CN115016465A - Autonomous underwater vehicle control method considering saturation and dead zone characteristics of rudder - Google Patents
Autonomous underwater vehicle control method considering saturation and dead zone characteristics of rudder Download PDFInfo
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Abstract
The invention relates to an autonomous underwater vehicle control method considering the saturation and dead zone characteristics of a rudder, and belongs to the technical field of automatic control. The method comprises the following steps: acquiring self attitude, angular velocity and a reference attitude angle; inputting the reference attitude angle into a command filter to obtain a reference track and a track tracking error; designing an expected virtual control law, wherein the expected virtual control law comprises an adaptive sliding mode controller, an adaptive neural network controller and an adaptive dead zone inverse compensator, and the saturation characteristic of a rudder is considered by utilizing a hyperbolic tangent function; and solving the control input of the rudder by a dynamic inverse method. According to the invention, through processing the dead zone and the saturation characteristic of the rudder, the original control input is saturated or the dead zone is converted into a corresponding ideal input value, so that the precision of the controller is higher, and the performance of the controller can be better exerted.
Description
Technical Field
The invention belongs to the technical field of automatic control, and relates to nonlinear characteristic processing of a rudder in a motion control process of an under-actuated autonomous underwater vehicle.
Background
The Autonomous Underwater Vehicle (AUV) has the advantages of small volume, strong maneuvering capability, strong intelligence, high concealment, high operation safety and the like, and can complete tasks such as ocean monitoring, ocean archaeology, Underwater operation and the like without manual intervention and large-scale water surface support.
Compared with unmanned ships and surface ships, the dynamic system of the AUV is more complex and has the characteristics of nonlinearity, time-varying property and the like. Due to the complex marine environment, the AUV may be disturbed by ocean currents, surges, etc. during underwater navigation. In recent years, experts at home and abroad carry out more detailed research on the aspect of motion control, and aim to improve the maneuverability, stability, robustness and the like of the AUV.
Most of existing under-actuated underwater vehicle control methods do not consider the nonlinear characteristic of a rudder or solve the saturation characteristic only through direct amplitude limiting, and the control mode can cause damage to the steering engine and a mechanical structure in engineering practice. Some researchers have considered rudder saturation characteristics or dead zone characteristics for underwater vehicle control, but not both.
Disclosure of Invention
Technical problem to be solved
In order to avoid the defects of the prior art, the saturation and dead zone characteristics of the rudder of the underwater vehicle are considered at the same time, so that the control precision is higher, and the economy and the safety are better.
Technical scheme
An autonomous underwater vehicle control method considering the saturation and dead zone characteristics of rudders is characterized by comprising the following steps:
s1: acquiring self attitude, angular velocity and a reference attitude angle;
s2: inputting the reference attitude angle into a command filter to obtain a reference track and a track tracking error;
s3: designing an expected virtual control law, wherein the expected virtual control law comprises an adaptive sliding mode controller, an adaptive neural network controller and an adaptive dead zone inverse compensator, and the saturation characteristic of a rudder is considered by utilizing a hyperbolic tangent function;
s4: and solving the control input of the rudder by a dynamic inverse method.
The further technical scheme of the invention is as follows: s1 specifically includes: obtaining attitude information eta through attitude sensor carried by AUV 2 And angular velocity v of aircraft 2 (ii) a Acquiring a reference course angle psi according to a task instruction or a sight guidance method issued by an upper computer d From a reference pitch angle theta d 。
The further technical scheme of the invention is as follows: s2 specifically includes: defining a command filter
Wherein,
A d ＝diag{ζ r1 ω r1 ,ζ r2 ω r2 ,ζ r3 ω r3 is the positive definite parameter matrix, ω ri ,ζ ri ,
Is the natural frequency and damping ratio of the filter; the reference trajectory is initialized by the initial state of the AUV, i.e. η 2r (0)＝η 2 (0) And
v (0) is the velocity of AUV at time zero, η 2r Is a smooth reference trajectory;
the tracking error is defined as
Wherein e is ψ e θ 
Respectively tracking errors of course angles, pitch angles and roll angles;
the error after the first order command filter is defined as
Wherein, Λ and K a Is a positive constant gain vector, K a Depends on the relevant control force coefficient and the rudder limit; tanh is a hyperbolic tangent function,
is a virtual control that expects angular velocity as an attitude error.
The further technical scheme of the invention is as follows: s3 specifically includes: and designing the expected acceleration based on an approximate dynamic model, wherein the expected acceleration is represented by the following formula, so that the system approaches to a sliding mode surface r to be 0
Wherein,
the error is estimated for the dead zone parameters,
adaptive law relating to dead zone input
As the transpose of the Jacobian matrix, d is the non-parameterizable dead-zone estimation residual,
is an estimate of the upper bound of the residual,
and
positive parameters for the design;
u as is an adaptive sliding mode controller, and is defined as follows
Wherein, K s ＝diag{K s1 ,K s2 ,K s3 Is a diagonal positive definite matrix,
for adaptive selection of coefficients, K b Is a positive fixed constant gain matrix; the sign function sgn (r) is defined as
Wherein r is 1 ,r 2 ,r 3 Sgn (·) is a scalar sign function, an element of the error r;
neural networks designed to compensate for the uncertainty of the kinetic model
Wherein,
is an estimation matrix of W, V;
accordingly, the estimation error is defined as
u ar Is a robust signal, designed as follows
Wherein,
for the purpose of the two adaptive control parameters,
the further technical scheme of the invention is as follows: s4 specifically includes: thrust control of the rudder delta is calculated by a pseudo-inverse method using an approximate form of a dynamic model
Wherein,
is that
And the inverse must exist because of
For an under-actuated underwater vehicle, the method is a full-rank matrix;
is that
The inverse function of (d); delta is [ delta ] d δ e δ r ] T Differential rudder, horizontal rudder and vertical rudder;
and
are estimated system parameters and functions.
A computer system, comprising: one or more processors, a computer readable storage medium, for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the above-described method.
A computer-readable storage medium having stored thereon computer-executable instructions for performing the above-described method when executed.
A computer program comprising computer executable instructions which when executed perform the method described above.
Advantageous effects
Compared with the existing control method, the autonomous underwater vehicle control method considering the saturation and dead zone characteristics of the rudder has the following beneficial effects:
1. strong robustness and high control precision
According to the invention, through processing the dead zone and the saturation characteristic of the rudder, the original control input is saturated or the dead zone is converted into a corresponding ideal input value, so that the precision of the controller is higher, and the performance of the controller can be better exerted.
2. Higher safety and better economy
According to the invention, the efficiency and the safety of the rudder are enhanced by processing the saturation characteristic of the rudder, and the damage of the steering engine or the damage of mechanical components such as a rudder plate, a connecting shaft and the like caused by excessive input of the rudder is avoided.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 is a flow chart of the present invention;
FIG. 2AUV trajectory tracking trajectory;
FIG. 3X-axis tracking error and control inputs;
FIG. 4Y tracking error and control inputs;
FIG. 5Z tracking error and control inputs.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below 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. In addition, the technical features involved in the respective embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment of the invention provides an underwater vehicle control method considering the saturation dead zone characteristic of a rudder based on an adaptive neural network, which comprises the steps of constructing a virtual control signal kappa by using a sliding mode controller with neural network compensation under an adaptive control framework based on dynamic inverse, and tracking a smooth reference track eta by using a hyperbolic tangent function and the nonlinear characteristic of an adaptive dead zone inverse compensator to process the nonlinear characteristic of an execution mechanism 2r (t) of (d). The trajectory is defined by the pose of the target point
Obtained after passing through the command filter. And the dynamic inverse control module converts the virtual signal into an actual propeller control signal through an approximate model of the underwater vehicle. As shown in fig. 1, the steps of the present invention are specifically as follows:
step 1: obtaining attitude information eta through attitude sensor carried by AUV 2 And angular velocity v of aircraft 2 . Acquiring a reference course angle psi according to a task instruction or a sight guidance method issued by an upper computer d From a reference pitch angle theta d The reference roll angle is typically 0 °.
Step 2: defining a command filter
Wherein,
A d ＝diag{ζ r1 ω r1 ,ζ r2 ω r2 ,ζ r3 ω r3 is the positive definite parameter matrix, ω ri ,ζ ri ,
Is the natural frequency and damping ratio of the filter. The reference trajectory is initialized by the initial state of the AUV, i.e. η 2r (0)＝η 2 (0) And
v (0) is the velocity of AUV at time zero, η 2r Is a smooth reference trajectory.
The tracking error is defined as
Wherein e is ψ e θ 
Respectively a course angle tracking error, a pitch angle tracking error and a roll angle tracking error.
The error after the first order command filter is defined as
Wherein, Λ and K a Is a positive constant gain vector, K a The value of (c) depends on the relevant control force coefficient and the rudder limit. tanh is a hyperbolic tangent function,
virtual control of desired angular velocity as attitude error。
And step 3: and designing the expected acceleration based on an approximate dynamic model, wherein the expected acceleration is represented by the following formula, so that the system approaches to a sliding mode surface r to be 0
Wherein,
the error is estimated for the dead zone parameters,
adaptive law relating to dead zone input
As the transpose of the Jacobian matrix, d is the non-parameterizable dead-zone estimation residual,
is an estimate of the upper bound of the residual,
and
are positive parameters of the design.
u as Is an adaptive sliding mode controller, and is defined as follows
Wherein, K s ＝diag{K s1 ,K s2 ,K s3 Is diagonal positiveThe matrix is determined according to the number of the matrix,
for adaptive selection of coefficients, K b A positive constant gain matrix. The sign function sgn (r) is defined as
Wherein r is 1 ,r 2 ,r 3 Sgn (·) is a scalar sign function that is an element of the error r.
Neural networks designed to compensate for the uncertainty of the kinetic model
Wherein,
is the estimation matrix of W, V.
Accordingly, the estimation error is defined as
u ar Is a robust signal, designed as follows
Wherein,
for the purpose of the two adaptive control parameters,
and 4, step 4: thrust control of the rudder delta is calculated by a pseudo-inverse method using an approximate form of a dynamic model
Wherein,
is that
And the inverse must exist because of
For an under-actuated underwater vehicle, the method is a full rank matrix.
Is that
Is the inverse function of (c). Delta is [ delta ] d δ e δ r ] T Differential rudder, horizontal rudder and vertical rudder.
And
are estimated system parameters and functions.
In order to verify the effectiveness of the above control algorithm, the following embodiments are also provided in the present invention.
AUV initial state is
x(0)＝-3 y(0)＝1 z(0)＝-3 φ(0)＝0 θ(0)＝0 ψ(0)＝0
u(0)＝0.5 v(0)＝0.5 w(0)＝0 p(0)＝0 q(0)＝0 r(0)＝0
The initial position of the target is (0.25,0,0), and the target makes a uniform linear motion along the x axis, and the speed is set to be 0.1 m/s. Setting a dynamic target tracking task to enable the final expected state of the AUV to be
Δx＝-2,Δy＝0,Δz＝0,
Δθ＝0,Δψ＝0
The tracking results are shown in fig. 2-5.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present disclosure.
Claims (8)
1. An autonomous underwater vehicle control method considering the saturation and dead zone characteristics of rudders is characterized by comprising the following steps:
s1: acquiring self attitude, angular velocity and a reference attitude angle;
s2: inputting the reference attitude angle into a command filter to obtain a reference track and a track tracking error;
s3: designing an expected virtual control law, wherein the expected virtual control law comprises an adaptive sliding mode controller, an adaptive neural network controller and an adaptive dead zone inverse compensator, and the saturation characteristic of a rudder is considered by utilizing a hyperbolic tangent function;
s4: and solving the control input of the rudder based on a dynamic inverse method.
2. The autonomous underwater vehicle control method taking into account the saturation and dead zone characteristics of rudders, according to claim 1, characterized in that S1 is specifically: obtaining attitude information eta through attitude sensor carried by AUV 2 And angular velocity v of aircraft 2 (ii) a Acquiring a reference course angle psi according to a task instruction or a sight guidance method issued by an upper computer d From a reference pitch angle theta d 。
3. The autonomous underwater vehicle control method taking into account the saturation and dead zone characteristics of rudders, according to claim 2, characterized in that S2 is embodied as: defining a command filter
Wherein,
A d ＝diag{ζ r1 ω r1 ,ζ r2 ω r2 ,ζ r3 ω r3 is the positive definite parameter matrix, ω ri ,
Is the natural frequency and damping ratio of the filter; the reference trajectory is initialized by the initial state of the AUV, i.e. η 2r (0)＝η 2 (0) And
v (0) is the velocity of AUV at time zero, η 2r Is a smooth reference trajectory;
the tracking error is defined as
Wherein e is ψ e θ 
Respectively tracking errors of course angles, pitch angles and roll angles;
the error after the first order command filter is defined as
Wherein, Λ and K a Is a positive constant gain vector, K a The value of (c) depends on the relevant control force coefficient and the limit of the rudder; tanh is a hyperbolic tangent function,
is a virtual control that expects angular velocity as an attitude error.
4. The autonomous underwater vehicle control method taking into account the saturation and dead zone characteristics of rudders, according to claim 3, characterized in that S3 is embodied as: and designing the expected acceleration based on an approximate dynamic model, wherein the expected acceleration is represented by the following formula, so that the system approaches to a sliding mode surface r to be 0
Wherein,
the error is estimated for the dead zone parameters,
adaptive law relating to dead zone input
As the transpose of the Jacobian matrix, d is the non-parameterizable dead-zone estimation residual,
is an estimate of the upper bound of the residual,
and
for positive reference of designCounting;
u as is an adaptive sliding mode controller, and is defined as follows
Wherein, K s ＝diag{K s1 ,K s2 ,K s3 Is a diagonal positive definite matrix,
for adaptive selection of coefficients, K b Is a positive fixed constant gain matrix; the sign function sgn (r) is defined as
Wherein r is 1 ,r 2 ,r 3 Sgn (·) is a scalar sign function, an element of the error r;
neural networks designed to compensate for the uncertainty of the dynamical model
Wherein,
is an estimation matrix of W, V;
accordingly, the estimation error is defined as
u ar Is a robust signal, designed as follows
Wherein,
for the purpose of the two adaptive control parameters,
5. the autonomous underwater vehicle control method taking into account the saturation and dead zone characteristics of the rudder according to claim 4, characterized in that S4 is in particular: thrust control of rudder delta is calculated by a pseudo-inverse method by using an approximate form of a dynamic model
Wherein,
is that
And the inverse must exist because of
For an under-actuated underwater vehicle, the method is a full-rank matrix;
is that
The inverse function of (d); delta is [ delta ] d δ e δ r ] T Differential rudder, horizontal rudder and vertical rudder;
and
are estimated system parameters and functions.
6. A computer system, comprising: one or more processors, a computer readable storage medium, for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of claim 1.
7. A computer-readable storage medium having stored thereon computer-executable instructions for, when executed, implementing the method of claim 1.
8. A computer program comprising computer executable instructions which when executed perform the method of claim 1.
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