Gas turbine auto-disturbance rejection speed control method and system based on sliding mode observer

Abstract

The present application discloses a gas turbine self-disturbance rejection speed control method and system based on a sliding mode observer, which relates to the technical field of gas turbines. The method uses the fuel flow rate as the input and the gas turbine power turbine speed as the state quantity to establish the operating state equation of the gas turbine, uses an adaptive high-order sliding mode observer to obtain the estimated value of the uncertain disturbance, designs the power turbine speed controller based on the self-disturbance rejection control theory, uses the engine set speed as the control target value, and realizes robust control of the speed by real-time compensation of the disturbance value estimated by the observer, so that the controller can still maintain good control accuracy when the system parameters suddenly change. The engine power turbine speed control method of the present application has strong robustness to engine modeling errors and external disturbances, and can significantly improve the tracking performance and self-disturbance rejection capability of the system.

Description

Technical Field

[0001] The present application relates to the technical field of gas turbines, and in particular to a gas turbine self-disturbance rejection speed control method and system based on a sliding mode observer. Background Art

[0002] A gas turbine is an internal combustion power machine that uses a continuously flowing gas as a working fluid to drive the impeller to rotate at high speed, converting the energy of the fuel into useful work. The gas turbine uses a starting motor or compressed air to drive the compressor to compress the air during the starting process. After ignition and combustion, it enters the slow speed or above working condition, and then drives the compressor through the power turbine to achieve a self-stabilizing cycle, and performs work outward to achieve power output.

[0003] Gas turbines usually use closed-loop speed control, with fuel flow as the control input. However, the strong nonlinear characteristics of the gas turbine itself and the efficiency degradation caused by long-term operation usually lead to modeling errors. The speed sensor often fluctuates or distorts the signal acquisition due to harsh environments or electromagnetic interference, causing the control system to malfunction, resulting in downgrades, emergency shutdowns and other faults. Summary of the invention

[0004] The present application aims to solve the technical problem that the existing gas turbine control system cannot effectively eliminate the disturbance term due to modeling error or when the speed sensor is subject to external interference, resulting in control instability. A gas turbine self-disturbance rejection speed control method based on an adaptive high-order sliding mode observer is proposed. The method includes:

[0005] S110, with fuel flow as input u(t) , gas turbine power turbine speed is the state quantity x(t) , also known as the output y(t) , construct the state equation of the gas turbine based on the aerodynamic thermodynamic characteristics of the gas turbine;

[0006] S120, designing an adaptive high-order sliding mode observer based on the state equation of the gas turbine;

[0007] S130, the desired target speed of the given gas turbine control system is x d , then the tracking error is expressed as

[0008] , on this basis, the sliding surface, sliding mode approach rate and active disturbance rejection control rate are designed;

[0009] S140, with the desired target speed of the gas turbine x d As a state quantity x The tracking target is set, and the fuel flow is controlled according to the automatic disturbance rejection control rate in the presence of modeling errors and external disturbances of the sensor.

[0010] Furthermore, the S110 further includes: the state equation of the gas turbine is constructed as follows:

[0011] ;

[0012] in, f(x) is the nonlinear transfer function of the gas turbine, T(t) is the gas turbine load power, d(t) The uncertainties caused by sensor or load disturbances and modeling errors in the process of model building are for x(t) The derivative of A , B is a reversible matrix of known appropriate dimension obtained by fitting the aerodynamic thermodynamic model, and t is the time quantity.

[0013] Further, define the uncertainty d(t) is globally bounded and differentiable, and the derivative is ,and d(t) Satisfies the Lipschitz condition: ,in, , represents the upper bound of the uncertainty term of the model, which is a known constant. Represents the norm of the function.

[0014] Furthermore, the S120 further includes: the adaptive high-order sliding mode observer is used to obtain the uncertainty term d(t) Estimated value of Z Derivative of 2 and auxiliary speed estimation variables Z Derivative of 1 , then the sliding mode observer is expressed as:

[0015] ;

[0016] In the formula, e represents the difference between the estimated speed of the state observer and the actual speed. is the symbolic function, , , , given ; , , , are all positive odd numbers, and let > , < , , , , , , , These are given parameters for the sliding mode observer.

[0017] Further, let Indicates the uncertainty d(t) The estimation error is d(t) Derivative of the estimation error for:

[0018] ;

[0019] From this we get: ;

[0020] in, , d 0 is the corresponding constant term, and all the dots on the parameters represent the derivative of the parameter.

[0021] Furthermore, the S130 further includes:

[0022] The sliding surface is designed as: ,in, c 1>0 is a given constant coefficient;

[0023] The sliding mode approach rate is designed as:

[0024] ;

[0025] Among them, the uncertain d(t) Estimation is performed by a sliding mode observer;

[0026] The designed active disturbance rejection control rate is:

[0027] ;

[0028] in, u(t) It represents the control rate of the ADRC, which is the fuel control flow rate; d 1>0, d 2>0; c 1. d 1. d 2 are given control coefficients.

[0029] Further including: d 1>0, d When 2>0, the sliding mode approach rate is:

[0030] ;

[0031] When the system state is far from the sliding surface, the parameter Ignoring the impact on the approach rate, the approach rate is approximately , that is, ; where t0 represents the initial time of system control. As time changes, the system will tend to the sliding surface at an exponential rate. When the system is near the sliding surface, s 0, in the function The influence of the term is weakened, and the convergence rate is approximately: .

[0032] Further includes: To ensure rapid approach to the die surface and effectively suppress chattering, design d 1 is an adjustable parameter, which adjusts the approach rate adaptively according to the approach degree of the system. , where λ and h All are given approach rate control coefficients;

[0033] When the system state is far away from the sliding surface, |s| +∞, , h tends to (1+ λ )> h , so the speed at which the system state approaches the sliding surface will increase; when the system state moves near the sliding surface, |s| 0, ,but d 1 is represented by:

[0034] ;

[0035] When the system approaches the sliding surface, ,but d 1 0; the control system approach step will quickly approach 0 as the error decreases, which can suppress the system chattering; d 1 Substitute the control rate u(t) get:

[0036] .

[0037] Furthermore, after S140, it also includes: proving through Lyapunov function that the adaptive high-order sliding mode observer makes the gas turbine system stable, and the proof process includes: let δ = Z 2- d Denotes the estimation error of the uncertainty term, we can get:

[0038] ;

[0039] This yields:

[0040] ;

[0041] in, , d 0 is the corresponding constant term; then the above formula is expressed as:

[0042] ;

[0043] Introducing variables , then from the above formula we get:

[0044] ;

[0045] Depend on e The definition of r (0)= r 0, that is:

[0046] ;

[0047] From this we get:

[0048] ; (1)

[0049] make , then:

[0050] ;

[0051] because is the initial state of the system, is a constant, then the derivative of (1) is obtained; ;

[0052] Because in r When ∞, it is monotonically decreasing, then the quadratic Lyapunov function is defined as:

[0053] ;

[0054] right V 1 Taking the derivative we get:

[0055] ;

[0056] Known θ(r) Monotonically decreasing, that is, the above formula is expressed as:

[0057] ;

[0058] because , , , and there is >|D|, obtained by definition,

[0059] ;

[0060] ;

[0061] in, ; That is, , the variable gain state observer is stable;

[0062] After S140, it also includes: proving that the self-disturbance rejection control rate makes the gas turbine system stable through the Lyapunov function, and the proof process includes:

[0063] The Lyapunov function is constructed as:

[0064] ;

[0065] right V 2 Taking the derivative we get:

[0066] ;

[0067] Under the action of the active disturbance rejection control rate, the system is asymptotically stable and the system error will converge to zero within a finite time.

[0068] On the other hand, the present application also provides a gas turbine self-disturbance rejection speed control system based on an adaptive high-order sliding mode observer, the system comprising a memory for storing computer program instructions and a processor for executing program instructions, wherein when the computer program instructions are executed by the processor, the system is triggered to execute the above-mentioned gas turbine self-disturbance rejection speed control method based on an adaptive high-order sliding mode observer.

[0069] The beneficial technical effect of the present application is: the present application discloses a gas turbine self-disturbance rejection speed control method and system based on a sliding mode observer, which relates to the technical field of gas turbines. The method uses the fuel flow rate as the input and the speed of the gas turbine power turbine as the state quantity to establish the operating state equation of the gas turbine, uses an adaptive high-order sliding mode observer to obtain the estimated value of the uncertain disturbance, designs the power turbine speed controller based on the self-disturbance rejection control theory, uses the set speed of the gas turbine as the control target value, and realizes robust control of the speed by compensating the disturbance value estimated by the observer in real time, so that the controller can still maintain good control accuracy when the system parameters suddenly change. The gas turbine power turbine speed control method of the present application has strong robustness to the gas turbine modeling error and external disturbance, and can significantly improve the tracking performance and self-disturbance rejection capability of the system.

[0070] When designing the speed control rate, the present application takes into account the large inertia and strong time lag of the gas turbine during actual operation. The frequent switching of the controller output on the sliding surface can easily cause the system to vibrate. Therefore, an adaptive adjustment parameter is designed to adaptively adjust the approach rate as the system state approaches the sliding surface, which better suppresses the sliding mode control jitter and effectively improves the system stability. In addition, compared with the traditional PID control, the gas turbine self-resistance speed control method based on the adaptive high-order sliding mode observer designed in the present application has a strong dependence on the control input and the control is easy to diverge when disturbed. The present application can quickly track the actual speed output, has strong robustness to the engine modeling error and external interference, and can significantly improve the tracking performance and self-resistance capability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 is a flow chart of a gas turbine self-disturbance rejection speed control method based on an adaptive high-order sliding mode observer in one embodiment of the present application;

[0072] Figure 2 is a structural diagram of a gas turbine auto-disturbance rejection speed controller based on an adaptive high-order sliding mode observer in one embodiment of the present application;

[0073] Figure 3 It is a power turbine speed output curve of the active disturbance rejection control and PID control based on the adaptive high-order sliding mode observer in one embodiment of the present application;

[0074] Figure 4 is an output curve diagram of a speed sensor of a power turbine in an embodiment of the present application that fails;

[0075] Figure 5 yes Figure 4 The control error comparison curve of the active disturbance rejection control based on adaptive high-order sliding mode observer and PID control in the corresponding case. DETAILED DESCRIPTION

[0076] In order to more clearly understand the purpose, features and advantages of the present disclosure, the technical solutions 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. It should be noted that the embodiments of the present disclosure and their features can be combined with each other without conflict. Many specific details are provided in the following description to fully understand the present disclosure, but in fact the present disclosure can be implemented in other ways, which may be different from the following description. Obviously, the embodiments in the specification only represent some embodiments of the present disclosure, not all embodiments.

[0077] According to the operating principle of the gas turbine, the gas turbine drives the compressor to compress the air during the startup process through the starting motor or compressed air. After ignition and combustion entering the slow speed or above operating condition, the power turbine drives the compressor to achieve a self-stabilizing cycle, and performs work outward to achieve power output.

[0078] Combine the following Figure 1 and Figure 2 , a gas turbine self-disturbance rejection speed control method based on an adaptive high-order sliding mode observer is introduced. The specific steps of the method are as follows:

[0079] S110, with fuel flow as input u(t) , gas turbine power turbine speed is the state quantity x(t) , also known as the output y(t) , based on the aerodynamic thermodynamic characteristics of the gas turbine, the state equation of the gas turbine is constructed. f(x) represents the nonlinear transfer function of the gas turbine, T(t) represents the gas turbine load, d(t) represents the uncertainty caused by sensor or load disturbance and modeling error in the process of building the model. A and B are reversible matrices of known appropriate dimensions.

[0080] S120, Design of an adaptive high-order sliding mode observer based on the system state equation of a gas turbine to obtain the uncertainty d(t) Estimated value Z 2 and auxiliary speed estimation variables Z 1, the sliding mode observer is expressed as:

[0081] ;

[0082] In the formula, e represents the difference between the estimated speed of the state observer and the actual speed. is the symbolic function, , , , given ; , , , are all positive odd numbers, and let > , < , , , , , , , These are given parameters for the sliding mode observer.

[0083] S130, the desired target speed of the given gas turbine control system is x d , then the tracking error can be expressed as On this basis, the sliding surface is designed as:

[0084] ;

[0085] The designed sliding mode approach rate is:

[0086] ;

[0087] Among them, the uncertain d(t) It can be estimated by a sliding mode observer.

[0088] The designed active disturbance rejection sliding mode control rate is:

[0089] ;

[0090] in, u(t) It represents the control rate of the ADRC, which is the fuel control flow rate; d 1>0, d 2>0; c 1. d 1. d 2 are given control coefficients, which are selected according to the characteristics of the control object and design experience. In order to ensure rapid approach to the die surface and effectively suppress chattering, the design d 1 is an adjustable parameter, which adjusts the approach rate adaptively according to the approach degree of the system.

[0091] ;

[0092] S140, combined with the aerodynamic thermodynamic model of the gas turbine, determines the self-disturbance rejection speed control rate based on the adaptive high-order sliding mode observer; the gas turbine set speed x d As a state quantity x The tracking target is obtained and the fuel flow is controlled according to the control rate in the presence of modeling errors and external disturbances of the sensor.

[0093] The gas turbine speed control method of the present application is an active fault-tolerant control method, which estimates the modeling error and external interference in real time through an observer, has strong robustness, and effectively avoids the strong dependence of traditional control on model accuracy and the problem of easy control divergence when external interference occurs suddenly.

[0094] In order to more clearly explain the gas turbine self-disturbance rejection speed control method based on the adaptive high-order sliding mode observer of the present application, the following is combined with Figure 1 and Figure 2 The examples of this application are described in detail.

[0095] S210, with fuel flow as input u(t) , gas turbine power turbine speed is the state quantity x(t) , also known as the output y(t) , the state equation of the gas turbine is constructed as:

[0096] ;

[0097] in, f(x) is the nonlinear transfer function of the gas turbine, T(t) is the gas turbine load power, d(t) The uncertainties caused by sensor or load disturbances and modeling errors in the process of model building are for x(t) The derivative of A , B is a reversible matrix of known appropriate dimension obtained by fitting the aerodynamic thermodynamic model, and t is the time quantity.

[0098] S220, based on gas turbine characteristics uncertainty d(t) Satisfy the first assumption, the first assumption is: define the uncertainty d(t) Globally bounded and differentiable, its derivative is defined as ,and d(t) Satisfies the Lipschitz condition:

[0099]

[0100] Among them, represents the upper bound of the uncertainty term of the model, which is obtained through experience and is a known constant; Represents the norm of the function.

[0101] In this embodiment, the designed adaptive high-order sliding mode observer is:

[0102] ;

[0103] In the formula, is the symbolic function, , , , given ; , , , are all positive odd numbers, and let > , < .make Denotes the estimation error of the uncertain term, we can get

[0104] ;

[0105] From this we can get:

[0106] ;

[0107] in, , d 0 is the corresponding constant term.

[0108] S230, the gas turbine speed control method of the present application also includes: designing an anti-disturbance speed controller based on the observation value of the adaptive high-order sliding mode observer to achieve gas turbine speed control.

[0109] Given the desired target speed of the gas turbine control system is x d , then the tracking error can be expressed as , and design the sliding surface on this basis:

[0110] ;

[0111] In the formula, c 1>0, c 1 is a given constant coefficient; then:

[0112] ;

[0113] Among them, the uncertain d(t) It is estimated by the sliding mode observer; then the active disturbance rejection control rate is:

[0114] ;

[0115] in, d 1>0, d 2>0; thus, the sliding mode approach rate is:

[0116] ;

[0117] When the system state is far from the sliding surface, the parameter Ignoring the impact on the approach rate, the approach rate is approximately , that is, ; where t0 represents the initial time of system control. As time changes, the system will tend to the sliding surface at an exponential rate. When the system is near the sliding surface, s 0, in the function The influence of the term is weakened, and the convergence rate is approximately: .

[0118] To ensure rapid approach to the die surface and effectively suppress chattering, the design d 1 is an adjustable parameter, which adjusts the approach rate adaptively according to the approach degree of the system. , where λ and h All are given approach rate control coefficients;

[0119] When the system state is far away from the sliding surface, |s| +∞, , h tends to (1+ λ )> h , so the speed at which the system state approaches the sliding surface will increase; when the system state moves near the sliding surface, |s| 0, ,but d 1 is represented by:

[0120] ;

[0121] When the system approaches the sliding surface, ,but d 1 0; the control system approach step will quickly approach 0 as the error decreases, which can suppress the system chattering; d 1 Substitute the control rate u(t) get:

[0122] .

[0123] In some embodiments, the observer and the active disturbance rejection control rate designed by the present application can be proved to stabilize the gas turbine system through the Lyapunov function.

[0124] 1) The proof process of the adaptive high-order sliding mode observer includes:

[0125] make δ = Z 2- d represents the estimation error of the uncertainty term,

[0126] ;

[0127] This yields:

[0128] ;

[0129] in, , d 0 is the corresponding constant term; then the above formula is expressed as:

[0130] ;

[0131] Introducing variables , then from the above formula we get:

[0132] ;

[0133] Depend on e The definition of r (0)= r 0, that is:

[0134] ;

[0135] From this we get:

[0136] ; (1)

[0137] make , then:

[0138] ;

[0139] because is the initial state of the system, is a constant, then the derivative of (1) is obtained; ;

[0140] Because in r When ∞, it is monotonically decreasing, then the quadratic Lyapunov function is defined as:

[0141] ;

[0142] right V 1 Taking the derivative we get:

[0143] ;

[0144] Known θ(r) Monotonically decreasing, that is, the above formula is expressed as:

[0145] ;

[0146] because , , , and there is >|D|, obtained by definition,

[0147] ;

[0148] ;

[0149] in, ; That is, , the variable gain state observer is stable.

[0150] 2) The process of proving that the speed control rate makes the gas turbine control system stable includes:

[0151] In order to verify the stability of the control system, the Lyapunov function is constructed again as

[0152] ;

[0153] right V 2 Taking the derivative we get:

[0154] ;

[0155] Under the action of the active disturbance rejection control rate, the system is asymptotically stable and the system error will converge to zero within a finite time.

[0156] In order to verify the gas turbine active disturbance rejection control strategy based on sliding mode observer, a dual-shaft gas turbine model is established to replace the actual controlled object using the gas turbine test data. The gas turbine speed and power turbine speed are taken as state variables, and the model is normalized to obtain the parameter expression:

[0157] ;

[0158] The parameters of the gas turbine are set as follows: from the 0.4 working condition, the hydraulic dynamometer simulates the load and the power turbine speed is controlled. The initial working state is the power turbine speed of 2300r / min. At the 20th second, it suddenly increases to the 0.75 working condition, the given set speed increases to 3000r / min, and at 35 seconds, the external disturbance is superimposed. d(t) =0.5sin2 πt , comparing the effects of conventional PID control and observer-based active disturbance rejection sliding mode control.

[0159] from Figure 3 It can be seen that both conventional PID control and observer-based auto-disturbance rejection sliding mode control can track the set speed, but the sliding mode control rate has better dynamic response and smaller overshoot than PID control, and basically no jitter occurs. At 35 seconds, when external disturbances occurred, both PID control and sliding mode control performed stable control. Although they both tended to be stable in the end, when the operating conditions suddenly increased, the control effect was compared. The maximum overshoot of sliding mode control was reduced by about 60% compared with PID control, and the time to enter steady state was also shorter; in the case of sudden external disturbances, the maximum overshoot of the sliding mode control algorithm was reduced by about 76.1%, and the steady state time was shortened by 57.1%. For details, please refer to the performance comparison table of auto-disturbance rejection control and PID control based on adaptive high-order sliding mode observer in Table 1.

[0160]

[0161] In order to further verify the robustness of the ADRC algorithm, the pulse disturbance fault that is more common in the speed sensor is selected to compare the control effects of different algorithms. Figure 4As shown, the gas turbine is set to run at a constant speed of 2500r / min. At t=20 seconds, a pulse-type fault occurs in the speed sensor. The interference pulse causes the speed sampling value to drop by 500RPM instantaneously. The control effects of different control algorithms are observed.

[0162] like Figure 5 As shown in the figure, it can be seen from the speed control error curve that after the sensor pulse disturbance fault occurs, the system tends to be stable after the PID control performs speed regulation, but the adjustment cycle is long and the error is large; the speed tracking error of the self-disturbance rejection sliding mode control is reduced by about 50% compared with the PID control, the stabilization speed is also faster, and the overall robustness is better. In summary, the adaptive high-order sliding mode observer can quickly realize the uncertainty estimation, and the self-disturbance rejection sliding mode control algorithm has significantly improved the control effect compared with the traditional PID control method through real-time compensation and adaptive adjustment of the approach rate, and has stronger robustness and stability.

[0163] The present invention also provides a gas turbine self-disturbance rejection speed control system based on an adaptive high-order sliding mode observer, the system comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein when the computer program instructions are executed by the processor, the system is triggered to execute the aforementioned gas turbine self-disturbance rejection speed control method based on an adaptive high-order sliding mode observer.

[0164] In summary, the present invention provides a gas turbine self-disturbance rejection speed control method and system based on an adaptive high-order sliding mode observer, which relates to the technical field of gas turbines. The method uses the fuel flow rate as the input and the gas turbine power turbine speed as the state quantity to establish the operating state equation of the gas turbine, uses the adaptive high-order sliding mode observer to obtain the estimated value of the uncertain disturbance, designs the power turbine speed controller based on the self-disturbance rejection control theory, uses the engine set speed as the control target value, and realizes robust control of the speed by real-time compensation of the disturbance value estimated by the observer, so that the controller can still maintain good control accuracy when the system parameters suddenly change. The engine power turbine speed control method of the present application has strong robustness to engine modeling errors and external disturbances, and can significantly improve the tracking performance and self-disturbance rejection capability of the system.

[0165] It should be noted that the system of the present invention may also include one or more of the following components: a processor and a memory.

[0166] Optionally, the processor uses various interfaces and lines to connect various parts within the entire autonomous operation equipment, and executes various functions of the autonomous operation equipment and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory. Optionally, the processor can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a neural network processor (NPU). Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content that needs to be displayed on the touch display; and the NPU is used to implement artificial intelligence (AI) functions.

[0167] The memory may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory includes a non-transitory computer-readable storage medium. The memory may be used to store instructions, programs, codes, code sets, or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function, instructions for implementing each of the above method embodiments, etc.; the data storage area may store data created according to the use of the autonomous operation device, etc.

[0168] The present disclosure also provides a computer-readable storage medium storing a computer program, wherein the computer program is used to be executed by a processor to implement the positioning control method of the autonomous working equipment as described in the above embodiment.

[0169] Although the present invention has been described in detail by referring to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention or any person skilled in the art who is familiar with the present invention may easily think of changes or substitutions within the technical scope disclosed by the present invention, and shall be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A gas turbine auto-disturbance rejection speed control method based on a sliding mode observer, characterized in that: The method includes: S110, with fuel flow as input u(t) , gas turbine power turbine speed is the state quantity x(t) , also known as the output y (t) , construct the state equation of the gas turbine based on the aerodynamic thermodynamic characteristics of the gas turbine; S120, designing an adaptive high-order sliding mode observer based on the state equation of the gas turbine; S130, the desired target speed of the given gas turbine control system is x d , then the tracking error is expressed as , on this basis, the sliding surface, sliding mode approach rate and active disturbance rejection control rate are designed; S140, with the desired target speed of the gas turbine x d As a state quantity x The tracking target is set, and the fuel flow is controlled according to the automatic disturbance rejection control rate in the presence of modeling errors and external disturbances of the sensor.

2. The method according to claim 1, characterized in that The S110 further includes: constructing the state equation of the gas turbine as follows: ； in, f(x) is the nonlinear transfer function of the gas turbine, T(t) is the gas turbine load power, d(t) The uncertainties caused by sensor or load disturbances and modeling errors in the process of model building are for x(t) The derivative of A , B is a reversible matrix of known appropriate dimension obtained by fitting the aerodynamic thermodynamic model, and t is the time quantity.

3. The method according to claim 2, characterized in that: The uncertainty d(t) is globally bounded and differentiable, and the derivative is ,and d(t) Satisfies the Lipschitz condition: ,in, , represents the upper bound of the uncertainty term of the model, which is a known constant. Represents the norm of the function.

4. The method according to claim 3, characterized in that The S120 further includes: the adaptive high-order sliding mode observer is used to obtain the uncertainty term d(t) Estimated value of Z Derivative of 2 and auxiliary speed estimation variables Z Derivative of 1 , then the sliding mode observer is expressed as: ； In the formula, e represents the difference between the estimated speed of the state observer and the actual speed. is the symbolic function, , , , given ; , , , are all positive odd numbers, and let > , < , , , , , , , These are given parameters for the sliding mode observer.

5. The method according to claim 4, characterized in that make Indicates the uncertainty d(t) The estimation error is d(t) Derivative of the estimation error for: ； From this we get: ; in, , d 0 is the corresponding constant term, and all the dots on the parameters represent the derivative of the parameter.

6. The method according to claim 5, characterized in that The S130 further includes: The sliding surface is designed as: ,in, c 1>0 is a given constant coefficient; The sliding mode approach rate is designed as: ； Among them, the uncertain d(t) Estimation is performed by a sliding mode observer; The designed active disturbance rejection control rate is: ； in, u(t) It represents the control rate of the ADRC, which is the fuel control flow rate; d 1>0, d 2>0; c 1. d 1. d 2 are given control coefficients.

7. The method according to claim 6, characterized in that Further including: d 1>0, d When 2>0, the sliding mode approach rate is: ； When the system state is far from the sliding surface, the parameter Ignoring the impact on the approach rate, the approach rate is approximately , that is, ; where t0 represents the initial time of system control. As time changes, the system will tend to the sliding surface at an exponential rate. When the system is near the sliding surface, s 0, in the function The influence of the term is weakened, and the convergence rate is approximately: .

8. The method according to claim 7, characterized in that Further including: To ensure rapid approach to the die surface and effectively suppress chattering, the design d 1 is an adjustable parameter, which adjusts the approach rate adaptively according to the approach degree of the system. , where λ and h All are given approach rate control coefficients; When the system state is far away from the sliding surface, |s| +∞, , h tends to (1+ λ )> h , so the speed at which the system state approaches the sliding surface will increase; when the system state moves near the sliding surface, |s| 0, ,but d 1 is represented by: ； When the system approaches the sliding surface, ,but d 1 0; the control system approach step will quickly approach 0 as the error decreases, which can suppress the system chattering; d 1 Substitute the control rate u(t) get: 。 9. The method according to claim 8, characterized in that After S140, it also includes: Proving that the adaptive high-order sliding mode observer makes the gas turbine system stable through the Lyapunov function, and the proof process includes: Let δ = Z 2- d Denotes the estimation error of the uncertain term, we can get: ； This yields: ； in, , d 0 is the corresponding constant term; then the above formula is expressed as: ； Introducing variables , then from the above formula we get: ； Depend on e The definition of r (0)= r 0, that is: ； From this we get: ；（1） make , then: ； because is the initial state of the system, is a constant, then the derivative of (1) is obtained; ; Because in r When ∞, it is monotonically decreasing, then the quadratic Lyapunov function is defined as: ； right V 1 Taking the derivative we get: ； Known θ(r) Monotonically decreasing, that is, the above formula is expressed as: ； because , , , and there is >|D|, obtained by definition, ； ； in, ; That is, , the variable gain state observer is stable; After S140, it also includes: proving that the self-disturbance rejection control rate makes the gas turbine system stable through the Lyapunov function, and the proof process includes: The Lyapunov function is constructed as: ； right V 2 Taking the derivative we get: ； Under the action of the active disturbance rejection control rate, the system is asymptotically stable and the system error will converge to zero within a finite time.

10. A gas turbine self-disturbance rejection speed control system based on a sliding mode observer, the system comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein: When the computer program instructions are executed by the processor, the system is triggered to execute the method according to any one of claims 1 to 9.

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