CN106708068B - Bionical fluctuation fin promotes submarine navigation device path tracking control method - Google Patents
Bionical fluctuation fin promotes submarine navigation device path tracking control method Download PDFInfo
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Abstract
The present invention discloses a kind of bionical fluctuation fin propulsion submarine navigation device path tracking control method.This method comprises: acquiring bionical fluctuation fin promotes the real-time position of submarine navigation device and course；The current location of submarine navigation device and desired track path are promoted according to bionical fluctuation fin, calculates sight line point and desired course angle that bionical fluctuation fin promotes submarine navigation device currently to need to track；Submarine navigation device current location, course and sight line point are promoted according to bionical fluctuation fin, bionical fluctuation fin is designed using Backstepping and the dynamics Controlling of submarine navigation device is promoted to restrain；Dynamics Controlling amount is established based on fuzzy reasoning and bionical fluctuation fin promotes submarine navigation device to fluctuate the mapping relations between fin control parameter, obtains the long fin control amount in two sides；Submarine navigation device is promoted to carry out real-time navigation control bionical fluctuation fin according to the long fin control amount in two sides.Thus the embodiment of the present invention solves the technical issues of how making bionical fluctuation fin that submarine navigation device be promoted accurately to realize underwater path trace.
Description
Technical Field
The invention relates to the technical field of bionics, in particular to a path tracking control method for an underwater vehicle propelled by a bionic wave fin.
Background
Currently, autonomous underwater vehicles have been widely used in the fields of oceans and military affairs, such as marine organism observation, underwater resource exploration, marine military strikes, and the like. With the increasing requirements on the maneuverability, stability, anti-interference capability, noise and other aspects of the underwater vehicle, the bionic underwater vehicle adopting the fluctuated fin for propulsion gradually receives the attention of researchers and engineers.
In the last decade researchers have designed a variety of wave fin propelled underwater vehicles. As early as 2001, the university of herring watts, uk, designed a long fin drive. In 2012, Nanyang university of science and technology developed a bionic machine bat ray. In 2013, a bionic long-fin driven robotic fish is developed by simulating a saury at northwest university. However, most researchers above focus on the control of the wave fin, and rarely consider the precise motion control of the underwater vehicle, which is often very important for the practical application of the bionic underwater vehicle. The main reason for the above defects may be that the underwater vehicle propelled by the wave fin is a multivariable, nonlinear, strongly coupled under-actuated system, and it is difficult to establish an accurate system model and to implement accurate closed-loop position control.
The goal of path tracking control is to move the vehicle along a previously planned spatial trajectory. For the path tracking problem of underwater vehicles, researchers at home and abroad also carry out some research works. For example, Aguiar and the like adopt a Lyapunov direct method and a backstepping design method to design a nonlinear adaptive path point tracking controller, and simulation results show that the controller can control an under-actuated underwater vehicle to move along a path consisting of specified path points. The method is characterized in that a path tracking error model is established based on a virtual guide aiming at the problem of linear path tracking control of an under-actuated underwater vehicle, such as Wangman construction, and a path tracking controller is designed by adopting a feedback gain back-stepping method. A simplified adaptive neural network control framework is designed for the problem of under-actuated ship path tracking by using a back-stepping method in Zhangnational celebration and the like, and the effectiveness of the framework is proved by numerical simulation. Although the above-mentioned documents achieve ideal results in path tracking control, most methods rely on accurate mathematical models, however, accurate mathematical models of underwater vehicles, especially those propelled by the wave fins, are often difficult to obtain in practice, which results in insufficient adaptability of the controller to model parameter uncertainty and external disturbance, and thus low tracking accuracy, and few researchers apply the proposed path tracking control methods to practical systems, which may be caused by uncertainty and complexity of the underwater environment. It should be noted that the driving mode of the bionic heave fin propulsion underwater vehicle is greatly different from that of the traditional propeller-driven underwater vehicle, and a path tracking method needs to be specially designed for the bionic heave fin propulsion underwater vehicle.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
In order to solve the above problems in the prior art, namely to solve the technical problem of how to accurately track the underwater path of the underwater vehicle propelled by the bionic skeg, a path tracking control method for the underwater vehicle propelled by the bionic skeg is provided.
In order to achieve the purpose, the following technical scheme is provided:
a bionic wave fin propulsion underwater vehicle path tracking control method comprises the following steps:
determining a desired tracking path;
acquiring the real-time position and course of the bionic fin propulsion underwater vehicle;
calculating a sight line point and an expected course angle which need to be tracked currently by the underwater vehicle propelled by the bionic wave fin according to the current position and the expected tracking path of the underwater vehicle propelled by the bionic wave fin;
designing a dynamic control law of the bionic wave fin propulsion underwater vehicle by utilizing a backstepping method according to the current position, the course and the sight line point of the bionic wave fin propulsion underwater vehicle;
establishing a mapping relation between the dynamic control quantity and the control parameters of the bionic wave fin propelling underwater vehicle wave fin based on fuzzy reasoning to obtain control quantities of long fins on two sides;
and performing real-time navigation control on the bionic wave fin propelled underwater vehicle according to the control quantity of the long fins on the two sides, and realizing path tracking control.
Preferably, the determining of the desired tracking path specifically comprises:
determining a desired tracking path according to:
Ω(s)＝[xd(s),yd(s)]T
where Ω(s) represents the desired traceDiameter; s represents the arc length of the desired tracking path; x is the number ofd(s)、yd(s) represents the coordinates of a point on the desired tracking path.
Preferably, the method for calculating the current sight point and the expected heading angle to be tracked of the underwater vehicle propelled by the bionic heave fin according to the current position and the expected tracking path of the underwater vehicle propelled by the bionic heave fin comprises the following steps:
determining a sight line point according to the current position of the bionic fin propulsion underwater vehicle;
determining a direction angle of a vector of a current position of the bionic fin propelled underwater vehicle pointing to a sight line point as a first expected course angle;
and compensating by using the sight line navigation system to obtain a second expected course angle, and using the second expected course angle as an expected course angle of the bionic fluctuated fin propulsion underwater vehicle.
Preferably, the step of determining the sight line point according to the current position of the bionic fin propulsion underwater vehicle specifically comprises the following steps:
if the distance between the bionic wave fin propulsion underwater vehicle and the expected tracking path is smaller than a distance threshold, determining an intersection point at the front end of the expected tracking path as a sight line point;
and if the distance between the underwater vehicle propelled by the bionic wave fin and the expected tracking path is greater than or equal to the distance threshold value, determining a point on the expected tracking path, which is closest to the current position of the underwater vehicle propelled by the bionic wave fin, as a sight line point.
Preferably, a dynamic control law for propelling the underwater vehicle by the bionic wave fin is designed by a backstepping method according to the current position, the course and the sight line point of the underwater vehicle propelled by the bionic wave fin, and the method specifically comprises the following steps:
according to the sight point coordinates, the following tracking error equation is established:
wherein e isxyPropelling a horizontal distance between the underwater vehicle and the expected tracking path for the bionic heave fin; psieIs a course angle deviationA difference; ψ represents a heading; psiDRepresenting a second desired heading angle; x is the number ofd、ydRepresenting the position of the gaze point; x and y respectively represent the real-time position of the bionic wave fin propelled underwater vehicle;
according to a tracking error equation, establishing the following kinematic model of the bionic wave fin propulsion underwater vehicle:
wherein,representing the horizontal distance between the bionic fin propulsion underwater vehicle and the expected tracking path;a derivative representing a heading angle deviation; u, v and r are respectively expressed as the advancing and retreating speed, the lateral moving speed and the yaw speed of the bionic wave fin propulsion underwater vehicle;
and (3) calculating to obtain a kinematic tracking control law according to the kinematic model:
wherein δ is an arbitrarily small normal number; n is any natural number; psieIs the course angle deviation; k is a radical of1,k2Design parameters for the controller and satisfy k2>k1>0；
According to the kinematics tracking control law, the following dynamics control laws are obtained through calculation:
wherein, tauu、τrRespectively, the kinetic control quantities, τuIndicating a propulsive force in a forward or backward direction, τrRepresenting a yaw moment; k is a radical ofi(i-1 … 4) represents the controller design parameters,and satisfy ki>0，k2>k1>0；Representing derivatives of a parameter of a tracking control law of kinematics control, where1＝k1(exy-δ)cosn(ψe) N is a positive integer,m11、m22、m33representing the mass of the bionic wave fin propulsion underwater vehicle and elements on the diagonal line of an additional mass matrix; d11、d33Representing elements on a diagonal of the linear damping matrix; beta is a1、β3Representing the amount of kinematic error, beta1＝u-α1，β3＝r-α3。
Preferably, a mapping relation between the dynamic control quantity and the control parameters of the bionic wave fin propulsion underwater vehicle wave fin is established based on fuzzy reasoning to obtain the control quantity of the long fins on two sides, and the method specifically comprises the following steps:
establishing a mapping relation between dynamic control quantity and bionic wave fin propulsion underwater vehicle wave fin control parameters based on fuzzy reasoning, and fuzzifying; the control parameters of the bionic wave fin propulsion underwater vehicle wave fin comprise left long fin surface wave frequency, right long fin surface wave frequency, fin surface wave amplitude and adjacent fin line phase difference;
establishing a fuzzy rule base;
obtaining fuzzy control quantities of fluctuation frequency of left and right fins, wave amplitude of fin surface and phase difference of adjacent fin rays by adopting a minimum method according to a fuzzy rule base, propulsion force in the advancing and retreating directions after fuzzification and yaw moment;
and performing deblurring operation by adopting a weighted average method according to the fuzzy control quantity to obtain the control quantity of the long fins on two sides.
Preferably, a mapping relation between the dynamic control quantity and the bionic wave fin propulsion underwater vehicle wave fin control parameters is established based on fuzzy reasoning, and fuzzification is carried out, wherein the mapping relation specifically comprises the following steps:
determining domains of advancing and retreating direction propelling force, yawing moment, fluctuation frequency of left and right fins, fin surface wave amplitude and adjacent fin ray phase difference;
and selecting a fuzzy language subset and a triangular membership function so as to perform fuzzification.
The embodiment of the invention provides a path tracking control method for a bionic wave fin propelled underwater vehicle. The method comprises the following steps: determining a desired tracking path; acquiring the real-time position and course of the bionic fin propulsion underwater vehicle; calculating a sight line point and an expected course angle which need to be tracked currently by the underwater vehicle propelled by the bionic wave fin according to the current position and the expected tracking path of the underwater vehicle propelled by the bionic wave fin; designing a dynamic control law of the bionic wave fin propulsion underwater vehicle by utilizing a backstepping method according to the current position, the course and the sight line point of the bionic wave fin propulsion underwater vehicle; establishing a mapping relation between the dynamic control quantity and the control parameters of the bionic wave fin propelling underwater vehicle wave fin based on fuzzy reasoning to obtain control quantities of long fins on two sides; and performing real-time navigation control on the bionic wave fin propelled underwater vehicle according to the control quantity of the long fins on the two sides, and realizing path tracking control. By adopting the technical scheme, the embodiment of the invention solves the technical problem of accurately realizing the underwater path tracking by propelling the underwater vehicle by the bionic wave fin, improves the underwater motion control precision of the underwater vehicle by the bionic wave fin, improves the path tracking precision and also shortens the redundant range of the underwater vehicle by the bionic wave fin.
Drawings
FIG. 1 is a schematic structural diagram of a bionic heave fin propulsion underwater vehicle path tracking controller according to an embodiment of the invention;
FIG. 2 is a schematic flow chart of a method for controlling the path tracking of a bionic wave fin propelled underwater vehicle according to an embodiment of the invention;
FIG. 3 is a schematic diagram of a line-of-sight navigation system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of the operation of a propulsion and yaw moment-traveling wave parameter mapping model based on fuzzy inference according to an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a linear path tracking of a bionic heave fin propelled underwater vehicle according to an embodiment of the invention;
FIG. 6 is a schematic diagram illustrating a trajectory tracked by a straight path of a bionic heave fin propelled underwater vehicle according to an embodiment of the invention;
FIG. 7 is a schematic diagram of a bionic heave fin propelled underwater vehicle straight-line path tracking error curve according to an embodiment of the invention;
FIG. 8 is a schematic diagram of a bionic heave fin propelled underwater vehicle circular path tracking according to an embodiment of the invention;
FIG. 9 is a schematic diagram of a path tracking trajectory of a bionic heave fin propelled underwater vehicle according to an embodiment of the invention;
FIG. 10 is a schematic diagram of a bionic wave fin propelled underwater vehicle circular path tracking error curve according to an embodiment of the invention.
Detailed Description
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and are not intended to limit the scope of the present invention.
The method provided by the embodiment of the invention is based on a bionic wave fin propulsion underwater vehicle path tracking controller. Fig. 1 schematically shows the structure of a bionic heave fin propulsion underwater vehicle path tracking controller. As shown in fig. 1, the controller mainly includes: the system comprises a sight line navigation system, a backstepping method controller and a parameter mapping system based on fuzzy reasoning. The line-of-sight navigation system receives a desired tracking path and a real-time position (x, y) fed back by a bionic fin propulsion underwater vehicle (RobCutt-II), and then outputs a line-of-sight point to the backstepping controller; the backstepping method controller also receives real-time position and course information fed back by the RobContt-II, outputs propulsion force and yawing moment in the advancing and retreating directions and outputs the propulsion force and the yawing moment to a parameter mapping system based on fuzzy reasoning; and after the parameter mapping system based on fuzzy reasoning processes the data, outputting the left long fin surface wave frequency, the right long fin surface wave frequency, the fin surface wave amplitude and the phase difference of adjacent fin rays to the RobButt-II.
The embodiment of the invention provides a path tracking control method for a bionic wave fin propelled underwater vehicle. As shown in fig. 2, the method may include:
s1: a desired tracking path is determined.
This step describes the parameterized equations for a given desired tracking path. The desired tracking path may be planned in advance.
Specifically, the step may include:
determining a desired tracking path according to:
Ω(s)＝[xd(s),yd(s)]T
where Ω(s) represents the desired tracking path; s represents the arc length of the desired tracking path; x is the number ofd(s)、yd(s) represents the coordinates of a point on the desired tracking path.
Ω(s)＝[xd(s),yd(s)]TThe coordinates in the fixed coordinate system for a given desired path are expressed as a function of a scalar parameter.
S2: and acquiring the real-time position and the real-time course of the underwater vehicle propelled by the bionic fluctuated fin.
In practical application, the real-time position (x, y) and heading psi of the bionic fin propulsion underwater vehicle (RobCutt-II) can be acquired by an inertial navigation system or a global vision system.
S3: and calculating the sight point and the expected course angle which need to be tracked currently by the underwater vehicle propelled by the bionic wave fin according to the current position and the expected tracking path of the underwater vehicle propelled by the bionic wave fin.
Specifically, the step may include:
s31: and determining a sight line point according to the current position of the bionic fin propulsion underwater vehicle.
The step may further comprise:
s311: if the distance between the bionic wave fin propulsion underwater vehicle and the expected tracking path is smaller than a distance threshold, determining an intersection point at the front end of the expected tracking path as a sight line point;
s312: and if the distance between the underwater vehicle propelled by the bionic wave fin and the expected tracking path is greater than or equal to the distance threshold value, determining a point on the expected tracking path, which is closest to the current position of the underwater vehicle propelled by the bionic wave fin, as a sight line point.
Fig. 3 schematically illustrates the operation of the line-of-sight navigation system.
For example, as shown in fig. 3, let the real-time position of the bionic fin propulsion underwater vehicle obtained in the second step be p (x, y), the heading direction be ψ, and the existence of the bionic fin propulsion underwater vehicle with p (x, y) as the center and the radius γ>A virtual circle of 0 accompanies this. If the distance between the underwater vehicle propelled by the bionic fluctuated fin and the expected tracking path omega is less than gamma, a virtual circle accompanying the underwater vehicle propelled by the bionic fluctuated fin intersects the expected tracking path at two points p'los,plos(xd,yd) At this time, the sight line point is selected as the intersection point p of the more front end on the expected tracking pathlos(xd,yd) (ii) a If the distance between the underwater vehicle propelled by the bionic wave fin and the expected tracking path is larger than or equal to gamma, a virtual circle accompanying the underwater vehicle propelled by the bionic wave fin does not have a crossing point with the expected tracking path or only intersects at one point, and at the moment, the sight line point is selected as the point, closest to the current position of the underwater vehicle propelled by the bionic wave fin, on the expected tracking path.
S32: and determining the direction angle of a vector of the current position of the bionic fin propelled underwater vehicle pointing to the sight line point as a first expected heading angle.
After the gaze point is determined, to control movement of the RobButt-II toward the gaze point, the first desired heading angle ψ of the RobButt-II may be setdThe direction angle defined as the vector pointing from the RobCutt-II current position to the gaze point, i.e. the first desired heading angle, may be defined as:
wherein x ise＝x-xd,ye＝y-yd；xdAnd ydRepresenting the position of the gaze point; sgn (·) denotes a sign function, and sgn (0) ═ 1; psidRepresenting a first desired voyageA direction angle; and x and y represent the real-time position of the RobCutt-II.
S33: and compensating by using the sight line navigation system to obtain a second expected course angle, and using the second expected course angle as an expected course angle of the bionic fluctuated fin propulsion underwater vehicle.
To reduce the tracking error in the presence of unknown disturbances, this step adds a compensation term based on the first desired heading angle described by the above equation.
For example, the second desired heading angle is obtained using the line-of-sight navigation system according to:
ψD＝ψd+c0tanh(c1exy)·flr
wherein e isxyIs the horizontal distance between RobContt-II and the desired tracking path; c. C0,c1Is an adjustable parameter; f. oflrAs a function of sign, f when RobCltt-II is to the left of the desired tracking pathlr1, when RobButt-II is on the desired pathlrWhen robutt-II is to the right of the desired tracking path, f ═ 0lr＝-1；ψDRepresenting a second desired heading angle.
S4: and designing a dynamics control law of the bionic wave fin propulsion underwater vehicle by utilizing a backstepping method according to the current position, the course and the sight line point of the bionic wave fin propulsion underwater vehicle.
Specifically, the step may include:
s41: according to the sight point coordinates, the following tracking error equation is established:
wherein e isxyPropelling a horizontal distance between the underwater vehicle and the expected tracking path for the bionic heave fin; psieIs the course angle deviation; ψ represents a heading; psiDRepresenting a second desired heading angle.
S42: according to a tracking error equation, establishing the following kinematic model of the bionic wave fin propulsion underwater vehicle:
wherein,a derivative representing a horizontal distance between the biomimetic skeg propelled underwater vehicle and the desired tracking path;a derivative representing a heading angle deviation; u, v and r are respectively expressed as the advancing and retreating speed, the lateral moving speed and the yaw speed of the bionic wave fin propulsion underwater vehicle.
S43: and (3) calculating to obtain a kinematic tracking control law according to the kinematic model:
wherein δ is an arbitrarily small normal number; n is any natural number; v represents the lateral moving speed of the bionic wave fin propelling underwater vehicle; psieIs the course angle deviation; k is a radical of1,k2Design parameters for the controller and need to satisfy k2>k1>0。
S45: according to the kinematics tracking control law, the following dynamics control laws are obtained through calculation:
wherein, tauu、τrRespectively, the kinetic control quantities, τuIndicating a propulsive force in a forward or backward direction, τrRepresenting a yaw moment; k is a radical ofi(i-1 … 4) represents a controller design parameter and satisfies ki>0，k2>k1>0；Representing derivatives of a parameter of a tracking control law of kinematics control, where1＝k1(exy-δ)cosn(ψe) N is a positive integer,ψeis the course angle deviation; m is11、m22、m33Representing the quality of the RobButt-II and elements on the diagonal of the additional quality matrix; d11、d33Representing elements on a diagonal of the linear damping matrix; beta is a1、β3Representing the amount of kinematic error, beta1＝u-α1，β3＝r-α3。
S5: and establishing a mapping relation between the dynamic control quantity and the control parameters of the bionic wave fin propelling underwater vehicle wave fin based on fuzzy reasoning to obtain the control quantity of the long fins on two sides.
Wherein, the control parameters of the bionic wave fin propelling underwater vehicle wave fin include, but are not limited to, the wave frequency F of the left long fin surfaceLRight long fin surface wave frequency FRAmplitude A of the surface wave of the fin and phase difference between adjacent fins
FIG. 4 exemplarily shows a propulsion and yaw moment-traveling wave parameter mapping model working diagram based on fuzzy inference, which includes fuzzification, fuzzy inference, a fuzzy rule base and defuzzification.
Specifically, the step S5 may include:
s51: and establishing a mapping relation between the dynamic control quantity and the control parameters of the bionic wave fin propulsion underwater vehicle wave fin based on fuzzy reasoning for fuzzification. The control parameters of the bionic wave fin propulsion underwater vehicle wave fin comprise the left long fin surface wave frequency, the right long fin surface wave frequency, the fin surface wave amplitude and the phase difference of adjacent fin rays.
Further, step S51 may further include:
s511: determining the domains of the advancing and retreating direction propelling force, the yawing moment, the fluctuation frequency of the left fin and the right fin, the wave amplitude of the fin surface and the phase difference of the adjacent fin rays.
For example, the following settings may be made: advancing and retreating direction propulsion force tauuHas a discourse field of [ -7,7]Yaw moment τrHas a discourse field of [ -5,5 [)]Left and right fin fluctuation frequency FLAnd FRAll are [ -40,40 [ ]]The discourse domain of the amplitude A of the fin surface wave is taken as [10,40 ]]Phase difference between adjacent finsThe domain of discourse is [0,120]。
S512: and selecting a fuzzy language subset and a triangular membership function so as to perform fuzzification.
The selection of the subset of fuzzy languages is exemplified below: tau isu、τr、FL、FR、A、Respectively correspond to fuzzy variables Tu、Tr、UA、Wherein, UAThe fuzzy linguistic value element set of (1) is taken as { PS, PM, PB, PL }; t isu、Tr、The fuzzy language value elements are selected as { NB, NM, NS, Z, PS, PM, PB };is { Z, PS, PM, PB }. Wherein { NB, NM, NS, Z, PS, PM, PB } represents negative big, negative middle, negative small, zero, positive small, positive middle, positive big, respectively.
S52: and establishing a fuzzy rule base.
In practical application, a fuzzy rule base can be established according to experience obtained by a RobButt-II motion control experiment. Specifically, the fuzzy rule base can be established according to the following criteria:
(1) setting a course control priority higher than a control priority of a forward and backward direction;
the principle can ensure that when the rotating moment and the advancing and retreating thrust are both large, the left and right wave fins perform differential motion to generate large rotating moment and small advancing and retreating thrust.
(2) When the rotating moment is small and the advancing and retreating thrust is large, the left and right wave fins generate traveling waves with different frequencies and the same direction, so that the large thrust and the small rotating moment are generated.
Table 1 exemplarily shows a fuzzy rule base.
Table 1:
s53: and obtaining fuzzy control quantities of fluctuation frequencies of the left fin and the right fin, the amplitude of the surface wave of the fins and the phase difference of adjacent fin rays by adopting a minimum method according to the fuzzy rule base, the propulsion force in the advancing and retreating directions and the yawing moment after fuzzification.
S54: and performing deblurring operation by adopting a weighted average method according to the fuzzy control quantity to obtain the control quantity of the long fins on two sides.
The control quantity of the long fins on the two sides obtained in the step can be traveling wave parameters of the left and right fluctuation fins of the RobCutt-II.
The fuzzy inference and defuzzification processes are described below in connection with the preferred embodiment by taking the example of determining the wave frequency of the wave fin on the left side of the underwater vehicle.
Sa 1: the applicability of the ith fuzzy rule is calculated according to the following formula:
wherein,denotes at the current input τuTime-fuzzy variable TuThe degree of membership of the jth linguistic value of (a);denotes at the current input τwTime-fuzzy variable TwThe degree of membership of the kth linguistic value of (1); mu.siIndicating the applicability of the ith fuzzy rule.
Sa 2: obtaining the following fluctuation frequency of the left fluctuation fin through fuzzy reasoning and defuzzification:
wherein, FLA clear value representing the left-hand fin ripple frequency output by the fuzzy inference system (see FIG. 4); m represents the current input (tau) in the fuzzy rule baseu,τw) The number of fuzzy rules activated;indicating that the ith fuzzy rule corresponds to FLThe fuzzy output language value of (1) is the center of the membership function; mu.si(τu,τw) Indicating the applicability of the ith fuzzy rule.
S6: and performing real-time navigation control on the bionic wave fin propelled underwater vehicle according to the control quantity of the long fins on the two sides, and realizing path tracking control.
After the technical scheme is adopted, the invention has the following technical effects: calculating the 'sight point' p to be tracked by the current RobButt-II according to the current position of the RobButt-II and the expected pathlosThe sight line navigation principle is adopted to simulate actual sailor operation, difficulty in planning and acquiring a complex target air route by the underwater vehicle is avoided, and working efficiency of the underwater vehicle can be improved on the premise of ensuring precision. According to the current position, the course and the 'sight point' p of the RobContt-IIlosData design RobButt-II dynamics control law tau by utilizing backstepping methodu,τrThe method is divided into a kinematics and dynamics two-step design controller, the design difficulty of the controller is simplified, the stability of a path tracking error closed-loop system is ensured based on the Lyapunov stability theory, and the controller has certain robustness on model parameter uncertainty caused by the underwater environment actionAnd (4) the bar property. And establishing a relation between the dynamic control quantity and the control parameter of the RobCutt-II wave fin based on fuzzy reasoning, so that the path tracking control method can be practically applied to the motion control of the bionic wave fin propulsion underwater vehicle.
The following examples are presented to demonstrate the invention.
To verify validity, path tracking verification may be performed, for example, in an indoor pool of 5m × 4m × 1.1 m. The global visual tracking system installed on the top of the pool is connected to the console through a USB, and by processing images of the RobConut-II and the surrounding environment thereof, the console can calculate the current position and the course of the RobConut-II in real time and send the current position and the course to the RobConut-II internal controller through a wired network based on a UDP protocol to be used as pose feedback. The verification results of the RobButt-II tracking straight trace are shown in FIGS. 5-7. Fig. 5 exemplarily shows a bionic heave fin propelled underwater vehicle straight-line path tracking schematic diagram at different times. Fig. 6 is a schematic diagram for exemplarily showing a bionic wave fin propelling underwater vehicle straight-line path tracking track. Fig. 7 is a schematic diagram illustrating a bionic heave fin propelled underwater vehicle straight line path tracking error curve. It can be seen that the embodiment of the invention can enable the RobCutt-II to move to the expected path and then move along the expected path, and the tracking error of the controller with the heading compensation is smaller than that of the controller without the heading compensation.
The verification results of the round trajectory tracked by the RobCutt-II are given in fig. 8-10. Fig. 8 exemplarily shows a bionic heave fin propelled underwater vehicle in a circular path tracking schematic at different times. Fig. 9 is a schematic diagram for exemplarily showing a bionic wave fin propelling underwater vehicle circular path tracking track. FIG. 10 is a schematic diagram illustrating a bionic wave fin propulsion underwater vehicle circular path tracking error curve.
It can be seen from fig. 5-10 that both methods can control the robutt-II to arrive at and follow the desired path, but the controller based on the backstepping method can control the robutt-II to arrive at the desired path faster and with less tracking error.
By adopting the technical scheme, the embodiment of the invention can obviously improve the underwater motion control precision of the bionic wave fin propelling underwater vehicle, improve the precision of path tracking, shorten the redundant range of the bionic wave fin propelling underwater vehicle, has more stable control capability and provides guarantee for the efficient completion of underwater motion and operation.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (7)
1. A method for controlling path tracking of an underwater vehicle propelled by a bionic heave fin, the method comprising:
determining a desired tracking path;
acquiring the real-time position and the real-time course of the underwater vehicle propelled by the bionic wave fin;
calculating a sight line point and an expected course angle which need to be tracked currently by the underwater vehicle propelled by the bionic wave fin according to the current position of the underwater vehicle propelled by the bionic wave fin and the expected tracking path;
designing a dynamic control law of the underwater vehicle propelled by the bionic wave fin by using a backstepping method according to the current position, the course and the sight line point of the underwater vehicle propelled by the bionic wave fin;
establishing a mapping relation between the dynamic control quantity and the control parameters of the bionic wave fin propelling underwater vehicle wave fin based on fuzzy reasoning to obtain control quantities of long fins on two sides;
and performing real-time navigation control on the bionic wave fin propelled underwater vehicle according to the control quantity of the long fins on the two sides, so as to realize path tracking control.
2. The method of claim 1, wherein the determining a desired tracking path specifically comprises:
determining the desired tracking path according to:
Ω(s)＝[xd(s),yd(s)]T
wherein Ω(s) represents the desired tracking path; the s represents an arc length of the desired tracking path; said xd(s) said yd(s) represents coordinates of a point on the desired tracking path.
3. The method according to claim 1, wherein the calculating a current required tracking sight point and a desired heading angle of the underwater vehicle propelled by the bionic skeg according to the current position of the underwater vehicle propelled by the bionic skeg and the desired tracking path comprises:
determining the sight line point according to the current position of the bionic wave fin propulsion underwater vehicle;
determining the direction angle of a vector of the current position of the bionic fin propelled underwater vehicle pointing to the sight line point as a first expected course angle;
and compensating by using a sight line navigation system to obtain a second expected course angle, and taking the second expected course angle as the expected course angle of the bionic fluctuated fin propelled underwater vehicle.
4. The method of claim 3, wherein the determining the gaze point based on the current position of the biomimetic skeg-propelled underwater vehicle comprises:
if the distance between the bionic fin propulsion underwater vehicle and the expected tracking path is smaller than a distance threshold, determining an intersection point of the front end on the expected tracking path as the sight line point;
and if the distance between the underwater vehicle propelled by the bionic wave fin and the expected tracking path is greater than or equal to the distance threshold, determining a point on the expected tracking path, which is closest to the current position of the underwater vehicle propelled by the bionic wave fin, as the sight line point.
5. The method according to claim 3, wherein the step back method for designing the dynamic control law of the underwater vehicle propelled by the bionic skeg according to the current position, the heading and the sight line point of the underwater vehicle propelled by the bionic skeg comprises the following specific steps:
according to the sight point coordinates, the following tracking error equation is established:
wherein, said exyPropelling a horizontal distance between an underwater vehicle and the desired tracking path for the biomimetic skeg; the psieIs the course angle deviation; the psi represents a heading; the psiDRepresenting the second desired heading angle; said xdThe ydRepresenting the position of the gaze point; the x and the y respectively represent the real-time position of the bionic wave fin propelling underwater vehicle;
according to the tracking error equation, establishing the following kinematic model of the bionic wave fin propulsion underwater vehicle:
wherein, theRepresenting a horizontal distance between the biomimetic skeg propelling underwater vehicle and the desired tracking path; the above-mentionedA derivative representing a heading angle deviation; the u, the v and the r are respectively expressed as the advancing and retreating speed, the lateral moving speed and the yaw angular speed of the bionic wave fin propelled underwater vehicle;
and calculating to obtain a kinematic tracking control law according to the kinematic model:
wherein δ is an arbitrarily small normal number; n is any natural number;
according to the kinematic tracking control law, calculating to obtain the following kinematic control law:
wherein, the value of τ isuThe above-mentioned [ tau ]rRespectively represent the kinetic control quantities, saiduRepresenting a propulsive force in a forward or reverse direction, saidrRepresenting a yaw moment; k isi(i-1 … 4) represents a controller design parameter and satisfies ki>0，k2>k1>0; the above-mentionedThe above-mentionedRepresenting a kinematic control tracking control law parameter alpha1、α3Wherein said α is1＝k1(exy-δ)cosn(ψe) N is a positive integer, saidM is11M is the same as22M is the same as33Elements on a diagonal of a matrix representing mass and additional mass of the bionic heave fin propulsion underwater vehicle; d is11D said33Representing elements on a diagonal of the linear damping matrix; beta is the same as1Beta of the formula3Representing the amount of kinematic error, said beta1＝u-α1Said beta is3＝r-α3。
6. The method according to claim 1, wherein the mapping relationship between the dynamic control quantity and the control parameter of the bionic wave fin propulsion underwater vehicle wave fin is established based on fuzzy reasoning to obtain the control quantity of the long fins on two sides, and the method specifically comprises the following steps:
establishing a mapping relation between the dynamic control quantity and the control parameters of the bionic wave fin propulsion underwater vehicle wave fin based on fuzzy reasoning, and fuzzifying; the control parameters of the bionic wave fin propelling underwater vehicle wave fin comprise left long fin surface wave frequency, right long fin surface wave frequency, fin surface wave amplitude and adjacent fin line phase difference;
establishing a fuzzy rule base;
obtaining fuzzy control quantities of fluctuation frequency of left and right fins, wave amplitude of fin surfaces and phase difference of adjacent fin rays by adopting a minimum method according to the fuzzy rule base, the propulsion force in the advancing and retreating directions and the yawing moment after fuzzification;
and performing deblurring operation by adopting a weighted average method according to the fuzzy control quantity to obtain the control quantity of the long fins on the two sides.
7. The method according to claim 6, wherein the establishing of the mapping relationship between the dynamic control quantity and the bionic wave fin propulsion underwater vehicle wave fin control parameter based on fuzzy reasoning and the fuzzification specifically comprise:
determining the domains of the advancing and retreating direction propelling force, the yawing moment, the fluctuation frequency of the left fin and the right fin, the wave amplitude of the fin surface and the phase difference of the adjacent fin rays;
and selecting a fuzzy language subset and a triangular membership function so as to perform fuzzification.
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| CN108227715B (en) * | 2018-01-12 | 2020-12-04 | 上海海事大学 | Wave-resistant energy-saving unmanned ship path tracking method |
| CN109283842B (en) * | 2018-08-02 | 2022-01-07 | 哈尔滨工程大学 | Unmanned ship track tracking intelligent learning control method |
| CN110398963A (en) * | 2019-07-13 | 2019-11-01 | 珠海格力智能装备有限公司 | Deviation rectifying control method and device for trackless navigation, storage medium and controller |
| CN110488847A (en) * | 2019-08-09 | 2019-11-22 | 中国科学院自动化研究所 | The bionic underwater robot Hovering control mthods, systems and devices of visual servo |
| CN111176292B (en) * | 2020-01-13 | 2022-11-22 | 天津工业大学 | Wave glider path tracking control method based on side margin |
| CN111781938B (en) * | 2020-06-23 | 2021-06-18 | 中国科学院声学研究所 | Under-actuated underwater vehicle and stabilizing method and device thereof |
| CN111829528B (en) * | 2020-07-27 | 2022-02-08 | 中国科学院自动化研究所 | Real-time path planning method and system for bionic gliding machine dolphin |
| CN112034865B (en) * | 2020-08-12 | 2021-10-08 | 浙江大学 | Full-drive underwater vehicle track tracking control method based on optimization algorithm |
| CN112558620B (en) * | 2020-12-15 | 2022-09-23 | 西北工业大学 | Course correction path tracking method of under-actuated autonomous underwater vehicle |
| CN113342011A (en) * | 2021-06-08 | 2021-09-03 | 西北工业大学 | Gliding course control method of simulated bat aircraft based on rolling mechanism |
| CN113867156A (en) * | 2021-12-02 | 2021-12-31 | 湖南工商大学 | Method and device for tracking robotic fish path by fusing BP-RBF neural network |
| CN114397899A (en) * | 2021-12-09 | 2022-04-26 | 中国科学院自动化研究所 | Bionic robot fish three-dimensional path tracking control method and device |
| CN114545953B (en) * | 2022-04-26 | 2022-07-12 | 中国科学院自动化研究所 | Bionic fish path control method and device and bionic fish |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106292287A (en) * | 2016-09-20 | 2017-01-04 | 哈尔滨工程大学 | A kind of UUV path following method based on adaptive sliding-mode observer |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8286909B2 (en) * | 2008-02-08 | 2012-10-16 | Stratocomm Corporation | Boundary layer propulsion airship with related system and method |
-
2017
- 2017-01-19 CN CN201710039658.7A patent/CN106708068B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106292287A (en) * | 2016-09-20 | 2017-01-04 | 哈尔滨工程大学 | A kind of UUV path following method based on adaptive sliding-mode observer |
Non-Patent Citations (3)
| Title |
|---|
| Target-Tracking Control Design for a Robotic Fish with Caudal Fin;Songlin Chen,等;《Proceedings of the 32nd Chinese Control Conference》;20130728;第844-849页 * |
| 微小型仿生机器鱼设计与实时路径规划;周超，等;《自动化学报》;20080731;第34卷(第7期);第772-777页 * |
| 模块化仿生波动长鳍水下推进器的设计与实现;王睿，王硕;《华中科技大学学报（自然科学版）》;20151031;第43卷;第408-411页 * |
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