High-altitude cabin air inlet pressure system cascade self-disturbance control method

Abstract

The application relates to a high-altitude cabin air intake pressure system cascade active disturbance rejection control method with enhanced time delay compensation and a novel nonlinear extended state observer. The method comprises the following steps: equivalent of a high-altitude cabin air intake pressure system model to a position inner loop model and a pressure outer loop model, and establishment of a position inner loop model with a time delay link and a pressure outer loop model with disturbance; for the position loop model with time delay, a self-disturbance rejection control with time delay compensation is designed; for strong measurement noise existing in the air intake pressure system, an enhanced discrete optimal control algorithm-based tracking differentiator is used to obtain accurate differential signals, and an enhanced time delay compensator is designed; for strong flow disturbance in the pressure outer loop, a nonlinear ESO is designed based on a new error feedback gain function; finally, the time delay and strong disturbance problems existing in the high-altitude cabin air intake pressure system cascade active disturbance rejection control processing system with enhanced time delay compensation and the novel nonlinear extended state observer are solved, and the air intake pressure control performance is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of high-altitude cabin intake pressure system control, and particularly relates to a high-altitude cabin intake pressure system cascade self-disturbance control method. BACKGROUND

[0002] An aero-engine high-altitude simulation test stand (referred to as a high-altitude cabin) is a large test device for simulating an engine working environment on the ground and obtaining high-altitude performance of the engine, and is an essential link for independently developing an advanced aero-engine. Main constituent systems of the high-altitude cabin include: a gas source system, an intake and exhaust system, and a gas extraction system. Among them, the intake pressure system is an important constituent part of the high-altitude cabin, and provides stable gas source requirements for aero-engine high-altitude flight speed simulation. Therefore, control performance of the intake pressure system will directly affect the effectiveness of aero-engine function and performance evaluation.

[0003] The high-altitude cabin intake pressure system has complex structure and composition, and has significant characteristics such as high nonlinearity, strong uncertainty, and numerous unknown disturbances. In addition, since the control of the intake pressure system is realized by adjusting the gas flow through a large hydraulic servo system, and due to the pre-compression of the intermediate position spring in the regulating valve and the friction characteristics of the piston in the hydraulic cylinder, the output signal contains a pure time delay link. At the same time, there is strong measurement noise in the harsh aero-engine test environment. The above factors make it extremely challenging to precisely control the intake pressure system.

[0004] Because of its simple structure and low cost, the traditional PID or PI control is the most common control method for the high altitude chamber intake pressure system. Considering the strong air flow disturbance, time delay of servo system and measurement noise in the actual control of intake pressure system, the above control strategy with PID control as the core is obviously difficult to meet the control requirements of faster response, strong anti-disturbance and high precision in modern advanced aero-engine test intake pressure system. In recent years, active disturbance rejection control (ADRC) as an effective active anti-disturbance control technology not only has strong anti-disturbance ability, but also inherits many advantages of PID control such as: not relying on the model and simple structure. By using the idea of state observation, the system internal and external disturbances affecting the control performance are attributed to the total disturbance, and the total disturbance is expanded as a new system state variable. Through the core disturbance observation part of ADRC, the extended state observer (ESO) is used to observe the total disturbance in real time and compensate the disturbance influence through feedforward. Considering the practicability of ESO and meeting the separation design principle, ESO is usually proposed separately and combined with mature negative feedback controller to form a composite control strategy based on ESO. Especially, the proportional derivative (PD) control based on linear ESO, namely linear ADRC control strategy, as a two-degree-of-freedom control, not only retains the simple control structure, but also has the characteristics of strong anti-disturbance, easy parameter tuning and not relying on accurate mathematical model, etc. Therefore, it is successfully applied to the high altitude chamber intake pressure system.

[0005] Documents (Qian Qi, But Zhihong, Zhang Song, et al. Linear active disturbance rejection control method for aero-engine transition state test inlet pressure [J]. Journal of Aerospace Power, 2019, 34(10): 2271-2279.) and documents (But Zhihong, Zhang Song, Bai Keqiang, et al. High-altitude test inlet pressure environment simulation control technology based on extended state observer [J]. Propulsion Technology, 2021, 42(09): 2119-2128.) successfully apply traditional linear active disturbance rejection control technology to the inlet pressure system, improving the stability and anti-interference ability of the inlet pressure system. Documents (Zhang Song, Bai Keqiang, But Zhihong, et al. Research progress of high-altitude test engine inlet pressure control based on ESO [J]. Science and Technology Review, 2021, 39(11): 109-117.) compare and summarize the performance of basic active disturbance rejection control and other control methods. In order to further improve the control performance of the high-altitude chamber inlet pressure system, documents (But Zhihong, Zhang Song, Zhang and Hong, et al. High-altitude chamber flight altitude simulation cascade LADRC robust control technology. Journal of Aerospace Power, 2023, 1-9) establish the model of the high-altitude chamber inlet pressure system as two first-order typical inertia systems, equivalent to a double-loop control loop. Specifically, it includes the inner loop of the position of the regulating valve and the outer loop of the pressure, and applies traditional linear active disturbance rejection control to the two loops. However, compared with the single-loop PID control or single-loop active disturbance rejection control mentioned above, the cascade control method based on linear active disturbance rejection control improves the inlet pressure control performance. When studying the output signal time delay problem of the large hydraulic valve in the position inner loop and the large and fast air flow disturbance in the pressure outer loop, the cascade control method based on linear active disturbance rejection control is difficult to handle the existing time delay and strong disturbance, and cannot greatly improve the system control performance.

[0006] Problems in the prior art:

[0007] (1) In the high-altitude chamber inlet pressure system, the output signal of the regulating valve position inner loop has a time delay, which will increase the observation error of the extended state observer in the inner loop active disturbance rejection control, leading to system oscillation or even divergence. Therefore, effective time delay compensation is the key to ensuring the control performance of the position inner loop.

[0008] (2) In the time delay compensation method, Smith predictor is widely used due to its simple structure and easy implementation. The principle of the predictor compensation is to obtain the differential signal of the output signal. However, due to the harsh environment of aero-engine testing, the high-altitude chamber inlet pressure system has random noise in the full frequency band, which makes the system output signal contain strong measurement noise. Therefore, the traditional time delay compensation differential signal acquisition method, such as the subtraction of small inertia elements and inertia elements to obtain the differential signal, is not applicable. In the presence of strong measurement noise, obtaining accurate output signal differential information is the key to designing an effective time delay compensator.

[0009] (3) In the high-altitude cabin intake pressure system pressure outer ring, due to the transient test of the aero-engine, the rapid and severe state change causes the engine intake flow to change greatly and instantaneously, the traditional linear ESO cannot effectively handle it, and a new ESO with stronger observation performance is needed to more accurately estimate the total disturbance of the pressure outer ring in real time, improve the anti-interference performance of the outer ring controller, and obtain accurate pressure control. SUMMARY

[0010] The purpose of the present application is to solve the problems existing in the prior art, and to provide a high-altitude cabin intake pressure system cascade active disturbance rejection control method, which is aimed at the position inner loop time delay and strong disturbance of the pressure outer loop of the high-altitude cabin intake pressure system, and is based on the cascade active disturbance rejection control method of enhanced time delay compensation and new nonlinear ESO.

[0011] To achieve the above-mentioned purpose, the technical scheme of the present application is: a high-altitude cabin intake pressure system cascade active disturbance rejection control method, comprising:

[0012] Step 1, the high-altitude cabin intake pressure system model is equivalent to a position inner loop model and a pressure outer loop model, and a position inner loop model with time delay and a pressure outer loop model with disturbance are established according to the system characteristics, the system transfer function is obtained and converted into a state space equation;

[0013] Step 2, for the time-delayed position inner loop model, an enhanced time-delay compensation link is introduced, and a self-disturbance control with time-delay compensation is designed to ensure the smooth small overshoot tracking performance of the intake pressure system position inner loop;

[0014] Step 3, for the strong measurement noise existing in the intake pressure system, the traditional differentiator cannot obtain accurate differential signals, therefore a tracking differentiator based on enhanced discrete optimal control algorithm, i.e. Fast algorithm, is proposed to obtain accurate differential signals, and an enhanced time-delay compensator is designed based on the differential signals to better compensate the time-delayed output signals and suppress the influence of time delay on the control performance;

[0015] Step 4, for the strong flow disturbance in the pressure outer loop, a new error feedback gain function is designed to design a nonlinear ESO, compared with the feedback gain function characteristics of the traditional ESO, since the function has the characteristics of "greater gain when the error is small, and smaller gain when the error is large", the newly designed nonlinear ESO has more accurate disturbance observation performance. Therefore, the active disturbance rejection control based on the nonlinear ESO improves the anti-disturbance performance of the pressure outer loop; at the same time, the position inner loop active disturbance rejection control with enhanced time delay compensation and the pressure outer loop active disturbance rejection control based on the new nonlinear ESO form a high-altitude cabin intake pressure system cascade active disturbance rejection control with enhanced time delay compensation and new nonlinear extended state observer, which effectively handles the time delay and strong disturbance problems existing in the system and improves the intake pressure control performance.

[0016] In an embodiment of the present application, in step 1, the inner loop model of the position is approximated as a small inertia link, considering the time delay link, and the specific transfer function is as follows:

[0017]

[0018] Wherein, K m is the inner loop proportional gain value, T m is the inner loop time constant, s is the Laplace variable, and τ is the time delay constant; the corresponding differential equation form is:

[0019]

[0020] Wherein, x1, is the inner loop system state quantity, y is the inner loop system output signal, y1 includes the inner loop output signal with time delay τ, t is the current time, and u1 is the control input signal. Wherein, the inner loop proportional gain value K m , the inner loop time constant T m and the accurate value of the time delay constant τ cannot be obtained in most cases, which represents the uncertainty of the parameters; the unmodeled dynamic friction force and the external unknown disturbance d1 are another key problem existing in the valve position inner loop model; the uncertainties, unmodeled dynamics and external unknown disturbances involved are attributed to the total disturbance f1, and formula (3) is obtained:

[0021]

[0022] Wherein, b 01 is the estimated value of the actual control gain b1 of the position inner loop model. d1 is the external disturbance.

[0023] In an embodiment of the present application, in step 1, the high-altitude cabin inlet pressure system model can be equivalent to a single-in and single-out cavity structure in nature, and the inlet pressure differential equation is as follows:

[0024]

[0025] Wherein, P, T, V and R are the gas pressure, gas temperature, gas volume and gas constant in the cavity, respectively; h g is the specific enthalpy of the gas; c p is the specific constant pressure heat capacity of the gas; h in , h out are the specific enthalpy of the inflow gas and the specific enthalpy of the outflow gas, respectively. Wherein, the inflow gas flow W in is the flow characteristic model of the regulating valve, and the simplified equation is as follows:

[0026]

[0027] wherein, a, p1, P in are the equivalent cross-sectional area of the valve, the density of the inflow gas, the flow coefficient of the valve and the inflow gas pressure respectively; the required gas flow of the test aero-engine W out is expressed as:

[0028]

[0029] wherein, W ahs is the converted gas flow of the test aero-engine; η is the fan converted speed of the test aero-engine; thus, formula (4) is rewritten as:

[0030]

[0031] wherein, the outer loop proportional gain

[0032] k=a / u2, u2 is the intake pressure outer loop model control input; the outer loop time constant The intake pressure controlled model is written as:

[0033]

[0034] wherein, x2, is the outer loop system state quantity, y2 is the outer loop system output signal, since there is a Combining formula (2) and (9), and considering the internal and external disturbance factors of the pressure outer loop model, we have:

[0035]

[0036] wherein, is the outer loop system, the total disturbance of the outer loop The actual control gain of the outer loop model d2 is the external disturbance of the pressure outer loop model, b 02 is the estimated value of the actual control gain b2 of the pressure outer loop model.

[0037] In an embodiment of the present application, after the processing of the Smith predictor, the transfer function relationship from the control signal u to the output signal y0 of the Smith predictor is as follows:

[0038]

[0039] wherein, s is the Laplace operator, u(s) is the control input after Laplace transformation. The time domain expression corresponding to formula (10) is: The output signal y0 of the Smith predictor can be obtained from the time delay constant τ, the actual output signal y of the system and the differential information thereof, and thus the problem of time delay compensation is converted into how to reasonably extract continuous signals, i.e. tracking and differential signals, from the discontinuous or output signals with measurement noise in actual engineering.

[0040] In an embodiment of the present application, in the extraction of the differential signal, a small time constant inertial link is used to obtain the differential signal as shown in formula (11) and (12):

[0041]

[0042]

[0043] Wherein, the smaller the time constant T, T1 and T2 of the inertial link, the closer the delay signal y(t-T) to the output signal y(t), and thus the differential signal is closer to the ideal differential signal; however, in the process of obtaining the approximate differential signal using the small time constant inertial link, the smaller the value of T, the more serious the amplification of the external measurement noise in the output signal y(t), and even the differential signal is completely covered. Therefore, a tracking differentiator based on enhanced discrete optimal control algorithm is proposed to obtain the differential signal in the Smith predictor, and the given signal tracked by the tracking differentiator is used to complete the design of the enhanced time delay compensator, so as to obtain better time delay compensation effect; the specific expression of the tracking differentiator based on the enhanced discrete optimal control algorithm is as follows:

[0044]

[0045] Wherein, k is a constant and k = 0, 1, 2, 3…; v0 is the output signal of the tracking differentiator, v1 and v2 are the tracking signal and the differential signal thereof respectively, e0 is the tracking error, h is the sampling period, i.e. the integral step, r0 is the fast factor of the tracking differentiator, h0 is the filter factor of the tracking differentiator, sign is a switching function, t1 and t2 are the time of the initial point reaching the switching curve and the time of the initial point reaching the origin respectively.

[0046] Combined with formula (10) and (13), the compensation signal of the enhanced time delay compensator based on the tracking differentiator is as follows:

[0047]

[0048] Wherein, y0(t) is the compensation signal; v1 and v2 are the tracking signal and the differential signal thereof of the output signal y(t) of the system respectively; is the estimated value of the actual time delay.

[0049] In an embodiment of the present application, based on formula (3) and formula (13)-(14), the time delay compensation ADRC control law algorithm is designed as follows:

[0050] Firstly, a second-order ESO is designed as follows:

[0051]

[0052] Wherein, Z = [z1, z2] T , z1 is the estimated value of the position inner loop model output y1, and the observation value of the total disturbance f1 is defined as z2; the gain values β1 and β2 of the observer are respectively set to 2ω 01 and Wherein ω 01 is the observer bandwidth. Considering that the system output signal can be directly measured by the sensor and in order to better overcome the bandwidth problem of the ESO, the state quantity is selected as the observer output, and a new state quantity is defined as The reduced-order ESO is as follows:

[0053]

[0054] Wherein, the gain value β0 of the reduced-order ESO = ω 01 ; assuming that the appropriate observer bandwidth ω 01 is selected, the reduced-order ESO can accurately observe the total disturbance f1, and the observation error tends to zero; at this time, based on the observation value of the RESO, the negative feedback control law u0 is selected and the controller output quantity u1 is designed as follows:

[0055]

[0056] Wherein, r1 is the system reference value, e1 is the feedback error, K p1 is the inner loop proportional controller gain; combined with formula (14), the time delay compensation ADRC control law algorithm is as follows:

[0057]

[0058] In an embodiment of the present application, for formula (9), a new observation error feedback gain function is introduced to design a new nonlinear ESO as follows:

[0059]

[0060] Wherein, δ1, δ2, δ3 are respectively the estimated value of the pressure loop output y2 and its differential information and the total disturbance f2, γ1, γ2, γ3 are the observer gains, and the parameters α and ξ are respectively the filtering factor and the boundary layer thickness, and the error feedback gain function According to the estimation of the new nonlinear ESO, the controller of the pressure outer loop model is designed as follows:

[0061]

[0062] Wherein, r2 is the outer loop system reference value, e2 is the outer loop feedback error, K p2 is the outer loop proportional controller gain, K d is the outer loop differential controller gain.

[0063] In an embodiment of the application, the working principle of the high-altitude cabin air inlet pressure system cascade control structure is that the outer loop controller feeds back the error between the actual pressure signal measured by the pressure sensor and the set air inlet pressure value, and the signal is converted to be used as the given signal of the inner loop and the actual valve position signal obtained by the position sensor, and the inner loop controller is used to realize the control of the hydraulic servo system, drive the regulating valve to act, change the valve opening degree to realize the gas flow regulation, and finally complete the pressure control of the air inlet pressure system.

[0064] The application further provides a high-altitude cabin air inlet pressure system cascade active disturbance rejection control system, which comprises a memory, a processor and computer program instructions stored in the memory and capable of being executed by the processor, and when the processor executes the computer program instructions, the method steps described above can be realized.

[0065] The application further provides a computer readable storage medium, which stores computer program instructions capable of being executed by a processor, and when the processor executes the computer program instructions, the method steps described above can be realized.

[0066] Compared with the prior art, the application has the following beneficial effects:

[0067] (1) The introduction of the enhanced time delay compensation can effectively avoid the oscillation and divergence of the valve position control caused by the time delay, not only can improve the tracking rapidity and smoothness of the valve position and thus improve the air inlet pressure control performance, but also can ensure the safety and service life of the valve during the aero-engine test.

[0068] (2) Based on the tracking differentiator of the enhanced discrete optimal control algorithm, compared with the traditional inertial link to obtain the differential mode, the noise influence can be effectively filtered to provide a more accurate differential signal, the time delay compensator is designed, a better compensation signal is obtained for the design of the position inner loop active disturbance rejection control, and the control performance of the valve position is improved.

[0069] (3) Design a new nonlinear ESO with the error feedback function of "greater gain for small error, smaller gain for large error", which can more accurately observe the total disturbance of the intake pressure system, so that the anti-disturbance performance of the pressure outer ring based on the new nonlinear ESO is improved. Combined with the position inner ring of the time-delayed active disturbance rejection control, a cascade active disturbance rejection control method is formed to realize high-quality control of the high-altitude cabin intake pressure system. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 A high-altitude cabin intake pressure system cascade control structure for an embodiment of the application;

[0071] Figure 2 An equivalent intake cavity schematic diagram for an embodiment of the application;

[0072] Figure 3 A Smith predictor basic principle for an embodiment of the application;

[0073] Figure 4 A Smith predictor equivalent control block diagram for an embodiment of the application;

[0074] Figure 5 Compensation signals of different differentiators under measurement noise for an embodiment of the application;

[0075] Figure 6 A feedback gain function characteristic curve for an embodiment of the application;

[0076] Figure 7 A high-altitude cabin intake pressure system cascade active disturbance rejection control structure block diagram for an embodiment of the application;

[0077] Figure 8 A position inner ring response curve for an embodiment of the application;

[0078] Figure 9 A position inner ring control signal for an embodiment of the application;

[0079] Figure 10 A pressure outer ring response curve for an embodiment of the application;

[0080] Figure 11 A pressure outer ring control signal for an embodiment of the application;

[0081] Figure 12 A high-altitude cabin intake pressure system cascade active disturbance rejection control flowchart for an embodiment of the application with enhanced time delay compensation and a new nonlinear extended state observer. DETAILED DESCRIPTION

[0082] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0083] like Figure 12 As shown, a cascade active disturbance rejection control method for a high-altitude cabin inlet pressure system includes:

[0084] Step 1: Equivalent the high-altitude cabin intake pressure system model to an inner position model and an outer pressure model. Based on the system characteristics, establish the inner position model with time delay and the outer pressure model with disturbance respectively, obtain the system transfer function and transform it into a state-space equation.

[0085] Step 2: For the position inner loop model with time delay, an enhanced time delay compensation stage is introduced, and an active disturbance rejection control with time delay compensation is designed to ensure the smooth tracking performance of the position inner loop of the intake pressure system with small overshoot.

[0086] Step 3: In response to the strong measurement noise in the intake pressure system, traditional differentiators cannot obtain accurate differential signals. Therefore, a tracking differentiator based on the enhanced discrete optimal control algorithm, namely the Fast algorithm, is proposed to obtain accurate differential signals. Based on this differential signal, an enhanced time delay compensator is designed to better compensate for the output signal with time delay and suppress the impact of time delay on control performance.

[0087] Step 4: To address strong flow disturbances in the outer pressure loop, a nonlinear ESO is designed based on a novel error feedback gain function. Compared to the feedback gain function characteristics of a traditional ESO, this function exhibits a higher gain for smaller errors and a lower gain for larger errors, resulting in more accurate disturbance observation performance for the newly designed nonlinear ESO. Therefore, active disturbance rejection control based on this nonlinear ESO improves the disturbance rejection performance of the outer pressure loop. Simultaneously, combining the position inner loop active disturbance rejection control with enhanced time delay compensation and the pressure outer loop active disturbance rejection control based on the novel nonlinear ESO forms a cascade active disturbance rejection control system for the high-altitude cabin intake pressure system with enhanced time delay compensation and a novel nonlinear extended state observer. This effectively addresses the time delay and strong disturbance problems in the system, improving intake pressure control performance.

[0088] The following is a detailed implementation process of the present invention.

[0089] This invention discloses a cascade active disturbance rejection control method for a high-altitude cabin intake pressure system. For example... Figure 1The basic working principle of the high-altitude cabin intake pressure system cascade control structure is that the outer ring controller feeds back the error between the actual pressure signal measured by the pressure sensor and the set intake pressure value, and the signal is converted to be the given signal of the inner ring and subtracted from the actual valve position signal obtained by the position sensor. The control of the hydraulic servo system is realized by the inner ring controller to drive the regulating valve to act and change the valve opening to regulate the gas flow, and finally complete the pressure control of the intake pressure system. The specific implementation process is as follows:

[0090] Step 1:

[0091] (1) In actual engineering control, the valve position inner loop model is approximated as a small inertia link, considering the time delay link, and the specific transfer function model is as follows:

[0092]

[0093] Where, K m is the inner loop proportional gain value, T m is the inner loop time constant, s is the Laplace variable, and τ is the time delay constant; the corresponding differential equation form is:

[0094]

[0095] Where, x1, is the inner loop system state variable, y is the inner loop system output signal, y1 is the inner loop output signal containing time delay τ, t is the current time, and u1 is the control input signal. The accurate values of the inner loop proportional gain value K m , the inner loop time constant T m and the time delay constant τ cannot be obtained in most cases, which is a parameter uncertainty; the unmodeled dynamic friction force and the external unknown disturbance d1 are another key problem in the valve position inner loop model; the uncertainties, unmodeled dynamics and external unknown disturbances are summarized as the total disturbance f1, and formula (3) is obtained:

[0096]

[0097] Where, b 01 is the estimated value of the position loop actual control gain b1, and d1 is the external disturbance.

[0098] (2) The high-altitude table intake pressure control system contains complex pipelines, and different gas flows are uniformly mixed in the three-way, four-way and mixer. The model can be equivalent to a single-in single-out cavity structure as shown in Figure 2 , and the intake pressure differential equation is as follows:

[0099]

[0100] Where P, T, V, R are the gas pressure, temperature, volume and gas constant in the chamber respectively; h g is the gas specific enthalpy; c p is the gas specific constant pressure heat capacity; h in is the gas specific enthalpy; c out are the inflow and outflow gas specific enthalpy respectively. Where W in is the regulating valve flow characteristic model, its simplified equation is:

[0101]

[0102] Where a, p1, P in are the valve equivalent cross-sectional area, inflow gas density, valve flow coefficient and inflow gas pressure respectively; W out is the required gas flow of the test aero-engine, which is expressed as:

[0103]

[0104] Where W ahs is the engine's converted gas flow; η is the fan's converted speed of the engine. Thus, equation (4) can be rewritten as:

[0105]

[0106] Where the outer loop proportional gain

[0107] k = a / u2, u2 is the intake pressure outer loop model control input; the outer loop time constant The intake pressure controlled model is written as:

[0108]

[0109] Where x2, is the outer loop system state quantity, y2 is the outer loop system output signal, and since there is a time delay between the intake pressure outer loop model control input u2 and the actual control, Combining equations (2) and (9), and considering the internal and external disturbance factors of the pressure outer loop model, we get:

[0110]

[0111] Where, is the outer loop system, and the total disturbance of the outer loop The outer loop model actual control gain d2 is the external disturbance of the pressure outer loop model, b 02 is the estimate of the pressure outer loop model actual control gain b2.

[0112] Step 2:

[0113] In a typical Smith predictor design, the basic block diagram is shown in Figure 3 As shown in Figure 3 , the transfer function relationship between the control signal u and the output signal y0 of the Smith predictor is as follows:

[0114]

[0115] where s is the Laplace operator and u(s) is the control input after Laplace transformation. The time-domain expression corresponding to equation (10) is: Obviously, the output signal y0 of the Smith predictor can be obtained from the time delay τ, the actual output signal y and its differential information. Based on equation (10), the equivalent control block diagram of the Smith predictor is shown in Figure 4 Therefore, the problem of time delay compensation is transformed into how to reasonably extract continuous signals (i.e. tracking) and differential signals from the discontinuous or noisy output signals in actual engineering. In the traditional engineering experience of differential signal extraction, small time constant inertial elements are usually used to obtain

[0116]

[0117] where the smaller the time constant T, T1, T2 of the inertial element, the closer the delayed signal y(t-T) to the output signal y(t), and thus the closer the differential signal to the ideal differential signal. However, in the process of using small time constant inertial elements to obtain the approximate differential signal , the smaller the value of T, the more serious the amplification of external measurement noise in the output signal y(t), and even the differential signal is completely covered. In view of the above problems, a tracking differentiator based on enhanced discrete optimal control algorithm (i.e. Fast algorithm) is proposed, which has strong filtering effect and can quickly track the given signal and extract the differential signal. Therefore, the tracking differentiator is used to obtain the differential signal in the principle of Smith predictor, and its tracked given signal is used to complete the design of the enhanced time delay compensator to obtain better time delay compensation effect. The specific expression of the tracking differentiator is:

[0118]

[0119] where k is a constant and k = 0, 1, 2, 3...; v0 is the output signal of the tracking differentiator, v1 and v2 are the tracking signal and its derivative signal of v0, respectively, e0 is the tracking error, h is the sampling period, i.e. the integration step size, r0 is the fast factor of the tracking differentiator, h0 is the filtering factor of the tracking differentiator, sign is the switching function, and t1 and t2 are the time when the initial point reaches the switching curve and the time when the initial point reaches the origin, respectively.

[0120] Combining equations (10) and (13) above, the algorithm for obtaining the compensation signal from the enhanced time delay compensator based on the tracking differentiator is as follows:

[0121]

[0122] Where y0(t) is the compensation signal; v1 and v2 are the tracking signal and the differential signal of the system output signal y(t), respectively; This is an estimate of the actual time delay.

[0123] To preliminarily test the time delay compensation effect of the tracking differentiator based on the enhanced discrete optimal control algorithm (i.e., the Fast algorithm) under measurement noise, a digital simulation comparison was conducted with that of the Smith predictor based on traditional small time constant inertial elements and the difference method. Figure 5 As shown. The signal compensation effect compared to the other two methods is compared to the compensation signal obtained by the tracking differentiator based on the enhanced discrete optimal control algorithm (i.e., the Fast algorithm). Figure 5 The advantages of this differential extraction algorithm are clearly evident. It not only effectively overcomes noise problems and ensures the smoothness of the output signal, but also compensates for the effects of time delays in the system output signal. Therefore, the enhanced time delay compensator designed based on this method exhibits excellent filtering characteristics and compensation performance for systems with noise and time delays. This further ensures that the subsequent active disturbance rejection control strategy based on the enhanced time delay compensator can achieve better control quality of the intake pressure system.

[0124] Step 3:

[0125] Based on the valve position system model (3) established above and the designed enhanced time delay compensator (13)-(14), the time delay compensation ADRC algorithm is designed as follows. First, the second-order ESO of the valve position system is designed as follows:

[0126]

[0127] Where Z = [z1, z2] T z1 is the estimated value of the position loop system output y1, and the observed value of the total position loop disturbance f1 is defined as z2. The observer gains β1 and β2 are tuned to 2ω using the bandwidth method. 01 and where ω 01 is the observer bandwidth. Considering that the system output signal can be measured directly by sensors and in order to better overcome the bandwidth problem of the ESO, the state variable is selected as the observer output, and a new state variable is defined as The reduced-order ESO can be obtained as follows:

[0128]

[0129] where the gain value of the reduced-order ESO is β0= ω 01 ; assuming that the observer bandwidth ω 01 is properly selected, the reduced-order ESO can accurately observe the total disturbance f1, and the observation error tends to zero. The specific proof process is expanded in the following. At this time, based on the observation value of the RESO, the negative feedback control law u0is selected and the controller output quantity u1is designed as follows:

[0130]

[0131] where r1is the system reference value, e1is the inner loop feedback error, K p1 is the inner loop proportional controller gain; combined with the enhanced time delay compensator designed in the above formula (14), the proposed time delay compensation ADRC control law algorithm is as follows:

[0132]

[0133] Step 4:

[0134] For the controlled model of the intake pressure formula (9), a new observation error feedback gain function is introduced to design a new nonlinear ESO as follows:

[0135]

[0136] where δ1, δ2, δ3 are the estimated values of the pressure loop output y2 and its differential information and the total disturbance f2, respectively, γ1, γ2, γ3 are the observer gains, and the parameters α and ξ are the filtering factor and the boundary layer thickness, respectively. The error feedback gain function is shown in the characteristic curve of the traditional error feedback gain function as Figure 6 According to the estimated value of the new nonlinear ESO, the controller of the pressure loop is designed as follows:

[0137]

[0138] where r2 is the system reference value of the outer loop, e2 is the outer loop feedback error, K p2 is the outer loop proportional controller gain, and K dis the gain of outer loop differential controller. Figure 7

[0139] To verify the control effect of the cascade active disturbance rejection control method of the altitude chamber air intake pressure system in the actual altitude chamber air intake pressure system, the experimental results of the position loop and the pressure loop are shown in Figures 8-11 Compared with the classical method, the TDC-CNADRC method effectively suppresses the valve position oscillation, ensures smooth tracking and minimizes overshoot. In addition, the thrust transient test results using this scheme show that the maximum pressure error is increased from 3.4 kPa to 2.2 kPa; at the same time, the maximum return time is shortened from 7.3 s to 5.2 s. Therefore, the cascade active disturbance rejection control method with enhanced time delay compensation and a new type of nonlinear extended state observer proposed in the present application can effectively suppress the time delay of the valve and strong flow disturbance, and effectively improve the control performance of the altitude chamber air intake pressure system.

[0140] The above is the preferred embodiment of the present application, any changes made according to the technical solutions of the present application, as long as the generated function does not exceed the scope of the technical solutions of the present application, belongs to the protection scope of the present application.​

Claims

1. A cascade active disturbance rejection control method for a high altitude cabin intake pressure system, characterized in that, Comprising: Step 1, the high altitude cabin intake pressure system model is equivalent to the position inner loop model and the pressure outer loop model, and the position inner loop model with time delay link and the pressure outer loop model with disturbance are established according to the system characteristics, the system transfer function is obtained and is converted into state space equation; Step 2, for the position inner loop model with time delay, an enhanced time delay compensation link is introduced, and a self-anti-disturbance control with time delay compensation is designed to ensure the smooth small overshoot tracking performance of the position inner loop of the intake pressure system; Step 3, for the strong measurement noise existing in the intake pressure system, a tracking differentiator based on enhanced discrete optimal control algorithm, namely Fast algorithm, is proposed to obtain accurate differential signal, and an enhanced time delay compensator is designed based on the differential signal to compensate the output signal with time delay and suppress the influence of time delay on control performance; Step 4, for the strong flow disturbance in the pressure outer loop, a new error feedback gain function is designed to improve the anti-disturbance performance of the pressure outer loop; meanwhile, the position inner loop self-anti-disturbance control with enhanced time delay compensation and the pressure outer loop self-anti-disturbance control based on the new nonlinear ESO are combined to form a high altitude cabin intake pressure system cascade self-anti-disturbance control with enhanced time delay compensation and new nonlinear extended state observer, which effectively deals with the time delay and strong disturbance problems in the system and improves the intake pressure control performance.

2. The cascade adaptive disturbance rejection control method for a high altitude cabin pressure system according to claim 1, wherein, In step 1, the position inner loop model is approximated as a small inertia link, and the specific transfer function considering the time delay link is as follows: where K m is the inner loop proportional gain value, T m is the inner loop time constant, s is the Laplace variable, and τ is the time delay constant; in differential equation form, it is: wherein x1, is the inner loop system state quantity, y is the inner loop system output signal, y1 is the inner loop output signal containing the time delay constant τ, t is the current time, u1 is the control input signal; the inner loop proportional gain value K m , the inner loop time constant T m The accurate value of the time delay constant τ cannot be obtained in most cases, which is manifested as the uncertainty of the parameters; the unmodeled dynamic friction force and the external unknown disturbance d1 are another key problem existing in the valve position inner loop model; the uncertainties, unmodeled dynamics and external unknown disturbances involved are attributed to the total disturbance f1, and formula (3) is obtained: wherein b 01 is the estimate of the inner loop model actual control gain b1, and d1 is the external disturbance.

3. The cascade adaptive disturbance rejection control method for a high altitude cabin pressure system according to claim 2, wherein, In step 1, the high altitude cabin intake pressure system model can be essentially equivalent to a single-in single-out cavity structure, and the intake pressure differential equation is as follows: Wherein, P, T, V, R are gas pressure, gas temperature, gas volume and gas constant in the cavity respectively; h g is the specific enthalpy of the gas; c p is the specific heat capacity at constant pressure of the gas; h in , h out are the specific enthalpy of the inflow gas and the outflow gas respectively; the inflow gas flow W in is the flow characteristic model of the regulating valve, and the simplified equation is as follows: Wherein, α, ρ1, P in The valve equivalent cross-sectional area, the inflow gas density, the valve flow coefficient, and the inflow gas pressure are respectively represented by α, ρ1, out is represented as: where W ahs is the corrected gas flow of the test aeroengine; η is the corrected fan speed of the test aeroengine; thus, equation (4) is rewritten as: where the outer loop proportional gain k = a / u2, u2 is the pressure outer loop model control input; outer loop time constant The intake pressure controlled model is written as: where x2, is the outer loop system state variable, y2is the outer loop system output signal, and since there is a delay between the pressure outer loop model control input u2and the actual control Combining equations (2) and (9), and considering the inner and outer disturbance factors of the pressure outer loop model, we have: wherein is the outer loop system, the total disturbance to the outer loop is the outer loop model actual control gain d2 is the outer disturbance to the pressure outer loop model, b 02 is the estimate of the pressure outer loop model actual control gain b2.

4. The cascade adaptive disturbance rejection control method for a high altitude cabin pressure system according to claim 3, wherein, After the processing of the Smith predictor, the transfer function relationship between the control signal u and the output signal y0 of the Smith predictor is as follows: where s is Laplace operator, u(s) is the control input after Laplace transform, and the time domain expression corresponding to equation (10) is: The output signal y0 of the Smith predictor can be obtained from the time delay constant τ, the actual output signal y of the system and its differential information. Therefore, the time delay compensation problem is transformed into how to reasonably extract continuous signals, i.e. tracking and differential signals, from the discontinuous or noisy output signals in actual engineering.

5. The cascade adaptive disturbance rejection control method for a high altitude cabin pressure system according to claim 4, wherein, In the differential signal extraction, a small time constant inertia link is used to obtain as shown in equations (11) and (12): Wherein, the smaller the inertia link time constant T, T1, T2, the closer the delay signal y(t-T) to the output signal y(t), so that the differential signal The closer to the ideal differential signal; however, in the process of using small time constant inertia link to obtain approximate differential signal The smaller the T value, the more serious the amplification of external measurement noise in the output signal y(t), and even completely cover the differential signal Therefore, the tracking differentiator based on enhanced discrete optimal control algorithm is proposed to obtain the differential signal in Smith predictor At the same time, the given signal tracked by it is used to complete the design of enhanced time delay compensator to obtain better time delay compensation effect; the specific expression of tracking differentiator based on enhanced discrete optimal control algorithm is: wherein, The output signals of the tracking differentiator are v1, v2, which are the tracking signal and the differential signal of v0, respectively, e0 is the tracking error, h is the sampling period, i.e., the integration step, r0 is the fast factor of the tracking differentiator, h0 is the filter factor of the tracking differentiator, sign is a switching function, t1 and t2 are the times at which the initial point reaches the switching curve and the origin, respectively. Based on equations (10) and (13), the compensation signal of the enhanced time delay compensator based on the tracking differentiator is as follows: Wherein, y0(t) is the compensation signal; v1, v2 are respectively the tracking signal of the system output signal y(t) and the differential signal thereof; is the estimation of the actual time delay.

6. The cascade adaptive disturbance rejection control method for a high altitude cabin pressure system according to claim 5, wherein, Based on equations (3) and (13)-(14), the time delay compensation ADRC control law algorithm is designed as follows: Firstly, a second-order ESO is designed as follows: where Z = [z1, z2] T , z1 is the estimation of the inner-loop model output y1, and z2 is the observation of the total disturbance f1; the gain values β1 and β2 of the observer are tuned to 2ω 01 and where ω 01 is the bandwidth of the observer, and the state variable is the output of the observer, and the new state variable is defined as The reduced-order ESO is as follows: where the gain value of the reduced-order ESO is β0= ω 01 ; assuming that the selected observer bandwidth ω 01 , the reduced-order ESO can accurately observe the total disturbance f1, and the observation error tends to zero; at this time, based on the observation value of the RESO, the negative feedback control law u 01 is designed as follows: where r1 is the system reference value, e1 is the feedback error, K p1 is the inner loop proportional controller gain; combining equation (14), the time-delay compensated ADRC control law is as follows:

7. The cascade adaptive disturbance rejection control method for a high altitude cabin pressure system according to claim 6, wherein, For equation (9), a new observation error feedback gain function is introduced to design a new nonlinear ESO as follows: where δ1, δ2, δ3 are the estimates of the pressure loop output y2 and its derivative information and the total disturbance f2, γ1, γ2, γ3 are the observer gains, and α and ξ are the filter factor and the boundary layer thickness, respectively, and K is the error feedback gain function According to the estimates of the new nonlinear ESO, the controller of the pressure outer loop is designed as follows: wherein r2 is an outer loop system reference value, e2 is an outer loop feedback error, K p2 is an outer loop proportional controller gain, K d is an outer loop derivative controller gain.

8. The cascade adaptive disturbance rejection control method for a high altitude cabin pressure system according to claim 1, wherein, The working principle of the high altitude cabin intake pressure system cascade control structure is that the error feedback control signal between the actual pressure signal measured by the pressure sensor and the set intake pressure value is converted as the given signal of the inner loop, and the actual valve position signal obtained by the position sensor is subtracted, and the control of the hydraulic servo system is realized through the inner loop controller to drive the regulating valve to act and change the valve opening to regulate the gas flow, and finally the pressure control of the intake pressure system is completed.

9. A high altitude cabin air pressure system cascade active disturbance rejection control system, characterized by, The computer program instructions stored in the memory and capable of being executed by the processor can realize the method steps of any one of claims 1-8 when the processor executes the computer program instructions.

10. A computer readable storage medium having stored thereon computer program instructions capable of being executed by a processor, the computer program instructions, when executed by the processor, capable of implementing the method steps of any one of claims 1-8.

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