; wherein
K is the gain of Kalman filtering
P is the Ricini equation
The solution of (1); coefficient A aug And C aug According to the formula
Determining, and A, C, L, M is an augmented linear state variable model reflecting the performance degradation of the engine obtained by regarding the degradation parameter h as the control input of the engine and linearizing the nonlinear on-board engine model at a healthy steady-state reference point
Coefficient (c):
w is the system noise, R is the measurement noise, and the corresponding covariance matrices are the diagonal matrices Q and R.
Further, the linear degradation conservative robust controller group resolving module obtains an adaptive linear degradation conservative robust controller according to an input degradation parameter h and a scheduling parameter alpha through interpolation.
Further, the linear degradation conservative robust controller group resolving module selects two adjacent set working points alpha according to the current scheduling parameter alpha of the aero-engine i And alpha i+1 And two set operating points alpha are obtained i And alpha i+1 Corresponding to the normal state h of the engine 1 And setting the degree of degradation h base Linear droop conservative robust controller K i 、
K i+1 And
according to the formula
After calculating to obtain the current degradation parameter h of the aeroengine, setting two working points alpha i And alpha i+1 Linear droop conservative robust controller K i And K i+1 (ii) a According to the formula
And calculating to obtain the linear degradation conservative robust controller K (alpha) currently adapted to the aero-engine.
Further, the input limiting module adopts a multidimensional rectangular saturation function, and controls an input vector u to be:
wherein v is 1 And v m To control the elements of a vector v, v 1，max And v m,max Is 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 aviation engine conservative robust gain reduction scheduling controller with limited input provided by the invention utilizes the inherent modules in the traditional gain scheduling controller, improves the gain scheduling controller group by additionally arranging a degradation parameter estimation loop and an input limiting module, and adds a group of linear conservative robust reduction controllers under a certain degradation degree of the engine to obtain a resolving module of the linear conservative robust reduction controller group. The designed linear degradation conservative robust controller adopts a small perturbation uncertainty engine model, so that a degradation term in the uncertainty of the engine is eliminated, the perturbation range of the uncertain model is reduced, and the conservative property of the robust gain scheduling controller is reduced. The degradation parameter estimation loop realizes reliable estimation of degradation parameters, further combines the traditional scheduling parameters, realizes gain scheduling control during engine performance degradation on the premise of ensuring safe work of the engine, improves the control precision of gain scheduling during engine performance degradation to the maximum extent, shortens the transition time of a control system, reduces the dynamic deviation and the static deviation of the control system, has strong robustness and low conservation, and fully exerts the performance of the engine. 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 block diagram of an input-limited aero-engine de-conservative robust gain scheduling controller according to the present invention;
FIG. 2 is a schematic diagram of a linear degradation conservative robust controller set in an input limited aero-engine degradation conservative robust gain scheduling controller according to the present invention;
fig. 3 is a schematic structural diagram of a degradation parameter estimation loop in the degradation parameter scheduling control loop according to the present embodiment;
FIG. 4 is a schematic diagram of the structure of a Kalman filter in the degradation parameter estimation loop of the present embodiment;
FIG. 5 is a block diagram of an engine model perturbation;
FIG. 6 is a plot of a perturbation of an engine model with the degeneration term isolated;
FIG. 7 is a perturbation map of a new engine model after degradation;
FIG. 8 is a schematic diagram of an uncertain model structure;
FIG. 9 is a schematic diagram of an uncertainty model of a non-linear model of an engine;
FIG. 10 is a schematic of controller interpolation.
Detailed Description
The aero-engine has strong nonlinearity and model uncertainty, the traditional robust gain scheduling control directly considers the engine degradation as the uncertainty of an engine model to design a robust controller, the conservativeness of the controller is greatly increased, the performance of the engine is seriously reduced, and the engine is damaged due to overlarge control input. The analytical study procedure of the present invention is given below in view of this problem.
1. Estimation of engine performance degradation
The performance degradation of the engine refers to the normal aging phenomenon of the engine caused by natural abrasion, fatigue, fouling and the like after the engine runs for many times in a circulating way. At this time, the performance of some engines may slowly deviate from the rated state. Taking the turbine component as an example, its operating efficiency slowly decreases as it operates with the engine for multiple cycles. The ability to convert high temperature and high pressure gases into mechanical energy will be reduced and the engine's linearized model at one operating point will change.
The final characteristic of the degradation of the engine performance is the variation of the working efficiency and the flow of the different rotor components, the variation of the efficiency or flow coefficients of the fan, compressor, main combustion, high-pressure turbine and low-pressure turbine components, which are called degradation or health parameters, can characterize the degradation of the engine performance.
Method for establishing engine nonlinear model with degradation parameters based on component method
y＝g(x,u,h)
Wherein
In order to control the input vector,
in the form of a state vector, the state vector,
in order to output the vector, the vector is output,
for the degenerate 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 that produces the system output.
And (3) taking the degradation parameter h as the control input of the engine, and linearizing the nonlinear model of the engine at the healthy steady-state reference point by adopting a small perturbation method or a fitting method.
Wherein
A′＝A,B′＝(B L),C′＝C,
D′＝(D M),Δu′＝(Δu Δh) T
w is system noise, r is measurement noise, h is a degradation parameter, and Δ h is h-h 0 (ii) a The w and R 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[ww T ]＝Q
E(r)＝0 E[rr T ]＝R
Δ represents the variation of the parameter, h 0 Representing an engine initial state degradation parameter.
Further obtains an augmented linear state variable model reflecting the performance degradation of the engine
Wherein the coefficient matrix is obtained by:
these coefficients have different values at different operating states of the engine.
In fact, the degradation 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" and mainly include the temperature and pressure at the outlet of the air inlet, the outlet of the fan, the outlet of the compressor, the rear of the high-pressure turbine and the rear of 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 degradation parameter can cause the corresponding change of the measured parameter, and an aerodynamic-thermodynamic relation exists between the degradation parameter and the measured parameter. Thus, an optimal estimation filter can be designed to achieve optimal estimation of the degradation parameters by measuring the parameters.
Since the process of engine performance degradation is relatively slow, a reasonable assumption can be made that the rate of change of Δ h is
Further converting the degradation parameter into a state variable to obtain
Wherein
The established degradation parameter estimation loop mainly comprises two parts, wherein one part is a nonlinear airborne engine model based on performance degradation, and the other part is a piecewise linear Kalman filter consisting of a piecewise linear model and a Kalman filter corresponding to a steady-state point. 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, the degradation parameter is expanded, online real-time estimation is carried out through the piecewise linear Kalman filter, and finally the output is fed back to the nonlinear airborne engine model for online real-time updating. The real-time tracking of the actual engine is realized, and the airborne self-adaptive model of the engine is established.
The kalman estimation equation is:
k is the gain of Kalman filtering
P is the Ricini equation
The solution of (1); healthy steady-state reference value (x) output by using nonlinear airborne model aug,NOBEM ,y NOBEM ) As formula
The initial value of (a) can be obtained by the following calculation formula:
the degradation parameter h of the engine can be obtained according to the calculation formula.
2. Robust controller design with uncertain model of degradation 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 degradation parameters) can be expressed as a camera block delta. Referring to FIG. 5, an uncertain model of the engine is built by adding a camera block to the nominal model
It can also be expressed as
G(s)＝[I+Δ(s)]G nom (s)
Wherein G(s) is an uncertain model of the engine, G nom (s) is the nominal model and Δ(s) is the perturbation block.
The uptake block Δ(s) contains performance degradation, which can be predicted by measuring the parameters, see fig. 6. Dividing the pickup block Delta(s) into pickup blocks Delta(s) free of engine performance degradation h (s) and a degradation parameter. Referring to FIG. 7, perturbation blocks Δ without engine performance degradation are added to the nominal model h (s) and a degradation parameter, representing the engine uncertainty model as
It can also be represented as
G(s)＝[I+Δ h (s)]G h_nom (s)
In the formula,. DELTA. h (s) is a pickup block free from engine performance degradation, G h_nom (s) is a new nominal model in the engine performance degradation state h, and satisfies
G(s)＝[I+Δ(s)]G nom (s)
＝[I+Δ h (s)+h(s)]G nom (s)
＝[I+Δ h (s)]G h_nom (s)
We can obtain that the content of the Chinese patent application,
referring to fig. 8, the upper and lower small circular areas represent the linear uncertainty model of the engine without degradation and performance degradation h, respectively, and the large circular area represents the linear uncertainty model of the engine in the general robust controller design. In the design of a general robust controller, the degradation of the engine is directly considered as uncertainty in the model, without changing the nominal model of the engine. Therefore, the uncertainty radius of the uncertainty term must be large enough to accommodate the uncertainty model of the degraded engine, making the perturbation radius of the uncertainty model too large. Aiming at the condition of engine performance degradation h, a new nominal model is established in the state, and an uncertain engine model is established by taking the new nominal model as the center of a circle. Selecting perturbation blocks delta without engine performance degradation for a new nominal model under a certain degradation state h (s) the smallest perturbation radius camera block is selected that can cover all uncertainties of the engine except for degradation. Referring to FIG. 8, through an estimation of the degradation of engine performance, the perturbation radius of the camera block in the engine uncertainty | | | Δ h The perturbation range of the uncertain model is reduced
And finally, designing a robust controller by using a traditional robust controller design method according to a small perturbation uncertain model, wherein the designed robust controller is lower in conservation.
3. Gain scheduling control design with degradation parameters
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 gain scheduling control with degradation parameters is to select a series of operating points, obtain engine linearized models in a normal state and some performance degradation states, and design corresponding linear degradation conservative robust controllers respectively to obtain the linear degradation conservative robust controller group in fig. 1.
Referring to FIG. 9, a set of scheduling parameter values α is selected i 1, 2.. times.n, which represents the dynamic range of the system, and divides the flight envelope into several subintervals and takes these points as operating points. At the operating point, there are these equations
Wherein
For the selected i-th operating point, u di To be at the time of day
Steady state control input required to maintain equilibrium, h di Is a time of day
The degradation parameter of (2).
By using a small disturbance method, linear models of degradation parameters of all working condition points can be obtained, and linear models of the engine in a normal state and a performance degradation h state are obtained.
Referring to fig. 9, the upper and lower solid lines represent non-linear models of engine no degradation and performance degradation h, respectively. 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. The upper and lower series of small dashed circles represent a series of small perturbation ranges without degradation and without degradation terms with degradation, respectively, and the large dashed circle represents a large perturbation range with degradation terms. Aiming at small perturbation uncertain linear models in the normal state and the degradation state of the engine, a series of linear degradation conservative robust controllers are respectively designed to obtain a linear degradation conservative robust controller group in the figure 1. The controller gain is then linearly interpolated between the selected operating points so that the closed loop system 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 degradation parameter h that reflects the degradation of the engine performance. The working principle is that a linear reduction conservative robust controller group resolving module in the figure 1 carries out linear interpolation according to a scheduling parameter and a degradation parameter to obtain a corresponding linear reduction conservative robust controller to control a system.
4. Interpolation of controller
This section illustrates the scheduling calculation principle of the linear-reduction conservative robust controller set calculation module in fig. 1 that obtains the corresponding linear-reduction conservative robust controller through scheduling parameter and degradation parameter scheduling linear interpolation.
In the normal state and the performance degradation h of the engine respectively base Designing a series of linear degradation conservative robust controllers under the state, and aiming at each selected working point alpha i And (5) controlling. This will result in the controller in the linear reduction conservative robust controller set solution module in FIG. 1
Then, the controller is interpolated according to the scheduling parameter alpha and the degradation parameter h, and then the obtained interpolated controller is used for controlling the system.
Referring to FIG. 10, two adjacent operating points α are selected according to the current engine scheduling parameter α i And alpha i+1 According to the engine at a selected operating point alpha i Actual degree of degradation of, controller K at engine performance degradation h i Using the selected operating point alpha i Controller K in normal state and performance degradation h-base state of engine i And
obtained by linear interpolation
Likewise, the operating point α can be obtained i+1 Controller at actual degradation h
We use piecewise linear interpolation method to reduce conservative robust controller set K from linear 1 ,K 2 ,..,K n Linear interpolation is performed between each pair of controllers. A linear interpolation controller K (α) at the current degradation degree h of the current scheduling parameter α is obtained, i is 1,2
According to the formula, a corresponding controller under a certain degradation parameter of a certain scheduling parameter can be obtained, and the engine is effectively controlled.
5. 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
Wherein v is 1 And v m To control the elements of a vector v, v 1，max And v m,max Is the clipping value of the corresponding element of the control vector v. For all
The following formula gives sat (·)
Based on the above process, the following provides a health degradation-based aero-engine conservative robust gain reduction scheduling controller provided in this embodiment, as shown in fig. 1, which mainly includes a linear degradation conservative robust controller set resolving module, an input limiting module, and a degradation parameter estimation loop.
Wherein, a linear degradation conservative robust controller group resolving module, an input limiting module, a degradation parameter estimation loop, an aeroengine body and a plurality of sensors on the aeroengine form a degradation parameter scheduling control loop 10.
The linear degradation conservative robust controller group resolving 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 aeroengine body, and the sensor obtains an aeroengine measurement parameter y; and the control input vector u and the measurement parameter y are jointly input into a degradation parameter estimation loop, the degradation parameter estimation loop obtains a degradation parameter h of the aero-engine through calculation, and the degradation parameter h is output to a linear degradation conservative robust controller group calculation module.
The linear reduction conservative robust controller group resolving module, the input limiting 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 linear reduction conservative robust controller group resolving 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:
wherein v is 1 And v m To control the elements of a vector v, v 1，max And v m,max The clipping values for the corresponding elements of the control vector v.
The linear degradation conservative robust controller group calculation module is internally designed with a plurality of linear degradation conservative robust controllers which are respectively designed by utilizing a plurality of small perturbation uncertainty engine models, and the small perturbation uncertainty engine models are obtained by linearizing aero-engine nonlinear models which are under different set working points of an aero-engine and contain degradation parameters and then adding perturbation blocks which do not contain engine performance degradation; aiming at the nonlinear model of the aero-engine in a certain degradation state, the added pickup block without engine performance degradation is the minimum pickup radius pickup block capable of covering all uncertainties of the aero-engine except degradation.
In a preferred embodiment, the design of several linear degradation conservative robust controllers can be achieved by the following process: respectively in the normal state h of the engine 1 And setting the degree of degradation h base Selecting n working points in a full flight envelope according to a scheduling parameter alpha to linearize an engine nonlinear model containing a degradation parameter to obtain 2n linearized models, adding a perturbation block without engine performance degradation to the linearized models to obtain a small perturbation uncertainty engine model, and designing robust controllers for the 2n small perturbation uncertainty engine models respectively to serve as corresponding linear degradation conservative robust controllers and form a linear degradation conservative robust controller group.
The linear degradation conservative robust controller group resolving module calculates and obtains an adaptive linear degradation conservative robust controller by utilizing a plurality of linear degradation conservative robust controllers designed in the linear degradation conservative robust controller group according to an input degradation parameter h and a scheduling parameter alpha, and the linear degradation conservative robust controller generates a control vector v according to a difference e between a reference input r and a measurement parameter y.
In a preferred embodiment, the adaptive linear degradation conservative robust controller can be obtained by interpolating according to the input degradation parameter h and the scheduling parameter α:
firstly, two adjacent set working points alpha are selected according to the current scheduling parameter alpha of the aeroengine i And alpha i+1 And two set operating points alpha are obtained i And alpha i+1 Corresponding to the normal state h of the engine 1 And setting the degree of degradation h base Linear droop conservative robust controller K i 、
K i+1 And
according to the formula
After calculating to obtain a current degradation parameter h of the aeroengine, setting two working points alpha i And alpha i+1 Linear droop conservative robust controller K i And K i+1 (ii) a According to the formula
And calculating to obtain the linear degradation conservative robust controller K (alpha) currently adapted to the aero-engine.
The degradation parameter estimation loop comprises a nonlinear airborne engine model and a piecewise linearization Kalman filter;
the nonlinear airborne engine model is an engine nonlinear model with degradation parameters:
y＝g(x,u,h)
wherein
In order to control the input vector,
in the form of a state vector, the state vector,
in order to output the vector, the vector is output,
for the degenerate 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 degradation parameter h of a previous period, and the output healthy steady-state reference value (x) of the nonlinear onboard engine model aug,NOBEM ,y NOBEM ) 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 model aug,NOBEM ,y NOBEM ) According to the formula
Calculated to obtain whenA degradation parameter h of the engine of the previous cycle; wherein
K is the gain of Kalman filtering
P is the Ricini equation
The solution of (1); coefficient A aug And C aug According to the formula
Determining and A, C, L, M an augmented linear state variable model reflecting the performance degradation of the engine, which is obtained by regarding the degradation parameter h as the control input of the engine and linearizing the nonlinear on-board engine model at a healthy steady-state reference point
Coefficient (c):
w is the system noise, R 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 (8)
1. An input-limited aero-engine conservative robust gain reduction scheduling controller, characterized by: the system comprises a linear reduction conservative robust controller group resolving module, an input limiting module and a degradation parameter estimation loop;
wherein the linear degradation conservative robust controller group resolving module, the input limiting module, the degradation parameter estimation loop, the aircraft engine body and a plurality of sensors on the aircraft engine form a degradation parameter scheduling control loop;
the linear degradation conservative robust controller group resolving 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 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 a degradation parameter estimation loop, the degradation parameter estimation loop obtains a degradation parameter h of the aero-engine through calculation, and the degradation parameter h is output to a linear degradation conservative robust controller group calculation module;
the linear reduction conservative robust controller group resolving module, the input limiting module, the aircraft engine body and a plurality of sensors on the aircraft engine also form a scheduling parameter scheduling control loop; a sensor outputs a scheduling parameter alpha to a linear reduction conservative robust controller group resolving 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 linear degradation conservative robust controller group calculation module is internally designed with a plurality of linear degradation conservative robust controllers which are respectively designed by utilizing a plurality of small perturbation uncertainty engine models, and the small perturbation uncertainty engine models are obtained by linearizing aero-engine nonlinear models which are under different set working points of an aero-engine and contain degradation parameters and then adding perturbation blocks which do not contain engine performance degradation; aiming at an aeroengine nonlinear model in a certain degradation state, the added pickup block without engine performance degradation is a minimum perturbation radius pickup block capable of covering all uncertainties of the aeroengine except degradation;
the linear degradation conservative robust controller group resolving module calculates and obtains an adaptive linear degradation conservative robust controller by utilizing a plurality of linear degradation conservative robust controllers designed in the linear degradation conservative robust controller group according to an input degradation parameter h and a scheduling parameter alpha, and the linear degradation conservative robust controller generates a control vector v according to a difference e between a reference input r and a measurement parameter y.
2. The input-limited aero-engine de-conservative robust gain scheduling controller of claim 1, wherein: the process of designing a plurality of linear degradation conservative robust controllers in the linear degradation conservative robust controller group resolving module is as follows: respectively in the normal state h of the engine 1 And setting the degree of degradation h base Selecting n working points in a full flight envelope according to a scheduling parameter alpha to linearize an engine nonlinear model containing a degradation parameter to obtain 2n linearized models, adding a perturbation block without engine performance degradation to the linearized models to obtain a small perturbation uncertainty engine model, and designing robust controllers for the 2n small perturbation uncertainty engine models respectively to serve as corresponding linear degradation conservative robust controllers and form a linear degradation conservative robust controller group.
3. The input-limited aero-engine de-conservative robust gain scheduling controller of claim 1, wherein: the degradation parameter estimation loop comprises a nonlinear airborne engine model and a piecewise linearization Kalman filter;
the nonlinear airborne engine model is an engine nonlinear model with degradation parameters:
y＝g(x,u,h)
wherein
In order to control the input vector,
in the form of a state vector, the state vector,
in order to output the vector, the vector is,
for the degenerate 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 degradation parameter h of a previous period, and the output healthy steady-state reference value (x) of the nonlinear onboard engine model aug,NOBEM ,y NOBEM ) The method comprises the steps of taking the time as an estimation initial value of the current period 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 model aug,NOBEM ,y NOBEM ) According to the formula
Calculating to obtain a degradation parameter h of the engine in the current period; wherein
K is the gain of Kalman filtering
P is the Ricini equation
The solution of (2); coefficient A aug And C aug According to the formula
Determining, and A, C, L, M is an augmented linear state variable model reflecting the performance degradation of the engine obtained by regarding the degradation parameter h as the control input of the engine and linearizing the nonlinear on-board engine model at a healthy steady-state reference point
Coefficient (c):
w is the system noise, R is the measurement noise, and the corresponding covariance matrices are the diagonal matrices Q and R.
4. The input-limited aero-engine de-conservative robust gain scheduling controller as claimed in claim 2, wherein: and the linear reduction conservative robust controller group resolving module obtains an adaptive linear reduction conservative robust controller according to the input degradation parameter h and the scheduling parameter alpha by interpolation.
5. The input-limited aero-engine de-conservative robust gain scheduling controller of claim 1, wherein: the linear reduction conservative robust controller group resolving module firstly resolves the current dispatch of the aero-engineTwo set working points alpha adjacent to each other before and after the parameter alpha is selected i And alpha i+1 And obtaining two set operating points alpha i And alpha i+1 Corresponding to the normal state h of the engine 1 And setting the degree of degradation h base Linear degradation conservative robust controller K i 、
K i+1 And
according to the formula
After calculating to obtain a current degradation parameter h of the aeroengine, setting two working points alpha i And alpha i+1 Linear droop conservative robust controller K i And K i+1 (ii) a According to the formula
And calculating to obtain the linear degradation conservative robust controller K (alpha) currently adapted to the aero-engine.
6. The input-limited aero-engine de-conservative robust gain scheduling controller of claim 1, wherein: the input limiting module adopts a multidimensional rectangular saturation function, and controls an input vector u to be:
wherein v is 1 And v m To control the elements of a vector v, v 1，max And v m,max Is the clipping value of the corresponding element of the control vector v.
7. The input-limited aero-engine de-conservative robust gain scheduling controller as claimed in claim 1, wherein: the scheduling parameter alpha comprises the fan rotating speed or the compressor rotating speed of the aircraft engine.
8. The input-limited aero-engine de-conservative robust gain scheduling 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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