A fault-tolerant control method for anti- gyro drift of high-speed unmanned aerial vehicle

Abstract

The application provides a high-speed unmanned aerial vehicle anti-gyroscope drift fault-tolerant control method, which comprises the following steps: step 1, an output model containing sensor faults is established; step 2, a nonlinear disturbance observer is established to estimate the disturbance; step 3, a sliding mode control law is designed, and the disturbance estimation result of the observer is combined to obtain an angular rate expected signal; and step 4, a proportional control law is designed to obtain a rudder amount set value. According to the control characteristics of the fixed-wing unmanned aerial vehicle, the actual engineering application situation, the gyro pitch angle and roll angle attitude unit faults, the nonlinear disturbance observer, the sliding mode control and the proportional control method, the application not only has the sensor fault tolerance capability, but also has the engineering practicability, so that the fixed-wing unmanned aerial vehicle can fly safely under the gyro fault.

Description

Technical Field

[0001] This invention relates to a fault-tolerant control method for high-speed unmanned aerial vehicles (UAVs) to prevent gyro drift. Background Technology

[0002] For fixed-wing aircraft, attitude sensors play a crucial role in the aircraft's feedback control law. It's easy to imagine that a faulty sensor will provide inaccurate signals. If a sensor malfunction occurs during the flight mission, the control law calculated based on the erroneous feedback signal will, at best, reduce control effectiveness, and at worst, cause control divergence, leading to mission failure or even the destruction of the aircraft and loss of life. Therefore, considering sensor malfunction issues in the design of aircraft tracking control laws is of paramount importance.

[0003] Furthermore, the failure rate of the angular rate measurement unit in engineering is very low, and much lower than that of the attitude angle measurement unit. Therefore, it is of particular engineering significance to design a fault-tolerant controller that can ensure the safe flight of the aircraft and even the successful completion of the mission under the failure of the attitude measuring gyroscope, considering the failure of the pitch angle and roll angle sensors. Summary of the Invention

[0004] Purpose of the invention: The technical problem to be solved by the present invention is to provide a fault-tolerant control method for high-speed UAVs to resist gyro drift, which can effectively solve the problem of safe flight of fixed-wing high-speed UAVs when the attitude measuring gyroscope fails and cannot accurately measure the attitude or even outputs an incorrect attitude.

[0005] This invention proposes a control law that can ensure the safe flight of an aircraft under attitude sensor failure. Based on the UAV control system, it uses an angular rate sensor to measure the angular rate and performs angular rate feedback control.

[0006] The control system includes a flight control unit, an actuator, and a gyroscope; the flight control unit and the gyroscope are integrated and connected, communicate with the actuator through an integrated cable, and are installed on the fuselage.

[0007] The control method specifically includes the following steps:

[0008] Step 1: Establish an output model that includes sensor faults;

[0009] Step 2: Establish a nonlinear disturbance observer to estimate the disturbance;

[0010] Step 3: Design the sliding mode control law and combine it with the observer disturbance estimation results to obtain the expected angular rate signal;

[0011] Step 4: Design the proportional control law to obtain the rudder output setting value.

[0012] Step 1 includes:

[0013] Step 1-1: Establish a general sensor fault model;

[0014] Steps 1-2: Establish an output model that includes the total fault function;

[0015] Steps 1-3 establish the dynamic equations of the output model that include the total fault function.

[0016] Step 1-1 includes: The dynamic equations for the pitch and roll angles of the fixed-wing UAV are shown in equation (1):

[0017]

[0018] Where x1 = θ, x2 = φ, x1 and x2 represent pitch angle and roll angle respectively, and the superscript · in the formula indicates the derivative; p, q and r represent roll rate, pitch rate and yaw rate respectively;

[0019] Let y = [θ] out φ out ] T y1=θ out Represents the observed pitch angle, y2 = φ out Let the roll angle observation value be represented. Then the sensor fault model is shown in Equation (2), which includes deviation, drift, misalignment, and failure:

[0020]

[0021] Where i = 1, 2, b i (t) represents the deviation fault, ρ i (t) represents the failure; t represents time, t Fi Indicates the time when the fault occurred, κ i Indicates the drift failure coefficient; This represents the initial boundary value of the misalignment deviation at the moment the fault occurs. This represents the failure factor boundary.

[0022] Steps 1-2 include: defining the total fault of all fault types in equation (2) as f. si :

[0023] f si =(ρ i (t)-1)x i +b i (t) (3)

[0024] The output model is defined by equation (3) as follows:

[0025] y i =x i +f si (4).

[0026] Steps 1-3 include: Differentiating equation (4), we get:

[0027]

[0028] in,

[0029]

[0030]

[0031] d yi i = 1, 2 are considered as composite perturbations;

[0032] The output equation obtained after transformation only contains sensor measurements and composite disturbances;

[0033] Setting 1: The pitch angle θ and roll angle φ satisfy the following inequalities:

[0034]

[0035] Setting 2: The reference trajectory itself and its first derivative are continuous and bounded;

[0036] Setting 3: The system's equivalent disturbance is unknown, but the system's equivalent disturbance itself and its first derivative are bounded.

[0037] Step 2 includes:

[0038] Step 2-1: Derive and establish the output model as an affine nonlinear model;

[0039] Step 2-2: Design a nonlinear disturbance observer.

[0040] Step 2-1 includes: rewriting equation (5) into an affine nonlinear form as shown in equation (6):

[0041]

[0042] Where f(y) represents the state matrix, g(y) represents the control matrix, u represents the input matrix, d represents the disturbance matrix, and the superscript T represents the matrix transpose.

[0043] In step 2-2, the nonlinear disturbance observer is designed as follows:

[0044]

[0045] in, d yi The estimate, y oi l i (y i ), p oi k is an internal variable of the observer. oi It is the constant gain of the observer;

[0046] When system (6) satisfies setting 3, and k oi >0, the observer (7) error is uniformly bounded and can be improved by choosing an appropriate k oi To reduce.

[0047] Step 3 includes:

[0048] Step 3-1, define the tracking error and design the sliding surface:

[0049] Define attitude tracking error e i :

[0050] e i =y i -y id (8)

[0051] Among them, y id The desired signal is generated by the outer loop control system.

[0052] Design sliding surface s i As shown in equation (9):

[0053] s i =e i (9)

[0054] Differentiating equation (9), we get:

[0055]

[0056] Step 3-2, Design the anti-chattering sliding mode reaching law:

[0057] To avoid chattering, a reaching law is chosen:

[0058]

[0059] Where i = 1, 2; k i1 α i k i2 β i Represents the reaching law coefficient, α i >1, 0 < β i <1,k i1 >0,k i2 >0; when s i When s > 1, the first term in equation (11) can increase the sliding mode approach rate, when s i When <1, the second item has the effect of smoothly and quickly approaching the switching surface;

[0060] Step 3-3: Based on the results of the nonlinear disturbance observer, design the sliding mode control law to generate the expected pitch rate and roll rate signals (Equation 12 is the sliding mode control law; u = [p, q] obtained from Equation 12 is both the input of attitude control and the output of the angular rate control loop. Therefore, the result obtained by the attitude control law is the expectation of the angular rate control loop, u1 is the expected roll rate signal, and u2 is the expected pitch rate signal):

[0061] Design sliding mode control law u using observer (7) i :

[0062]

[0063] Based on the cascade concept, let p d =u1, q d =u2, when p→p d And q→q d At that time, there was e i Consistency is ultimately bounded.

[0064] Step 4 includes:

[0065] Step 4-1: Read the attitude angular rate information fed back by the angular rate sensor;

[0066] Step 4-2: Based on the desired signal and feedback signal, a proportional control law can be designed to generate the aileron and elevator control setpoints.

[0067] The expected pitch rate q is obtained from equation (12). d Expected roll rate p d Then design the proportional control law as shown in equation (13):

[0068]

[0069] In the formula, δ a δ e These represent the aileron deflection angle and the elevator deflection angle, respectively, k p k q This represents the proportionality coefficient.

[0070] In engineering practice, the failure rate of gyro attitude measurement units is far higher than that of angular rate measurement units, posing a significant challenge to flight safety. This invention, combining practical engineering considerations, proposes a sliding mode fault-tolerant control law based on a nonlinear disturbance observer to address pitch and roll angle sensor failures. First, based on the attitude angle dynamic equation and the gyro fault model, gyro faults are treated as disturbances and estimated using a nonlinear disturbance observer. Then, the desired angular rate signal is designed using the sliding mode control law. Finally, proportional control is used to design the control variables, enhancing its practical engineering applicability.

[0071] Beneficial Effects: This invention proposes a fault-tolerant control method for high-speed unmanned aerial vehicles (UAVs) to resist gyro drift. Based on the control characteristics of fixed-wing UAVs and practical engineering applications, this control law addresses gyro pitch and roll angle attitude unit faults. Utilizing a nonlinear disturbance observer and sliding mode control and proportional control methods, it not only possesses sensor fault tolerance capabilities but also demonstrates engineering feasibility, ensuring the safe flight of fixed-wing UAVs under gyro fault conditions. Attached Figure Description

[0072] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, and the advantages of the present invention in the above and / or other aspects will become clearer.

[0073] Figure 1 This is a schematic diagram of the fault-tolerant control principle.

[0074] Figure 2 This is a schematic diagram of the sliding mode fault-tolerant control law principle for a nonlinear disturbance observer.

[0075] Figure 3a The simulation diagram (height) shows the comparison of fault-tolerant control laws under fault conditions.

[0076] Figure 3b A simulation diagram comparing fault-tolerant control laws under fault conditions (heading).

[0077] Figure 3c The simulation diagram shows the comparison of fault-tolerant control laws under fault conditions (pitch measurement values).

[0078] Figure 3d The simulation diagram shows the comparison of fault-tolerant control laws under fault conditions (roll measurement values).

[0079] Figure 4a The simulation diagram shows the comparison of fault-tolerant control laws under fault conditions (angle of attack).

[0080] Figure 4b The simulation diagram shows the comparison of fault-tolerant control laws under fault conditions (sideslip angle).

[0081] Figure 4c The simulation diagram shows the comparison of fault-tolerant control laws under fault conditions (actual pitch angle value).

[0082] Figure 4d The simulation diagram shows the comparison of fault-tolerant control laws under fault conditions (actual roll angle value). Detailed Implementation

[0083] Example 1

[0084] This embodiment provides a fault-tolerant control method for high-speed unmanned aerial vehicles (UAVs) to resist gyro drift. This method, based on gyro-acquired data, a nonlinear disturbance observer, sliding mode fault-tolerant control, and proportional control, enables safe flight of a fixed-wing UAV under gyro attitude sensor failure. Specifically, it includes the following steps:

[0085] Step 1: During the flight of the UAV, the coupling between attitude and outer loop state variables is continuously monitored. When a sensor failure is detected, the flight control switches from the conventional control law to the fault-tolerant control law.

[0086] Step 2: Treat the fault signal as a disturbance, estimate the fault using a nonlinear disturbance observer, and transmit the estimation result to the attitude control loop;

[0087] Step 3: Based on the observer disturbance estimation results and the attitude angle expectation signal generated by the outer loop, the angular rate expectation signal is obtained through the sliding mode fault-tolerant control law;

[0088] Step 4: Based on the desired angular rate signal and the attitude angular rate fed back by the angular rate sensor, the final rudder input setting value is obtained through a proportional control law.

[0089] Working principle: Figure 1 This is a schematic diagram of the fault-tolerant control principle. Based on this diagram, the fault-tolerant flight process of a fixed-wing UAV is broken down as follows:

[0090] (1) After the UAV is launched, the coupling between the UAV attitude and the outer loop data can be monitored in real time by a human in the loop, or the attitude and outer loop data feedback can be determined by the flight control to determine whether the attitude measuring gyroscope has malfunctioned, and the control law can be switched to the fault-tolerant control law by remote control or automatic execution of the flight control program.

[0091] (2) The fault-tolerant control law generates the attitude angle rate expectation signal based on the attitude angle and attitude angle rate information fed back by the gyroscope and the attitude angle expectation signal generated by the outer loop control system, and generates the rudder deflection signal through proportional control to enable the UAV to maintain trajectory control capability.

[0092] (3) Based on the fault-tolerant control law effect, ground operators can choose to return to base or continue to perform the mission.

[0093] Example 2

[0094] This embodiment, based on Embodiment 1 above, further includes the following steps to better implement the present invention: Figure 2 As shown, a model was built using Matlab to realize fully digital simulation closed-loop control, which was then used to analyze the effect of the fault-tolerant control law.

[0095] In step 2, the specific operation for generating the fault-tolerant rudder deflection command is as follows:

[0096] Step 2.1: Based on the sensor fault model and the dynamic equations of the pitch and roll angles of the fixed-wing UAV, establish the sensor fault output model;

[0097] Step 2.2: Design a nonlinear disturbance observer to obtain fault estimates;

[0098] Step 2.3: Based on the fault estimate and the attitude expectation signal generated by the outer loop, design a sliding mode fault-tolerant control law to obtain the angular rate expectation signal;

[0099] Step 2.4: Design a proportional control law based on the desired angular rate signal and the measured angular rate value.

[0100] Working principle: Based on the sliding mode fault-tolerant control principle of the nonlinear disturbance observer, the design of the sliding mode fault-tolerant control law of the nonlinear disturbance observer mainly includes:

[0101] Fault output modeling;

[0102] Design of a nonlinear disturbance observer;

[0103] Design of sliding mode fault-tolerant proportional control law.

[0104] 1. Fault Output Model

[0105] This section mainly focuses on modeling the pitch and roll angle outputs under faulty attitude sensor conditions.

[0106] The dynamic equations for the pitch and roll angles of the fixed-wing UAV are shown in equation (1):

[0107]

[0108] In the formula, x1=θ, x2=φ, representing pitch angle and roll angle respectively, and p, q, and r represent roll rate, pitch rate and yaw rate respectively.

[0109] The sensor fault model is shown in equation (2), including deviation, drift, misalignment, and failure:

[0110]

[0111] In the formula, i = 1, 2, y1 = θ out Represents the observed pitch angle, y2 = φ out This represents the observed roll angle.

[0112] Define the total fault of all fault types in equation (2) as f. si :

[0113] f si =(ρ i (t)-1)x i +b i (t) (3)

[0114] The output model can be defined by equation (3):

[0115] y i =xi +f si (4)

[0116] Differentiating equation (4), we get:

[0117]

[0118] In the formula,

[0119]

[0120]

[0121] Assumption 1: The pitch and roll angles satisfy the following inequalities:

[0122]

[0123] Assumption 2: The reference trajectory itself and its first derivative are continuous and bounded.

[0124] Assumption 3: The equivalent disturbance of the system is unknown, but it and its first derivative are bounded.

[0125] 2. Nonlinear disturbance observer

[0126] This section establishes a nonlinear disturbance observer based on the fault output model.

[0127] Equation (5) can be simplified to the form shown in equation (6):

[0128]

[0129] The nonlinear disturbance observer can be designed in the following form:

[0130]

[0131] In the formula, d yi The estimate, y oi p oi k is an internal variable of the observer. oi It is the constant gain of the observer.

[0132] Lemma 1: When system (6) satisfies Assumption 3, and k oi >0, the observer (7) error is uniformly bounded, and can be improved by choosing an appropriate k oi To reduce.

[0133] 3. Sliding mode fault tolerance proportional control law

[0134] Define attitude tracking error:

[0135] e i =y i-y id (8)

[0136] In the formula, y id The desired signal is generated by the outer loop control system.

[0137] The sliding surface is designed as shown in equation (9):

[0138] s i =e i (9)

[0139] Differentiating equation (9), we get:

[0140]

[0141] To avoid chattering, a reaching law is chosen:

[0142]

[0143] In the formula, α i >1, 0 < β i <1,k i1 >0,k i2 >0. When s i When s > 1, the first term in equation (11) can increase the sliding mode approach rate, while when s i When the value is less than 1, the second term effectively facilitates a smooth and rapid approach to the switching surface. Therefore, this approach law can alleviate the problem of sliding mode chattering while ensuring the approach effect.

[0144] By combining the observer (7), a sliding mode control law can be designed:

[0145]

[0146] From equation (12), the expected attitude angular rate q can be obtained. d p d Then design the proportional control law as shown in equation (13):

[0147]

[0148] In the formula, δ a δ e These represent the aileron deflection angle and the elevator deflection angle, respectively.

[0149] Using a certain type of high-speed unmanned aerial vehicle (UAV) as the simulation object, a pure digital closed-loop simulation environment was built based on Matlab. The UAV performs the following tasks:

[0150] At a constant altitude of 8km, perform five maneuvers in sequence: 1. Level flight for 15s; 2. Left turn for 5s; 3. Level flight for 15s; 4. Right turn for 5s; 5. Level flight for 10s.

[0151] The following setup failures occurred:

[0152] The pitch channel experiences a 10° sensor deviation fault when 5s≤t<10s, and simultaneously experiences a 30% failure and a 5° / s drift when t≥37s; the roll channel experiences a 5° / s drift fault when t≥5s. The output model is shown in equations (14)~(15).

[0153]

[0154]

[0155] Simulation results of the fault-tolerant control law proposed in this invention are as follows: Figure 3a , Figure 3b , Figure 3c , Figure 3d , Figure 4a , Figure 4b , Figure 4c , Figure 4d As shown in the figure. In the figure, the subscript "out" represents the sensor measurement value, and no subscript represents the actual value; the solid line represents the simulation result of the fault-tolerant control law, corresponding to the left axis, and the dashed line represents the result of the PID control law, corresponding to the right axis, to illustrate the effect of the fault-tolerant control law. Figure 3a , Figure 3b , Figure 3c , Figure 3d , Figure 4a , Figure 4b , Figure 4c , Figure 4d It can be seen that the output model can effectively simulate attitude measurement failures of the attitude measuring gyroscope, and the fault-tolerant control method for anti-gyroscope drift of high-speed UAV proposed in this invention can ensure the safe flight and trajectory tracking capability of UAV under various sensor failure types.

[0156] In its specific implementation, this application provides a computer storage medium and a corresponding data processing unit. The computer storage medium is capable of storing a computer program, which, when executed by the data processing unit, can run the invention's content regarding a fault-tolerant control method for high-speed unmanned aerial vehicles against gyro drift, as well as some or all of the steps in various embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0157] Those skilled in the art will clearly understand that the technical solutions in the embodiments of the present invention can be implemented using computer programs and their corresponding general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of computer programs, i.e., software products. These computer program software products can be stored in a storage medium and include several instructions to cause a device containing a data processing unit (which may be a personal computer, server, microcontroller, MUU, or network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of the present invention.

[0158] This invention provides a fault-tolerant control method for high-speed unmanned aerial vehicles (UAVs) to resist gyro drift. Many methods and approaches exist for implementing this technical solution; the above description is merely a preferred embodiment. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention. All components not explicitly stated in this embodiment can be implemented using existing technologies.

Claims

1. A fault-tolerant control method for anti- gyro drift of high-speed unmanned aerial vehicles, characterized in that, The method comprises the following steps: Step 1, establishing an output model containing sensor faults; Step 2, establishing a nonlinear disturbance observer to estimate the disturbance; Step 3, designing a sliding mode control law, combining the disturbance estimation result of the observer, to obtain an angular rate expected signal; Step 4, designing a proportional control law to obtain a rudder output setting value; Step 3 comprises: Step 3-1, defining a tracking error and designing a sliding mode surface: Defining the pose tracking error e i : e i = y i - y id (8) where y id represents the desired signal, generated by the outer loop control system; i = 1, 2, yi = θ out represents the pitch angle observation, y2 = φ out represents the roll angle observation; Designing a sliding surface s i As shown in equation (9): s i = e i (9) Taking the derivative of equation (9), the derivative of the sliding mode surface s is obtained i ​ where y = [0 out φ out ] T ; the superscript T represents matrix transposition; d yi is regarded as a composite disturbance; f i (y) represents a state matrix corresponding to i, g i (y) represents a control matrix corresponding to i, and u represents an input matrix, represents the derivative of y id . Step 3-2, designing a chattering-resistant sliding mode reaching law: In order to avoid chattering, the reaching law is selected as: where p i represents the failure fault, k i1 , a i , k i2 , b i represents the approaching law coefficient, a i > 1, 0 < b i < 1, k i1 > 0, k i2 > 0; when s i > 1, the first term in formula (11) can increase the sliding mode approaching rate, and when s i < 1, the second term plays a smoothing effect on the fast approaching switching surface; Step 3-3, combining the nonlinear disturbance observer result, designing a sliding mode control law to generate a pitch angle rate expected signal and a roll angle rate expected signal: A sliding mode control law u is designed in combination with an observer i : wherein represents d yi an estimate of From the cascade idea, let p d = u1, q d = u2, when p→ p d and q→ q d , there is e i consistent eventually bounded.

2. The method of claim 1, wherein, Step 1 comprises: Step 1-1, establishing a general sensor fault model; Step 1-2, establishing an output model containing a total fault function; Step 1-3, establishing a dynamic equation of the output model containing the total fault function.

3. The method of claim 2, wherein, Step 1-1 comprises: the dynamic equations of the pitch angle and roll angle of the fixed-wing unmanned aerial vehicle are as shown in formula (1): Wherein, x1=θ, x2=φ, x1 and x2 represent the pitch angle and roll angle respectively, and the superscript · in the formula represents the derivative; p, q and r represent the roll angle rate, pitch angle rate and yaw angle rate respectively; The sensor fault model is as shown in formula (2), including bias, drift, misalignment and failure: where b i (t) represents a deviation fault, p i (t) represents a failure fault at time t; t Fi represents the time of fault occurrence, k i represents a drift fault coefficient; represents the initial value boundary of the misalignment deviation amount at the time of fault occurrence, represents a failure factor boundary.

4. The method of claim 3, wherein, Steps 1-2 include defining the total fault f comprising all fault types in formula (2) si : f si = (p i (t) - 1) x i + b i (t) (3) The output model is defined as follows according to formula (3): y i = x i + f si (4).

5. The method of claim 4, wherein, Step 1-3 comprises: deriving formula (4) to obtain: Wherein, The output equation obtained after transformation only contains sensor measurement values and composite disturbances; Setting 1: the pitch angle θ and roll angle φ satisfy the following inequalities: Setting 2: the reference trajectory itself and its first-order derivative are continuous and bounded; Setting 3: the equivalent disturbance of the system is unknown, but the equivalent disturbance of the system itself and its first-order derivative are bounded.

6. The method of claim 5, wherein, Step 2 comprises: Step 2-1, deducing to establish an output model as an affine nonlinear model; Step 2-2, designing a nonlinear disturbance observer.

7. The method of claim 6, wherein, Step 2-1 comprises: formula (5) is rewritten as an affine nonlinear form as shown in formula (6): Wherein, f(y) represents a state matrix, g(y) represents a control matrix, and d represents a disturbance matrix.

8. The method of claim 7, wherein, In step 2-2, the nonlinear disturbance observer is designed as follows: Among them, y oi l i (y i ), p oi k is an internal variable of the observer. oi It is the constant gain of the observer; When the system (6) satisfies condition 3, and k oi > 0, the observer (7) error is uniformly ultimately bounded and can be reduced by choosing a suitable k oi .

9. The method of claim 8, wherein, Step 4 comprises: Step 4-1, reading the attitude angular rate information fed back by the angular rate sensor; Step 4-2, designing a proportional control law from the expected signal and the feedback signal to generate aileron and elevator rudder output setting value: The pitch angle rate demand q is obtained from equation (12) d The roll angle rate demand p is obtained from equation (13) d The proportional control law is redesigned as shown in equation (14) where δ a , δ e represent aileron deflection angle, elevator deflection angle, respectively, k p , k q represent proportional coefficients.

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