Design method and device for controller of gas turbine and medium

Abstract

The invention discloses a design method and device for a controller of a gas turbine and a medium, and relates to the technical field of gas turbine control, and the method comprises the following steps: constructing a mathematical model of a control system of a micro gas turbine; determining a model dimension based on the mathematical model, and performing dimension reduction processing on the control system based on the model dimension to obtain a plurality of subsystems; and setting a system stability control quantity for each subsystem, and determining that the design of a controller in the control system is completed under the condition that the system stability control quantity reaches a preset stability condition. The problem that in the prior art, the control precision is poor when PID control is used for controlling the gas turbine is solved, the inherent characteristics of the micro gas turbine are considered in the controller design stage, and the designed controller can accurately control the gas turbine.

Description

Technical Field

[0001] The present application relates to the field of gas turbine control technology, and in particular to a design method, device, and medium for a gas turbine controller. Background Art

[0002] Micro gas turbines are a newly developed type of small internal combustion power machinery with a power range of 25-300KW. Their basic technical features are the use of radial impeller machinery and regenerative cycle. Micro gas turbines are mainly divided into two types: single-shaft and dual-shaft. Micro single-shaft gas turbines are composed of core components such as compressor, combustion chamber, turbine and regenerator. Figure 1 (This section is prior art.) Single-shaft micro gas turbines typically use the Brayton cycle. After filtering, air is compressed by a compressor. The compressed, high-pressure air enters the combustion chamber and mixes with fuel for combustion. The resulting high-temperature, high-pressure combustion gas propels the turbine to produce work. Simultaneously, the rotation of the turbine drives the compressor, achieving internal balance within the gas turbine. The high-temperature flue gas is then passed through a regenerator to heat the inlet air, improving the efficiency of the micro gas turbine.

[0003] Micro gas turbines typically use closed-loop speed control, regulating fuel flow to ensure stable operation. Because micro gas turbines are commonly used in distributed energy, transportation, land, sea, and air defense, high precision and strong interference immunity are key goals in their control system design. However, the inherent nonlinear coupling characteristics of micro gas turbines and the efficiency degradation caused by long-term operation lead to persistent modeling errors and parameter perturbations. Harsh environments such as high temperature, vibration, and oil mist can also cause external interference on sensor lines such as position and speed, resulting in fluctuations in the acquired signals.

[0004] In the prior art, traditional PID control is used to control gas turbines. However, PID control is highly dependent on model accuracy and is easily affected by external interference, which reduces control accuracy and results in poor control accuracy of the gas turbine. Summary of the Invention

[0005] In response to the above-mentioned problems and technical needs, the applicant has proposed a design method, equipment and medium for a gas turbine controller to solve the problem of poor control accuracy when using PID control for gas turbine control in the existing technology, and to take into account the inherent characteristics of the micro gas turbine during the controller design stage, so that the designed controller can accurately control the gas turbine.

[0006] An embodiment of the present application provides a method for designing a controller for a gas turbine, the method comprising:

[0007] Constructing a mathematical model of a control system for a micro gas turbine, wherein the mathematical model is constructed based on a target fuel quantity, a turbine speed, a turbine gas flow rate, a combustion chamber fuel flow rate, a fuel valve opening, and aerodynamic thermodynamic characteristics of the fuel turbine;

[0008] Determining a model dimension based on the mathematical model, and performing dimensionality reduction processing on the control system based on the model dimension to obtain a plurality of subsystems;

[0009] Setting a system stability control variable for each subsystem, and determining that the controller design in the control system is completed when it is determined that the system stability control variables all meet preset stability conditions;

[0010] Among them, different subsystems correspond to different system stability control quantities, and different system stability control quantities correspond to different stability conditions.

[0011] According to the design method of the gas turbine controller provided by the embodiment of the present application, the subsystem includes: a first-order system, and the system stability control quantity includes: a first stability control quantity;

[0012] Setting a system stability control variable for each subsystem, and determining that the system stability control variables all meet preset stability conditions, determining that the controller design in the control system is complete, including:

[0013] Setting a first stabilizing control variable for the first-order system;

[0014] Setting a desired speed value, and calculating a difference between the desired speed value and a target speed;

[0015] When it is determined that the first stable control variable and the difference satisfy a first stable condition, setting a first sliding surface;

[0016] Based on the first stability condition and the first sliding surface, the designed control system tends to be stable.

[0017] According to the design method of the gas turbine controller provided by an embodiment of the present application, the first stability condition includes: a first stability formula;

[0018] Among them, the first stable formula includes:

[0019]

[0020] in, e represents the difference between the expected speed and the target speed, c1 represents the first convergence adjustment coefficient, which is a constant greater than zero, and m1 represents the first stable control variable;

[0021] The first sliding surface includes: the first sliding surface formula:

[0022] The first sliding surface formula includes:

[0023] s1=k1e+m1;

[0024] Wherein, s1 represents the first sliding surface, and k1 represents a constant greater than zero.

[0025] According to the design method of the gas turbine controller provided by the embodiment of the present application, the subsystem further includes: a second-order system and a third-order system, and the system stability control quantity further includes: a second stability control quantity and a third stability control quantity;

[0026] Setting a system stability control variable for each subsystem, and determining that the system stability control variables all meet preset stability conditions, determining that the controller design in the control system is complete, including:

[0027] Setting a second stabilizing control variable for the second-order system and setting a third stabilizing control variable for the third-order system;

[0028] setting a second sliding surface when it is determined that the second stable control variable and the difference satisfy a second stable condition, and the third stable control variable and the difference satisfy a third stable condition;

[0029] Based on the second sliding surface, the second stability condition and the third stability condition, the designed control system tends to be stable.

[0030] According to the design method of the gas turbine controller provided by the embodiment of the present application, the second stability condition includes: a second stability formula, and the third stability condition includes: a third stability formula:

[0031] Among them, the second stable formula includes:

[0032]

[0033] Wherein, m2 represents the second stable control variable, c2 represents the second convergence adjustment coefficient, which is a constant greater than zero, and e represents the difference between the desired speed and the target speed;

[0034] Among them, the third stable formula includes:

[0035] e (3) =m3-c3e;

[0036] Wherein, m3 represents the third stable control variable, c3 represents the third convergence adjustment coefficient, and is a constant greater than zero;

[0037] The second sliding surface includes: a second sliding formula;

[0038] The second sliding mode formula includes:

[0039] s2=k1e+m3+m2+m1;

[0040] Wherein, s2 represents the second sliding surface, k1 represents a constant greater than zero, and m1 represents the first stable control variable.

[0041] According to the gas turbine controller design method provided in an embodiment of the present application, determining that the controller design in the control system is complete includes:

[0042] Design backstepping sliding mode control formula;

[0043] Among them, the backstepping sliding mode control formula includes:

[0044] u=u m +u d ;

[0045] Where, u represents the target fuel quantity, u m represents the main control rate, u d represents the compensation control rate;

[0046] in,

[0047] Among them, g n =a 12 a 22 a 32 a 42 , k2 is a constant, m1 represents the first stable control quantity, c1 represents the first convergence adjustment coefficient, which is a constant greater than zero, and e represents the difference between the expected speed and the target speed. represents the fourth-order derivative of the expected value of the speed, represents the third-order derivative of the expected value of the speed, represents the second-order derivative of the expected value of the speed, γ1 is a constant greater than zero, s2 represents the second sliding surface, z=[z1z2z3z4] T , M1=-a 41 a 31 a 21 a 11 , M2=a 31 a 11 (a 21 +a 41 )+a 41 a 21 (a 11 +a 31 ), M3=-(a 11 +a 21 )(a 31 +a 41 )-a 11 a21 -a 31 a 41 , M4=a 11 +a 21 +a 31 +a 41 , T=-a 41 a 31 a 21 a 13 +a 12 a 22 a 32 a 43 , z1=x1, x1 represents the turbine speed, a ij are all constants;

[0048] Among them, y d =(g n z1) -1 [k3(s2+σsgn(s2))];

[0049] Among them, k3 is a constant and σ is a constant.

[0050] According to the gas turbine controller design method provided in an embodiment of the present application, determining that the controller design in the control system is complete includes:

[0051] Establishing a nonlinear disturbance observer and obtaining a disturbance estimate obtained by the nonlinear disturbance observer;

[0052] Calculate the observation error between the estimated value of the disturbance and the actual value of the disturbance;

[0053] An observer gain corresponding to the observation error is determined, and a sliding mode active disturbance rejection control variable is back-calculated based on the observer gain and the disturbance estimation value to obtain a final controller.

[0054] According to the design method of the gas turbine controller provided by the embodiment of the present application, the nonlinear disturbance observer includes: a nonlinear disturbance observation formula;

[0055] Among them, the nonlinear perturbation observation formula includes:

[0056]

[0057] Where w represents the observer state variable, Represents the disturbance estimate, L represents the observer gain, which is greater than zero;

[0058] The optimized backstepping sliding mode control formula includes:

[0059]

[0060] An embodiment of the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method for designing a gas turbine controller as described in any one of the above items are implemented.

[0061] An embodiment of the present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for designing a controller of a gas turbine as described in any one of the above items are implemented.

[0062] The gas turbine controller design method, device and medium provided in the embodiments of the present application are constructed by constructing a mathematical model of the control system of the micro gas turbine, the mathematical model being constructed based on the target fuel quantity, turbine speed, turbine gas flow, combustion chamber fuel flow, fuel valve opening and the aerodynamic thermodynamic characteristics of the gas turbine; determining the model dimension based on the mathematical model, and performing dimensionality reduction processing on the control system based on the model dimension to obtain multiple subsystems. The present application takes into account the aerodynamic thermodynamic characteristics of the gas turbine (i.e., the nonlinear strong coupling of the gas turbine itself, efficiency degradation caused by long-term operation and parameter perturbation) to design the control system in a hierarchical manner; and setting a system stability control variable for each subsystem. When it is determined that the system stability control variables have all met the preset stability conditions, the controller design in the control system is determined to be complete. The present application performs stability design on each subsystem to ensure the stability of the resulting controller, thereby enabling the designed controller to quickly track the output data of the gas turbine and achieve a control effect of fast response and high-precision control. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0064] Figure 1 This is a schematic diagram of the operation of an existing gas turbine provided in an embodiment of the present application;

[0065] Figure 2 1 is a flow chart of a method for designing a gas turbine controller provided in an embodiment of the present application;

[0066] Figure 3 is a schematic diagram of a design of a controller based on a system model provided in an embodiment of the present application;

[0067] Figure 41 is a schematic diagram of a turbine speed output curve of reverse-stepping sliding mode active disturbance rejection speed control and PID control when the gas turbine load decreases, as provided in an embodiment of the present application;

[0068] Figure 5 1 is a schematic diagram of a turbine speed output curve of reverse sliding mode active disturbance rejection speed control and PID control when the gas turbine load increases, as provided in an embodiment of the present application;

[0069] Figure 6 1 is a schematic diagram of a fuel control output curve of a reverse sliding mode active disturbance rejection speed control and a PID control when the gas turbine load decreases, as provided in an embodiment of the present application;

[0070] Figure 7 1 is a schematic diagram of a fuel control output curve of a reverse sliding mode active disturbance rejection speed control and a PID control when the gas turbine load increases, as provided in an embodiment of the present application;

[0071] Figure 8 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0072] To make the purpose, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0073] The embodiment of the present application provides a method for designing a controller for a gas turbine. The method can be applied to a smart terminal, a server, or a control system of a gas turbine. The present application uses the method applied to a server as an example to illustrate the method, and some other descriptions in the embodiment are for illustrative purposes only and are not intended to limit the scope of protection of the present application, so they will not be described one by one. The specific implementation of the method is as follows: Figure 2 As shown:

[0074] Step 201: construct a mathematical model of a control system of a micro gas turbine.

[0075] The mathematical model is constructed based on the target fuel quantity, turbine speed, turbine gas flow, combustion chamber fuel flow, fuel valve opening and aerodynamic thermodynamic characteristics of the fuel turbine.

[0076] The mathematical model also involves other parameters in the control system, such as turbine rotor moment of inertia and load torque, etc.

[0077] Among them, the aerodynamic thermodynamic characteristics of gas turbines include: inherent nonlinear strong coupling, efficiency degradation caused by long-term operation, and parameter perturbations.

[0078] Step 202 : determining a model dimension based on the mathematical model, and performing dimensionality reduction processing on the control system based on the model dimension to obtain a plurality of subsystems.

[0079] Among them, the subsystems include: first-order system, second-order system and third-order system.

[0080] Step 203 : setting a system stability control variable for each subsystem, and determining that the controller design in the control system is completed when it is determined that the system stability control variables all meet the preset stability conditions.

[0081] Among them, different subsystems correspond to different system stability control quantities, and different system stability control quantities correspond to different stability conditions.

[0082] The system stability control quantity includes: a first stability control quantity, a second stability control quantity and a third stability control quantity. The first stability control quantity corresponds to a first-order system, the second stability control quantity corresponds to a second-order system, and the third stability control quantity corresponds to a third-order system.

[0083] Specifically, the present application considers the characteristics of the gas turbine in both the process of creating the mathematical model and designing the controller. Steps 202 and 203 correspond to the controller design process.

[0084] The gas turbine controller design method provided in the embodiment of the present application is obtained by constructing a mathematical model of the control system of the micro gas turbine, the mathematical model being constructed based on the target fuel quantity, turbine speed, turbine gas flow, combustion chamber fuel flow, fuel valve opening and aerodynamic thermodynamic characteristics of the gas turbine; determining the model dimension based on the mathematical model, and performing dimensionality reduction processing on the control system based on the model dimension to obtain multiple subsystems. The present application takes into account the aerodynamic thermodynamic characteristics of the gas turbine (i.e., the nonlinear strong coupling of the gas turbine itself, efficiency degradation caused by long-term operation, and parameter perturbation) to design the control system in a hierarchical manner; and setting a system stability control variable for each subsystem. When it is determined that the system stability control variables have all met the preset stability conditions, the controller design in the control system is determined to be complete. The present application performs stability design on each subsystem to ensure the stability of the resulting controller, thereby enabling the designed controller to quickly track the output data of the gas turbine and achieve a control effect of fast response and high-precision control.

[0085] Specifically, according to the operating principle of a micro gas turbine, the startup process typically utilizes a starter motor or high-pressure gas to drive the compressor components. At this point, the combustion engine is in an unstable transient state, which is not discussed in this invention. After the gas turbine enters the slow-running mode or above, it enters the Brayton cycle. The air is filtered and compressed by the compressor. The compressed, high-pressure air enters the combustion chamber and mixes with the fuel to burn. The resulting high-temperature, high-pressure gas drives the turbine to produce work. Simultaneously, the rotation of the turbine drives the compressor to rotate, achieving internal balance within the gas turbine. The high-temperature flue gas removed is passed through a regenerator to heat the inlet air, improving the efficiency of the micro gas turbine.

[0086] Specifically, the fuel control command (corresponding to the target fuel quantity) is used as the input quantity, and the turbine speed, turbine gas flow, combustion chamber fuel quantity, and fuel valve opening are used as state quantities. Normalization is performed based on the rated value, and the system state equation is constructed based on the aerodynamic thermodynamic characteristics of the gas turbine (this process ignores the gas exhaust loss and the interaction with the structural components), as shown in formula (1):

[0087]

[0088] Where J represents the turbine rotor moment of inertia, T0 represents the load torque, x1 represents the turbine speed, x2 represents the turbine gas flow rate, and T d represents the time constant of gas flowing through the turbine, x3 represents the amount of fuel in the combustion chamber, T a represents the fuel transport time constant, k a represents the fuel system gain, x4 represents the fuel valve opening, θ1 represents the first fuel valve constant, θ2 represents the second fuel valve constant, k f represents the fuel coefficient, u represents the fuel control command (corresponding to the target fuel quantity), θ3 represents the third fuel valve constant, k l Indicates the turbine load constant.

[0089] in, represents the first-order derivative of x1, represents the first-order derivative of x2, represents the first derivative of x3, represents the first derivative of x4.

[0090] For the convenience of description, the coefficients of each parameter in formula (1) are simplified to corresponding symbols to obtain formula (2):

[0091]

[0092] in,

[0093] In order to simplify the model, coordinate transformation is performed, and z1=x1 is set to obtain formula (3):

[0094]

[0095] make We get formula (4):

[0096]

[0097] By analogy, let We get formula (5):

[0098]

[0099] Where, define M1 = -a 41 a 31 a 21 a 11 , M2=a 31 a 11 (a 21 +a 41 )+a 41 a 21 (a 11 +a 31 ), M3=-(a 11 +a 21 )(a 31 +a 41 )-a 11 a 21 -a 31 a 41 , M4=a 11 +a 21 +a 31 +a 41 , g n =a 12 a 22 a 32 a 42 , T=-a 41 a 31 a 21 a 13 +a 12 a 22 a 32 a 43 .

[0100] Among them, formula (5) corresponds to the mathematical model of the control system.

[0101] Specifically, when the gas turbine is running, there are external disturbances and efficiency attenuation, which lead to certain perturbations in the system characteristic parameters. Based on this, the system state equation containing uncertain terms is obtained, as shown in formula (6):

[0102]

[0103] Among them, ΔM i and Δg n Represent the existing modeling parameter perturbations and external disturbances respectively. Rewrite the system state equation (6) into (7):

[0104]

[0105] in, Represents the total uncertainty of the system.

[0106] Based on the gas turbine characteristics, the total uncertainty term n of the system satisfies the first assumption. The first assumption is that the uncertainty term n is bounded and its derivative is also bounded, that is, there are constants γ1>0 and γ2>0, so that the uncertainty term satisfies:

[0107] |n|≤γ1 and

[0108] This application first designs a sliding mode function using a hierarchical backstepping control approach, employs multi-level virtual control to achieve precise speed tracking, and utilizes a disturbance observer to estimate and compensate for modeling errors, parameter perturbations, and external disturbances in real time. The controller is robust to gas turbine uncertainties, has low reliance on model accuracy, and accurately captures gas turbine status and performs fuel control.

[0109] In order to achieve the above purpose, the design scheme of the controller using reverse slip auto-disturbance rejection speed control is described in detail below:

[0110] In a specific embodiment, the subsystem includes: a first-order system, and the system stability control variable includes: a first stability control variable.

[0111] The system stability control quantity is set for each subsystem. When it is determined that the system stability control quantity has reached the preset stability condition, the specific implementation of the controller design in the control system is determined to be completed, including:

[0112] A first stabilizing control variable is set for the first-order system; a desired speed value is set, and the difference between the desired speed value and the target speed is calculated; when it is determined that the first stabilizing control variable and the difference satisfy a first stabilizing condition, a first sliding surface is set; based on the first stabilizing condition and the first sliding surface, a control system is designed to be stable.

[0113] In a specific embodiment, based on the system state equation of the gas turbine, the expected speed value is given and the tracking error is calculated, as shown in formula (8):

[0114] e=z d -z1……(8)

[0115] Where, e represents the difference between the expected speed and the target speed, z drepresents the expected speed value, and z1 represents the target speed.

[0116] Taking the derivative of formula (8), we get formula (9):

[0117]

[0118] In order to achieve the speed control target, the energy function is designed according to the Lyapunov stability theory, see formula (10):

[0119]

[0120] Wherein, V1 represents the energy value.

[0121] Set the first stable control quantity and satisfy formula (11):

[0122]

[0123] Wherein, m1 represents the first stable control variable, c1 represents the first convergence adjustment coefficient, and is a constant greater than zero.

[0124] Formula (12) is obtained by formula (11):

[0125]

[0126] The first stable formula is obtained by formula (10) and formula (12), see formula (13):

[0127]

[0128] Furthermore, based on the first stability formula, in order to improve the robustness of the controller, the first sliding surface (corresponding to the first sliding surface formula) is designed, see formula (14):

[0129] s1=k1e+m1……………………(14)

[0130] Wherein, s1 represents the first sliding surface, and k1 represents a constant greater than zero.

[0131] Among them, k1 is used to improve the convergence speed of the tracking error (difference e).

[0132] Among them, if t→∞, s1→0, then e→0 and m1→0, that is, The system eventually stabilizes.

[0133] Among them, the present application performs real-time control based on the operation of the gas turbine, and each dynamic parameter includes a parameter value corresponding to each moment, and t represents the moment.

[0134] In a specific embodiment, the subsystem further includes: a second-order system and a third-order system, and the system stability control quantity further includes: a second stability control quantity and a third stability control quantity.

[0135] The system stability control quantity is set for each subsystem. When it is determined that the system stability control quantity has reached the preset stability condition, the specific implementation of the controller design in the control system is determined to be completed, including:

[0136] A second stable control variable is set for the second-order system, and a third stable control variable is set for the third-order system; a second sliding surface is set when it is determined that the second stable control variable and the difference satisfy the second stable condition, and the third stable control variable and the difference satisfy the third stable condition; based on the second sliding surface, the second stable condition and the third stable condition, the control system is designed to be stable.

[0137] Specifically, in order to obtain the actual control input, the second stable control quantity is set and the second stable formula is satisfied, see formula (15):

[0138]

[0139] Among them, m2 represents the second stable control quantity, c2 represents the second convergence adjustment coefficient, which is a constant greater than zero. represents the second-order derivative.

[0140] Similarly, the third stable control quantity is set and the third stable formula is satisfied, see formula (16):

[0141]

[0142] Among them, m3 represents the third stable control quantity, c3 represents the third convergence adjustment coefficient, which is a constant greater than zero, and e (3) represents the third-order derivative.

[0143] And design the second sliding surface (corresponding to the second sliding formula), see formula (17):

[0144] s2=k1e+m3+m2+m1…………(17)

[0145] Wherein, s2 represents the second sliding surface, k1 represents a constant greater than zero, and m1 represents the first stable control variable.

[0146] Taking the first-order derivative of formula (17), we get formula (18):

[0147]

[0148] Among them, k2=k1+c1+c2+c3.

[0149] Reconstruct the Lyapunov function, see formula (19):

[0150]

[0151] Among them, V2 is used to characterize the stability of the control system.

[0152] Taking the first-order derivative of formula (19), we get formula (20):

[0153]

[0154] in, z=[z1z2z3z4] T .

[0155] In a specific embodiment, a backstepping sliding mode control formula is designed. The backstepping sliding mode control formula (corresponding to a controller) represents that the controller design of the control system is complete.

[0156] The backstepping sliding mode control formula is shown in formula (21):

[0157] u=u m +u d …………………………(twenty one)

[0158] Where u represents the control rate (equivalent to the fuel control command), u m represents the main control rate, u d Indicates the compensation control rate.

[0159] in, u d =(g n z1) -1 [k3(s2+σsgn(s2))].

[0160] Here, sgn(.) represents the sign function.

[0161] Among them, k3 and σ are both positive constants, which are used to improve the system robustness and tracking error convergence speed.

[0162] Furthermore, formula (21) must satisfy formula (22):

[0163]

[0164] Among them, selecting appropriate values ​​of c1, k3 and σ can ensure the stability of the backstepping sliding mode controller.

[0165] Specifically, substituting the control rate u into the Lyapunov function, we get formula (23):

[0166]

[0167]

[0168] According to the first assumption, γ1≥|n·sgn(s2)|, and γ1+n·sgn(s2)≥0.

[0169] Assumption Matrix v=[e m1] T , thus we get formula (24):

[0170]

[0171] And we get formula (25):

[0172]

[0173] If G is a positive definite matrix, let That is, we can get formula (22).

[0174] While the above process utilizes the upper bound of the uncertainty term to control disturbances, improving the robustness of the controller and being simple and reliable, in real-world conditions, due to system modeling errors and external disturbances, the upper bound estimate of the uncertainty term is often inaccurate, and a large margin can affect control accuracy. To further improve system control performance, a disturbance observer is established to estimate the uncertainty term.

[0175] In a specific embodiment, determining that the controller design in the control system is complete includes:

[0176] A nonlinear disturbance observer is established to obtain the disturbance estimate obtained by the nonlinear disturbance observer; the observation error between the disturbance estimate and the actual disturbance value is calculated; the observer gain corresponding to the observation error is determined, and the sliding mode active disturbance rejection control quantity is back-calculated based on the observer gain and the disturbance estimate to obtain the final controller.

[0177] In a specific embodiment, the nonlinear disturbance observer includes: a nonlinear disturbance observation formula.

[0178] The nonlinear perturbation observation formula is shown in formula (26):

[0179]

[0180] Where w represents the observer state variable, Represents the disturbance estimate (the estimated value of the uncertain term), L represents the observer gain, which is greater than zero.

[0181] Calculating observation errors We can get formula (27):

[0182]

[0183] Solve equation (27) to obtain equation (28):

[0184]

[0185] By determining the appropriate observer gain, the observation error converges. At this time, the disturbance estimate is substituted into formula (21) to obtain the final controller, see formula (29):

[0186]

[0187] Then, the Lyapunov function is used to prove that the self-disturbance rejection rate (control rate) of the backstepping sliding mode control obtained above makes the gas turbine stable.

[0188] Substituting the backstepping sliding mode control active disturbance rejection rate into the Lyapunov function, we get formula (30):

[0189]

[0190] Since the perturbation estimate converges exponentially, and the definitions of c1, k3, and σ, we know that when t→∞, there exists This proves that the backstepping sliding mode active disturbance rejection controller is stable.

[0191] Specifically, through Figure 3 Please describe this application in detail:

[0192] The system model includes: a back-stepping sliding mode controller (controller) and a gas turbine model. The back-stepping sliding mode controller is used to control the gas turbine.

[0193] Based on the speed sensor (corresponding Figure 3 Speed ​​in), flow sensor (corresponding to Figure 3 flow) and position sensors (corresponding to Figure 3 The position in the gas turbine model is obtained from x i ,i=1,2,3,4. i The equation created (Formula 1) is transformed into coordinates to obtain the value obtained by z i , i=1,2,3,4 is represented by equation (Formula 6). Calculate the expected speed value and the target speed, get the difference, and design a disturbance observer based on the disturbance estimate, difference and z output by the disturbance observer. i Design the controller and obtain the final controller.

[0194] Among them, the uncertainty term n needs to be considered when designing the gas turbine model.

[0195] In order to verify the stability and effectiveness of the controller designed in this application, the model is normalized. Under ISO conditions, the main parameters of the gas turbine are shown in Table 1:

[0196]

[0197]

[0198] Table 1 Main parameters of gas turbine

[0199] Under steady-state operation, the initial turbine speed is the rated value. At 20 seconds, the speed suddenly drops from the 0.85 working condition to the 0.65 working condition, and the load suddenly increases from the 0.7 working condition to the 0.95 working condition. The external speed disturbance n(t) = 0.05sin 2πt is superimposed to compare the effects of the backstepping sliding mode active disturbance rejection control (controller control designed in this application) and the conventional PID control.

[0200] from Figure 4 and Figure 5 It can be seen that both conventional PID control and observer-based active disturbance rejection sliding mode control can track the set speed during sudden operating conditions. However, when the operating conditions suddenly decrease, the back-stepping sliding mode active disturbance rejection control reduces the maximum overshoot by approximately 50.7% compared to PID control, and shortens the time to reach steady state (±0.5% of the target value) by approximately 16.1%. When the operating conditions suddenly increase, the sliding mode control algorithm reduces the maximum overshoot by approximately 41.5% and shortens the steady state time by 21.4% compared to PID control. Furthermore, during steady-state control, the back-stepping sliding mode active disturbance rejection control achieves better disturbance compensation.

[0201] In summary, the backstepping sliding mode active disturbance rejection control can better realize the rapid switching of micro gas turbines under different operating conditions. Compared with the traditional PID control method, it has obvious improvements in dynamic response and overshoot control, and has stronger robustness and stability.

[0202] and through Figure 6 and Figure 7 A comparison is made between the backstepping sliding mode auto-disturbance rejection speed control (the control method of the designed controller) and the PID control.

[0203] Table 2 shows the comparison of the speed control effects of the backstepping sliding mode active disturbance rejection control and PID control when the gas turbine load changes.

[0204]

[0205] Table 2 Speed ​​control effect comparison table

[0206] In the controller design process, this application uses the fuel control command as the input; the turbine speed, turbine gas flow, combustion chamber fuel flow, and fuel valve opening, a total of four state quantities, to construct the state equation of the micro single-shaft gas turbine control system. The controller is designed based on the backstepping sliding mode control theory, using the micro gas turbine turbine speed as the control target value, and a multi-level (multi-order) virtual controller is designed to achieve precise speed tracking. At the same time, a nonlinear disturbance observer is designed to estimate and compensate for uncertain disturbances, and the fuel control quantity is adjusted in the presence of gas turbine modeling errors, parameter perturbations, and external interference.

[0207] The controller of this application has fast dynamic response, small overshoot, strong robustness to engine modeling errors, parameter perturbations, and external disturbances, low dependence on model accuracy, and can accurately obtain the state of the gas turbine and perform fuel control. This controller has low dependence on model accuracy and can accurately obtain the state of the micro gas turbine and control it in the presence of modeling errors, parameter perturbations, and external disturbances.

[0208] Compared with traditional PID control, the reverse-thrust sliding-mode anti-disturbance speed control of the micro single-shaft gas turbine designed in this application has a strong dependence on model accuracy and is easily affected by external interference, which reduces the control accuracy. However, when the micro gas turbine changes operating conditions, this application can quickly track the actual speed output, has a control effect with fast response speed and high control accuracy, and has smaller overshoot and faster convergence in the presence of modeling errors, parameter perturbations and external interferences.

[0209] Figure 8 An example of a physical structure diagram of an electronic device is shown below. Figure 8 As shown, the electronic device may include: a processor 801, a communications interface 802, a memory 803, and a communication bus 804. The processor 801, the communications interface 802, and the memory 803 communicate with each other via the communication bus 804. The processor 801 may call logic instructions in the memory 803 to execute the method for designing a gas turbine controller.

[0210] In addition, the logic instructions in the above-mentioned memory 803 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program code.

[0211] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the design method of the gas turbine controller provided by the above methods.

[0212] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to perform the design method of the gas turbine controller provided by the above embodiments.

[0213] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0214] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0215] Finally, it should be noted that the above description is merely a preferred embodiment of the present application and the present application is not limited to the above embodiments. It is understood that other improvements and variations directly derived or conceived by those skilled in the art without departing from the spirit and concept of the present application should be considered to be included within the scope of protection of the present application.

Claims

1. A method for designing a gas turbine controller, characterized in that: The method comprises: Constructing a mathematical model of a control system for a micro gas turbine, wherein the mathematical model is constructed based on a target fuel quantity, a turbine speed, a turbine gas flow rate, a combustion chamber fuel flow rate, a fuel valve opening, and aerodynamic thermodynamic characteristics of the fuel turbine; Determining a model dimension based on the mathematical model, and performing dimensionality reduction processing on the control system based on the model dimension to obtain a plurality of subsystems; Setting a system stability control variable for each subsystem, and determining that the controller design in the control system is completed when it is determined that the system stability control variables all meet preset stability conditions; Among them, different subsystems correspond to different system stability control quantities, and different system stability control quantities correspond to different stability conditions.

2. The method for designing a gas turbine controller according to claim 1, wherein: The subsystem includes: a first-order system, and the system stability control quantity includes: a first stability control quantity; Setting a system stability control variable for each subsystem, and determining that the system stability control variables all meet preset stability conditions, determining that the controller design in the control system is complete, including: Setting a first stabilizing control variable for the first-order system; Setting a desired speed value, and calculating a difference between the desired speed value and a target speed; When it is determined that the first stable control variable and the difference satisfy a first stable condition, setting a first sliding surface; Based on the first stability condition and the first sliding surface, the designed control system tends to be stable.

3. The method for designing a gas turbine controller according to claim 2, wherein: The first stability condition includes: a first stability formula; Among them, the first stable formula includes: in, e represents the difference between the expected speed and the target speed, c1 represents the first convergence adjustment coefficient, which is a constant greater than zero, and m1 represents the first stable control variable; The first sliding surface includes: the first sliding surface formula: The first sliding surface formula includes: s1=k1e+m1; Wherein, s1 represents the first sliding surface, and k1 represents a constant greater than zero.

4. The method for designing a gas turbine controller according to claim 2, wherein: The subsystem further comprises: a second-order system and a third-order system, and the system stability control quantity further comprises: a second stability control quantity and a third stability control quantity; Setting a system stability control variable for each subsystem, and determining that the system stability control variables all meet preset stability conditions, determining that the controller design in the control system is complete, including: Setting a second stabilizing control variable for the second-order system and setting a third stabilizing control variable for the third-order system; setting a second sliding surface when it is determined that the second stable control variable and the difference satisfy a second stable condition, and the third stable control variable and the difference satisfy a third stable condition; Based on the second sliding surface, the second stability condition and the third stability condition, the designed control system tends to be stable.

5. The method for designing a gas turbine controller according to claim 4, wherein: The second stability condition includes: a second stability formula, and the third stability condition includes: a third stability formula: Among them, the second stable formula includes: Wherein, m2 represents the second stable control variable, c2 represents the second convergence adjustment coefficient, which is a constant greater than zero, and e represents the difference between the desired speed and the target speed; Among them, the third stable formula includes: <h2 style=";text-align:left;direction:ltr">e<h2 style=";text-align:left;direction:ltr"> (3) <h2 style=";text-align:left;direction:ltr"> =m3-c3e; Wherein, m3 represents the third stable control variable, c3 represents the third convergence adjustment coefficient, and is a constant greater than zero; The second sliding surface includes: a second sliding formula; The second sliding mode formula includes: s2=k1e+m3+m2+m1; Wherein, s2 represents the second sliding surface, k1 represents a constant greater than zero, and m1 represents the first stable control variable.

6. The method for designing a gas turbine controller according to any one of claims 1 to 5, characterized in that: Verify that the controller design in the control system is complete, including: Design backstepping sliding mode control formula; Among them, the backstepping sliding mode control formula includes: in=in m +in d ; Where, u represents the target fuel quantity, u m represents the main control rate, u d represents the compensation control rate; in, Among them, g n =a 12 a 22 a 32 a 42 , k2 is a constant, m1 represents the first stable control quantity, c1 represents the first convergence adjustment coefficient, which is a constant greater than zero, and e represents the difference between the expected speed and the target speed. represents the fourth-order derivative of the expected value of the speed, represents the third-order derivative of the expected value of the speed, represents the second-order derivative of the expected value of the speed, γ1 is a constant greater than zero, s2 represents the second sliding surface, z=[z1z2z3z4] T , M1=-a 41 a 31 a 21 a 11 , M2=a 31 a 11 (a 21 +a 41 )+a 41 a 21 (a 11 +a 31 ), M3=-(a 11 +a 21 )(a 31 +a 41 )-a 11 a 21 -a 31 a 41 , M4=a 11 +a 21 +a 31 +a 41 , T=-a 41 a 31 a 21 a 13 +a 12 a 22 a 32 a 43 , z1=x1, x1 represents the turbine speed, a ij are all constants; Among them, u d =(g n z1) -1 [k3(s2+σsgn(s2))]; Among them, k3 is a constant and σ is a constant.

7. The method for designing a gas turbine controller according to claim 6, wherein: Verify that the controller design in the control system is complete, including: Establishing a nonlinear disturbance observer and obtaining a disturbance estimate obtained by the nonlinear disturbance observer; Calculate the observation error between the estimated value of the disturbance and the actual value of the disturbance; An observer gain corresponding to the observation error is determined, and a sliding mode active disturbance rejection control variable is back-calculated based on the observer gain and the disturbance estimation value to obtain a final controller.

8. The method for designing a gas turbine controller according to claim 7, wherein: The nonlinear disturbance observer includes: a nonlinear disturbance observation formula; Among them, the nonlinear perturbation observation formula includes: Where w represents the observer state variable, Represents the disturbance estimate, L represents the observer gain, which is greater than zero; The optimized backstepping sliding mode control formula includes:

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for designing a gas turbine controller according to any one of claims 1 to 8 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program implements the steps of the method for designing a controller of a gas turbine according to any one of claims 1 to 8.

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