Layered optimization method for dynamic control law of aero-engine

Abstract

The invention discloses a layered optimization method for a dynamic control rule of an aero-engine, and belongs to the field of aero-engines. The method comprises the following steps: determining control parameter values and controlled parameter values of a starting point and an ending point of a dynamic process of an engine; engine dynamic control rule optimization without consideration of a controller is carried out; solving the optimization problem by using a differential evolution algorithm, wherein an obtained optimization result is a theoretical optimal curve of an engine dynamic control rule without considering controller response; selecting a control parameter by utilizing the optimal solution of the output theory of the controller in combination with simulation of a control system, and carrying out controller input instruction optimization of the parameter; an optimization result obtained by solving is an engine dynamic control rule curve of the combined controller; and judging whether a control rule curve of all the control parameters is obtained or not, and completing optimization. According to the method, the solving difficulty of the optimization problem is reduced, the optimization efficiency is improved, and the technical difficulty that the optimization result has oscillation when only one optimization problem exists is solved.

Description

Technical Field

[0001] The invention belongs to the field of aeroengines, and in particular relates to a hierarchical optimization method for dynamic control laws of aeroengines. Background Art

[0002] For aircraft engines, the optimization design of engine dynamic control laws is of great significance to the final performance of the engine. At present, the optimization design of engine dynamic control laws is generally divided into two steps: first, the control law optimization design is carried out based on the overall performance, and the optimal control law is passed to the control system after it is obtained. If the control result output after the controller responds can meet the requirements, it is considered that the control law can be adopted. Otherwise, the control law needs to be readjusted and then tested by the control system until the output of the control system can meet the response requirements of the engine dynamic process. This method separates the overall performance simulation and the control system simulation. The response characteristics of the control system are not taken into account in the process of optimizing the control law design, so there is no way to fully explore the performance potential of the engine in the dynamic process.

[0003] Since the response characteristics of the control system are taken into account, the optimization results obtained when carrying out the optimization design of the dynamic control law often have oscillations and cannot be directly applied to the dynamic process control of the engine. Therefore, it is necessary to develop a new optimization method for the dynamic control law of the engine, which can not only consider the response characteristics of the control system when optimizing the dynamic control law, but also reduce the difficulty of solving the optimization problem and solve the technical difficulties of oscillations in the optimization results. Summary of the invention

[0004] Technical issues to be solved:

[0005] In order to avoid the shortcomings of the prior art, the present invention provides a hierarchical optimization method for the dynamic control law of an aircraft engine. The present invention decomposes the optimization problem of the dynamic control law of an aircraft engine of a joint controller into two sub-optimization problems. The minimum error between the actual output of the controller and the theoretical optimal solution is the first optimization goal, and the smoothness of the input command of the controller is the second optimization goal. In this way, a multi-objective optimization problem is constructed, and the optimization problem is solved using a differential evolution algorithm. The input command of the controller is obtained as the dynamic control law curve of the aircraft engine of the joint controller. The present invention can consider the response characteristics of the control system when optimizing the dynamic control law of the engine, and solve the problem of oscillation in the optimization result.

[0006] The technical solution of the present invention is: a hierarchical optimization method for dynamic control laws of aircraft engines, the specific steps are as follows:

[0007] Determine the control parameters and controlled parameters of the engine dynamic process;

[0008] Carry out steady-state performance optimization of aircraft engines to obtain the control parameter values ​​and controlled parameter values ​​at the starting and ending points of the engine dynamic process;

[0009] Construct optimization problems and optimize the dynamic control law of the engine without considering the controller;

[0010] The differential evolution algorithm is used to solve the optimization problem of the engine dynamic control law without considering the controller. The optimization result is the theoretical optimal curve of the engine dynamic control law without considering the controller response. If the dynamic control law is optimized by the joint controller, the output result of the control parameter after the controller response must be based on the theoretical optimal curve.

[0011] Using the theoretical optimal solution of the controller output obtained above, combined with the control system simulation, a control parameter is selected and the controller input command optimization of the parameter is carried out;

[0012] A differential evolution algorithm is used to solve the controller input instruction optimization problem, and the obtained optimization result is an engine dynamic control law curve of the joint controller;

[0013] Determine whether the control law curves of all control parameters are obtained. If so, the optimization is completed, and the control law curve of the control parameters obtained is the dynamic control law curve of the aircraft engine of the joint controller; if not, continue to select control parameters, use the differential evolution algorithm to solve the controller input instruction optimization problem, and repeat the cycle until the control law curves of all control parameters are obtained and the optimization is completed.

[0014] A further technical solution of the present invention is: the control parameters refer to parameters that can control the working state of the engine, including adjustable geometric parameters of the engine and fuel flow; the controlled parameters are performance parameters of the engine, including thrust and high-pressure / low-pressure physical speed.

[0015] A further technical solution of the present invention is that the steady-state performance optimization of the aero-engine is carried out using a differential evolution algorithm.

[0016] A further technical solution of the present invention is: the objective function expression of the engine dynamic control law without considering the controller is as follows:

[0017]

[0018] Where J[k] represents the objective function of the kth time step; P[k+1] represents the performance parameter value after the kth time step; P obj Indicates the target value of the performance parameter; P start represents the starting value of the performance parameter; X[j] k+1 represents the value of the jth adjustable parameter after the kth time step; X[j]obj represents the target value of the jth adjustable parameter, which is equal to the value of the steady-state adjustable parameter corresponding to the target value of the performance parameter; X[j] up and X[j] low denote the upper and lower limits of the jth adjustable parameter respectively; D denotes the number of adjustable parameters; ω denotes the weight factor; the first term on the right side of the equal sign of the expression indicates that P[k+1] needs to be as close to its target value as possible in each time step, and the second term on the right side of the equal sign indicates that X[j] k+1 As close to its target value as possible; when X[j] k+1 When it approaches its target value, it will also cause P[k+1] to approach its target value.

[0019] A further technical solution of the present invention is: the optimization parameters of the controller input instruction optimization process are the input instructions of each parameter controller, and the starting value and the ending value thereof are the steady-state input instructions of the controller.

[0020] A further technical solution of the present invention is: the objective function expression of the controller input instruction optimization problem is as follows:

[0021]

[0022] Where J[k] represents the objective function of the kth time step; P[k+1] represents the actual output value of the controller after the kth time step; P best [k+1] represents the theoretical optimal output value of the controller after the kth time step; P obj The target value of the actual output value of the controller, that is, the final value of the control parameter; P start represents the starting value of the control parameter; R[k+1] represents the rate of change of the controller input command after the kth time step ends, R obj Indicates the target value of the controller input command change rate; ω E The weight factor representing the relative error between the actual output value of the controller and the theoretical optimal output value, ω R Represents the weight factor of the controller input command change rate; the first item on the right side of the equal sign in this expression indicates that the actual output value of the controller in each time step is as close to its theoretical optimal value as possible; the second item on the right side of the equal sign indicates that the controller input command change rate is as close to its target value as possible, in order to ensure the smoothness of the input command; the third item on the right side of the equal sign indicates that the actual output value of the controller is as close to its target value as possible, which is to ensure the rapidity of the dynamic control law.

[0023] An aircraft engine dynamic control law hierarchical optimization system, comprising an engine dynamic process simulation model, an aircraft engine steady-state performance optimization model, an engine dynamic control law optimization model, and a controller input instruction optimization model;

[0024] Determine engine dynamic process control parameter values ​​and controlled parameter values ​​based on an engine dynamic process simulation model;

[0025] Through the aircraft engine steady-state performance optimization model, the control parameter values ​​and controlled parameter values ​​of the starting and ending points of the engine dynamic process are obtained;

[0026] The engine dynamic control law optimization model is used to solve the engine dynamic control law optimization problem without a controller, and the theoretical optimal curve of the engine dynamic control law without considering the controller response is obtained;

[0027] The controller input command optimization problem is solved through the controller input command optimization model, and the optimization result obtained is the engine dynamic control law curve of the joint controller.

[0028] An electronic device comprises at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the hierarchical optimization method of the dynamic control law of the aircraft engine.

[0029] A computer-readable digital storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the hierarchical optimization method for dynamic control laws of an aircraft engine when the instructions are executed.

[0030] Beneficial Effects

[0031] The beneficial effect of the present invention is that the hierarchical optimization method of the aircraft engine dynamic control law of the present invention decomposes the optimization problem of the aircraft engine dynamic control law of the joint controller into two sub-optimization problems. After completing the first sub-optimization problem and obtaining the theoretical output optimal solution of the controller, the control law curve change rate, smoothness and other indicators are introduced into the objective function of the second sub-optimization problem. By decomposing the joint optimization problem of the two systems and reconstructing the objective function of the reverse optimization of the control system, the overall difficulty of solving the optimization problem is reduced, and the technical difficulty of the oscillation of the optimization result can be effectively solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic flow chart of a hierarchical optimization method for dynamic control laws of an aircraft engine which can be selected in an embodiment of the present invention;

[0033] Figure 2The control law curve of the combustion chamber fuel supply quantity of the single-shaft turbojet engine acceleration process of the joint controller is obtained by directly solving the optimization problem without using the method proposed by the present invention;

[0034] Figure 3 It is the control law curve of the fuel supply to the combustion chamber during the acceleration process of a single-shaft turbojet engine without considering the controller response, that is, the theoretical optimal solution of the output of the fuel controller;

[0035] Figure 4 The invention adopts the hierarchical optimization method proposed in the present invention to solve the optimization problem and obtains the control law curve of the combustion chamber command fuel supply quantity of the joint controller in the acceleration process of the single-shaft turbojet engine. DETAILED DESCRIPTION

[0036] The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0037] Based on the technical problems such as the difficulty in solving existing optimization problems and the oscillation of optimization results, the present invention provides a hierarchical optimization method for dynamic control laws of aircraft engines, and the specific steps are as follows:

[0038] Step 1: Determine the control parameters and controlled parameters of the engine dynamic process;

[0039] Step 2: Carry out steady-state performance optimization of the aircraft engine to obtain the control parameter values ​​and controlled parameter values ​​of the starting and ending points of the engine dynamic process;

[0040] Step 3: Construct an optimization problem and optimize the dynamic control law of the engine without considering the controller.

[0041] Step 4: Use the differential evolution algorithm to solve the optimization problem in step 3. The optimization result obtained is the theoretical optimal curve of the engine dynamic control law without considering the controller response. If the joint controller is used to optimize the dynamic control law, the result of the control parameter output after the controller response must be based on the theoretical optimal curve. Therefore, the optimization result obtained in this step is the theoretical optimal solution of the controller output;

[0042] Step 5: Using the theoretical optimal solution of the controller output in step 4, combined with the control system simulation, select a control parameter and carry out the optimal design of the controller input command for the parameter.

[0043] Step 6: Use the differential evolution algorithm to solve the optimization problem in step 5, and the optimization result obtained is the engine dynamic control law curve of the joint controller;

[0044] Step 7: Determine whether the control law curves of all control parameters are obtained, if so, go to step 8, otherwise go to step 5;

[0045] Step 8: The control law curve of the optimized control parameters is the dynamic control law curve of the aircraft engine of the joint controller.

[0046] The invention discloses a hierarchical optimization system for dynamic control laws of an aero-engine, comprising an engine dynamic process simulation model, an aero-engine steady-state performance optimization model, an engine dynamic control law optimization model, and a controller input instruction optimization model; determining engine dynamic process control parameter values ​​and controlled parameter values ​​based on the engine dynamic process simulation model; obtaining control parameter values ​​and controlled parameter values ​​at the starting point and the ending point of the engine dynamic process through the aero-engine steady-state performance optimization model; solving the engine dynamic control law optimization problem without a controller through the engine dynamic control law optimization model, and obtaining a theoretical optimal curve of the engine dynamic control law without considering the controller response; solving the controller input instruction optimization problem through the controller input instruction optimization model, and obtaining an optimization result that is an engine dynamic control law curve of a joint controller.

[0047] The present invention provides an electronic device, comprising at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the hierarchical optimization method of the dynamic control law of the aircraft engine.

[0048] The present invention provides a computer-readable digital storage medium, wherein the computer-readable digital storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the hierarchical optimization method for dynamic control laws of an aircraft engine when the processor executes the computer instructions.

[0049] The above technical solution is further described below with reference to the accompanying drawings and examples:

[0050] Reference Figure 1 As shown, this embodiment provides a hierarchical optimization method for dynamic control laws of an aircraft engine, and the specific steps are as follows:

[0051] Step 1: Determine the control parameters and controlled parameters of the engine dynamic process. The control parameters refer to the parameters that can control the working state of the engine. Taking a single-shaft turbojet engine as an example, assuming that it has no adjustable geometric structure, the control parameter of the single-shaft turbojet engine is only the fuel supply to the combustion chamber, and the controlled parameter is the thrust.

[0052] Step 2: Carry out steady-state performance optimization of the single-shaft turbojet engine to obtain the optimal fuel flow and thrust values ​​when the engine is in slow and intermediate states.

[0053] Step three: Optimize the design of the control law of the acceleration process of a single-shaft turbojet engine with a joint fuel controller. The optimization parameter during the acceleration process is the input command of the fuel controller, hereinafter referred to as the combustion chamber command fuel supply. The output command of the fuel controller is referred to as the combustion chamber fuel supply. The starting value and ending value of the combustion chamber command fuel supply are the values ​​of the combustion chamber fuel supply in the slow state and the intermediate state, respectively. In order to ensure stable and safe operation of the engine during acceleration, the following constraints are set: the relative physical speed and relative converted speed of the compressor shall not exceed 100%, the compressor surge margin shall not be less than 15%, the total temperature at the combustion chamber outlet shall not exceed 1700K, and the change rate of the combustion chamber command fuel supply shall not exceed 10kg / s 2 , The rate of change of fuel supply to the combustion chamber shall not exceed 2kg / s 2 The objective function for optimizing the control law of the acceleration process of a single-shaft turbojet engine is as follows:

[0054]

[0055] Where J[k] represents the objective function of the kth time step; P[k+1] represents the thrust value after the kth time step; P obj Indicates the target value of thrust; P start represents the starting value of thrust; X[k+1] represents the value of the fuel supply of the combustion chamber after the kth time step; X obj Indicates the target value of the fuel supply to the combustion chamber; X up and X low They represent the upper and lower limits of the j-th adjustable parameter respectively; ω represents the weight factor. When the thrust change does not reach 95% of its total change, ω is taken as 0, and ω is taken as 0.8 at other times.

[0056] Step 4: Directly use the differential evolution algorithm to solve the optimization problem in step 3. The optimization result is the control law curve of the combustion chamber command fuel supply during the acceleration process of the single-shaft turbojet engine of the joint controller, such as Figure 2 As shown in the figure, it can be seen that the combustion chamber command fuel supply curve has very serious oscillations and cannot be directly input to the fuel controller, so the hierarchical optimization method proposed in the present invention must be adopted.

[0057] Step 5: Optimize the design of the control law for the acceleration process of a single-axis turbojet engine without considering the controller response. At this time, the fuel supply to the combustion chamber is the command fuel supply to the combustion chamber. Therefore, it is only necessary to replace the optimization parameters in step 3 with the fuel supply to the combustion chamber and remove the restriction on the rate of change of the command fuel supply to the combustion chamber in the constraint. At this time, X in the formula in step 3 represents the value of the fuel supply to the combustion chamber.

[0058] Step 6: Use the differential evolution algorithm to solve the optimization problem in step 5. The optimization result is the control law curve of the combustion chamber fuel supply during the acceleration process of the single-shaft turbojet engine without considering the controller response, that is, the theoretical optimal solution of the controller output, such as Figure 3 shown.

[0059] Step 7: Use the theoretical optimal solution of the fuel controller output obtained in step 6 to optimize the input command of the fuel controller. The optimization parameter is the input command of the fuel controller, that is, the fuel supply of the combustion chamber, and its starting value and ending value are the same as those in step 3. Since this optimization does not require calling the engine performance calculation model, the only constraint parameter left is: the change rate of the fuel supply of the combustion chamber command does not exceed 10kg / s 2 The objective function of the optimization problem is as follows:

[0060]

[0061] Where J[k] represents the objective function of the kth time step; P[k+1] represents the value of the combustion chamber command fuel supply after the kth time step; P best [k+1] represents the theoretical optimal output value of the fuel controller after the kth time step; P obj The target value of the actual output value of the fuel controller, that is, the end value of the fuel supply command of the combustion chamber; P start represents the starting value of the fuel supply of the combustion chamber; R[k+1] represents the value of the change rate of the fuel supply of the combustion chamber after the kth time step. obj Indicates the target value of the rate of change of the combustion chamber command fuel supply; ω E The weight factor representing the relative error between the actual output value of the fuel controller and the theoretical optimal output value, ω R The weight factor representing the rate of change of the fuel supply command of the combustion chamber. When the thrust change does not reach 95% of its total change, ω E Take it as 0.7, ω R Take it as 0.2, and the rest of the time ω E and ω R All are taken as 0.

[0062] Step 8: Use the differential evolution algorithm to solve the optimization problem in step 7. The optimization result is the control law curve of the combustion chamber command fuel supply, that is, the control law curve of the combustion chamber fuel supply during the acceleration process of the single-axis turbojet engine combined with the fuel controller, such as Figure 4 As shown in the figure, it can be seen that the combustion chamber fuel supply control law curve is very smooth, and there is only a small "overshoot phenomenon" at the end of the optimization. Therefore, the hierarchical optimization method proposed in the patent of this invention can well solve the problem of oscillation of the optimization result in step four.

[0063] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and intent of the present invention.

Claims

1. A hierarchical optimization method for dynamic control laws of aircraft engines, characterized in that The specific steps are as follows: Determine the control parameters and controlled parameters of the engine dynamic process; Carry out steady-state performance optimization of aircraft engines to obtain the control parameter values ​​and controlled parameter values ​​at the starting and ending points of the engine dynamic process; Construct optimization problems and optimize the dynamic control law of the engine without considering the controller; The differential evolution algorithm is used to solve the optimization problem of the engine dynamic control law without considering the controller. The optimization result is the theoretical optimal curve of the engine dynamic control law without considering the controller response. If the dynamic control law is optimized by the joint controller, the output result of the control parameter after the controller response must be based on the theoretical optimal curve. Using the theoretical optimal solution of the controller output obtained above, combined with the control system simulation, a control parameter is selected and the controller input command optimization of the parameter is carried out; A differential evolution algorithm is used to solve the controller input instruction optimization problem, and the obtained optimization result is an engine dynamic control law curve of the joint controller; Determine whether the control law curves of all control parameters are obtained. If so, the optimization is completed, and the control law curve of the control parameters obtained is the dynamic control law curve of the aircraft engine of the joint controller; if not, continue to select control parameters, use the differential evolution algorithm to solve the controller input instruction optimization problem, and repeat the cycle until the control law curves of all control parameters are obtained and the optimization is completed.

2. The hierarchical optimization method for dynamic control laws of an aircraft engine according to claim 1, characterized in that: The control parameters refer to parameters that can control the working state of the engine, including adjustable geometric parameters of the engine and fuel flow; the controlled parameters are performance parameters of the engine, including thrust and high-pressure / low-pressure physical speed.

3. The hierarchical optimization method for dynamic control laws of an aircraft engine according to claim 2, characterized in that: The steady-state performance optimization of the aero-engine is carried out using a differential evolution algorithm.

4. The hierarchical optimization method for dynamic control laws of an aircraft engine according to claim 3, characterized in that: The objective function expression of the engine dynamic control law without considering the controller is as follows: Where J[k] represents the objective function of the kth time step; P[k+1] represents the performance parameter value after the kth time step; P obj Indicates the target value of the performance parameter; P start represents the starting value of the performance parameter; X[j] k+1 represents the value of the jth adjustable parameter after the kth time step; X[j] obj represents the target value of the jth adjustable parameter, which is equal to the value of the steady-state adjustable parameter corresponding to the target value of the performance parameter; X[j] up and X[j] low denote the upper and lower limits of the jth adjustable parameter respectively; D denotes the number of adjustable parameters; ω denotes the weight factor; the first term on the right side of the equal sign of the expression indicates that P[k+1] needs to be as close to its target value as possible in each time step, and the second term on the right side of the equal sign indicates that X[j] k+1 Get as close to its target value as possible; When X[j] k+1 When it approaches its target value, it will also cause P[k+1] to approach its target value.

5. The hierarchical optimization method for dynamic control laws of an aircraft engine according to claim 4, characterized in that: The optimization parameters of the controller input instruction optimization process are the input instructions of each parameter controller, and the starting value and the ending value thereof are the steady-state input instructions of the controller.

6. The hierarchical optimization method for dynamic control laws of an aircraft engine according to claim 5, characterized in that: The objective function expression of the controller input instruction optimization problem is as follows: Where J[k] represents the objective function of the kth time step; P[k+1] represents the actual output value of the controller after the kth time step; P best [k+1] represents the theoretical optimal output value of the controller after the kth time step; P obj The target value of the actual output value of the controller, that is, the final value of the control parameter; P start represents the starting value of the control parameter; R[k+1] represents the rate of change of the controller input command after the kth time step ends, R obj Indicates the target value of the controller input command change rate; ω E The weight factor representing the relative error between the actual output value of the controller and the theoretical optimal output value, ω R The weight factor representing the rate of change of the controller input command; The first item on the right side of the equal sign in this expression indicates that the actual output value of the controller in each time step is as close to its theoretical optimal value as possible; the second item on the right side of the equal sign indicates that the input command change rate of the controller is as close to its target value as possible, in order to ensure the smoothness of the input command; the third item on the right side of the equal sign indicates that the actual output value of the controller is as close to its target value as possible, which is to ensure the rapidity of the dynamic control law.

7. A hierarchical optimization system for dynamic control laws of aircraft engines, characterized by: Used to implement the hierarchical optimization method for dynamic control laws of aircraft engines as described in any one of claims 1 to 6; Including engine dynamic process simulation model, aviation engine steady-state performance optimization model, engine dynamic control law optimization model, controller input instruction optimization model; Determine engine dynamic process control parameter values ​​and controlled parameter values ​​based on an engine dynamic process simulation model; Through the aircraft engine steady-state performance optimization model, the control parameter values ​​and controlled parameter values ​​of the starting and ending points of the engine dynamic process are obtained; The engine dynamic control law optimization model is used to solve the engine dynamic control law optimization problem without a controller, and the theoretical optimal curve of the engine dynamic control law without considering the controller response is obtained; The controller input command optimization problem is solved through the controller input command optimization model, and the optimization result obtained is the engine dynamic control law curve of the joint controller.

8. An electronic device, characterized in that: It includes at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the hierarchical optimization method for dynamic control laws of an aircraft engine as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the hierarchical optimization method for dynamic control laws of an aircraft engine as described in any one of claims 1-6 when executed.

Images