CN108227723A - A kind of underwater robot and its application process of stability analysis and structure optimization - Google Patents

Abstract

The invention discloses an underwater robot and its application method for stability analysis and structure optimization, including a carrier device, a camera and lighting device, a control and navigation device, and a driving device part. The main body adopts a torpedo structure, and the control and navigation device is placed Inside it; drive devices are installed at both ends of the main structure and the tail, and the camera and lighting devices are fixed at the front end of the underwater robot; through optical fibers, wireless data transmission antennas and the control unit of the main control end through the main control digital transmission equipment to cooperate with each other , to realize two operation modes; the underwater robot in the sailing mode is fast and flexible to move directly, and the hovering operation mode greatly increases the hovering stability of the underwater robot to improve the precision and accuracy of the operation; in the hovering stage of the underwater robot , the horizontal propellers on both sides are reversed to vertical propellers to achieve precise hovering, the tail fins are reversed to horizontal propellers to offset the influence of turbulence, and the control parameters obtained by quantitative analysis of Lyapunov exponents are introduced.

Description

An underwater robot and its application method for stability analysis and structure optimization

technical field

The invention specifically relates to an underwater robot and an application method for stability analysis and structure optimization thereof, belonging to the technical field of robots.

Background technique

In recent years, operational underwater robots have received extensive attention from scholars and research institutions at home and abroad. When the robot hovers or moves underwater, it is easily affected by external disturbances such as ocean currents, and it is difficult to maintain a stable attitude and achieve precise operations. The stability of the system itself can be improved through mechanical structure design and control torque input. However, it is difficult for an underwater robot with poor stability to maintain its heading and depth. It must frequently adjust the control input torque to maintain the desired heading and depth, which will increase navigation resistance and system energy consumption, and even lose control. The system with too strong self-stability also reduces the maneuverability of the system. Therefore, in the design process of the robot, how to reasonably design the relationship between the mechanical structure of the system and the control input is of great significance for studying the stability and mobility of the system.

The motion stability of an underwater robot refers to the ability of the disturbed motion parameters to return to the initial motion state after being disturbed by ocean currents. At present, there are mainly two methods for stability research: one is that Routh-Hurwitz (1875, 1895) proposed to judge whether the system is stable by judging whether the characteristic root of the system is in the left half plane. Qian Weijian and others used the Guerwitz discriminant method to judge the real part sign of the root of the characteristic equation of the differential equation of the planar disturbance motion of the underwater robot, and analyzed the stability of the direct flight motion. However, this method does not analyze the stability of the specific design parameters and control parameters; the other is the Lyapunov direct method, which does not need to solve the dynamic equations, and qualitatively analyzes the system by constructing Lyapunov functions. Stability is widely used in motion stability analysis of nonlinear systems such as underwater robots. Based on the sliding mode control method, Joyjit et al. carried out speed tracking and head angle control on the snake robot, and proved the stability of the system in a finite time through Lyapunov stability analysis. When Lyapunov stability theory analyzes the stability of complex nonlinear systems with multiple degrees of freedom and strong coupling, it is difficult to construct suitable functions, which is still a difficult problem at present. In particular, when performing mechanical design and control optimization, qualitative analysis cannot give quantitative analysis indicators, and it is difficult to give quantitative analysis in terms of stability and maneuverability. Therefore, this paper uses the Lyapunov index method to quantitatively analyze the motion stability of the underwater robot during the hovering phase. Compared with Lyapunov's direct method, the main advantage of this method is its constructability, which makes it possible to analyze the hovering motion stability of underwater robots. At the same time, this paper optimizes the mechanical structure of the system to improve the hovering motion stability and increase the Clarity, accuracy, and flexibility of movement when taking pictures.

Contents of the invention

Aiming at the deficiencies in the existing technology, the technical problem to be solved by the present invention is: an underwater robot, which adopts the Lyapunov index method to establish the quantitative relationship between the system parameters and the stability of the hovering motion of the system, and then optimizes the mechanical structure of the system To improve the stability of hovering motion, increase the clarity, accuracy and flexibility of underwater photography.

In order to realize the foregoing invention object, the scheme that the present invention adopts is:

An underwater working robot includes a carrier device, a camera and lighting device, a control and navigation device, and a driving device. The main body adopts a torpedo structure, and the control and navigation devices are placed inside it, so that the underwater robot can execute the planned indicators. The two ends of the main structure and the empennage are equipped with driving devices, and the camera and lighting devices are fixed on the front end of the underwater robot.

Further, the carrier device includes a pressure-resistant cabin and a pressure-resistant front cover. The pressure chamber is made of acrylic material and ABS engineering plastics, with a novel and streamlined design. The pressure-resistant front cover is made of fiberglass, which is convenient for the camera device to obtain image information. The pressure-resistant front cover and the front-end pressure-resistant cabin are arranged in sequence.

Further control and navigation devices are placed inside the pressure-resistant cabin, using STM32F407 as the main control, with MS5837 depth sensor, MPU6050 and AK8975 attitude sensor, etc. The algorithm part is processed using a PID controller.

Further, the driving device includes horizontal propulsion propellers on both sides of the carrier and vertical propellers at the empennage. The propeller propeller can be rotated 180° according to actual needs.

Further, the camera and lighting device includes a video camera, a camera, a lamp, an infrared sensor, a laser sensor and a magnetic sensor, and is located in the pressure-resistant front cover of the front end of the underwater robot.

The underwater vehicle cooperates and coordinates with the control unit of the main control end through the optical fiber, the wireless data transmission antenna and the main control digital transmission equipment, and can realize two operation modes, one is the sailing mode, and the other is the hovering operation mode . The underwater robot in sailing mode can move quickly and flexibly, and the hovering operation mode greatly increases the hovering stability of the underwater robot to improve the precision and accuracy of the operation.

In order to achieve the above-mentioned quantitative relationship between the obtained system parameters and the stability of the system hovering motion, and to obtain the actual required PD control parameters, the technical solution adopted by the present invention is: a method based on Lyapunov index stability analysis , the steps are as follows:

(i). Construct the dynamic model of underwater robot, the standard form is as follows

(ii). Transform the model equation into the form of state equation

(iii). Calculate the Jacobian

(iv). Calculate the Lyapunov index

Finally, the quantitative relationship between system parameters and stability is obtained.

This scheme refers to the design scheme of the rotatable-wing UAV. The thrusters on both sides of the underwater robot in the navigation mode are horizontal, and the tail is a vertical thruster, which is conducive to obtaining forward thrust. In the hovering stage of the underwater robot, the horizontal propellers on both sides are twisted into vertical propellers to achieve precise hovering, and the tail is twisted into horizontal propellers to offset the influence of turbulence, and the control parameters obtained by Lyapunov exponent quantitative analysis are introduced.

Beneficial effect

Through the above technical solution, the beneficial effects of the technical solution of the present invention are:

1) Reduce frequent adjustment of control input and multi-torque to maintain desired heading and depth.

2) Keep the hovering posture stable.

3) Realize precise operation.

4) Improve the stability, speed and accuracy of underwater robots when performing tasks underwater.

5) Obtain the quantitative relationship between the system parameters and the stability of the hovering motion of the system.

Description of drawings

Figure 1 is a block diagram of the overall system structure.

Figure 2 is a flowchart of the stability algorithm

Figure 3 is the displacement curve of the hover phase line.

Figure 4 is the Lyapunov exponent spectrum of attitude during the hovering phase.

Figure 5 is the revised hovering stage line displacement curve.

Figure 6 is the modified Lyapunov exponent spectrum of the hovering phase attitude.

Figure 7 is the effectiveness of phase space state verification algorithm.

Fig. 8 is a schematic diagram of the structure of the sailing mode.

Figure 9 is a schematic diagram of the structure of the hovering mode.

Figure 10 is a right view of the hover mode.

Figure 11 is a work flow chart.

Detailed ways

Below in conjunction with accompanying drawing, the implementation of technical scheme is described in further detail:

Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

The body of the underwater hovering robot used in the present invention adopts a symmetrical and balanced structural design, including a carrier device, a camera and lighting device, a control and navigation device, and a driving device as shown in Figure 1. The main body adopts a torpedo structure, and the control and navigation devices are placed inside it, so that the underwater robot can execute the planned indicators. The two ends of the main structure and the empennage are equipped with driving devices, and the camera and lighting devices are fixed on the front end of the underwater robot.

The present invention provides a quantitative analysis method between a system parameter of the underwater hovering operation robot and the stability of the system hovering motion, the steps are as flow chart 2:

In this scheme, the HyView underwater robot is regarded as a rigid body, and its motion is regarded as a rigid body motion. The position and attitude of the robot in the earth coordinate system are represented by vector η=(φ,θ,ψ,x,y,z) ^T , where φ , θ, ψ are attitude angles in three directions of 3-2-1 Euler angles, x, y, z are linear displacements. The linear velocity and angular velocity of the robot in the body coordinate system are represented by h=(p, q, r, u, v, w) ^T , where p, q, r are angular velocities, and u, v, w are linear velocities. This program adopts the kinematics and dynamics equations of the system based on the Poincaré-Lagrangian equation as follows:

where J(θ) is the kinematic matrix, M is the inertia matrix, C(h) is the Coriolis force, and τ is the external force and external moment vector.

Since the HyView underwater robot is a complex nonlinear system with many parameters, the dynamic model is relatively complex. In order to facilitate the analysis, this paper simplifies the system appropriately and considers the main parameters that affect the movement of the underwater robot. Therefore, this paper will mainly consider the effects of hydrodynamic resistance, thrust, gravity, and buoyancy on it.

The main representative items of the dynamic model of the underwater robot obtained by solving equations (1) and (2) are as follows:

h=(p,q,r,u,v,w) ^T (3)

Among them: I _x , I _y , and Iz are the moments of inertia of the x, y, and z axes of the system respectively, m is the mass of the system, and g is the acceleration of gravity, see parameter table 1. φ is the roll angle (rad) of the system around the x-axis direction, θ is the pitch angle (rad) of the system around the y-axis direction, and ψ is the yaw angle (rad) of the system around the z-axis direction, p, q, r, u , v, w are the angular velocity and linear velocity of x, y, z axis respectively, S _φ = sinφ, C _φ = cosφ, S _θ = sinθ, C _θ ^-1 = cosθ, C _θ = secθ, T _θ = tanθ, S _ψ ＝sinψ, C _ψ ＝cosψ, L, K, N, f ₁ , f ₂ , and f ₃ are the total moment and force on the x, y, and z axes respectively, and the input force and moment of each joint adopt The PD control algorithm is as follows:

Where θ _d1 is the desired position or trajectory, k _pi and k _vi are proportional differential coefficients.

Transform equations (1) and (2) into the state equation of the system

In the formula, X＝[ηh] ^T ＝(φ,θ,ψ,x,y,z,p,q,r,u,v,w) ^T

The Lyapunov index can be obtained in two ways through the dynamic equation or the time series of the state quantity. This paper adopts the calculation method based on the dynamic equation, and its calculation formula is:

Among them, the state equation is obtained by transforming the dynamic equation of the nonlinear system. The size of the Lyapunov exponent is given by the Jacobian of the function f(X) at _Xi . Determined by |df(X)/dX|, the calculation steps are as follows:

(i).Construct a kinetic model, the standard form is as follows

(ii). Transform the model equation into the form of state equation

(iii). Calculate the Jacobian

(iv). Calculate the Lyapunov index

On the basis of the established dynamic model, the Lyapunov exponent spectrum of the whole system can be calculated by substituting Equation (5) into Equation (6).

The Lyapunov exponent is used to describe the average exponential rate of the two orbits of the initial value and the original value after the system is disturbed converge or diverge over time. When the Lyapunov exponent is less than 0, the phase orbit of the system is attracted to a stable fixed point, and the whole system is stable. The negative Lyapunov exponent is the basic characteristic of dissipative systems or non-conservative systems (such as damped harmonic oscillators), and the larger the negative value is, the faster the phase orbit converges, and the faster the system reaches the stable state. When the negative The system is ultrastable when the value tends to infinity. If the system is stable, at least one of its Lyapunov exponents is less than 0, and the sum of all exponents is less than 0 at the same time. When the Lyapunov exponent is greater than 0, the system is unstable or chaotic. When the Lyapunov exponent is 0, the phase trajectory is a periodic motion.

At the same time, the proportional differential coefficients for the PD control algorithm are k _p1 =2, k _v1 =300; k _p2 =2, k _v2 =300 and k _p3 =2, k _v3 =250; the desired track θ _d1 =x=1.7sin( 2x), θ _d1 =y=1.7sin(2y) and _θd1 =z=1.7sin(2z). The linear displacement in the three directions and the set expected trajectory are shown in Figure 3. The linear displacement in the X-axis direction can respond quickly and is consistent with the expected value. The linear displacement in the Y-axis direction is stable after 2s. The linear displacement in the Z-axis direction In the initial stage, the linear displacement of X and Y fluctuated greatly, and finally achieved a stable state. However, in the simulation, it was found that there was a 0.05m error with the expected state. The system tended to be stable after 60 iterations of the Lyapunov index, as shown in Figure 4. It shows that the interference received in the direction of the Z axis is larger than that of the X and Y axes, as shown in Figure 8.

In the initial stage, the stability is poor, and the operational hovering underwater robot needs to be arranged reasonably. In this paper, the thrust in the Z-axis direction of the operational hovering underwater robot is added in the simulation to stabilize T _Z = 150N, and k _p6 = 3, k _v6 is adjusted. = 300, to counteract the impact of the submerged-floating motion on the hovering, and then obtain the simulation as shown in Figure 5. At this time, the Lyapunov exponents are all negative (as shown in Figure 6), and the motion of the system is stable. The stability of the hovering motion state is affected by coupling interference such as buoyancy, gravity, and hydrodynamic force. Therefore, when designing and controlling a hovering underwater robot, the propeller and control parameters in the Z-axis direction should be set reasonably. When the proportional differential coefficient is given, change the initial conditions to φ=0.1, θ=0.1, ψ=0.1, x=0.1, y=0.1, z=0.1, and the attractors in the phase space are still stable in the same fixed On the point, as shown in Figure 7, the effectiveness of the algorithm is verified

In conjunction with accompanying drawings 8, 9, and 10, it can be seen that the underwater robot, including the robot body, is made of acrylic material and ABS engineering plastics, and the main body is made of a torpedo structure, which is conducive to reducing the weight of objects and increasing buoyancy under the condition of resisting water pressure. and reduce movement resistance.

The driving devices mounted on both sides of the robot body and the tail include horizontal propellers placed on both sides and vertical propellers at the tail as shown in Figure 8 . Under the action of the control and navigation device, this device can realize underwater attitude navigation in two modes. The STM32F407 acts as the main control board to receive the mode conversion command, start the tilting device between the body and the propeller, and realize the propeller through the control of the steering gear. The tilting angle of the system and the propeller propeller can be rotated 180° according to actual needs, and enter the hovering mode as shown in Figure 9. During the hovering stage of the underwater robot, the horizontal propellers on both sides are reversed into vertical propellers to achieve precise hovering. The empennage is twisted into a horizontal propeller to counteract the influence of turbulence and maintain X-Y plane stability, as shown in Figure 10. The PD control parameters obtained according to the Lyapunov index quantitative stability analysis are transferred, and the PD control algorithm is used to process the attitude information to achieve an accurate and stable state. The workflow is shown in Figure 11. Adding vertical propellers will make it difficult to adjust the control input and multi-torque to maintain the desired course and depth, which will increase the navigation resistance and the energy consumption of the system. Compared with other underwater robots equipped with six propellers, this paper can reduce resistance. Increased battery life not only reduces the difficulty of maintaining stable hovering control but also ensures the rapid movement of direct flight.

The camera and lighting device mounted on the robot body, the high-definition camera used in this paper can be used to observe the underwater environment during the hovering stage, and take a large number of pictures and videos for follow-up research work. Enhancing the stability of the underwater robot can greatly improve the quality of pictures and images. The quality of video acquisition reduces the difficulty of later data processing. Lights, infrared sensors, laser sensors, etc. make it adaptable to the seabed environment in different situations. Among them, infrared sensors and laser sensors can be used to measure the distance of the robot body to achieve obstacle avoidance ahead. .

The technical means disclosed in the technical solutions of the present invention are not limited to the technical means disclosed in the above technical means, but also include technical solutions composed of any combination of the above technical features.

Inspired by the above-mentioned ideal example according to the present invention, and through the above-mentioned description content, relevant workers can completely make various changes and modifications within the scope of not departing from the technical idea of the present invention. The technical scope of the present invention is not limited to the content in the specification, but must be determined according to the scope of the claims.

Claims (6)

1. a kind of underwater operation robot, which is characterized in that filled including carrier arrangement, camera shooting and lighting device, control and navigation It puts, driving device part, main body uses torpedo type structure, and control is placed inside it with navigation device so that underwater robot It is able to carry out plan target；Driving device is carried at agent structure both ends and empennage, the camera shooting and lighting device are fixed on water Lower robot front end.

2. robot as claimed in claim 1, which is characterized in that carrier arrangement includes pressure-resistant cabin, pressure-resistant front shroud；Pressure-resistant cabin Using acrylic material and ABS engineering plastics；Pressure-resistant front shroud is made of fiberglass, and image information is obtained convenient for photographic device；It is resistance to Pressure front shroud, front end pressure-resistant cabin are sequentially arranged.

3. robot as claimed in claim 1, which is characterized in that control is placed in navigation device inside pressure-resistant cabin, is used STM32F407 coordinates MS5837 depth transducers, MPU6050 and AK8975 attitude transducers as master control.

4. robot as claimed in claim 1, which is characterized in that driving device includes being placed in carrier both sides level propulsion spiral shell Revolve the vertical spin paddle at paddle and empennage；Screw propeller carries out 180 ° of rotation according to actual needs.

5. robot as claimed in claim 1, which is characterized in that camera shooting and lighting device include video camera, camera, Lamp, infrared sensor, laser sensor and magnetometric sensor, in the pressure-resistant front shroud of body front end.

6. robot stabilization analysis as claimed in claim 1 and the application process of structure optimization, which is characterized in that described Robot is cooperated by the control unit of optical fiber, wireless data sending antenna and main control end by master control data transmission equipment to be coordinated, real Existing two kinds of work patterns, one kind are sail modes, and another kind is hovering work pattern；Underwater robot in sail mode is fast The hoverning stability of underwater robot is significantly greatly increased to improve the accurate and accurate of operation in fast flexibly direct route movement, hovering work pattern Really；

To realize the quantitative relationship between above-mentioned acquisition systematic parameter and system hovering kinetic stability, actual needs is obtained The purpose of PD control parameter, using following protocol step：

(i) builds underwater human occupant dynamic model, and canonical form is as follows

(ii) model equation is converted into state equation form by

(iii) calculates Jacobi

(iv) calculates Liapunov exponent

Finally obtain the quantitative relationship between systematic parameter and stability.