An improved adaptive integral line-of-sight guidance law for unmanned surface vehicles with uncertainties

Su, Yixin; Wan, Lili; Zhang, Danhong; Huang, Fanrong

doi:10.1016/j.apor.2020.102488

Cited by 22 publications

(12 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The method for estimating the side angle using an observer can also be found in the literature [22][23][24]. In addition, the adaptive algorithm [25] and the MPC algorithm [26] can also be used for tracking the robot's path on the water surface. There are differences in the dynamics models of the designed robot on the ground and water surface.…”

Section: Introductionmentioning

confidence: 99%

“…Through the discussion of the above literatures, the main contributions of this paper are as follows: 1. Inspired by the literatures [20] and [25], the lateral velocity due to side-slipping, crosswinds, and currents are converted into sideslip rate in the body frame of the robot. Based on the backstepping control theory, a new adaptive position and heading angle controller is proposed to re-plan the linear velocity and angular velocity.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive ground and water surface control for cross-domain robots based on adaptive finite-time convergence sliding mode observer

Wang

Liu

Huang

2023

Preprint

View full text Add to dashboard Cite

The non-holonomic constraints cross-domain robot (CDR) is unable to follow the desired trajectory when moving on the ground or water surface due to the lateral side-slipping. Thus, an adaptive positionattitude controller is proposed in this paper to re-plan the robot’s angular velocity and linear velocity. To achieve adaptive control of the robot on the water surface and ground, an adaptive finite-time convergence sliding mode observer (AFSMO) is proposed. This observer is used to obtain time-varying and unknown lumped disturbance which includes uncertain dynamics parameters and environmental disturbances. An adaptive law is designed to improve observer accuracy and reduce output chattering. FSMO is also used to obtain the performance parameter to prevent driver saturation when the robot moves on the water surface. The performance parameter limits the maximum angular velocity and linear velocity. Simulation results demonstrate the effectiveness of the proposed control methods.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive ground and water surface control for cross-domain robots based on adaptive finite-time convergence sliding mode observer

Wang

Liu

Huang

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…In the virtual structure method, a virtual structure is defined that represents the desired formation of the agents (Liu & Zhang, 2018;Zhen et al, 2022). The path-following algorithm of multiple agents is designed based on the line-of-sight (LOS), and according to the formation reference point information, the agents can track the corresponding desired position at any initial position (Su et al, 2021;Tahk et al, 2005). However, these methods exhibit poor robustness, lack sufficient flexibility, and predominantly rely on centralised methods.…”

Section: Introductionmentioning

confidence: 99%

A Minimalistic and Decentralised Approach to Formation Control for Crowded UUV Swarms Inspired by Fish Schooling

Deng²,

Shao

et al. 2023

Preprint

View full text Add to dashboard Cite

In this paper, we propose a novel approach to formation control for a swarm of unmanned underwater vehicles (UUVs) inspired by the collective behaviour of fish schools. The approach addresses the challenges of centralised control, inflexibility, and high computational complexity in existing formation control methods. The proposed strategy for an individual agent consists of three parts: (1) coordinated strategy of collective motion without a predefined target, in which each individual agent adjusts its motion by rotating a fixed angle to the left or right based on the observed motion direction of its neighbours; (2) target guidance policy that the motion direction of each agent is guided by the target area; and (3) dispersion control strategy of avoiding overcrowding near the target area, in which each individual determines its own target position based on the relative positions of its neighbours and the target area. The simulation experiments demonstrate that using the proposed method, a group of individuals can perform an area coverage search in a flexible collective motion manner by simply making a left or right movement based on their own local perception. Furthermore, we validated the effectiveness of the proposed method using a UUV swarm consisting of 9 UUVs in a UUV simulator. The proposed method is flexible, decentralised, and has low computational complexity. Therefore, it can be applied to the formation control of large swarms of UUVs with limited perception and decision-making abilities.

show abstract

“…For the appropriate method of the trajectory tracking, it is a prerequisite that the control methodology of the trajectory tracking, either with deterministic model parameters or with uncertain model parameters, are known as precisely as possible. Moreover, the trajectory tracking methods of the control system usually include five types (line-of-sight (LOS) guidance algorithm [ 11 ], adaptive proportional-integral-differential (PID) algorithm [ 12 ], fuzzy control method [ 13 ], sliding mode control method [ 14 ], neural network control method [ 15 ]) during the regulating of control parameters. These methods could significantly improve control performance.…”

Section: Introductionmentioning

confidence: 99%

A trajectory tracking control system for paddle boat in intelligent aquaculture

Guo,

Zhang,

Zeng

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

Trajectory tracking plays a notable role in unmanned surface vehicles (USV), especially for the emerging intelligent aquaculture, as the level of integration, high-efficiency, and low-labor-intensity of such USV is determined by trajectory tracking. Here, we report a generic trajectory tracking control system for a paddle boat by establishing a three-degree-of-freedom kinematics model, which could precisely characterize the relationship between velocities, forces and moments of the paddle boat. A Pixhawk 4 as the core controller of the hardware system could be integrated with the other hardware submodules and could complete the wireless data transmission, monitoring and remote control functions. Meanwhile, we establish a fuzzy rule table, consider the advantages of line-of-sight (LOS) guidance and fuzzy adaptive proportional-integral-differential (PID) algorithm, combine the two parts and apply them as the key algorithm in the trajectory tracking of the paddle boat. Demonstrations include trajectory tracking effect at different velocities, turning effect at left-turn moment, and trajectory tracking effect at different turning angles. The results show that the paddle boat is able to travel under the trajectory formed by following the planned waypoints within the error allowed, which is called effective trajectory tracking. And can offer an alternative pathway toward achieving effective trajectory tracking control in advanced intelligent aquaculture USV for smartly and wirelessly operated pond drug spraying.

show abstract

An improved adaptive integral line-of-sight guidance law for unmanned surface vehicles with uncertainties

Cited by 22 publications

References 47 publications

Adaptive ground and water surface control for cross-domain robots based on adaptive finite-time convergence sliding mode observer

Adaptive ground and water surface control for cross-domain robots based on adaptive finite-time convergence sliding mode observer

A Minimalistic and Decentralised Approach to Formation Control for Crowded UUV Swarms Inspired by Fish Schooling

A trajectory tracking control system for paddle boat in intelligent aquaculture

Contact Info

Product

Resources

About