CN116513467A - High-speed aircraft optimal control method considering air inlet safety - Google Patents
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Abstract
The invention discloses a high-speed aircraft optimization control method considering air intake safety, which comprises the steps of firstly converting a nonlinear coupling model of a high-speed aircraft into a standard form facing control, establishing a finite time tracking controller, and ensuring the control stability of the aircraft; secondly, establishing a safety set for describing the safety condition of the air inlet channel of the high-speed aircraft aiming at the safety constraint and the dynamics characteristic of the high-speed aircraft, and constructing a control barrier function for guaranteeing the forward invariance of the safety set; in order to make the barrier function pay as small control performance cost as possible in the process of achieving the safety condition, the control barrier function is introduced into an optimization equation as a safety factor through expanding a state space, and a value function description optimization problem capable of comprehensively integrating tracking performance, input cost and safety constraint is constructed. In order to save the calculation cost, the single evaluation neural network is designed to approach the optimal control law, and the control performance is optimized on the premise of ensuring the safety of the system.
Description
Technical Field
The invention belongs to the field of design of longitudinal cruise control of an air suction type high-speed aircraft, and particularly relates to an optimization control method of the high-speed aircraft considering air inlet safety.
Background
Spacecraft have recently received attention from aerospace institutions and space exploration companies. High speed aircraft with thrust provided by scramjet engines are considered by the industry as an emerging technology that is reliable, efficient, and economical. The aircraft provides oxygen required by combustion through the inhaled air flow, does not need to carry an oxidant in the flight process, and improves the effective load. Meanwhile, the wave multiplier body structure is adopted to provide the flying lift force, so that the transportation cost is reduced. However, during the intake of the air flow, external intake conditions of the intake duct of the scramjet engine need to be ensured. Specifically, the safety control is to ensure that the flight speed and attack angle of the aircraft are within certain safety constraints, so that the engine air inlet is always kept in a starting state. Generally, the speed safety constraint of a high-speed aircraft can be simply realized by tracking reference instructions with high precision, but the problem of the safety constraint of the attack angle is difficult to solve. Because the attack angle is used as the included angle between the longitudinal machine body reference line and the incoming flow direction, the aerodynamic force and the moment are widely influenced, and therefore, the aircraft has to cooperate with the longitudinal maneuvering requirement of the aircraft while meeting the safety constraint, and the two major factors of tracking control performance and system safety are comprehensively planned, so that the aircraft control system provides new problems and challenges for the flight controller.
The primary premise of flight safety is to ensure the control stability of the aircraft in the track tracking process. However, the advanced aerodynamic profile of the high-speed air craft and the integrated design of the fuselage-propulsion device create highly nonlinear and strongly coupled characteristics of its mathematical model, and furthermore the perturbation of the aerodynamic parameters and the uncertainty of the external environment add further difficulties to the controller design. To address these issues, existing high speed aircraft control methods focus on the robustness and tracking performance of the flight controller, such as feedback linearization control, dynamic inverse control, sliding mode control, auto-disturbance rejection control, finite time control, and the like. The problems of track tracking control and stability of the aircraft can be solved to a certain extent by the aid of the scheme, but safety constraint is not considered, and requirements of control performance and air inlet safety of the aircraft cannot be met at the same time.
On the basis of controlling stability, the existing preset performance control method and the control method based on the barrier Lyapunov function are commonly used for solving the control constraint problem of the high-speed aircraft. The general idea of such a method is generally divided into two steps: firstly, a conservative safety reference instruction is constructed through artificial constraint, then the safety constraint problem is converted into a safety error tracking problem, and the tracking error is constrained forcedly through a preset performance control method and a control method based on an obstacle Lyapunov function, so that the tracking error is ensured to be constrained strictly in a preset error band.
While existing methods can directly obtain viable solutions that meet security constraints, there are still some problems that require improved optimization. On the one hand, the preset performance control method and the control method based on the barrier Lyapunov function take an artificially preset error band as a constraint boundary instead of adopting a safety constraint boundary in the original safety problem. For optimization problems, this reduces the scope of the search for knowledge to some extent. On the other hand, it is difficult to accurately preset the absolute safety command and error band in advance for aircraft systems with unknown uncertainty. Therefore, these artificial designs requiring offline preset links generally have a certain conservation. In addition, the adoption of the barrier function can forcedly ensure that the error precision is very likely to cause the oscillation of control and even the input saturation phenomenon under an uncertain environment.
Disclosure of Invention
Aiming at the defects or improvement demands of the prior art, the invention provides a high-speed aircraft optimization control method considering air inlet safety, and the design of a controller can be used for further optimizing performance under the condition of guaranteeing the external air inlet condition of an air inlet channel of a scramjet engine based on a control obstacle function and self-adaptive dynamic programming in the track tracking process of an air suction type high-speed aircraft.
To achieve the above object, according to a first aspect of the present invention, there is provided a high-speed aircraft optimization control method considering intake air safety, comprising:
s1, constructing a finite time tracking controller of an aircraft according to a kinetic equation and a tracking error of the aircraft;
s2, safety constraint according to attack angle aDetermining a security constraint function->To construct a control barrier function->
Wherein,, in order to balance the angle of attack,
s3, adding the components into an attack angle control channel of the controllerCorrecting the controller, and controlling the speed and the altitude of the aircraft based on the corrected controller;
wherein,,e α for tracking error of angle of attack, +.>The method comprises the steps of respectively evaluating an observation weight and an activation function of a neural network; the evaluation neural network is used for observing a value function of sigma to obtain +.>Is a near optimal solution of (1).
According to a second aspect of the present invention, there is provided a high-speed aircraft optimization control method system considering intake safety, comprising: a computer readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium and perform the method according to the first aspect.
According to a third aspect of the present invention there is provided a computer readable storage medium storing computer instructions for causing a processor to perform the method of the first aspect.
In general, the above technical solutions conceived by the present invention, compared with the prior art, enable the following beneficial effects to be obtained:
the invention relates to a high-speed aircraft tracking performance and safety requirement with an optimized angle, and provides a high-speed aircraft optimizing control method considering air intake safety based on a control obstacle function and self-adaptive dynamic programming, which comprises the steps of firstly converting a nonlinear coupling model of the high-speed aircraft into a standard form facing control, establishing an actual finite time tracking controller based on a disturbance observer and a filter, and ensuring the control stability of the aircraft; secondly, establishing a safety set for describing the safety condition of the air inlet channel of the high-speed aircraft aiming at the safety constraint and the dynamics characteristic of the high-speed aircraft, and constructing a control barrier function for guaranteeing the forward invariance of the safety set; in order to make the barrier function pay as small control performance cost as possible in the process of achieving the safety condition, an optimization method based on self-adaptive dynamic programming is adopted, the control barrier function is introduced into an optimization equation as a safety factor through an expansion state space, and the optimization problem can be comprehensively described by comprehensively integrating the tracking performance, the input cost and the value function description of the safety constraint. In order to save the calculation cost, the single evaluation neural network is designed to approach the optimal control law, and the control performance is optimized on the premise of ensuring the safety of the system.
Drawings
Fig. 1 is a general control block diagram of a high-speed aircraft optimization control method considering air intake safety according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of an output tracking curve of an aircraft according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of an aircraft tracking error curve according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of an aircraft track angle tracking control curve according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of an aircraft attack angle safety tracking control curve according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of an aircraft pitch rate tracking control curve provided by an embodiment of the invention.
Fig. 7 is a schematic diagram of an aircraft control input curve provided by an embodiment of the present invention.
Fig. 8 is a schematic diagram of an evaluation neural network weight updating curve according to an embodiment of the present invention.
Fig. 9 is a schematic diagram of a tracking filtering curve of a first-order tracking filter according to an embodiment of the present invention.
Fig. 10 is a schematic diagram of a disturbance observation curve of a second-order supercoiled disturbance observer according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
The embodiment of the invention provides a high-speed aircraft optimization control method considering air inlet safety, which is shown in fig. 1 and comprises the following steps:
s1, constructing a finite time tracking controller of the aircraft according to a kinetic equation and tracking errors of the aircraft.
Preferably, in S1, the design of the tracking controller based on the disturbance observer and the filter includes:
s11, converting the kinetic equation of the aircraft into a standard model facing control. That is, a control-oriented aircraft model is constructed.
Specifically, considering the longitudinal dynamics of an air-breathing high-speed aircraft, a kinematic model is constructed as follows
The air-breathing high-speed aircraft has five rigid body states, namely a speed V, a height h, a track angle gamma, an attack angle alpha, a pitch angle speed q and two elastic states eta 1 ，η 2 . G is gravity acceleration in the formula, I yy In order for the moment of inertia to be of interest,zeta is a constraint beam coupling constant i And omega i Separate tableShowing the damping coefficient of elastic dynamics versus natural vibration frequency. In addition, thrust T, drag D, lift L, pitching moment M, and additional force N 1 And N 2 The following are listed below
Wherein the control input phi is the fuel equivalence ratio, delta e Is rudder deflection angle. The atmospheric density is ρ, and the dynamic pressure is expressed asThe mean aerodynamic chord of the airfoil and the reference area are denoted +.>And S; z T Is a thrust coupling moment parameter. From the polynomial fit, the aerodynamic parameter expression is as follows
C M (δ e )＝c e δ e
The dynamic transformation is carried out on the air suction type high-speed aircraft model, and a standard form facing control is constructed as follows
Wherein,,
f h ＝0
d V ,d h ,d γ ,d α ,d q lumped perturbations, including model uncertainty and external perturbations, for each system dynamics. Further, let χ i ＝V,h,γ,α,q，μ i ＝Φ,γ,α,q,δ e I=1, 2,3,4,5, then the control-oriented standard model is expressed as
Wherein the lumped disturbance and its derivative that the aircraft can withstand is bounded, i.e
S12, constructing a second-order supercoiled disturbance observer according to the standard model so as to observe the state and lumped disturbance of each control channel.
Specifically, according to the system model standardThe second-order supercoiled disturbance observer is designed as follows:
wherein,,and->Respectively represent the χ for the states i And lumped disturbance->Observer parameters
Note that sgn (x) is a sign function, i.e., x > 0, sgn (x) =1; x < 0, sgn (x) = -1; x=0, sgn (x) =0.
S13, constructing a first-order tracking filter of a track angle, attack angle and pitch angle speed control channel.
Specifically, defining a virtual instruction filter signalFilter for the track angle, attack angle, pitch angle rate channels, respectively, defining the filter error as +.>The first order filter is constructed as follows:
wherein the filter parameters τ, a 1i ,a 2i ＞0,0＜b 1i ＜1,b 2i ＞1。
S14, constructing a finite time tracking controller of the aircraft according to the tracking error of the aircraft, the second-order supercoiled disturbance observer and the first-order tracking filter.
Specifically, the design of the tracking controller is performed based on the disturbance observer and the filter. Consider the altitude speed h of the desired tracking d And V d Define tracking error e v ＝V-V d ，e h ＝h-h d ， The finite time tracking controller is constructed according to the second-order supercoiled disturbance observer and the first-order tracking filter as follows:
wherein, the controller parameter 0 is less than lambda and less than 1, k χi1 ＞0,k χi2 > 0. Notice disturbance observations in controllersFrom the second order supercoiled disturbance observer designed in step S2.1, the virtual instruction filter signal +.>Differential signal +.>The first order tracking filter from the S2.2 step design.
S2, safety constraint according to attack angle aDetermining a security constraint function->To construct a control barrier function->
Wherein,, in order to balance the angle of attack,
specifically, S2 is a safety design based on a safety set and a control obstacle function, including:
s21, constructing a security set.
Taking into account the cruise speed and altitude desired to be maintained, according to the force-to-moment balance equation
Solving the matched equilibrium attack angleDefinitions->Representing the distance between the current angle of attack state and the equilibrium angle of attack. Safety constraint considering attack angle of intake condition +.>By means of a function->
Defining a security setThe following are listed below
Wherein,,representing the boundary of a security set, +.>Representing the interior of the security set.
S22, constructing a control barrier function.
According to a functionAnd security set->Constructing a control barrier function by first defining a logarithmic barrier function
To meet the double-sided constraint, let
Then constructing a control barrier function by a central gradient regression method as follows
Wherein,,
s3, adding the components into an attack angle control channel of the controllerThe controller is modified to optimize the control effect on the aircraft on the premise of ensuring safety; and controlling the speed and altitude of the aircraft based on the corrected controller;
wherein,,e α for tracking error of angle of attack, +.>The method comprises the steps of respectively evaluating an observation weight and an activation function of a neural network; the evaluation neural network is used for observing a value function of sigma to obtain +.>Is a near optimal solution of (1).
Step S3 is an optimal design based on adaptive dynamic programming, including:
s31, constructing an expansion state and corresponding value function considering safety constraint, namely: construction of the expanded stateSimultaneously taking tracking error, control cost and safety constraint into consideration to construct a value function of sigmaWherein (1)>Is a weight coefficient;
specifically, to take the security constraint into account in the optimization decision, an expansion state σ is constructed to reflect both the tracking performance of the angle of attack and the security constraint, as follows
The first derivative of the expanded state can be expressed as
Wherein,, error->And q v Q can be regarded as a disturbance which can be eliminated by the disturbance observer and tracking controller of the previous design. S32, constructing and evaluating a neural network to approximately solve optimal control, namely: evaluation neural network based->Observing said value function to obtain +.>Is a near optimal solution of (2)
Specifically, as a function of observed valuesConstructing an evaluation network as follows
Wherein the method comprises the steps ofIs the observation weight of the neural network, +.>N represents the number of hidden layer neurons of the neural network as an activation function of the neural network. By taking the partial derivative, it is possible to obtain
According to the function of the observed valueThe approximate Hamiltonian equation is constructed as follows
To approximate the solution of Hamiltonian equation, an objective function is designed
The update law of the neural network weight is designed as
Wherein,,further get->The approximate optimal control law is
Finally, according to the approximate optimal control lawCorrecting the tracking controller constructed in the step S2.3 to obtain the final optimized safety control law as follows
The optimized safety control law is implemented on a high-speed aircraft system model, and the method is evaluated in aspects of tracking performance, control input cost, safety constraint effect and the like, and the embodiment results are shown in figures 2-10.
In fig. 2, the altitude tracking curve and the speed tracking curve of the aircraft are sequentially shown from top to bottom, and as shown in fig. 2, the altitude and the speed of the aircraft are well tracked under the action of the controller. In fig. 3, a altitude tracking error curve and a speed tracking error curve of the aircraft are sequentially shown from top to bottom, and as shown in fig. 3, the altitude and the speed tracking of the aircraft can be quickly responded and the tracking error is eliminated under the action of the controller.
FIG. 4 is a schematic diagram of a track pitch tracking curve of an aircraft, as shown in FIG. 4, with the track pitch curve of the aircraft being quickly tracked in response to the controller. FIG. 5 is a schematic diagram of an aircraft attack angle tracking curve, as shown in FIG. 5, under the action of a controller, the attack angle curve of the aircraft can ensure safety constraint in the tracking process, is smooth and free of buffeting at a position close to a safety boundary, and can rapidly track instructions after being far away from the safety boundary. FIG. 6 is a schematic diagram of an aircraft pitch rate tracking curve, as shown in FIG. 6, with the pitch rate curve of the aircraft being rapidly tracked under the action of a controller.
In fig. 7, a throttle fuel equivalence ratio control input curve and a rudder deflection angle control input curve of the aircraft are sequentially shown from top to bottom, as shown in fig. 7, the control inputs of the throttle and rudder deflection angles are smooth, and the control signals are easy for an executing mechanism to execute control actions.
Fig. 8 is a schematic diagram of a neural network weight updating curve, and as shown in fig. 8, the weight of the neural network can be adaptively updated according to the error tracking and safety conditions of the aircraft, so as to ensure the attack angle constraint and control performance of the aircraft.
The filter tracking curves for the track pitch channel, the angle of attack channel and the pitch rate channel are shown in fig. 9 from top to bottom. As shown in fig. 9, the filter is able to respond quickly to the trace virtual command signal.
In fig. 10, disturbance observation curves of a speed channel, a altitude channel, a track inclination angle channel, an attack angle channel and a pitch angle speed channel are sequentially shown from top to bottom. As shown in fig. 10, the observer can quickly respond to the observed lumped disturbance.
The embodiment of the invention provides a high-speed aircraft optimization control method system considering air inlet safety, which comprises the following steps: a computer readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium and perform a method as in any of the embodiments described above.
Embodiments of the present invention provide a computer readable storage medium storing computer instructions for causing a processor to perform a method as described in any of the embodiments above.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (9)
1. The high-speed aircraft optimization control method considering air inlet safety is characterized by comprising the following steps of:
s1, constructing a finite time tracking controller of an aircraft according to a kinetic equation and a tracking error of the aircraft;
s2, safety constraint according to attack angle aDetermining a security constraint function->To construct a control obstacle function
Wherein,, in order to balance the angle of attack,
s3, adding the components into an attack angle control channel of the controllerCorrecting the controller, and controlling the speed and the altitude of the aircraft based on the corrected controller;
wherein,,e α for tracking error of angle of attack, +.>The method comprises the steps of respectively evaluating an observation weight and an activation function of a neural network; the evaluation neural network is used for observing a value function of sigma to obtain +.>Is the optimal solution, R is the optimal parameter.
2. The method of claim 1, wherein step S3 comprises:
s31, constructing an expanded state
S32, constructing a value function of sigma by considering tracking error, control cost and safety constraintWherein (1)>Is a weight coefficient; u (e) α ,u s ) Is a utility function;
s33, based on evaluation of the neural networkObserving said value function to obtain +.>Is a near optimal solution of (2)
3. The method of claim 1, wherein step S1 comprises:
s11, converting a kinetic equation of the aircraft into a control-oriented standard model;
s12, constructing a second-order supercoiled disturbance observer according to the standard model so as to observe the state and lumped disturbance of each control channel;
s13, constructing a first-order tracking filter of a track angle, attack angle and pitch angle speed control channel;
s14, constructing a finite time tracking controller of the aircraft according to the tracking error of the aircraft, the second-order supercoiled disturbance observer and the first-order tracking filter.
4. A method according to claim 1 or 3, wherein the finite time tracking controller of the aircraft is:
wherein,, for the lumped disturbance observation value of each control channel, from the second-order supercoiled disturbance observer, pneumatic parametersAerodynamic equation->V is the speed, h is the altitude, gamma is the track angle, alpha is the angle of attack, q is the pitch angle speed, eta 1 ，η 2 In two elastic states, g is gravitational acceleration, I yy For moment of inertia>Zeta is a constraint beam coupling constant i And omega i Respectively represent the damping coefficient of elastic dynamic and the natural vibration frequency. T is thrust, D is resistance, L is lift, M is pitching moment, N 1 And N 2 Are all additional forces; control input Φ is fuel equivalence ratio, δ e For rudder deflection angle, ρ is the atmospheric density and dynamic pressure is expressed as +.>The mean aerodynamic chord of the airfoil and the reference area are denoted +.>And S; z T The thrust coupling moment parameter is; tracking error e of each control channel v ＝V-V d ，e h ＝h-h d ，Controller parameters 0 < lambda < 1, < -> Virtual command filtering signals of the track angle, attack angle and pitch angle speed control channels respectively>Respectively->All from the first order tracking filter; h is a d And V d The height and speed of the desired tracking, respectively.
5. The method of claim 4, wherein the modified controller is:
6. the method of claim 3, wherein the second order supercoiled class disturbance observer is:
wherein χ is i ＝V,h,γ,α,q，i＝1,2,3,4,5，And->Respectively represent the χ for the states i And lumped disturbance->Observer parameters p > 1, -for the observations of (2)>sgn (x) is a sign function, when x > 0, sgn (x) =1; when x < 0, sgn (x) = -1; when x=0, sgn (x) =0.
7. The method of claim 3 or 6, wherein the first order tracking filter is:
wherein,, the filters are respectively used for controlling channels of track angle, attack angle and pitch angle speed; />α v ,q v Virtual command filtering signals of the track angle, attack angle and pitch angle speed control channels are respectively obtained; the filter parameter τ > 0, a 1i ＞0,a 2i ＞0,0＜b 1i ＜1,b 2i > 1; sgn (x) is a sign function, when x > 0, sgn (x) =1; when x < 0, sgn (x) = -1; when x=0, sgn (x) =0.
8. An optimization control method system of a high-speed aircraft considering air intake safety is characterized by comprising the following steps: a computer readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium and perform the method of any one of claims 1-7.
9. A computer readable storage medium storing computer instructions for causing a processor to perform the method of any one of claims 1-7.
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| CN110244751A (en) * | 2019-05-24 | 2019-09-17 | 北京控制工程研究所 | A kind of hypersonic aircraft attitude-adaptive recursion control method and system |
| CN111158398A (en) * | 2020-01-15 | 2020-05-15 | 哈尔滨工业大学 | Adaptive control method of hypersonic aircraft considering attack angle constraint |
| CN111273681A (en) * | 2020-04-09 | 2020-06-12 | 中北大学 | Hypersonic aircraft high-safety anti-interference control method considering limited attack angle |
| CN115793696A (en) * | 2022-12-28 | 2023-03-14 | 西北工业大学 | Hypersonic aircraft attitude control method, system, electronic equipment and medium |
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| CN117873136A (en) * | 2024-03-11 | 2024-04-12 | 西北工业大学 | Control method for cooperative flight and collision prevention of preset performance of high-speed aircraft |
| CN117873136B (en) * | 2024-03-11 | 2024-05-24 | 西北工业大学 | Control method for cooperative flight and collision prevention of preset performance of high-speed aircraft |
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