A fault-tolerant control method for aeroengine actuators affected by parameter uncertainty

Abstract

The present invention provides a fault-tolerant control method for an aeroengine actuator affected by parameter uncertainty. The present invention comprises the following steps: establishing a discrete aeroengine state space model with parameter uncertainty; using a discrete time fault observer on the state space model to obtain a dynamic error system; applying Lyapunov's second method to the dynamic error system obtained by S2 to obtain a dynamic error system that satisfies L ∞ Exponential observer gain matrix: The state observation value and fault estimation value obtained by the fault observer designed by S3 are used to establish an uncertain discrete system actuator fault-tolerant controller based on feedback control. The present invention takes the parameter uncertainty of the system into consideration in the discrete aircraft engine system, constructs a fault observer to estimate the system state and fault signal, and provides a basis for the design of a feedback-based fault-tolerant controller. The present invention improves the safety and reliability of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of aero-engines, and in particular to a fault-tolerant control method for an aero-engine actuator affected by parameter uncertainty. Background Art

[0002] The aircraft engine is the only power device for aircraft flight, which has an extremely important impact on the safety, reliability and economy of the aircraft. The actual working conditions of the aircraft engine system are very harsh. It often works continuously under harsh conditions such as high temperature, high pressure, and strong vibration. Once a failure occurs, the performance will be affected at the least, causing the aircraft to make an emergency landing and unable to complete the established mission; at the worst, a crash will occur. It can be seen that whether the aircraft engine can work healthily and stably will have an important impact on the flight safety performance of the aircraft. Therefore, when an aircraft engine fails, it is imperative to use relevant technologies to improve the reliability of engine operation and avoid unnecessary safety hazards. It is worth mentioning that in the research process of aircraft engine control systems, it is very important to construct a mathematical model of the system, but a simple mathematical model is difficult to reflect the complex aircraft engine control system. Therefore, there are inevitable differences between the model of the actual system and the model based on mathematics. This requires the introduction of system model uncertainty when constructing the mathematical model. The introduction of uncertainty factors can well compensate for the errors caused by factors such as uncertainty in system structure and parameters, non-structural perturbations, etc., and can more realistically reflect the controlled system.

[0003] Aircraft engine control systems rely on a large number of electronic components, sensors and actuators to ensure that the system operates stably throughout the flight envelope and generates thrust. Due to the extremely harsh working environment, these components are prone to failure during system operation, and once a failure occurs, the entire control system may fail, leading to serious consequences. As the direct drive element of the aircraft engine, the actuator is closely related to the adjustment of the system state. In actual engineering, if the actuator fails or fails for some reason, it will endanger the normal operation of the entire control system. If effective measures are not taken in time, wrong information will be provided to the system, causing serious consequences. Early fault-tolerant control technologies mostly used hardware redundancy technology, which achieved fault tolerance by redundantly backing up the system's prone to failure components and key components, and have been widely used in control systems, such as fighter jets, satellites, rockets, etc. However, since hardware redundancy requires backup of system components, or even multiple backups to achieve the same function, it has some inevitable disadvantages while improving the safety and reliability of the control system, such as increasing system cost, structure, weight and space occupied. Therefore, the use of hardware redundancy in some large and complex systems is subject to certain restrictions. Therefore, estimating actuator faults and implementing fault-tolerant control for aircraft engine control systems with parameter uncertainties is an important measure to improve system safety and extend its life. It is not only critical but also of great significance to practical engineering. Summary of the invention

[0004] According to the technical problems raised above, a fault-tolerant control method for an aero-engine actuator affected by parameter uncertainty is provided. The technical means adopted by the present invention are as follows:

[0005] A method for fault-tolerant control of an aero-engine actuator based on a feedback controller comprises the following steps:

[0006] S1. Establish a discrete aero-engine state space model with parameter uncertainty;

[0007] S2. Using a discrete-time fault observer on the state-space model to obtain a dynamic error system;

[0008] S3. Apply Lyapunov's second method to the dynamic error system obtained in S2 to find the solution that satisfies L ∞ Exponential observer gain matrix:

[0009] S4. Use the state observation values ​​and fault estimation values ​​obtained by the fault observer designed in S3 to establish an actuator fault-tolerant controller for uncertain discrete systems based on feedback control.

[0010] Furthermore, in S1, considering that the system is affected by parameter uncertainty, disturbance and noise and actuator failure occurs, the state space of the system is written as follows:

[0011]

[0012] Where x, u, y are the system state vector, control input vector, and measurement output vector, respectively. ω represents process disturbance, v represents measurement noise, f represents actuator fault, A, B, C, D ω ,D v is a matrix of known suitable dimensions, ΔA and ΔB are uncertainty matrices, which are unknown but bounded, satisfying the following:

[0013] ΔA=M 1 Δ 1 N 1 ,ΔB=M 2 Δ 2 N 2 , (2)

[0014] Among them, the matrix M 1 , N 1 , M 2 and N 2 It is known that Δ 1 and Δ 2 is an unknown matrix satisfying and is the identity matrix with appropriate dimensions;

[0015] In addition, without loss of generality, it is assumed that the initial state, process disturbance, and measurement noise are unknown, but the following conditions are satisfied:

[0016]

[0017] in, is the estimated value of the state, and is a known vector;

[0018] In order to estimate the actuator fault f(t), the actuator fault f(t) is regarded as an additional state of the system, and the system state space model is expressed as:

[0019]

[0020] Where ξ(k)=[x T (k) f T (k)] T , h(k)=f(k+1)-f(k),

[0021] Furthermore, S2 specifically includes the following steps:

[0022] Using a discrete-time fault observer for model (4), consider the following observer:

[0023]

[0024] in, and are the augmented state vector ξ(k), the estimated value of the fault f(k) and the measured output y(k), respectively. is the gain of the discrete-time fault observer, L x and L d are the gain matrices of the state observer and fault observer, respectively,

[0025] The estimation error is defined as Combining (4) and (5), the error dynamic system is obtained as:

[0026]

[0027] according to The error dynamics system is rewritten as:

[0028]

[0029] in, is the intermediate process matrix;

[0030] In error dynamic systems, due to the influence of parameter uncertainty, the state estimation and the control input u(k) of the system have an impact on the error system. In addition, the parameter uncertainty matrices ΔA and ΔB are unknown, so they have no significant impact on the state estimation. The influence of the control input u(k) of the system is regarded as an unknown disturbance, and the error dynamic system is simplified to:

[0031] e(k+1)=A d e(k)+B d d(k) (8)

[0032] in B d =D x +ΔD, D y =[0 D v 0 0 0].

[0033] Furthermore, S3 is specifically:

[0034] The designed discrete-time fault observer gain matrix needs to make the dynamic error system meet the condition of being robust to unknown disturbances d(k):

[0035]

[0036] Among them, γ>0, 0<α<1 are constants, V(0)=e T (0)Pe(0), P is a positive definite matrix, ‖d(k)‖ ∞ =max k≥0 ‖d(k)‖ is the L of d(k) ∞ norm;

[0037] The designed observer gain matrix L = G -1 W, parameters G, W, P, α, γ, and β need to satisfy the following linear matrix inequality conditions. The specific values ​​can be obtained by calculation using the optimization toolbox:

[0038]

[0039]

[0040] in,

[0041] The undefined symbols mentioned above are the matrices defined by the MATLAB toolbox when solving linear matrix inequalities. They have no practical significance and are only used to facilitate the calculation of the final gain matrix L. α, β, and γ are the parameters used in the process of calculating linear matrix inequalities.

[0042] Furthermore, in S4, according to (5), the observation result of the state can be expressed as:

[0043]

[0044] in, is the observed value of the fault, L x is the state observer gain;

[0045] In order to reduce the impact of actuator failure on the system, the fault-tolerant control law based on fault compensation is designed as follows:

[0046]

[0047] Among them, K x and K f are the gain matrices for estimated state and estimated fault, respectively.

[0048] Furthermore, substituting the fault-tolerant control law (11) into the state observation result (10) yields:

[0049]

[0050] In order to eliminate the influence of actuator fault on the system, the gain matrix of estimated fault is designed as:

[0051] FK f B=0 (13)

[0052] Then the state estimation result can be written as:

[0053]

[0054] In this case, in order to ensure that the designed fault-tolerant controller can not only achieve fault tolerance to actuator failures but also ensure the stability of the entire system, a vector is redefined Combining (8) and (14) we get:

[0055]

[0056] in,

[0057] definition:

[0058]

[0059] in,

[0060] The following system is obtained:

[0061]

[0062] Next, we use the bounded real lemma to design the relevant parameters so that right Robust, that is right Robust, feedback-based fault-tolerant controller gain K x It can be obtained from the following linear matrix inequality:

[0063]

[0064] in,

[0065] Compared with the hardware redundancy technology of the prior art, the present invention adopts analytical redundancy technology to design a feedback-based fault-tolerant controller for fault-tolerant control, which has low cost, simple structure and good fault-tolerant control effect. The present invention takes the parameter uncertainty of the system into consideration in the discrete aircraft engine system, constructs a fault observer to estimate the system state and fault signal, and provides a basis for the design of a feedback-based fault-tolerant controller. Furthermore, based on the estimated system state and fault signal, a feedback-based fault-tolerant controller is designed to compensate for the system fault in real time. The designed observer not only feeds back the estimated value of the state but also feeds back the estimated value of the fault, so that the system actuator can remain stable and maintain the expected H when a fault occurs. ∞ Performance indicators, unlike controllers that only include state feedback, can further improve the safety and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0067] Figure 1 The flowchart is a fault-tolerant control method for an aircraft engine actuator based on a feedback controller;

[0068] Figure 2 It is the fault estimation diagram of periodic faults of aircraft engine actuators under the fault observer;

[0069] Figure 3 This is the result diagram of fault-tolerant control of aircraft engine state under the feedback-based fault-tolerant control method;

[0070] Figure 4 Input diagram of the fault-tolerant controller for aircraft engine actuators under the feedback-based fault-tolerant control method. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] The continuous aircraft engine mathematical model is discretized using the Euler one-step method, and the sampling time interval T s= 0.025s. Then, considering the fault factor, the discrete state space equation of system (1) is obtained, and the corresponding parameter matrix is ​​as follows:

[0073]

[0074] When aircraft engine actuators are affected by periodic faults in the following forms:

[0075]

[0076] By solving the linear matrix inequality (LMI), the gain matrix of the fault observer can be obtained:

[0077]

[0078] The flow chart of the fault-tolerant control method for aircraft engine actuators based on feedback controller is as follows: Figure 1 As shown in Figure 2, further, in order to prove the significant performance of the proposed method in fault-tolerant control, a simulation is performed to verify it. The simulation results are shown in Figure 2. Figure 2-4 As shown, Figure 2 These are the fault estimation value and actual fault value observed by the fault observer. It can be seen from the figure that the fault is well estimated, which lays the foundation for the subsequent design of the fault-tolerant controller. Figure 3 The results of aircraft engine state fault-tolerant control under the feedback-based fault-tolerant control method are demonstrated. It can be seen that the proposed fault-tolerant controller with fault compensation has good fault-tolerant control performance. Figure 4 is the fault-tolerant controller input of the aero-engine actuator under the feedback-based fault-tolerant control method, and the control input is within the acceptable range of the system. In summary, the proposed fault-tolerant control method can effectively handle the aero-engine actuator fault problem affected by parameter uncertainty, ensuring the safety and reliability of the system.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fault-tolerant control method for an aero-engine actuator affected by parameter uncertainty, characterized in that: The following steps are involved: S1. Establish a discrete aero-engine state space model with parameter uncertainty; S2. Using a discrete-time fault observer on the state-space model to obtain a dynamic error system; S3. Apply Lyapunov's second method to the dynamic error system obtained in S2 to find the solution that satisfies L ∞ Exponential observer gain matrix: S4. Use the state observation value and fault estimation value obtained by the fault observer designed in S3 to establish an actuator fault-tolerant controller for uncertain discrete systems based on feedback control; In S1, considering that the system is affected by parameter uncertainty, disturbance and noise and actuator failure occurs, the state space of the system is written as follows: Where x, u, y are the system state vector, control input vector, and measurement output vector, respectively. ω represents process disturbance, v represents measurement noise, f represents actuator fault, k represents discrete time instant, F represents the system actuator fault matrix, A, B, C, D ω ,D v is a known matrix with a preset dimension, ΔA and ΔB are uncertainty matrices, which are unknown but bounded, satisfying the following: ΔA=M1Δ1N1, ΔB=M2Δ2N2, (2) Among them, the matrices M1, N1, M2 and N2 are known, and Δ1 and Δ2 are unknown matrices satisfying and is the identity matrix with preset dimensions; In addition, without loss of generality, it is assumed that the initial state, process disturbance, and measurement noise are unknown, but the following conditions are satisfied: in, is the estimated value of the state, and is a known vector; In order to estimate the following actuator fault f(k), the actuator fault f(k) is regarded as an additional state of the system, and the system state space model is expressed as: in, Among them, I nf represents the identity matrix with preset dimensions; S2 specifically includes the following steps: Using a discrete-time fault observer for model (4), consider the following observer: in, and are the augmented state vector ξ(k), the estimated value of the fault f(k) and the measured output y(k), respectively. is the gain of the discrete-time fault observer, L x and L f are the gain matrices of the state observer and fault observer respectively, The estimation error is defined as Combining (4) and (5), the error dynamic system is obtained as: according to The error dynamics system is rewritten as: in, is the intermediate process matrix; In error dynamic systems, due to the influence of parameter uncertainty, the state estimation and the control input u(k) of the system have an impact on the error system. In addition, the parameter uncertainty matrices ΔA and ΔB are unknown. Assuming that the system state and control input are bounded, they have no significant effect on the state estimation. The influence of the control input u(k) of the system is regarded as an unknown disturbance, and the error dynamic system is simplified to: e(k+1)=A d e(k)+B d d(k)(8) thereof B d =D x +ΔD, D y =[0 D v 0 0 0]; S3 is specifically: The designed discrete-time fault observer gain matrix needs to make the dynamic error system meet the condition of being robust to unknown disturbances d(k): Among them, γ>0, 0<α<1 are constants, P is a positive definite matrix, ‖d(k)‖ ∞ =max k≥0 ‖d(k)‖ is the L of d(k) ∞ norm; The designed observer gain matrix L = G -1 W, parameters G, W, P, α, γ, and β need to satisfy the following linear matrix inequality conditions, and use the optimization toolbox to calculate and obtain specific values: in, In S4, according to (5), the observation result of the state is expressed as: in, is the estimated value of the fault, L x is the state observer gain; In order to reduce the impact of actuator failure on the system, the fault-tolerant control law based on fault compensation is designed as follows: Among them, K x and K f are the gain matrices for estimated states and estimated faults, respectively; Substituting the fault-tolerant control law (11) into the state observation result (10), we get: In order to eliminate the influence of actuator fault on the system, the gain matrix of estimated fault is designed as: F-K f B=0(13) Then the state estimation result is written as: In this case, in order to ensure that the designed fault-tolerant controller can not only achieve fault tolerance to actuator failures but also ensure the stability of the entire system, a vector is redefined Combining (8) and (14) we get: in, definition: in, The following system is obtained: Next, we use the bounded real lemma to design the relevant parameters so that right Robust, that is right Robust, feedback-based fault-tolerant controller gain K x It is obtained by the following linear matrix inequality: in, Among them, Q1 is a positive definite symmetric matrix.

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