Improved Integral LOS Guidance and Path-Following Control for an Unmanned Robot Sailboat via the Robust Neural Damping Technique

2019 ◽  
Vol 72 (06) ◽  
pp. 1378-1398 ◽  
Author(s):  
Guoqing Zhang ◽  
Jiqiang Li ◽  
Bo Li ◽  
Xianku Zhang
Keyword(s):  
External Disturbance ◽  
Path Following ◽  
Basic Function ◽  
Lyapunov Theory ◽  
Neural Controller ◽  
Adaptive Parameter ◽  
Guidance Law ◽  
Path Following Control ◽  
Adaptive Neural Controller ◽  
Robust Adaptive

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.

scholarly journals Robust Adaptive Neural Cooperative Control for the USV-UAV Based on the LVS-LVA Guidance Principle

2022 ◽  
Vol 10 (1) ◽  
pp. 51
Author(s):  
Jiqiang Li ◽  
Guoqing Zhang ◽  
Bo Li
Keyword(s):  
Cooperative Control ◽  
Position Control ◽  
Path Following ◽  
Dynamic Surface Control ◽  
Basic Function ◽  
Compact Set ◽  
Control Input ◽  
Dynamic Surface ◽  
Robust Adaptive ◽  
Event Triggered

Around the cooperative path-following control for the underactuated surface vessel (USV) and the unmanned aerial vehicle (UAV), a logic virtual ship-logic virtual aircraft (LVS-LVA) guidance principle is developed to generate the reference heading signals for the USV-UAV system by using the “virtual ship” and the “virtual aircraft”, which is critical to establish an effective correlation between the USV and the UAV. Taking the steerable variables (the main engine speed and the rudder angle of the USV, and the rotor angular velocities of the UAV) as the control input, a robust adaptive neural cooperative control algorithm was designed by employing the dynamic surface control (DSC), radial basic function neural networks (RBF-NNs) and the event-triggered technique. In the proposed algorithm, the reference roll angle and pitch angle for the UAV can be calculated from the position control loop by virtue of the nonlinear decouple technique. In addition, the system uncertainties were approximated through the RBF-NNs and the transmission burden from the controller to the actuators was reduced for merits of the event-triggered technique. Thus, the derived control law is superior in terms of the concise form, low transmission burden and robustness. Furthermore, the tracking errors of the USV-UAV cooperative control system can converge to a small compact set through adjusting the designed control parameters appropriately, and it can be also guaranteed that all the signals are the semi-global uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the proposed algorithm has been verified via numerical simulations in the presence of the time-varying disturbances.

scholarly journals 3DOF Adaptive Line-Of-Sight Based Proportional Guidance Law for Path Following of AUV in the Presence of Ocean Currents

2019 ◽  
Vol 9 (17) ◽  
pp. 3518 ◽  
Author(s):  
Fengxu Liu ◽  
Yue Shen ◽  
Bo He ◽  
Junhe Wan ◽  
Dianrui Wang ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Path Following ◽  
Lyapunov Theory ◽  
Line Of Sight ◽  
Average Error ◽  
Drift Angle ◽  
Reference Path ◽  
Guidance Law ◽  
Look Ahead ◽  
Three Degrees Of Freedom

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.

scholarly journals Underactuated USV Path Following Mechanism Based on the Cascade Method

2021 ◽  
Author(s):  
Mingzhen Lin ◽  
Zhiqiang Zhang ◽  
Yandong Pang ◽  
Hongsheng Lin ◽  
Qing Ji
Keyword(s):  
Tracking Error ◽  
Path Following ◽  
Ocean Current ◽  
Control Law ◽  
Guidance Law ◽  
Path Following Control ◽  
Heading Control ◽  
Velocity Constraints ◽  
The Stability ◽  
Rudder Angle

Abstract The path following control under disturbance was studied for an underactuated unmanned surface vehicle (USV) subject to the rudder angle and velocity constraints. For this reason, a variable look-ahead integral line-of-sight (LOS) guidance law was designed on the basis of the disturbance estimation and compensation, and a cascade path following control system was created following the heading control law based on the model prediction. Firstly, the guidance law was designed using the USV three-degree-of-freedom (DOF) motion model and the LOS method, while the tracking error state was introduced to design the real-time estimation of disturbance observer and compensate for the influence of ocean current. Moreover, the stability of the system was analyzed. Secondly, sufficient attention was paid to the rudder angle and velocity constraints and the influence of system delay and other factors in the process of path following when the heading control law was designed with the USV motion response model and the model predictive control (MPC). The moving horizon optimization strategy was adopted to achieve better dynamic performance, effectively overcome the influence of model and environmental uncertainties, and further prove the stability of the control law. Thirdly, a simulation experiment was carried out to verify the effectiveness and advancement of the proposed algorithm. Fourthly, the “Sturgeon 03” USV was used in the lake test of the proposed control algorithm to prove its feasibility in the engineering practices.

Adaptive neural network–based fault estimation for nonlinear systems with actuator faults in simultaneous multiplicative and additive forms

2021 ◽  
pp. 014233122110585
Author(s):  
Yan Zhao ◽  
Minhang Song ◽  
Xiangguo Huang ◽  
Ming Chen
Keyword(s):  
Neural Network ◽  
Fault Tolerant ◽  
Fault Estimation ◽  
Actuator Faults ◽  
Closed Loop System ◽  
Adaptive Neural Network ◽  
Neural Controller ◽  
Adaptive Parameter ◽  
Practical Engineering ◽  
Adaptive Neural Controller

Non-linearities and actuator faults often exist in practical systems which may degrade system performance or even lead to catastrophic accidents. In this article, a fault-tolerant compensation control strategy is proposed for a class of non-linear systems with actuator faults in simultaneous multiplicative and additive forms. First, radial basis function neural network is employed to approximate the system non-linearity. The approximation is achieved by only one adaptive parameter, which simplifies the computation burden. Then, by means of the backstepping technique, an adaptive neural controller is developed to cope with the adverse effects brought by the system non-linearity and actuator faults in multiplicative and additive forms. Meanwhile, the proposed control design scheme can guarantee that the considered closed-loop system is stable. The novelty of the article lies in that the system non-linearity, the additive actuator faults, and the multiplicative actuator faults that often exist in practical engineering are catered for simultaneously. Furthermore, compared with some existing works, the approximation of the system non-linearity is achieved by only one adaptive parameter for the purpose of reducing the computation burden. Therefore, its applicability is more general. Finally, a numerical simulation and a comparative simulation are carried out to show the effectiveness of the developed controller.

scholarly journals Neural observer-based path following control for underactuated unmanned surface vessels with input saturation and time-varying disturbance

2019 ◽  
Vol 16 (5) ◽  
pp. 172988141987807
Author(s):  
Lei Wan ◽  
Jiangfeng Zeng ◽  
Yueming Li ◽  
Hongde Qin ◽  
Lei Zhang ◽  
...  
Keyword(s):  
Disturbance Observer ◽  
External Disturbance ◽  
Input Saturation ◽  
Path Following ◽  
Dynamic Surface Control ◽  
Dynamic Surface ◽  
Surface Control ◽  
Surface Vessels ◽  
Path Following Control ◽  
Control Scheme

In this study, a new neural observer-based dynamic surface control scheme is proposed for the path following of underactuated unmanned surface vessels in the presence of input saturation and time-varying external disturbance. The dynamic surface control technique is augmented by a robust adaptive radial basis function neural network and a nonlinear neural disturbance observer. Radial basis function neural network is employed to deal with system uncertainties, and the nonlinear neural disturbance observer is developed to compensate for the unknown compound disturbance that contains the input saturation approximation error and the external disturbance. Moreover, the stringent known boundary requirement of the unknown disturbance constraint is eliminated with the proposed nonlinear neural disturbance observer. Meanwhile, to deal with the non-smooth saturation nonlinearity, a new parametric hyperbolic tangent function approximation model with arbitrary prescribed precision is constructed, which results in the transient performance improvement for the path following control system. Stability analysis shows that all the signals in the closed-loop system are guaranteed to be ultimately bounded. Comparative simulation results further demonstrate the effectiveness of the proposed control scheme.

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