CN112947530A - Control method and system for yawing of distributed electric propulsion aircraft - Google Patents

Control method and system for yawing of distributed electric propulsion aircraft Download PDF

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CN112947530A
CN112947530A CN202110322279.5A CN202110322279A CN112947530A CN 112947530 A CN112947530 A CN 112947530A CN 202110322279 A CN202110322279 A CN 202110322279A CN 112947530 A CN112947530 A CN 112947530A
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yaw
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寇鹏
王京
梁得亮
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Xian Jiaotong University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
    • G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft

Abstract

The invention relates to a method and a system for controlling the yaw of a distributed electric propulsion airplane. Based on a linear state space model of the distributed electric propulsion airplane, after the airplane receives a yaw command from an empty pipe center, aiming at a yaw target angle, a flight control computer adopts a model prediction control algorithm to implement course attitude control on the airplane, so that the optimal thrust distribution of each propeller is realized, and the actual yaw angle can follow the yaw target angle as much as possible. Through a model prediction control algorithm, the propellers symmetrically distributed along the plane of symmetry of the airplane provide differential thrust to realize pure power yaw, or the propellers and the control rudder surface of the airplane jointly act to realize hybrid power yaw. The control of the invention can improve the fault tolerance of the system and provide more possibilities for realizing the airplane yaw.

Description

Control method and system for yawing of distributed electric propulsion aircraft
Technical Field
The invention belongs to the technical field of airplane yaw control, and particularly relates to a distributed electric propulsion airplane yaw control method and system.
Background
The traditional airplane controls six degrees of freedom of the airplane by operating three control surfaces, namely an elevator, a rudder and an aileron, on the surface of an airplane body, so that attitude control is realized, and the form is single; in addition, because the aircraft motion equation has a coupling phenomenon, a plurality of control surfaces are required to be matched with each other when course attitude control is implemented. When the airplane has system faults such as failure of a control plane and the airplane body is physically damaged, the difficulty in controlling the attitude of the airplane is increased. In recent years, with the promotion of aviation electrification, distributed electric propulsion airplanes are widely concerned and are continuously and rapidly developed.
For attitude control of a distributed electric propulsion aircraft, thrust may become an additional steerable quantity in addition to steering the three control surfaces. Due to the characteristics of high response speed and accurate measurement of output torque, the system can be more efficient by controlling the motor to realize thrust control. Through the published document retrieval and published data research of the prior art, few researches on the control strategy for controlling the distributed electric propulsion airplane to realize the dynamic yaw by utilizing the thrust of the electric propeller are carried out at present, the researches do not fully consider the dynamic model of the whole distributed electric propulsion airplane, and the optimal control on the thrust of the propeller is not realized.
Flight control problems often involve various equality and inequality constraints due to constraints on the aircraft mechanical structure, flight stability, passenger comfort, and the like. Therefore, a control strategy capable of sufficiently handling the constraints is required to be found to realize the optimal thrust distribution of the electric thruster in the course control process of the airplane.
Disclosure of Invention
The invention aims to provide a distributed electric propulsion airplane yaw control method and a distributed electric propulsion airplane yaw control system to solve the problems.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method of controlling yaw of a distributed electric propulsion aircraft, comprising the steps of:
step 1, after a yaw command is sent out by an air traffic control center, a flight control computer receives yaw target information, and the flight control computer adopts a model predictive control algorithm to implement course attitude control on an airplane according to a yaw target angle;
step 2, calculating an optimal yaw scheme of the distributed electric propulsion airplane by a model prediction control algorithm based on a six-degree-of-freedom linear state space model of the airplane; the model predictive control algorithm applies control constraints and state constraints according to the performance indexes of the propeller and the airplane;
and 3, adjusting the thrust of each propeller and the deflection angles of the elevator, the rudder and the aileron according to the calculated values.
Further, the aircraft six-degree-of-freedom linear state space model is established according to the following steps:
based on a small disturbance principle, an airplane motion equation is linearized, and a six-degree-of-freedom linear state space model of a conventional airplane is established:
Figure BDA0002993265150000021
wherein the state quantity x [ [ Δ V Δ β Δ α Δ p Δ q Δ r Δ Φ Δ θ Δ ψ [ ]]TV is the flying speed, beta is the sideslip angle, alpha is the attack angle, p is the roll angle speed, q is the pitch angle speed, r is the yaw angle speed, phi is the roll angle, theta is the pitch angle, psi is the yaw angle; control quantity u ═ Δ δe Δδa Δδr]T，δeFor elevator deflection angle, deltaaFor aileron deflection angle, deltarIs a rudder deflection angle; the output quantity y is delta psi;
establishing a dynamic model of the propeller:
establishing an aircraft six-degree-of-freedom linear state space model with input quantity including electric propeller thrust:
Figure BDA0002993265150000022
wherein
Figure BDA0002993265150000023
u1＝[Δδe Δδa Δδr ΔTC1 … ΔTCn]T，C1＝[C 0 … 0]T,，TiWhere i is 1,2, …, n is the thrust output of each propeller, TCiI is 1,2, …, n is the thrust command of each propeller, and n is the number of the propellers of the airplane;
based on a forward Euler discretization formula, the obtained discrete time system model is as follows:
Figure BDA0002993265150000031
wherein A isu＝(1+TsA1)，Bu＝TsB1，TsIs the sampling period.
Further, the optimization goal of the model predictive control algorithm is as follows:
(1) the main optimization objective is to make the system output follow the change of the yaw target angle as much as possible
Figure BDA0002993265150000032
Wherein the yaw target angle refers to a target change value relative to the yaw angle of the airplane when the yaw command is sent out, y (k + i | k) is a system output value for predicting k + i moment at the current moment k, and yr(k + i) is a yaw target angle value at the moment of k + i, Q is a weighting coefficient, and p is a prediction time domain;
(2) it is desirable that the control action not be too great
Figure BDA0002993265150000033
Wherein u is1(k + i | k) is the control output of predicting k + i moment at the current moment k, R is a weighting coefficient matrix, and m is a control time domain;
the total objective function is obtained:
Figure BDA0002993265150000034
further, the model predictive control algorithm imposes control constraints and state constraints according to the performance indexes of the propeller and the airplane:
Xmin≤X(k+j|k)≤Xmax,j＝1,2,…,p (7)
wherein Xmin＝[ΔVmin Δβmin Δαmin Δpmin Δqmin Δrmin Δφmin Δθmin Δψmin]T，
Figure BDA0002993265150000035
Xmax＝[ΔVmax Δβmax Δαmax Δpmax Δqmax Δrmax Δφmax Δθmax Δψmax]TP is the prediction time domain;
U1min≤U1(k+j|k)≤U1max,j＝0,1,…,m-1 (8)
wherein U is1min＝[Δδemin Δδamin Δδrmin ΔTC1min ΔTC2min … ΔTCnmin]T
Figure BDA0002993265150000041
U1max＝[Δδemax Δδamax Δδrmax ΔTC1max ΔTC2max … ΔTCnmax]TM is a control time domain;
when the yaw mode is pure power yaw, deltaemin＝Δδamin＝Δδrmin＝0，Δδemax＝Δδamax＝Δδrmax0, wherein Δ δemin、Δδamin、ΔδrminThe lower limit value delta of the deflection angle variation of the elevator, the aileron and the rudderemax、Δδamax、ΔδrmaxThe upper limit values of the deflection angle variation of the elevator, the aileron and the rudder are respectively; when the yaw mode is hybrid yaw, deltaamin、Δδamax、Δδrmin、ΔδrmaxAre not 0.
Further, step 2 specifically comprises:
the variation of the elevator deflection angle, the rudder deflection angle and the aileron deflection angle is controlled to be 0, at the same time, the optimal distribution scheme of thrust of each propeller is calculated by a model prediction control algorithm when the variation of the thrust of at least one pair of propellers which are symmetrically distributed about the plane of an aircraft body coordinate system xoz is not 0, and the pure power yaw of the aircraft is realized by the differential thrust of the propellers.
Further, step 2 specifically comprises: controlling an elevator deflection angle, a rudder deflection angle and an aileron deflection angle, keeping at least one pair of thrust change values of the propellers symmetrically distributed about the plane of an aircraft body coordinate system xoz not to be 0, calculating an optimal control scheme by a model prediction control algorithm, and realizing hybrid power yaw of the aircraft through the combined action of a control plane and the propellers.
Further, in step 3, the thrusters are distributed symmetrically with respect to the plane of the aircraft body coordinate system xoz.
Further, the control system for the distributed electric propulsion aircraft yawing is characterized by comprising a yawing instruction receiving module, an optimal yawing scheme calculating module and an adjusting module;
the yaw instruction receiving module is used for receiving a yaw instruction sent by the hollow pipe center and then sending yaw target information to the flight control computer;
the optimal yaw scheme calculation module is used for calculating an optimal yaw scheme of the distributed electric propulsion airplane by utilizing a model prediction control algorithm based on a six-degree-of-freedom linear state space model of the airplane; ,
the adjusting module is used for adjusting the thrust of each propeller and the deflection angles of the elevator, the rudder and the aileron according to the calculated values.
Compared with the prior art, the invention has the following technical effects:
the invention enriches the yawing scheme of the airplane. Two yaw modes of pure power yaw and hybrid power yaw are provided based on a distributed electric propulsion technology, compared with the traditional airplane yaw mode, the control mode of the system is enriched, and multiple possibilities are provided for airplane yaw implementation.
The invention improves the fault tolerance of the system. When the airplane has system faults, such as failure of a control plane and failure of one or more propellers, the yaw function can still be realized by controlling the effective electric propeller.
The optimal control quantity distribution is realized based on the model prediction control method. Aiming at the yaw target angle, considering the constraints brought by state quantity, control quantity and the like, the model prediction control algorithm establishes the constraints in an optimization problem, ensures that the actual yaw angle of the airplane in the prediction time domain follows the yaw target angle as much as possible by constructing an objective function, and can find the optimal thrust distribution of the electric propeller by solving an open-loop optimal control problem.
Drawings
FIG. 1 is a schematic view of a distributed electric propulsion aircraft yaw according to an embodiment of the present invention.
Fig. 2a is a top view, fig. 2b is a side view and fig. 2c is a front view of an aircraft according to an embodiment of the invention.
FIG. 3 is a schematic view of a yaw control method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
A method of controlling yaw of a distributed, electrically-propelled aircraft, comprising:
step 1, after receiving a yaw command sent by an air traffic control center, a flight control computer adopts a model predictive control algorithm to control the course attitude of an airplane aiming at a yaw target angle;
step 2, calculating an optimal yaw scheme of the distributed electric propulsion aircraft by a model predictive control algorithm;
the model predictive control algorithm is based on a six-degree-of-freedom linear state space model of the aircraft with input quantities comprising electric propeller thrust.
The control quantity of the six-degree-of-freedom linear state space model of the airplane is the thrust variable quantity of each propeller of the airplane and the variable quantity of the deflection angles of the elevator, the rudder and the aileron, and the output quantity is the variable quantity of the yaw angle of the airplane.
The model predictive control algorithm imposes control constraints and state constraints according to the performance indexes of the propeller and the airplane. In consideration of factors such as the mechanical structure of the aircraft, the flight stability, the passenger comfort and the like, linear constraints are applied to the control quantity, namely the variation of the deflection angle and thrust of each control surface, and the state quantity, namely the variation of the sideslip angle and the roll angle of the aircraft.
Step 2 has 2 realization modes:
the first mode is as follows:
the variation of the elevator deflection angle, the rudder deflection angle and the aileron deflection angle is controlled to be 0, at the same time, the variation values of at least one pair of thrusters which are symmetrically distributed about the plane of an aircraft body coordinate system xoz are kept to be not 0, the optimal distribution scheme of the thrusters is calculated by a model prediction controller, and the pure power yaw of the aircraft is realized through the differential thrust of the thrusters.
The second mode is as follows:
controlling an elevator deflection angle, a rudder deflection angle and an aileron deflection angle, keeping at least one pair of thrust change values of the propellers symmetrically distributed about the plane of an aircraft body coordinate system xoz not to be 0, calculating an optimal control scheme by a model prediction control algorithm, and realizing hybrid power yaw of the aircraft through the combined action of a control plane and the propellers.
And 3, adjusting the thrust of each propeller and the deflection angles of the elevator, the rudder and the ailerons according to the calculated values.
Examples
A schematic view of a distributed electric propulsion aircraft yaw is shown in fig. 1, given in top view.
As shown in fig. 2a, 2b, and 2c, a method for controlling yaw of a distributed electric propulsion aircraft includes a propeller 1.1, a propeller 1.2, a propeller 1.3, a propeller 1.4, a propeller 1.5, a propeller 1.6, a propeller 1.7, a propeller 1.8, a propeller 1.9, a propeller 1.10, an aileron 2.1, an elevator 2.2, and a rudder 2.3.
The plane flies horizontally in a cruising state, and turns 30 degrees according to the requirement of a set planning route to adjust the flight direction.
The traditional six-degree-of-freedom linear state space model of the airplane is as follows:
Figure BDA0002993265150000061
wherein the state quantity x [ Δ V Δ β Δ p Δ q Δ r Δ θ Δ ψ [ [ Δ V Δ β Δ q Δ θ Δ ψ ]]TV is the flying speed, beta is the sideslip angle, alpha is the attack angle, p is the roll angle speed, q is the pitch angle speed, r is the yaw angle speed, phi is the roll angle, theta is the pitch angle, psi is the yaw angle; control quantity u ═ Δ δe Δδa Δδr]T，δeFor elevator deflection angle, deltaaFor aileron deflection angle, deltarIs a rudder deflection angle; the output y is Δ ψ.
The structure of the propeller 1.1, the propeller 1.2, the propeller 1.3, the propeller 1.4, the propeller 1.5, the propeller 1.6, the propeller 1.7, the propeller 1.8, the propeller 1.9 and the propeller 1.10 are the same.
On the basis of a traditional aircraft six-degree-of-freedom linear state space model, a system matrix and a control matrix are augmented, and the aircraft six-degree-of-freedom linear state space model with input quantity including electric propeller thrust is obtained by the following steps:
Figure BDA0002993265150000071
wherein
Figure BDA0002993265150000072
u1＝[Δδe Δδa Δδr ΔTC1 … ΔTC10]T，C1＝[C 0 … 0]T。
Based on the Euler discretization formula, the obtained discrete time system model is as follows:
Figure BDA0002993265150000073
wherein A isu＝(1+TsA1)，Bu＝TsB1，TsIs the sampling period.
Get the total objective function
Figure BDA0002993265150000074
And considering factors such as the mechanical structure of the airplane, the flight stability, the comfort of passengers and the like, the linear constraint applied to the system is as follows:
Xmin≤X(k+j|k)≤Xmax,j＝1,2,…,p (5)
wherein Xmin＝[ΔVmin Δβmin Δαmin Δpmin Δqmin Δrmin Δφmin Δθmin Δψmin]T，
Figure BDA0002993265150000075
Xmax＝[ΔVmax Δβmax Δαmax Δpmax Δqmax Δrmax Δφmax Δθmax Δψmax]TAnd p is a prediction time domain.
U1min≤U1(k+j|k)≤U1max,j＝0,1,…,m-1 (6)
Wherein U is1min＝[Δδemin Δδamin Δδrmin ΔTC1min ΔTC2min … ΔTC10min]T
Figure BDA0002993265150000081
U1max＝[Δδemax Δδamax Δδrmax ΔTC1max ΔTC2max … ΔTC10max]TAnd m is a control time domain.
When the yaw mode is pure power yaw, deltaemin＝Δδamin＝Δδrmin＝0，Δδemax＝Δδamax＝Δδrmax＝0。
The specific working process of the course control system is as follows:
in the first step, according to a yaw command of 30 degrees of yaw from the hollow pipe center, 30 degrees of yaw is sent to a flight control computer to be used as a reference input of a model prediction control algorithm.
And the second step is that the model predictive control algorithm solves the system based on the established linear state space model to obtain the optimal control quantity distribution scheme of the system output following the reference input. And obtaining the reference thrust of 10 propellers in a pure power yawing mode or the reference thrust of 10 propellers in a hybrid power yawing mode and the deflection angles of the ailerons 2.1, the elevators 2.2 and the rudders 2.3.
And thirdly, adjusting the thrust of the 10 propellers and the deflection angles of the ailerons 2.1, the elevators 2.2 and the rudders 2.3 according to the reference thrust of the 10 propellers in a pure power yaw mode or the reference thrust of the 10 propellers and the deflection angles of the ailerons 2.1, the elevators 2.2 and the rudders 2.3 in a hybrid power yaw mode.

Claims (8)

1. A control method for yawing of a distributed electric propulsion airplane is characterized by comprising the following steps:
step 1, after a yaw command is sent out by an air traffic control center, a flight control computer receives yaw target information, and the flight control computer adopts a model predictive control algorithm to implement course attitude control on an airplane according to a yaw target angle;
step 2, calculating an optimal yaw scheme of the distributed electric propulsion airplane by a model prediction control algorithm based on a six-degree-of-freedom linear state space model of the airplane; the model predictive control algorithm applies control constraints and state constraints according to the performance indexes of the propeller and the airplane;
and 3, adjusting the thrust of each propeller and the deflection angles of the elevator, the rudder and the aileron according to the calculated values.
2. The method for controlling the yaw of the distributed electric propulsion aircraft as claimed in claim 1, wherein the six-degree-of-freedom linear state space model of the aircraft is built according to the following steps:
based on a small disturbance principle, an airplane motion equation is linearized, and a six-degree-of-freedom linear state space model of a conventional airplane is established:
Figure FDA0002993265140000011
wherein the state quantity x [ [ Δ V Δ β Δ α Δ p Δ q Δ r Δ Φ Δ θ Δ ψ [ ]]TV is the flying speed, beta is the sideslip angle, alpha is the attack angle, p is the roll angle speed, q is the pitch angle speed, r is the yaw angle speed, phi is the roll angle, theta is the pitch angle, psi is the yaw angle; control quantity u ═ Δ δe Δδa Δδr]T，δeFor elevator deflection angle, deltaaFor aileron deflection angle, deltarIs a rudder deflection angle; the output quantity y is delta psi;
establishing a dynamic model of the propeller;
establishing an aircraft six-degree-of-freedom linear state space model with input quantity including electric propeller thrust:
Figure FDA0002993265140000012
wherein
Figure FDA0002993265140000013
u1＝[Δδe Δδa Δδr ΔTC1 … ΔTCn]T，C1＝[C 0 … 0]T，TiI is 1,2, …, n is eachThrust output of the propeller, TCiI is 1,2, …, n is the thrust command of each propeller, and n is the number of the propellers of the airplane;
based on a forward Euler discretization formula, the obtained discrete time system model is as follows:
Figure FDA0002993265140000021
wherein A isu＝(1+TsA1)，Bu＝TsB1，TsIs the sampling period.
3. The method of claim 1, wherein the model predictive control algorithm has an optimization objective of:
(1) the main optimization objective is to make the system output follow the change of the yaw target angle as much as possible
Figure FDA0002993265140000022
Wherein the yaw target angle refers to a target change value relative to the yaw angle of the airplane when the yaw command is sent out, y (k + i | k) is a system output value for predicting k + i moment at the current moment k, and yr(k + i) is a yaw target angle value at the moment of k + i, Q is a weighting coefficient, and p is a prediction time domain;
(2) it is desirable that the control action not be too great
Figure FDA0002993265140000023
Wherein u is1(k + i | k) is the control output of predicting k + i moment at the current moment k, R is a weighting coefficient matrix, and m is a control time domain;
the total objective function is obtained:
Figure FDA0002993265140000024
4. the method of claim 1, wherein the model predictive control algorithm imposes control constraints and state constraints based on propeller and aircraft performance metrics:
Xmin≤X(k+j|k)≤Xmax,j＝1,2,…,p (7)
wherein Xmin＝[ΔVmin Δβmin Δαmin Δpmin Δqmin Δrmin Δφmin Δθmin Δψmin]T，
Figure FDA0002993265140000025
Xmax＝[ΔVmax Δβmax Δαmax Δpmax Δqmax Δrmax Δφmax Δθmax Δψmax]TP is the prediction time domain;
U1min≤U1(k+j|k)≤U1max,j＝0,1,…,m-1 (8)
wherein U is1min＝[Δδemin Δδamin Δδrmin ΔTC1min ΔTC2min … ΔTCnmin]T，
Figure FDA0002993265140000031
U1max＝[Δδemax Δδamax Δδrmax ΔTC1max ΔTC2max … ΔTCnmax]TM is a control time domain;
when the yaw mode is pure power yaw, deltaemin＝Δδamin＝Δδrmin＝0，Δδemax＝Δδamax＝Δδrmax0, wherein Δ δemin、Δδamin、ΔδrminThe lower limit value delta of the deflection angle variation of the elevator, the aileron and the rudderemax、Δδamax、ΔδrmaxThe upper limit values of the deflection angle variation of the elevator, the aileron and the rudder are respectively; when the yaw mode is hybrid yaw, deltaamin、Δδamax、Δδrmin、ΔδrmaxAre not 0.
5. The method for controlling the yaw of the distributed electric propulsion aircraft according to claim 4, wherein the step 2 is specifically as follows:
the variation of the elevator deflection angle, the rudder deflection angle and the aileron deflection angle is controlled to be 0, at the same time, the variation values of at least one pair of thrusters which are symmetrically distributed about the plane of an aircraft body coordinate system xoz are kept to be not 0, the optimal distribution scheme of the thrusters is calculated by a model prediction control algorithm, and the pure power yaw of the aircraft is realized by the differential thrust of the thrusters.
6. The method for controlling the yaw of the distributed electric propulsion aircraft according to claim 4, wherein the step 2 is specifically as follows: controlling an elevator deflection angle, a rudder deflection angle and an aileron deflection angle, keeping at least one pair of thrust change values of the propellers symmetrically distributed about the plane of an aircraft body coordinate system xoz not to be 0, calculating an optimal control scheme by a model prediction control algorithm, and realizing hybrid power yaw of the aircraft through the combined action of a control plane and the propellers.
7. The method as claimed in claim 1, wherein in step 3, the propellers are symmetrically arranged about a plane of aircraft body coordinate system xoz.
8. A distributed electric propulsion airplane yaw control system is characterized in that the distributed electric propulsion airplane yaw control method based on any one of claims 1 to 7 comprises a yaw instruction receiving module, an optimal yaw scheme calculating module and an adjusting module;
the yaw instruction receiving module is used for receiving a yaw instruction sent by the hollow pipe center and then sending yaw target information to the flight control computer;
the optimal yaw scheme calculation module is used for calculating an optimal yaw scheme of the distributed electric propulsion airplane by utilizing a model prediction control algorithm based on a six-degree-of-freedom linear state space model of the airplane;
the adjusting module is used for adjusting the thrust of each propeller and the deflection angles of the elevator, the rudder and the aileron according to the calculated values.
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