scholarly journals Path Following Control for Underactuated Airships with Magnitude and Rate Saturation

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7176
Author(s):  
Huabei Gou ◽  
Xiao Guo ◽  
Wenjie Lou ◽  
Jiajun Ou ◽  
Jiace Yuan

This paper proposes a reinforcement learning (RL) based path following strategy for underactuated airships with magnitude and rate saturation. The Markov decision process (MDP) model for the control problem is established. Then an error bounded line-of-sight (LOS) guidance law is investigated to restrain the state space. Subsequently, a proximal policy optimization (PPO) algorithm is employed to approximate the optimal action policy through trial and error. Since the optimal action policy is generated from the action space, the magnitude and rate saturation can be avoided. The simulation results, involving circular, general, broken-line, and anti-wind path following tasks, demonstrate that the proposed control scheme can transfer to new tasks without adaptation, and possesses satisfying real-time performance and robustness.

2021 ◽  
Vol 28 (2) ◽  
pp. 18-26
Author(s):  
Ligang Li ◽  
Zhiyuan Pei ◽  
Jiucai Jin ◽  
Yongshou Dai

Abstract In order to improve the accuracy and robustness of path following control for an Unmanned Surface Vehicle (USV) suffering from unknown and complex disturbances, a variable speed curve path following a control method based on an extended state observer was proposed. Firstly, the effect of the environmental disturbances on the USV is equivalent to an unknown and time-varying sideslip angle, and the sideslip angle is estimated by using the extended state observer (ESO) and compensated in the Line of Sight (LOS) guidance law. Secondly, based on the traditional LOS guidance law, the design of the surge velocity guidance law is added to enable the USV to self-adjust the surge velocity according to the curvature of the curve path, thus further improving the tracking accuracy. Finally, the heading and speed controller of the USV is designed by using a sliding mode control to track the desired heading and speed accurately, and then the path following control of the USV’s curve path is realised. Simulation results verify the effectiveness of the proposed method.


2020 ◽  
Vol 53 (2) ◽  
pp. 9968-9973
Author(s):  
Yalun Wen ◽  
Prabhakar Pagilla

2020 ◽  
Vol 10 (18) ◽  
pp. 6447
Author(s):  
Mingyu Fu ◽  
Lulu Wang

This paper develops a finite-time path following control scheme for an underactuated marine surface vessel (MSV) with external disturbances, model parametric uncertainties, position constraint and input saturation. Initially, based on the time-varying barrier Lyapunov function (BLF), the finite-time line-of-sight (FT-LOS) guidance law is proposed to obtain the desired yaw angle and simultaneously constrain the position error of the underactuated MSV. Furthermore, the finite-time path following constraint controllers are designed to achieve tracking control in finite time. Additionally, considering the model parametric uncertainties and external disturbances, the finite-time disturbance observers are proposed to estimate the compound disturbance. For the sake of avoiding the input saturation and satisfying the requirements of finite-time convergence, the finite-time input saturation compensators were designed. The stability analysis shows that the proposed finite-time path following control scheme can strictly guarantee the constraint requirements of the position, and all error signals of the whole control system can converge into a small neighborhood around zero in finite time. Finally, comparative simulation results show the effectiveness and superiority of the proposed finite-time path following control scheme.


2019 ◽  
Vol 72 (06) ◽  
pp. 1378-1398 ◽  
Author(s):  
Guoqing Zhang ◽  
Jiqiang Li ◽  
Bo Li ◽  
Xianku Zhang

This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance.


2019 ◽  
Vol 9 (17) ◽  
pp. 3518 ◽  
Author(s):  
Fengxu Liu ◽  
Yue Shen ◽  
Bo He ◽  
Junhe Wan ◽  
Dianrui Wang ◽  
...  

In order to achieve high-precision path following of autonomous underwater vehicle (AUV) in the horizontal plane, a three degrees-of-freedom adaptive line-of-sight based proportional (3DOFAPLOS) guidance law is proposed. Firstly, the path point coordinate system is introduced, which is suitable for the conversion of an arbitrary path. Then, the appropriate look-ahead distance is obtained by an improved adaptive line-of-sight (ALOS) according to three degrees-of-freedom (3DOF), including the cross-track error, the curvature of reference path, and the forward speed. Moreover, combining three degrees-of-freedom ALOS (3DOFALOS) with proportional guidance law, the desired heading is calculated considering the drift angle. 3DOFAPLOS has two functions: in the convergence stage, 3DOFALOS plays a leading role, making AUV converge to the path more quickly and smoothly. In the guidance stage, proportional guidance law plays a major role in effectively resisting the influence of drift angle and making AUV sail along the reference path. If the path is curved, 3DOFALOS makes contributions in both stages, adjusting look-ahead distance in real time with respect to curvature. The stability of the designed closed system is proved by Lyapunov theory. Both simulation and experiment results have verified that 3DOFAPLOS has a satisfactory result, which improves tracking performance more than 50% compared with the traditional line-of-sight (LOS). Specifically, the mean average error (MAE) of path following under 3DOFAPLOS can be reduced by about 60%, and the root mean square error (RMSE) can be reduced by about 50% compared with LOS.


2020 ◽  
Vol 17 (3) ◽  
pp. 172988142093057
Author(s):  
Dong-Liang Chen ◽  
Guo-Ping Liu ◽  
Ru-Bo Zhang ◽  
Xingru Qu

In this article, the coordinated path-following control problem for networked unmanned surface vehicles is investigated. The communication network brings time delays and packet dropouts to the fleet, which will have negative effects on the control performance of the fleet. To attenuate the negative effects, a novel networked predictive control scheme is proposed. By introducing the predictive error into the control scheme, the proposed control strategy admits some advantages compared with existing networked predictive control strategies, for example, a degree of robustness to disturbances, lower requirements for the computing capacity of the onboard processors, high flexibility in controller design, and so on. Conditions that guarantee the control performance of the overall system are derived in the theoretical analysis. At last, experiments on hovercraft test beds are implemented to verify the effectiveness of the proposed control scheme.


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