Helicopter flight control performance determination method, device, equipment, medium and product

Abstract

The invention discloses a helicopter flight control performance determination method and device, equipment, a medium and a product, and relates to the field of helicopter flight control performance evaluation.The method comprises the steps that flight data of helicopter tail rotor fault flight are collected; calculating each index value by using an index model according to the flight data; the index model comprises a process index model and a transient index model; the process index model comprises a tracking index model, an airspeed keeping index model and a safety boundary index model; the transient index model comprises a landing state index model, a landing position index model and a controller delay index model; determining a comprehensive evaluation value of the flight control performance according to each index value and the weight after weight changing; according to the method and the device, the accuracy of helicopter flight control performance evaluation under the condition of the tail rotor fault is improved.

Description

Technical Field

[0001] The present application relates to the field of helicopter flight control performance evaluation, and in particular to a method, device, equipment, medium and product for determining helicopter flight control performance. Background Art

[0002] With the widespread use of helicopters in military, civilian, and scientific research applications, their reliability and safety have become increasingly core issues in research and engineering design. In particular, ensuring safe flight and mission completion through fault tolerance is crucial in the event of a failure during flight. The tail rotor, a crucial component of a helicopter, is responsible for directional control and lateral stability. Its failure can lead to severe flight instability or even loss of control. Therefore, ensuring helicopter flight performance in the event of a tail rotor failure has become a pressing technical challenge.

[0003] Traditional flight control systems mostly assume that the helicopter is operating in normal operating conditions and fail to account for the impact of system failures. To address the challenges posed by tail rotor failures to flight control, researchers have proposed various fault-tolerant control strategies, such as model-based fault diagnosis, fuzzy control, neural network control, and robust control. These approaches aim to maintain stable flight after a failure through real-time fault diagnosis and adaptive control algorithms, thereby preventing serious accidents caused by tail rotor failures.

[0004] Flight performance evaluation has become a key topic in the study of flight control under tail rotor failure. Performance evaluation not only aids in the design of more efficient fault-tolerant control systems but also provides quantitative metrics for helicopter safety verification. Currently, the technology for evaluating helicopter flight control performance under tail rotor failure is still under development. Therefore, a method is needed to improve the accuracy of flight control performance evaluation under tail rotor failure. Summary of the Invention

[0005] The purpose of this application is to provide a method, device, equipment, medium and product for determining helicopter flight control performance, which can improve the accuracy of helicopter flight control performance evaluation under tail rotor failure conditions.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a method for determining helicopter flight control performance, comprising:

[0008] Collect flight data of helicopter tail rotor failure flight;

[0009] Calculating each indicator value using an indicator model based on the flight data; the indicator model includes a process indicator model and a transient indicator model; the process indicator model includes a tracking indicator model, an airspeed holding indicator model, and a safety margin indicator model; the transient indicator model includes a landing state indicator model, a landing position indicator model, and a controller delay indicator model;

[0010] A comprehensive evaluation value of the flight control performance is determined based on the index values and the weights after weight change; the weights after weight change are determined using a dominance function based on a weight change theory.

[0011] Optionally, the indicators in the tracking indicator model include: roll angle tracking indicator, pitch angle tracking indicator, yaw angle tracking indicator and vertical speed tracking indicator; the indicators in the safety boundary indicator model include: angle safety boundary indicator and angular rate safety boundary indicator; the angle safety boundary indicator includes: roll angle safety indicator and pitch angle safety indicator; the angular rate safety boundary indicator includes: roll angular rate safety indicator and pitch angular rate safety indicator.

[0012] Optionally, the indicators in the landing state index model include: a yaw angle rate index, a flight speed index, a lateral speed index and a vertical speed index; the indicators in the landing position index model include: a longitudinal deviation index and a lateral deviation index.

[0013] Optionally, the method for determining the weight after weighting includes:

[0014] Acquiring simulated flight data for helicopter simulation or testing and dividing the simulated flight data into indicators;

[0015] The weight of each indicator is initialized using the hierarchical analysis method to obtain the initial weight;

[0016] Determining an indicator dominance set based on the characteristics of the indicator according to the indicator and the dominance function of the flight indicator; the characteristics of the indicator including normalization, continuity and monotonicity;

[0017] Determine the variable weight function by adopting the incentive-penalty variable weight method according to the indicator advantage set;

[0018] The initial weight is adjusted according to the variable weight function to obtain a weighted weight.

[0019] Optionally, the expression of the advantage function is:

[0020]

[0021] Among them, Q j is the dominance of the jth indicator, β is the adjustment factor, which adjusts the degree of influence of the adjustment indicator on the dominance of the indicator. is the distance between the evaluation value and the negative ideal value, is the distance between the evaluation value and the positive ideal value, It is the distance between the positive and negative ideal values of the indicator.

[0022] Optionally, the expression of the variable weight function is:

[0023]

[0024] Among them, S j (Q j ) represents the variable weight function value of the jth indicator, δ is the variable weight ratio, n is the indicator dimension, is the initial weight, Q j is the indicator dominance, x j is the jth index, S(x j ) is the weight of the j-th indicator, Q + is the maximum value set, Q - is the set minimum value, and j is the indicator number.

[0025] In a second aspect, the present application provides a device for determining helicopter flight control performance, comprising:

[0026] An acquisition module is used to collect flight data of helicopter tail rotor failure flights;

[0027] an indicator calculation module, configured to calculate various indicator values based on the flight data using an indicator model; the indicator model includes a process indicator model and a transient indicator model; the process indicator model includes a tracking indicator model, an airspeed holding indicator model, and a safety margin indicator model; the transient indicator model includes a landing state indicator model, a landing position indicator model, and a controller delay indicator model;

[0028] The comprehensive evaluation value determination module is used to determine the comprehensive evaluation value of the flight control performance according to each of the index values and the weighted weights; the weighted weights are determined based on the variable weight theory using the advantage function.

[0029] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for determining helicopter flight control performance.

[0030] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for determining helicopter flight control performance.

[0031] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the above-mentioned method for determining helicopter flight control performance.

[0032] According to the specific embodiments provided in this application, this application has the following technical effects:

[0033] The present application provides a method, apparatus, equipment, medium and product for determining the flight control performance of a helicopter. The index values of each indicator in the index model are calculated using flight data, wherein the index model includes a process index model and a transient index model; the process index model includes a tracking index model, an airspeed maintenance index model and a safety margin index model; the transient index model includes a landing state index model, a landing position index model and a controller delay index model. By calculating multi-dimensional index values, the inaccurate evaluation caused by a single indicator can be overcome, and then a comprehensive evaluation value is determined based on the index value and the weight after weighting, thereby further improving the accuracy of determining the flight control performance under tail rotor failure flight conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] 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. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 This is a diagram of an application environment of a method for determining helicopter flight control performance in one embodiment of the present application;

[0036] Figure 2 A flowchart of a method for determining helicopter flight control performance provided in one embodiment of the present application;

[0037] Figure 3 A schematic diagram of a method for determining helicopter flight control performance provided in one embodiment of the present application;

[0038] Figure 4 A schematic diagram of a tail rotor fault assessment indicator set provided in one embodiment of the present application;

[0039] Figure 5 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0041] Traditional evaluation methods often focus on a single metric, such as heading stability or control accuracy. However, the flight performance of a helicopter after a tail rotor failure is affected by multiple factors, such as the helicopter's position and attitude. Therefore, this application comprehensively considers multiple performance indicators and adopts a multi-level, multi-dimensional evaluation system to evaluate flight control performance under tail rotor failure.

[0042] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0043] The helicopter flight control performance determination method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 via a network. The data storage system can store data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send flight data of the helicopter tail rotor failure flight to the server 104. After the server 104 receives the flight data of the helicopter tail rotor failure flight, the server 104 calculates various indicator values based on the flight data using an indicator model; the indicator model includes a process indicator model and a transient indicator model; the process indicator model includes a tracking indicator model, an airspeed maintenance indicator model, and a safety margin indicator model; the transient indicator model includes a landing state indicator model, a landing position indicator model, and a controller delay indicator model; based on each of the indicator values and the weighted weights, a comprehensive evaluation value of the flight control performance is determined; the weighted weights are determined based on the variable weight theory using the advantage function. The server 104 can feedback the obtained comprehensive evaluation value to the terminal 102. In addition, in some embodiments, the helicopter flight control performance determination method can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly determine the helicopter flight control performance based on the flight data of the helicopter tail rotor failure flight, or the server 104 can obtain the flight data of the helicopter tail rotor failure flight from the data storage system and determine the helicopter flight control performance based on the flight data of the helicopter tail rotor failure flight.

[0044] Terminal 102 may include, but is not limited to, various desktop computers, laptops, smartphones, tablet computers, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, and smart car devices. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Server 104 may be implemented as a standalone server or a server cluster consisting of multiple servers, or may be a cloud server.

[0045] In an exemplary embodiment, Figure 2 As shown, a method for determining the flight control performance of a helicopter is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. In the embodiment of the present application, the method is applied to Figure 1 Taking the server 104 in FIG. 1 as an example, the method includes the following steps 201 to 203. In which:

[0046] Step 201: Collect flight data of a helicopter with a tail rotor failure.

[0047] Step 202: Calculate each indicator value using an indicator model based on the flight data; the indicator model includes a process indicator model and a transient indicator model; the process indicator model includes a tracking indicator model, an airspeed maintenance indicator model, and a safety margin indicator model; the transient indicator model includes a landing state indicator model, a landing position indicator model, and a controller delay indicator model.

[0048] Step 203: Determine a comprehensive evaluation value of the flight control performance based on the index values and the weighted weights; the weighted weights are determined using a dominance function based on the weighted theory.

[0049] Implementing the above steps 201 to 203 improves the accuracy of evaluating the flight control performance of the helicopter under the condition of a tail rotor failure.

[0050] In an exemplary embodiment of the present application, the indicators in the tracking indicator model include: roll angle tracking indicator, pitch angle tracking indicator, yaw angle tracking indicator and vertical speed tracking indicator; the indicators in the safety boundary indicator model include: angle safety boundary indicator and angular rate safety boundary indicator; the angle safety boundary indicator includes: roll angle safety indicator and pitch angle safety indicator; the angular rate safety boundary indicator includes: roll angular rate safety indicator and pitch angular rate safety indicator.

[0051] In an exemplary embodiment of the present application, the indicators in the landing state index model include: a yaw angle rate index, a flight speed index, a lateral speed index and a vertical speed index; the indicators in the landing position index model include: a longitudinal deviation index and a lateral deviation index.

[0052] In an exemplary embodiment of the present application, the method for determining the weight after weighting specifically includes: obtaining simulated flight data of helicopter simulation or testing and dividing the simulated flight data into indicators; initializing the weight of each indicator using the hierarchical analysis method to obtain the initial weight; determining the indicator dominance set based on the characteristics of the indicator according to the dominance function of the indicator and the flight indicator; the characteristics of the indicator include normalization, continuity and monotonicity; determining the variable weight function according to the indicator dominance set using the incentive-penalty variable weight method; adjusting the initial weight according to the variable weight function to obtain the weight after weighting.

[0053] In practical applications, for different types of helicopters, the flight data of the helicopter is first divided into transient indicators and process indicators, and then the process indicators are divided into tracking indicators, airspeed maintenance indicators and safety boundary indicators. The transient indicators are divided into landing status indicators, landing position indicators and control delay indicators. According to each indicator, each indicator model is constructed, and then the weight of the initialized indicator model is adjusted using the hierarchical analysis method. The weight is adjusted using the variable weight theory to obtain the weight after weighting. When evaluating helicopters of the same type, the constructed indicator model and the weight after weighting are directly used for evaluation.

[0054] In an exemplary embodiment of the present application, the expression of the advantage function is:

[0055]

[0056] Among them, Q j is the dominance of the jth indicator, β is the adjustment factor, which adjusts the degree of influence of the adjustment indicator on the dominance of the indicator. is the distance between the evaluation value and the negative ideal value, is the distance between the evaluation value and the positive ideal value, It is the distance between the positive and negative ideal values of the indicator.

[0057] In an exemplary embodiment of the present application, the expression of the variable weight function is:

[0058]

[0059] Among them, S j (Q j ) represents the variable weight function value of the jth indicator, δ is the variable weight ratio, n is the indicator dimension, is the initial weight, x j is the jth index, S(x j ) is the weight of the j-th indicator, Q + is the set maximum value, Q- is the set minimum value, and j is the indicator number.

[0060] Taking a new type of helicopter as an example, this application provides a specific process of the actual application of a method for determining the flight control performance of a helicopter. First, in view of the particularity of flight with a tail rotor failure, a process indicator model and a transient indicator model are established to form an evaluation indicator set. Then, flight data is collected through flight simulation or testing of the helicopter, and the weights of each evaluation indicator are initialized through the analytic hierarchy process using empirical data. Next, the variable weight theory is introduced to establish a dominance function to achieve real-time adjustment of the weights of each indicator. According to the mathematical model of each indicator and the collected flight data, the corresponding indicator value is calculated, and based on the weighted weights, the comprehensive performance evaluation value of the flight control is comprehensively calculated. This method can effectively evaluate the flight control performance of a helicopter under tail rotor failure, determine the pros and cons of flight control, and provide important theoretical support and practical basis for the design of flight control systems under tail rotor failure conditions. Figure 3 As shown, the following steps are included:

[0061] Step 1, establish Figure 4 The evaluation index set shown in the figure establishes a process index model and a transient index model based on the particularity of tail rotor failure flight.

[0062] Step 2: Collect the flight data of the helicopter through flight simulation or testing of the helicopter, and record the changes in the state of the helicopter during the flight.

[0063] Step 3: Use empirical data to compare each evaluation indicator with each other, and use the hierarchical analysis method to initialize the weight of each indicator.

[0064] Step 4: Considering the characteristics of each indicator, the variable weight theory is introduced to adjust the weight of each indicator in real time by establishing the advantage function.

[0065] Step 5: Calculate the index value based on the mathematical model of each index and the collected flight data.

[0066] Step 6: Calculate the comprehensive evaluation value of the flight control performance based on the values of each evaluation index and the weighted weights.

[0067] The specific contents of step 1 are as follows:

[0068] By analyzing the landing process of a helicopter with a tail rotor failure, an evaluation indicator set was established. In the tail rotor failure flight evaluation, the indicators are divided into process indicators and transient indicators. Process indicators are dynamically changing indicators, including tracking indicators, airspeed maintenance indicators, and safety margin indicators. Transient indicators include landing status indicators, landing position indicators, and controller delay indicators. The indicator set includes:

[0069] 1) Tracking Metrics

[0070] When a helicopter is performing obstacle gliding, it needs to track a specified desired trajectory. The greater the deviation from the desired trajectory, the worse the tracking performance. Tracking indicators include roll angle tracking, pitch angle tracking, yaw angle tracking, and vertical velocity tracking. Let the single state of the helicopter be x(t), the trajectory of this state in the reference trajectory be y(t), and the extreme deviation of the tracking be u x , then the tracking indicator model f at a certain moment btrack (t) Established as:

[0071]

[0072] Since the tracking index needs to be based on the flight time interval [t0,t f ] is calculated. In actual evaluation, the average value needs to be calculated to obtain the final indicator value.

[0073] 2) Airspeed maintenance indicator

[0074] When the helicopter is in the air, the airspeed must be maintained at a certain value. Let the airspeed state of the helicopter be v(t), and the minimum airspeed be l v , speed extreme deviation u v , airspeed maintenance index model f bv (t) Established as:

[0075]

[0076] Among them, c v is the airspeed penalty coefficient. Since the tracking index needs to be based on the flight time interval [t0,t f ] is calculated. In actual evaluation, it is necessary to find the average to obtain the final indicator value.

[0077] 3) Angle safety margin indicator

[0078] When a helicopter is flying, each angle state cannot exceed the safety boundary. For the state that exceeds the safety boundary, a safety boundary indicator is established. The angle safety boundary indicator includes the roll angle safety indicator and the pitch angle safety indicator. Let the helicopter's angle state be a(t) and the safety upper bound be u a , the safety lower bound is l a , the threshold is d a , angle safety margin index model f boundaryA (t) Established as:

[0079]

[0080] Since the angle safety margin index needs to be based on the flight time interval [t0,t f ] is calculated. In actual evaluation, it is necessary to find the average to obtain the final indicator value.

[0081] 4) Angular rate safety margin indicator

[0082] When a helicopter is flying, each angular rate state cannot exceed the safety boundary. For states that exceed the safety boundary, a safety boundary indicator is established. The angular rate safety boundary indicators include the roll angular rate safety indicator and the pitch angular rate safety indicator. Let the angular rate state of the helicopter be b(t), the safety boundary is the value that changes with time t, and the safety upper bound is u b (t), the safety lower bound is l b (t), the maximum safety upper bound is u bm , the minimum safe upper bound is u bl , the maximum safety lower bound is l bm , the minimum safe lower bound is l bl , the maximum time is d b , angular rate safety boundary index model f boundaryB (t) Established as:

[0083]

[0084] Among them, t b is the time value corresponding to the angular rate state on the safety boundary. Since the angular rate safety boundary index needs to be based on the flight time interval [t0,t f ] is calculated. In actual evaluation, it is necessary to find the average to obtain the final indicator value.

[0085] 5) Landing status indicators

[0086] When landing, the helicopter is required to have a yaw rate less than a limit value, a flight speed less than a limit value, a lateral speed less than a limit value, and a vertical speed less than a limit value. The landing state indicators include the yaw rate index, the flight speed index, the lateral speed index, and the vertical speed index. Assume that when landing, a certain state is x m , whose maximum value is limited to u m , landing state index model f br Build as:

[0087]

[0088] Among them, d m Set the indicator value when the landing state is at the boundary.

[0089] 6) Landing position indicator

[0090] When landing, the helicopter is required to have a longitudinal deviation less than the limit value and a lateral deviation less than the limit value. The landing position index includes the longitudinal deviation index and the lateral deviation index. Assume that when landing, a position deviation is x p , whose maximum value is limited to u p , landing position index model fbl Build as:

[0091]

[0092] Among them, d p Set the indicator value when the position deviation is at the boundary.

[0093] 7) Controller latency metrics

[0094] When the helicopter tail rotor fails, the controller is required to delay intervention for at least a certain time. Assume that when the tail rotor fails, the controller intervention time is t l , whose minimum value is l t , and its indicator model is established as:

[0095]

[0096] Among them, d t Set the indicator value when the intervention time is at the boundary.

[0097] The specific contents of step 2 are as follows:

[0098] Through flight simulation or actual flight testing of the helicopter, data on various state changes during flight is collected. Flight simulation provides a low-cost, efficient way to simulate flight performance under different flight environments and fault scenarios. Actual flight testing verifies the accuracy of simulation results and provides more representative data. During flight, various flight state changes related to evaluation indicators are collected. For process indicators, the helicopter's state changes continuously over a time interval are collected; for transient indicators, the helicopter's state at the time of evaluation is collected and used as data for subsequent indicator value calculations.

[0099] The specific contents of step 3 are as follows:

[0100] The Analytic Hierarchy Process (AHP) is used to initially assign weights to evaluation indicators. The AHP divides the indicator set into several levels based on the nature and importance of each indicator in the evaluation problem. Indicators with higher impact are considered high-level indicators, while those with lower impact are considered low-level indicators. Determining the impact of indicators is based on a comparison of their relative importance, effectively improving the accuracy of weighting. The specific process for weighting using the AHP is as follows:

[0101] Step 31: compare the indicators pairwise to determine the relative importance of the two indicators. After the indicators are compared, they are assigned values according to Table 1.

[0102] Table 1 Comparison of quantitative values of indicators

[0103] Degree value The importance of A relative to B 1 / 5 A Extremely minor 1 / 4 A is more secondary than B 1 / 3 A obviously minor 1 / 2 A slightly less important 1 Both are the same 2 A slightly important 3 A is obviously important 4 A is more important than B 5 A is extremely important

[0104] After comparing all indicators with each other, the indicator comparison matrix M is obtained, and the dimension of the matrix M is equal to the indicator dimension n.

[0105] Step 32: Find the maximum eigenvalue of the matrix M.

[0106] First calculate the average value of each row of matrix M The eigenvectors of the matrix M can be obtained in:

[0107]

[0108] Normalizing the mean vector yields the normalized mean vector C = (c1, c2, ..., c n ) T , c i is the normalized average value of each row, where:

[0109]

[0110] Then we can get the maximum eigenvalue λ of the M matrix max for:

[0111]

[0112] Among them, i is the row number and k is the column number.

[0113] Step 33: Determine the matrix consistency. The calculation formula is as follows:

[0114]

[0115] Among them, DI is the consistency index of matrix M. According to experimental experience, the random consistency index RI is obtained as shown in Table 2.

[0116] Table 2 Random consistency corresponding table

[0117] Order RI Order RI Order RI 1 0 5 1.12 9 1.46 2 0 6 1.26 10 1.49 3 0.52 7 1.36 11 1.52 4 0.89 8 1.41 12 1.54

[0118] Then calculate the consistency test index DR as:

[0119]

[0120] If DR is less than 0.1, the consistency test is satisfied. If DR is greater than or equal to 0.1, the process returns to step 31 and performs comparison again after adjusting the importance.

[0121] Step 34: Calculate the eigenvector corresponding to the maximum eigenvalue of the matrix. After obtaining the judgment matrix that satisfies the consistency test, perform unit normalization on the eigenroot of the judgment matrix, and calculate the eigenvector corresponding to the eigenroot using the following formula.

[0122] MW=λmax W

[0123] Among them, λ max Is the largest eigenvalue of the matrix, and W is the eigenvector. Then normalize the eigenvector W to get the initial weight vector in W 0 The i-th weight in , w' i is the i-th weight in W, w' j is the jth weight in W, and T is the matrix transpose symbol.

[0124] The specific contents of step 4 are as follows:

[0125] In helicopter flight control, when flight control is significantly influenced by a particular indicator, the influence of that indicator on the evaluation also increases. Therefore, it is necessary to establish a nonlinear incentive relationship between the indicator value and the weight, so that the weight of the evaluation indicator can be dynamically adjusted as the helicopter state changes. Therefore, variable weight theory is introduced to achieve dynamic performance evaluation of helicopters.

[0126] Suppose there is an evaluation index set (x1, x2, ..., x n ). For n indicators, there is an n-dimensional mapping relationship w j (j=1,2,…,n):[0,1] n →[0,1],(x1,x2,…,x n )|→w j (x1,x2,…,x n ) and satisfy the following relationship:

[0127] Normalization:

[0128] Continuity: w j (x1,x2,…,x n ) is about x j Continuous mapping of , where (j=1,2,…,n);

[0129] Monotonicity: w j (x1,x2,…,x n ) changes monotonically, where (j=1,2,…,n).

[0130] Then we can use the set (x1, x2, ..., x n ) is evaluated by variable weights, and in order to meet the weight determination The requirements of the weight change are:

[0131]

[0132] where wj is the weight value after weight change, represents the initial weight, S(x j ) is determined by the variable weight function.

[0133] In variable weight theory, the change in indicator weights is determined by the dominance of the indicator function. Since this is an evaluation of helicopter flight control, the importance of a particular indicator is primarily positively correlated with flight performance. Combining this with the ideal solution, the dominance function for flight indicators is established as shown below.

[0134]

[0135] Among them, Q j is the dominance of the jth indicator, g and h are both structural coefficients. β is the adjustment factor, which adjusts the degree of influence of the adjustment indicator on the dominance of the indicator. is the distance between the evaluation value and the negative ideal value, is the distance between the evaluation value and the positive ideal value, It is the distance between the positive and negative ideal values of the indicator.

[0136] In order to simplify the evaluation process as much as possible, the evaluation values of the indicators are normalized. Therefore, the difference between the distance between the evaluation value of the indicator and the negative ideal value and the distance between the evaluation value of the indicator and the positive ideal value is in the range of (-1, 1), while the distance between the positive ideal value and the negative ideal value is 1. So we can get:

[0137]

[0138] Solving the above equations yields:

[0139]

[0140]

[0141] Therefore, the advantage function can be obtained:

[0142]

[0143] When evaluating flight control, we should pay attention to the value of the adjustment factor so that the change of the dominance meets the actual requirements. n ) into the formula, we can get the evaluation index advantage set {Q1,Q2,…,Q n}.

[0144] After determining the indicator dominance, we can further establish the relationship between indicator dominance and weight. Specifically, we can use indicator dominance to determine the degree of change in the indicator weight. We employ an incentive-penalty variable weighting approach. For each evaluation indicator, we establish incentive and penalty ranges. We penalize indicator weights whose values exceed the limits, increasing their weights and thus their impact on the evaluation results. The variable weighting function uses an exponentially increasing penalty method and an exponentially decreasing incentive method. We do not process indicator weights whose values fall between the upper incentive limit and the lower penalty limit.

[0145] The variable weight function established above is:

[0146]

[0147] Among them, S j (Q j ) represents the variable weight function value of the jth indicator, which is the variable weight proportion. is the initial weight. At this time, the variable weight function value set of the index can be obtained as {S(x1),S(x2),…,S(x n )}, and normalization can be performed to obtain the final weight set.

[0148] The specific contents of step 5 are as follows:

[0149] Based on the collected process data, the indicator value at each moment along the time interval is calculated, and then the average is taken to obtain the final value of each process indicator. For transient indicators, the indicator value is directly calculated based on the indicator model.

[0150] The specific contents of step 6 are as follows:

[0151] Based on the values of each evaluation index and the weighted values, the comprehensive performance evaluation value of the flight control system is calculated. This comprehensive evaluation value reflects the overall performance of the helicopter flight control under the condition of tail rotor failure.

[0152] The present application includes the following steps: 1. Establishing an evaluation index set, and establishing a process index model and a transient index model in view of the particularity of flight under tail rotor failure; 2. Collecting helicopter flight data through helicopter flight simulation or testing; 3. Initializing the weights of each index using the hierarchical analysis method based on empirical data; 4. Introducing variable weight theory, and adjusting the weights of each index in real time by establishing a dominance function; 5. Calculating the index value based on the mathematical model of each index and the collected flight data; 6. Using the weighted weights based on the values of each evaluation index, calculating the comprehensive evaluation value of the flight control performance. This application addresses the problem of evaluating the flight control performance of a helicopter under tail rotor failure, proposes a method for evaluating flight control, determines the pros and cons of flight control performance, and provides the necessary foundation for the flight control system of a helicopter under tail rotor failure.

[0153] The present application also provides an application scenario, which adopts the above-mentioned method for determining the flight control performance of a helicopter. Specifically: The method for determining the flight control performance of a helicopter provided in this embodiment can be applied to the helicopter flight controller evaluation scenario under tail rotor failure. The helicopter flight controller evaluation scenario includes flight data collection, flight index calculation and controller comprehensive evaluation links. The flight data is collected from the helicopter's sensors into the evaluation device, and then the various evaluation indicators of the flight control are calculated, the weights are determined according to the variable weight function, and finally a comprehensive evaluation value is obtained. This implementation belongs to the flight control evaluation link under tail rotor failure in helicopter flight control.

[0154] Based on the same inventive concept, embodiments of the present application also provide a device for determining helicopter flight control performance, for implementing the aforementioned method for determining helicopter flight control performance. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for determining helicopter flight control performance provided below can be found in the aforementioned definition of the method for determining helicopter flight control performance, and will not be further elaborated here.

[0155] In an exemplary embodiment, a device for determining helicopter flight control performance is provided, comprising:

[0156] An acquisition module is used to collect flight data of helicopter tail rotor failure flights;

[0157] an indicator calculation module, configured to calculate various indicator values based on the flight data using an indicator model; the indicator model includes a process indicator model and a transient indicator model; the process indicator model includes a tracking indicator model, an airspeed holding indicator model, and a safety margin indicator model; the transient indicator model includes a landing state indicator model, a landing position indicator model, and a controller delay indicator model;

[0158] The comprehensive evaluation value determination module is used to determine the comprehensive evaluation value of the flight control performance according to each of the index values and the weighted weights; the weighted weights are determined based on the variable weight theory using the advantage function.

[0159] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 5As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store helicopter flight control performance data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining helicopter flight control performance is implemented.

[0160] Those skilled in the art will understand that Figure 5 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application and does not constitute a limitation on the computer device to which the solution of the present application is applied. A specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the above-mentioned method embodiments when executing the computer program.

[0161] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the above-mentioned method embodiments when executed by a processor.

[0162] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the above method embodiments are implemented.

[0163] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0164] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0165] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0166] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0167] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for determining helicopter flight control performance, characterized in that: The helicopter flight control performance determination method comprises: Collect flight data of helicopter tail rotor failure flight; Calculating each indicator value using an indicator model based on the flight data; the indicator model includes a process indicator model and a transient indicator model; the process indicator model includes a tracking indicator model, an airspeed holding indicator model, and a safety margin indicator model; the transient indicator model includes a landing state indicator model, a landing position indicator model, and a controller delay indicator model; A comprehensive evaluation value of the flight control performance is determined based on the index values and the weights after weight change; the weights after weight change are determined using a dominance function based on a weight change theory.

2. The method for determining helicopter flight control performance according to claim 1, wherein: The indicators in the tracking indicator model include: roll angle tracking indicator, pitch angle tracking indicator, yaw angle tracking indicator and vertical speed tracking indicator; the indicators in the safety boundary indicator model include: angle safety boundary indicator and angular rate safety boundary indicator; the angle safety boundary indicator includes: roll angle safety indicator and pitch angle safety indicator; the angular rate safety boundary indicator includes: roll angular rate safety indicator and pitch angular rate safety indicator.

3. The method for determining helicopter flight control performance according to claim 1, wherein: The indicators in the landing state indicator model include: a yaw angle rate indicator, a flight speed indicator, a lateral speed indicator, and a vertical speed indicator; the indicators in the landing position indicator model include: a longitudinal deviation indicator and a lateral deviation indicator.

4. The method for determining helicopter flight control performance according to claim 1, wherein: The method for determining the weight after the weight change specifically includes: Acquiring simulated flight data for helicopter simulation or testing and dividing the simulated flight data into indicators; The weight of each indicator is initialized using the hierarchical analysis method to obtain the initial weight; Determining an indicator dominance set based on the characteristics of the indicator according to the indicator and the dominance function of the flight indicator; the characteristics of the indicator including normalization, continuity and monotonicity; Determine the variable weight function by adopting the incentive-penalty variable weight method according to the indicator advantage set; The initial weight is adjusted according to the variable weight function to obtain a weighted weight.

5. The method for determining helicopter flight control performance according to claim 1, wherein: The expression of the advantage function is: Among them, Q j is the dominance of the jth indicator, β is the adjustment factor, which adjusts the degree of influence of the adjustment indicator on the dominance of the indicator. is the distance between the evaluation value and the negative ideal value, is the distance between the evaluation value and the positive ideal value, It is the distance between the positive and negative ideal values of the indicator.

6. The method for determining helicopter flight control performance according to claim 4, characterized in that: The expression of the variable weight function is: Among them, S j (Q j ) represents the variable weight function value of the jth indicator, δ is the variable weight ratio, n is the indicator dimension, is the initial weight, Q j is the indicator dominance, x j is the jth index, S(x j ) is the weight of the j-th indicator, Q + is the maximum value set, Q - is the set minimum value, and j is the indicator number.

7. A device for determining helicopter flight control performance, characterized in that: The helicopter flight control performance determination device comprises: An acquisition module is used to collect flight data of helicopter tail rotor failure flights; an indicator calculation module, configured to calculate various indicator values based on the flight data using an indicator model; the indicator model includes a process indicator model and a transient indicator model; the process indicator model includes a tracking indicator model, an airspeed holding indicator model, and a safety margin indicator model; the transient indicator model includes a landing state indicator model, a landing position indicator model, and a controller delay indicator model; The comprehensive evaluation value determination module is used to determine the comprehensive evaluation value of the flight control performance according to each of the index values and the weighted weights; the weighted weights are determined based on the variable weight theory using the advantage function.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining the flight control performance of a helicopter according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining the flight control performance of a helicopter according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for determining the flight control performance of a helicopter according to any one of claims 1 to 6 is implemented.

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