CN113342012B - Course control method of sliding and flapping integrated aircraft - Google Patents
Course control method of sliding and flapping integrated aircraft Download PDFInfo
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Abstract
The invention relates to a course control method of a sliding and flapping integrated aircraft, which comprises the steps of obtaining current course information through an attitude sensor and calculating a yaw value; according to the speed of the longitudinal plane of the current aircraft, when the speed of the gliding longitudinal plane of the aircraft is higher, the parameters obtained by the fuzzy PD control algorithm are converted into the rotation angle value of the rolling mechanism for course control by utilizing fuzzy PD control, when the speed is lower, in the following diving-floating conversion stage, the parameters obtained by the fuzzy PD control algorithm are used as CPG amplitude variables, and then a CPG controller outputs flapping wing control signals, which are specifically expressed as asymmetric flapping wing amplitudes for navigation.
Description
Technical Field
The invention belongs to a course control method of an underwater vehicle, relates to a course control method of a flapping-sliding integrated vehicle, and particularly relates to a course control method of a flapping-sliding vehicle by utilizing the asymmetric amplitude synergistic effect of a rolling mechanism and flapping wings.
Background
The underwater glider is a novel observation platform which does gliding movement in the ocean and collects and observes the ocean environment in the movement process, realizes the large-area multi-scale monitoring of the ocean by utilizing the self gravity and the buoyancy difference to drive the movement, and is suitable for the detection in the fields of ocean environment observation and military affairs. The simulated manta ray underwater vehicle realizes the integration of gliding and flapping by combining the gliding propulsion of a glider and the flexible propulsion of the simulated marine organism manta ray on the basis of the principle of the underwater glider, has the characteristics of long range and high maneuverability, can realize the underwater observation of wide-area coarse dimension and fixed-point fine dimension, and is more suitable for various complex sea areas.
Due to the fact that the underwater environment is complex, interference of water flow with different intensity and speed exists, and the aircraft can be easily influenced and cannot advance according to the set course. In order to solve the problem of yawing when an underwater vehicle executes tasks, the traditional underwater vehicle mostly depends on propeller propulsion, the propulsion speed is high, but the navigation attitude is difficult to flexibly change. And various methods for controlling the course of the underwater vehicle, such as a fuzzy control algorithm, a PID control algorithm and the like, are available, and most of the methods are designed based on kinematics and dynamics models established by the vehicle. The propulsion mode of the simulated manta ray aircraft is different from that of the traditional aircraft, and no more accurate model exists so far, so that the accurate course control is very difficult to realize by adopting the traditional method, and a new course control method needs to be designed. In the published documents, no example is provided for realizing the course control of the simulated bat craft by the cooperative action of a roll mechanism and an ornithopter.
Disclosure of Invention
Technical problem to be solved
Aiming at the simulated manta ray integrated with gliding and flapping, a fixed-navigation task is divided into two working conditions according to the longitudinal speed to carry out control scheme design, and a rolling mechanism and an flapping wing system controlled by a CPG neural network are adjusted by combining a fuzzy PD control algorithm, so that the fixed-navigation swimming task is completed.
Technical scheme
The invention realizes the basic principle of controlling the simulated bat underwater vehicle by adjusting the asymmetric amplitudes of a roll mechanism and a flapping wing, and comprises the following steps:
taking the submergence process of the simulated bat ray aircraft as an example for analysis and explanation, when the simulated bat ray aircraft submerges and glides at a certain speed, the transverse rolling mechanism is adjusted to deflect, and at the moment, the simulated bat ray aircraft deflects along the chord direction of the aircraft, so that the simulated bat ray aircraft presents a deflection state. Because an included angle exists between the aircraft body and the horizontal plane, the hydrodynamic force perpendicular to the surface of the aircraft generates a yawing moment which enables the aircraft to bypass a vertical shaft of the center of gravity, and the course of the simulated manta ray aircraft is changed. The course of the simulated manta ray aircraft can be corrected by utilizing the yawing moment.
When the speed of the longitudinal plane is low, the posture of the simulated bat ray underwater vehicle can be adjusted through flapping of the flapping wings at two sides with asymmetric dynamic amplitude. The implementation mode of the method is mainly that different expected amplitudes of the flapping wings on the two sides are utilized to generate different forward propulsion, namely the propulsion Fl of the flapping wing on the left side is not equal to the propulsion Fr of the flapping wing on the right side, so that forward propulsion resultant force and turning moment are generated, and the larger propulsion is obtained on the side with the larger flapping amplitude of the flapping wing, so that the aircraft can turn to the side with the smaller flapping amplitude or without flapping of the flapping wing, and the heading control effect is achieved.
A heading control method of a flapping-sliding integrated aircraft is characterized by comprising the following steps: the left side of the flapping integrated aircraft comprises 2 steering engines which are named as a first steering engine 1 and a second steering engine 2 respectively, and the right side of the flapping integrated aircraft is named as a third steering engine 3 and a fourth steering engine 4; each steering engine is controlled by the output of a conversion formula to form a unit; the first unit 1 on the left communicates with the second unit 2, and the unit 3 on the right communicates with the unit 4; the course control steps are as follows:
step 1: obtaining the current course angle of an underwater vehicle through an attitude sensor
The target course angle set by the task is
Yaw angle e:
and 2, step: and (3) deriving the yaw angle to obtain a course angle deviation change rate ec:
wherein t is the information updating time of the attitude sensor of the underwater vehicle;
and 3, step 3: fuzzifying the obtained yaw angle and heading deviation change rate, wherein the fuzzified linguistic variables are expressed by NB, namely negative large, NM, namely negative small, NS, namely zero, namely ZO, PS, namely positive small, PM, namely positive large, namely PB, and the fuzzy set is as follows:
ec＝{NB,NM,NS,ZO,PS,PM,PB}
e＝{NB,NM,NS,ZO,PS,PM,PB}
giving the fuzzified yaw angle and course deviation change rate into a fuzzy rule table, taking an ec value as a vertical coordinate and an e value as a horizontal coordinate, self-tuning the original PD number, and obtaining delta k according to the fuzzy rule table 1 and the fuzzy rule table 2 p 、k d Values, corrected PD parameters are:
wherein k is p Is the original scale factor, k d Is the original differential coefficient; Δ k of p The proportional coefficient setting adjustment, Δ k, is obtained by looking up a table for the fuzzy controller d Obtaining a differential coefficient setting adjustment quantity for a fuzzy controller by looking up a table; k is a radical of pF Adjusting quantity delta k for proportional coefficient setting obtained by looking up table of fuzzy controller p Coefficient of proportionality to original k p Added scaling factor, k dF Setting adjustment quantity delta k of differential coefficient obtained by looking up table of fuzzy controller d With the original differential coefficient ak d The added differential coefficients;
fuzzy rule Table 1
k p Fuzzy control coefficient correction table
Fuzzy rule Table 2
k d Fuzzy control coefficient correction table
And 4, step 4: the course control quantity calculated by the PID controller after the setting of the fuzzy controller is as follows:
dt is the micro-time separation;
discretizing to obtain:
wherein y (t) is the control output of the controller at the current moment; t is a discrete time interval;
and 5: according to the method, a navigation task is divided into the following two conditions by taking the longitudinal speed v acquired by an aircraft from an attitude sensor as a judgment condition:
a) when v is larger than a, the underwater vehicle is in a rapid submerging/floating stage, the course is controlled by adopting a rolling mechanism, the rolling mechanism inside the vehicle is adjusted to roll left and right according to the calculated control quantity, and the rolling angle of the vehicle is changed, so that the yaw attitude is realized, and the navigation task is finished;
calculating the offset angle of the rolling block of the rolling mechanism according to the control quantity:
in the formula: roll is the angle of the offset of the rolling block, B l The left-turning maximum deviation angle of the transverse rolling block is a positive value; b is r The maximum right-turning offset angle of the rolling block is a negative value; b z Is the zero position of the rolling block; the deflection range of the rolling block is [ B ] r B l ]The control quantity output of the controller, A is a control quantity conversion coefficient, M is a control quantity limit value, and the deflection of the mechanism caused by overlarge input y (t) values is prevented from exceeding the limit;
b) when v is less than or equal to a, the underwater vehicle is in a diving and floating conversion stage, the longitudinal speed is low, and the course is controlled by changing the asymmetric amplitude of the flapping wings;
step 6: converting the control quantity obtained by the fuzzy PD calculation, inputting the converted control quantity into a CPG network as an amplitude variation quantity, inputting the phase difference and the frequency of the flapping wing, and iteratively calculating through the CPG network to obtain the flapping angle of the flapping wing, thereby realizing course control by using asymmetric amplitude;
the conversion formula is:
wherein e yaw angle, Q is the desired amplitude during straight-ahead motion, y (t) is the controlled variable output of the controller, R 1 、R 2 、R 3 、R 4 Expected phase differences of the steering engines 1, 2, 3 and 4 are respectively obtained;
the CPG network of the flapping-sliding integrated aircraft comprises the following components:
each equation is respectively a phase equation, an amplitude equation and an output equation; phi in the formula i Denotes the phase, v, of the ith cell i Representing the natural frequency, ω ij Representing the coupling weight of the jth cell to the ith cell,
representing the desired phase difference; r is i Represents the amplitude, a i Normal number, R, representing the rate of convergence of the control amplitude i Representing a desired amplitude; theta i Representing the output value.
CPG net of integrated gliding and flapping aircraftThe topology of the network is: the first unit 1 on the left communicates with the second unit 2, the unit 3 on the right communicates with the unit 4; establishing the relation between the left side and the right side through the second unit 2 and the third unit 3; wherein the coupling weight omega of the jth unit to the ith unit ij Presence of only omega 12 、ω 13 、ω 23 Three forms, which can take the value of omega 12 ＝ω 34 ＝4、ω 23 ＝3。
The CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the first unit 1 on the left communicates with the second unit 2, and the unit 3 on the right communicates with the unit 4; establishing the relation between the left side and the right side through the first unit 1 and the third unit 3; wherein the coupling weight omega of the jth unit to the ith unit ij Presence of only omega 12 、ω 13 、ω 34 Three forms, which can take the value of omega 12 ＝ω 34 ＝2、ω 13 ＝1。
The CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the first unit 1 on the left communicates with the second unit 2, and the unit 3 on the right communicates with the unit 4; establishing the relation between the left side and the right side through the first unit 1 and the third unit 3 and the second unit 2 and the fourth unit 4; wherein the coupling weight omega of the jth unit to the ith unit ij Presence of only omega 12 、ω 34 、ω 13 、ω 24 Four forms, value omega 12 ＝ω 34 ＝4、ω 13 ＝ω 24 ＝2。
The CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the first unit 1 on the left communicates with the second unit 2, the unit 3 on the right communicates with the unit 4; establishing the relation between the left side and the right side through the second unit 2 and the third unit 3 and the first unit 1 and the fourth unit 4; wherein the coupling weight omega of the jth unit to the ith unit ij Presence of only omega 12 、ω 23 、ω 34 、ω 41 Four forms, value omega 12 ＝ω 23 ＝ω 41 ＝ω 34 ＝3。
The CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the first unit 1 on the left communicates with the second unit 2, and the unit 3 on the right communicates with the unit 4; tong (Chinese character of 'tong')The first unit 1 and the fourth unit 4 establish the relation between the left side and the right side; wherein the coupling weight omega of the jth unit to the ith unit ij Presence of only omega 12 、ω 34 、ω 14 Three forms, value is omega 12 ＝ω 34 ＝2、ω 14 ＝1。
Advantageous effects
The invention provides a heading control method of a sliding-flapping integrated aircraft, which comprises the steps of obtaining current heading information through an attitude sensor and calculating a yaw value; according to the speed of the longitudinal plane of the current aircraft, when the speed of the gliding longitudinal plane of the aircraft is higher, the parameters obtained by the fuzzy PD control algorithm are converted into the rotation angle value of the rolling mechanism for course control by utilizing fuzzy PD control, when the speed is lower, in the following diving-floating conversion stage, the parameters obtained by the fuzzy PD control algorithm are used as CPG amplitude variables, and then a CPG controller outputs flapping wing control signals, which are specifically expressed as asymmetric flapping wing amplitudes for navigation.
The invention has the following beneficial effects:
1. compared with an object which is difficult to model by a conventional underwater vehicle simulated manta ray, the fuzzy PD control has the characteristics of quick response, flexibility and the like of the fuzzy control, and has the effects of increasing the stability of a system, reducing the maximum deviation and the residual error, accelerating the control process and improving the control quality.
2. The traditional underwater vehicle adopts a propeller or a rudder to realize course control, and the simulated bat ray vehicle combines gliding propulsion of a glider and flexible propulsion of a simulated marine organism bat ray, and has the characteristic of integrating gliding and flapping, so that the traditional propulsion mode is not suitable for the simulated bat ray vehicle. Therefore, the bionic underwater vehicle adopts the asymmetric amplitude generated by the rolling mechanism and the flapping wings to carry out course control, has the characteristics of low power consumption when the glider glides to propel to control the course, and also has the characteristic of high maneuverability when the flapping propels to propel to control the course, and provides a new idea for the course control of the bionic underwater vehicle integrating gliding and flapping.
3. When the longitudinal speed is reduced and the course cannot be effectively controlled by the roll mechanism, the asymmetrical amplitude control is adopted instead, the yaw speed of the simulated bat ray underwater vehicle continuously changes along with the increase of the amplitude difference of the flapping wings at the two sides, the transition is more gradual, the turning speed is slow, the overshoot is reduced, and meanwhile, when the yaw speed is slow, the yaw control precision is obviously improved, so that the method is suitable for the course control which needs the accurate and stable course of the vehicle; the method overcomes the defect that the course of the traditional glider cannot be well controlled by adopting a rolling mechanism when the sailing speed is reduced, and also ensures that the sailor has higher accuracy in the whole course process and can complete the task needing accurate course control.
Drawings
FIG. 1 is a schematic view of a navigation principle of fuzzy PD control of an simulated bat ray aircraft according to the present invention;
FIG. 2 is a connection diagram of a CPG topology 1 constructed by the present invention;
FIG. 3 is a schematic connection diagram of CPG topology 2 constructed by the present invention;
fig. 4 is a schematic connection diagram of a CPG topology 3 constructed by the present invention;
fig. 5 is a schematic connection diagram of a CPG topology 4 constructed by the present invention;
FIG. 6 is a schematic connection diagram of a CPG topology 5 constructed by the present invention;
FIG. 7 is a flowchart illustrating the navigation process of the present invention.
Detailed Description
The invention will now be further described with reference to the following examples and drawings:
the method comprises the following steps of obtaining a current course angle and a current longitudinal speed of a vehicle through an attitude sensor, and selecting different execution mechanisms to adjust the course according to the longitudinal speed, wherein the method specifically comprises the following steps:
1. obtaining the current course angle of an underwater vehicle through an attitude sensor
The target course angle set by the task is
Then the yaw angle e, then
2. And (3) deriving the yaw angle to obtain a course angle deviation change rate ec, then:
wherein t is the attitude sensor information updating time of the underwater vehicle.
Discretizing the above equation into:
wherein e (t) is the course angle deviation of the current moment, and e (t-1) is the course angle deviation of the last moment.
3. Blurring the obtained yaw angle and heading deviation change rate to obtain a fuzzy quantity with a discrete domain of {3, 2, 1, 0, -1, -2, -3}, wherein the blurred linguistic variables are expressed by negative large (NB), Negative Medium (NM), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Medium (PM) and positive large (PB). The fuzzy sets are as follows:
ec＝{NB,NM,NS,ZO，PS，PM，PB} (4)
e＝{NB,NM,NS,ZO,PS,PM,PB} (5)
giving the fuzzified yaw angle and course deviation change rate to a fuzzy rule table for table lookup, namely performing table query by taking an ec value as a vertical coordinate and an e value as a horizontal coordinate, performing self-tuning on the original PD parameters, wherein the fuzzy rule table is shown in tables 3 and 4, and obtaining delta k according to the fuzzy rule table p And k d Values, corrected PD parameters are:
wherein k is p Is the original scale factor, k d Is an original differential coefficient; Δ k p Look-up tables for fuzzy controllersThe obtained proportional coefficient setting adjustment quantity, delta k d Obtaining a differential coefficient setting adjustment quantity for a fuzzy controller by looking up a table; k is a radical of formula pF Adjusting quantity delta k for proportional coefficient setting obtained by looking up table of fuzzy controller p Coefficient of proportionality to original k p Summed scaling factor, k dF Adjusting quantity delta k for setting differential coefficient obtained by looking up table of fuzzy controller d Coefficient of differentiation from the original delta k d The added differential coefficients;
attached Table 3:
k p fuzzy control coefficient correction table
Attached table 4:
k d fuzzy control coefficient correction table
The course control quantity calculated by the PD controller after the setting of the fuzzy controller is as follows:
discretization can obtain:
the knowledge related to fluid power can be used, and under the condition that the longitudinal speed of the aircraft is low, the yaw moment generated by the roll angle is small, and the turning effect is not obvious. Based on the design, the rolling mechanism and the flapping wings cooperate to realize navigation of the aircraft. According to the method, a navigation task is divided into the following two conditions by taking the longitudinal speed v acquired by an aircraft from an attitude sensor as a judgment condition:
a) rapidly floating up and submerging: and when v is larger than a, the underwater vehicle is in a rapid submerging/floating stage, the course is controlled by adopting the roll mechanism, the roll mechanism in the vehicle is adjusted to roll left and right according to the calculated control quantity, and the roll angle of the vehicle is changed, so that the yaw attitude is realized, and the navigation task is finished.
Wherein, the offset angle of the rolling block of the rolling mechanism is calculated according to the control quantity, and the specific formula is as follows:
in the formula: roll is the angle of the offset of the rolling block, B l The left-turning maximum deviation angle of the transverse rolling block is a positive value; b r The maximum right-turning offset angle of the rolling block is a negative value; b is z Is the zero position of the rolling block. The deflection range of the rolling block is [ B ] r B l ]And y (t) the control quantity output of the controller, wherein A is a control quantity conversion coefficient, and M is a control quantity limit value, so that the mechanism deflection is prevented from exceeding the limit value due to the overlarge value of the input y (t).
If y (t) is calculated to be 6, the roll fast deflection range is [ -48,48], A is 0.1, and M is 5, then the roll is calculated to be 48.
b) When diving and floating are switched: when v is less than or equal to a, the underwater vehicle is in a diving and floating conversion stage, the longitudinal speed is low, and the course is controlled by changing the asymmetric amplitude of the flapping wings;
in order to enable flapping wings to flap smoothly, an artificial CPG neural control network is constructed to realize the flapping control of the simulated bat ray aircraft, a CPG phase oscillator model which is connected most simply is adopted, the left pectoral fin of the simulated bat ray aircraft comprises 2 steering engines which are named as steering engines 1 and 2 respectively, and the right pectoral fin steering engines are named as steering engines 3 and 4 respectively. Each steering engine is controlled by a phase oscillator model, and the mutual connection among the steering engines is realized through a coupling item. The left pectoral fin unit 1 is connected with the unit 2; the right pectoral fin unit 3 is in communication with the unit 4; the connection between the left and right pectoral fins is established by the pectoral fin intermediate units 2 and 3. The connection mode is shown in fig. 2, and the model mainly comprises a phase equation, an amplitude equation and an output equation, and specifically comprises the following steps:
wherein each equation is a phase equation, an amplitude equation and an output equation. Phi in the formula i Denotes the phase, v, of the ith cell i Representing the natural frequency, ω ij Representing the coupling weight of the jth cell to the ith cell,
representing the desired phase difference; r is a radical of hydrogen i Denotes the amplitude, a i Normal number, R, representing the rate of convergence of the control amplitude i Representing a desired amplitude; theta.theta. i Representing the output value.
The mutual connection among the steering engines is realized through coupling terms, omega ij Represents the coupling term of the jth unit to the ith unit, and the connection mode is omega ij Presence of only omega 12 、ω 13 、ω 23 Three forms, which can take the value of omega 12 ＝ω 34 ＝4、ω 23 ＝3。
The control quantity obtained by the fuzzy PD calculation is converted by a formula (11-12) and then is input into a CPG network as an amplitude variation quantity, the phase difference and the frequency of the arranged flapping wings are input at the same time, and the angle theta of the flapping wings is obtained by iterative calculation of the CPG network i Thus realizing course control by using asymmetric amplitude.
Wherein Q is a desired amplitude of the direct current, y (t) is a control amount output of the controller, and R 1 、R 2 、R 3 、R 4 The desired phase difference is for steering engines 1, 2, 3, 4, respectively.
When the aircraft e is larger than 0 and the course is adjusted by left turning, the amplitude of the left side of the flapping wing is reduced, the amplitude of the right side of the flapping wing is increased, the propulsion Fl of the left side flapping wing is smaller than the propulsion Fr of the right side flapping wing, and the left turning is completed to reach the target course; when the aircraft e <0 needs to turn right to adjust the course, the amplitude of the left side of the flapping wing is increased, the amplitude of the right side of the flapping wing is reduced, the propulsion Fl of the left side flapping wing is greater than the propulsion Fr of the right side flapping wing, and the right turn is completed to reach the target course.
If the course is adjusted by turning left when e is larger than 0, the phase difference between the two sides of the input flapping wing is 30, the frequency is 0.3hz, the Q is 30 degrees, and the y (t) calculated by the fuzzy PD controller is 4, so that the navigation vehicle turns by using the amplitude value at the left side of 14 degrees, the amplitude value at the right side of 46 degrees, the phase difference between the two sides of 30 degrees and the frequency of 0.3hz to achieve the purpose of controlling the course.
Fig. 7 shows a flowchart of the specific procedure.
When the CPG phase oscillator model topology adopts the graph of FIG. 3, the unit connection in the oscillator model is the unit 1 and the unit 2; unit 1 is connected with unit 3; unit 3 is connected to unit 4. Omega ij Representing the coupling term of the j-th cell to the i-th cell, in such a way that ω ij Presence of only omega 12 、ω 13 、ω 34 Three forms, which can take the value of omega 12 ＝ω 34 ＝2、ω 13 ＝1。
When the CPG phase oscillator model topology adopts the graph of FIG. 4, the unit connection in the oscillator model is the unit 1 and the unit 2; unit 3 is connected with unit 4; unit 1 is connected with unit 3; unit 2 is connected to unit 4. Omega ij Representing the coupling term of the j-th cell to the i-th cell, in such a way that ω ij Presence of only omega 12 、ω 34 、ω 13 、ω 24 Four forms, which can take the value of omega 12 ＝ω 34 ＝4、ω 13 ＝ω 24 ＝2。
When the CPG phase oscillator model topology employs FIG. 5, the cells in the oscillator modelThe connection is that the unit 1 is connected with the unit 2; unit 2 is connected with unit 3; unit 3 is connected with unit 4; unit 4 is connected to unit 1. Omega ij Representing the coupling term of the j-th cell to the i-th cell, in such a way that ω ij Presence of only omega 12 、ω 23 、ω 34 、ω 41 Four forms, which can take the value of omega 12 ＝ω 23 ＝ω 41 ＝ω 34 ＝3。
When the CPG phase oscillator model topology adopts the graph of FIG. 6, the unit connection in the oscillator model is the unit 1 and the unit 2; unit 3 is connected with unit 4; unit 1 is connected to unit 4. Omega ij Representing the coupling term of the j-th cell to the i-th cell, in such a way that ω ij Presence of only omega 12 、ω 34 、ω 14 Three forms, which can take the value of omega 12 ＝ω 34 ＝2、ω 14 ＝1。
Claims (6)
1. A heading control method of a flapping-sliding integrated aircraft is characterized by comprising the following steps: the left side of the sliding and flapping integrated aircraft comprises 2 steering engines which are respectively named as a first steering engine unit (1) and a second steering engine unit (2), and the right side of the sliding and flapping integrated aircraft is named as a third steering engine unit (3) and a fourth steering engine unit (4); each steering engine unit is controlled by the output of a conversion formula to form a unit; the course control steps are as follows:
step 1: obtaining current course angle of underwater vehicle through attitude sensor
The target course angle set by the task is
Yaw angle e:
and 2, step: and (3) deriving the yaw angle to obtain a course angle deviation change rate ec:
wherein t is the information updating time of the attitude sensor of the underwater vehicle;
and step 3: fuzzifying the obtained yaw angle and heading deviation change rate, wherein the fuzzified linguistic variables are expressed by NB, namely negative large, NM, namely negative small, NS, namely zero, ZO, PS, namely positive small, PM, namely positive large, PB, and the fuzzy set is as follows:
ec＝{NB,NM,NS,ZO,PS,PM,PB}
e＝{NB,NM,NS,ZO,PS,PM,PB}
giving the fuzzified yaw angle and course deviation change rate to a fuzzy rule table, taking the ec value as a vertical coordinate and the e value as a horizontal coordinate, self-tuning the original PD number, and obtaining delta k according to the fuzzy rule table 1 and the fuzzy rule table 2 p 、k d Values, corrected PD parameters are:
wherein k is p Is the original scale factor, k d Is the original differential coefficient; Δ k p The proportional coefficient setting adjustment quantity, delta k, obtained by looking up a table for a fuzzy controller d Obtaining a differential coefficient setting adjustment quantity for a fuzzy controller by looking up a table; k is a radical of pF For the adjustment quantity delta k of the proportional coefficient setting obtained by the look-up table of the fuzzy controller p With the original proportionality coefficient k p Summed scaling factor, k dF Setting adjustment quantity delta k of differential coefficient obtained by looking up table of fuzzy controller d With the original differential coefficient ak d The added differential coefficients;
fuzzy rule Table 1
k p Fuzzy control coefficient correction table
Fuzzy rule table 2
k d Fuzzy control coefficient correction table
And 4, step 4: the course control quantity calculated by the PID controller after the fuzzy controller is set is as follows:
dt is the differential time;
discretizing to obtain:
wherein y (t) is the control output of the controller at the current moment; t is a discrete time interval;
and 5: according to the method, a navigation task is divided into the following two conditions by taking the longitudinal speed v acquired by an aircraft from an attitude sensor as a judgment condition:
a) when v is larger than a, the underwater vehicle is in a rapid submerging/floating stage, a rolling mechanism is adopted to control the course, the rolling mechanism inside the vehicle is adjusted to roll left and right according to the calculated control quantity, and the rolling angle of the vehicle is changed, so that the yaw attitude is realized, and the navigation task is finished;
calculating the offset angle of the rolling block of the rolling mechanism according to the control quantity:
in the formula: roll is the angle of the offset of the rolling block, B l Maximum left-turn offset of the rolling blockAngle, positive; b r The maximum right-turning offset angle of the rolling block is a negative value; b is z Is the zero position of the rolling block; the deflection range of the rolling block is [ B ] r B l ]Outputting the control quantity of the controller, wherein A is a control quantity conversion coefficient, and M is a control quantity limit value, so that the mechanism deflection is prevented from exceeding the limit value due to the overlarge value of the input y (t);
b) when v is less than or equal to a, the underwater vehicle is in a diving and floating conversion stage, the longitudinal speed is low, and the course is controlled by changing the asymmetric amplitude of the flapping wings;
and 6: converting the control quantity obtained by the fuzzy PD calculation, inputting the converted control quantity into a CPG network as an amplitude variation quantity, inputting the phase difference and the frequency of the arranged flapping wing, and obtaining the flapping angle of the flapping wing by the iterative calculation of the CPG network, thereby realizing the purpose of finishing course control by using asymmetric amplitude;
the conversion formula is:
wherein e yaw angle, Q is desired amplitude during straight-stream, y (t) is output of control quantity of controller, and R 1 、R 2 、R 3 、R 4 Expected phase differences of the steering engines 1, 2, 3 and 4 are respectively obtained;
the CPG network of the flapping-sliding integrated aircraft comprises the following components:
each equation is respectively a phase equation, an amplitude equation and an output equation; in the formula i Representing the phase, v, of the ith cell i Representing natural frequency, ω ij Representing the coupling weight of the jth cell to the ith cell,
representing the desired phase difference; r is i Denotes the amplitude, a i Normal number, R, representing the rate of convergence of the control amplitude i Representing a desired amplitude; theta.theta. i Representing the output value.
2. The heading control method of the integrated vehicle of claim 1, wherein the method comprises the following steps: the CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the left first steering engine unit (1) is communicated with the second steering engine unit (2), and the right third steering engine unit (3) is communicated with the fourth steering engine unit (4); the left side and the right side are connected through a second steering engine unit (2) and a third steering engine unit (3); wherein the coupling weight omega of the jth steering engine unit to the ith steering engine unit ij Presence of only omega 12 、ω 13 、ω 23 Three forms, which can take the value of omega 12 ＝ω 13 ＝4、ω 23 ＝3。
3. The method for controlling the heading of an integrated vehicle according to claim 1, wherein: the CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the left first steering engine unit (1) is communicated with the second steering engine unit (2), and the right third steering engine unit (3) is communicated with the fourth steering engine unit (4); establishing a left-right side relation through the first steering engine unit (1) and the third steering engine unit (3); wherein the coupling weight omega of the jth steering engine unit to the ith steering engine unit ij Presence of only omega 12 、ω 13 、ω 34 Three forms, which can take the value of omega 12 ＝ω 34 ＝2、ω 13 ＝1。
4. The heading control method of the integrated vehicle of claim 1, wherein the method comprises the following steps: the CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the first steering engine unit (1) on the left side is communicated with the second steering engine unit (2), and the third steering engine unit (3) on the right side is communicated with the fourth steering engine unit (4); through a first steering engine unit (1) and a third steering engine unitThe left side and the right side of the steering engine unit (3) are connected with the second steering engine unit (2) and the fourth steering engine unit (4); wherein the coupling weight omega of the jth steering engine unit to the ith steering engine unit ij Presence of only omega 12 、ω 34 、ω 13 、ω 24 Four forms, value omega 12 ＝ω 34 ＝4、ω 13 ＝ω 24 ＝2。
5. The heading control method of the integrated vehicle of claim 1, wherein the method comprises the following steps: the CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the left first steering engine unit (1) is communicated with the second steering engine unit (2), and the right third steering engine unit (3) is communicated with the fourth steering engine unit (4); the left side and the right side are connected through a second steering engine unit (2), a third steering engine unit (3), a first steering engine unit (1) and a fourth steering engine unit (4); wherein the coupling weight omega of the jth steering engine unit to the ith steering engine unit ij Presence of only omega 12 、ω 23 、ω 34 、ω 41 Four forms, value omega 12 ＝ω 23 ＝ω 41 ＝ω 34 ＝3。
6. The heading control method of the integrated vehicle of claim 1, wherein the method comprises the following steps: the CPG network topology structure of the flapping-sliding integrated aircraft is as follows: the first steering engine unit (1) on the left side is communicated with the second steering engine unit (2), and the third steering engine unit (3) on the right side is communicated with the fourth steering engine unit (4); the left side and the right side are connected through the first steering engine unit (1) and the fourth steering engine unit (4); wherein the coupling weight omega of the jth steering engine unit to the ith steering engine unit ij Presence of only omega 12 、ω 34 、ω 14 Three forms, value is omega 12 ＝ω 34 ＝2ω 14 ＝1。
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