scholarly journals Barrier Lyapunov Function-Based Adaptive Control of an Uncertain Hovercraft with Position and Velocity Constraints

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Mingyu Fu ◽  
Taiqi Wang ◽  
Chenglong Wang
Keyword(s):  
Lyapunov Function ◽  
Tracking Error ◽  
Path Following ◽  
External Disturbances ◽  
Barrier Lyapunov Function ◽  
Yaw Rate ◽  
Path Following Control ◽  
Control Scheme ◽  
Velocity Constraints ◽  
Theoretical Analyses

This paper considers the problem of constrained path following control for an underactuated hovercraft subject to parametric uncertainties and external disturbances. A four-degree-of-freedom hovercraft model with unknown curve-fitted coefficients is first rewritten into a parameterized form. By introducing a barrier Lyapunov function into the line-of-sight guidance, the specific transient tracking performance in terms of position error is guaranteed. A novel constrained yaw rate controller is proposed to ensure time-varying yaw rate constraint satisfaction, in which the yaw rate barrier is required to vary with the speed of the hovercraft. Moreover, a command filter is incorporated into the control design to generate the desired virtual controls and its time derivatives. Theoretical analyses show that, under the proposed controller, the position tracking error constraints and the yaw rate constraint can be strictly guaranteed. Finally, numerical simulations illustrate the effectiveness and advantages of the proposed control scheme.

scholarly journals Finite-Time Path Following Control of an Underactuated Marine Surface Vessel with Input and Output Constraints

2020 ◽  
Vol 10 (18) ◽  
pp. 6447
Author(s):  
Mingyu Fu ◽  
Lulu Wang
Keyword(s):  
Finite Time ◽  
Input Saturation ◽  
Path Following ◽  
Parametric Uncertainties ◽  
External Disturbances ◽  
Time Path ◽  
Path Following Control ◽  
Control Scheme ◽  
Marine Surface ◽  
Surface Vessel

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.

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.

scholarly journals Robust Tracking Control of the Euler–Lagrange System Based on Barrier Lyapunov Function and Self-Structuring Neural Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yi Wang ◽  
He Ma ◽  
Weidong Wu
Keyword(s):  
Neural Network ◽  
Robust Control ◽  
Lyapunov Function ◽  
Tracking Control ◽  
Tracking Error ◽  
Robust Tracking ◽  
Robust Tracking Control ◽  
Barrier Lyapunov Function ◽  
Control Scheme ◽  
Unknown Disturbances

This article studies the robust tracking control problems of Euler–Lagrange (EL) systems with uncertainties. To enhance the robustness of the control systems, an asymmetric tan-type barrier Lyapunov function (ATBLF) is used to dynamic constraint position tracking errors. To deal with the problems of the system uncertainties, the self-structuring neural network (SSNN) is developed to estimate the unknown dynamics model and avoid the calculation burden. The robust compensator is designed to estimate and compensate neural network (NN) approximation errors and unknown disturbances. In addition, a relative threshold event-triggered strategy is introduced, which greatly saves communication resources. Under the proposed robust control scheme, tracking behavior can be implemented with disturbance and unknown dynamics of the EL systems. All signals in the closed-loop system are proved to be bounded by stability analysis, and the tracking error can converge to the neighborhood near the origin. The numerical simulation results show the effectiveness and the validity of the proposed robust control scheme.

scholarly journals Adaptive Integral Sliding Mode based Path Following Control of Unmanned Surface Vehicle

2021 ◽  
Author(s):  
José Antonio González-Prieto ◽  
Carlos Pérez-Collazo ◽  
Yogang Singh
Keyword(s):  
Simulation Study ◽  
Sliding Mode ◽  
Path Following ◽  
External Disturbances ◽  
Unmanned Surface Vehicle ◽  
Yaw Rate ◽  
Path Following Control ◽  
Different Types ◽  
Unknown Disturbances ◽  
System Uncertainties

This paper investigates the path following control problem for a unmanned surface vehicle (USV) in the presence of unknown disturbances and system uncertainties. The simulation study combines two different types of sliding mode surface based control approaches due to its precise tracking and robustness against disturbances and uncertainty. Firstly, an adaptive linear sliding mode surface algorithm is applied, to keep the yaw error within the desired boundaries and then an adaptive integral non-linear sliding mode surface is explored to keep an account of the sliding mode condition. Additionally, a method to reconfigure the input parameters in order to keep settling time, yaw rate restriction and desired precision within boundary conditions is presented. The main strengths of proposed approach is simplicity, robustness with respect to external disturbances and high adaptability to static and dynamics reference courses without the need of parameter reconfiguration.

scholarly journals A 3D Path Following Control Scheme for Robot Manipulators

2020 ◽  
Vol 53 (2) ◽  
pp. 9968-9973
Author(s):  
Yalun Wen ◽  
Prabhakar Pagilla
Keyword(s):  
Robot Manipulators ◽  
Path Following ◽  
Path Following Control ◽  
Control Scheme

Barrier Lyapunov function-based robot control with an augmented neural network approximator

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zuguo Zhang ◽  
Qingcong Wu ◽  
Xiong Li ◽  
Conghui Liang
Keyword(s):  
Neural Network ◽  
Lyapunov Function ◽  
Control Algorithm ◽  
Tracking Performance ◽  
Content Type ◽  
Barrier Lyapunov Function ◽  
Output Error ◽  
Control Scheme ◽  
Stringent Constraint ◽  
Continuous Dynamic

Purpose Considering the complexity of dynamic and friction modeling, this paper aims to develop an adaptive trajectory tracking control scheme for robot manipulators in a universal unmodeled method, avoiding complicated modeling processes. Design/methodology/approach An augmented neural network (NN) constituted of radial basis function neural networks (RBFNNs) and additional sigmoid-jump activation function (SJF) neurons is introduced to approximate complicated dynamics of the system: the RBFNNs estimate the continuous dynamic term and SJF neurons handle the discontinuous friction torques. Moreover, the control algorithm is designed based on Barrier Lyapunov Function (BLF) to constrain output error. Findings Lyapunov stability analysis demonstrates the exponential stability of the closed-loop system and guarantees the tracking errors within predefined boundaries. The introduction of SJFs alleviates the limitation of RBFNNs on discontinuous function approximation. Owing to the fast learning speed of RBFNNs and jump response of SJFs, this modified NN approximator can reconstruct the system model accurately at a low compute cost, and thereby better tracking performance can be obtained. Experiments conducted on a manipulator verify the improvement and superiority of the proposed scheme in tracking performance and uncertainty compensation compared to a standard NN control scheme. Originality/value An enhanced NN approximator constituted of RBFNN and additional SJF neurons is presented which can compensate the continuous dynamic and discontinuous friction simultaneously. This control algorithm has potential usages in high-performance robots with unknown dynamic and variable friction. Furthermore, it is the first time to combine the augmented NN approximator with BLF. After more exact model compensation, a smaller tracking error is realized and a more stringent constraint of output error can be implemented. The proposed control scheme is applicable to some constraint occasion like an exoskeleton and surgical robot.

Yaw rate tracking-based path-following control for four-wheel independent driving and four-wheel independent steering autonomous vehicles considering the coordination with dynamics stability

2020 ◽  
Vol 235 (1) ◽  
pp. 260-272
Author(s):  
Yixiao Liang ◽  
Yinong Li ◽  
Ling Zheng ◽  
Yinghong Yu ◽  
Yue Ren
Keyword(s):  
Autonomous Vehicles ◽  
Longitudinal Velocity ◽  
Path Following ◽  
Linear Matrix ◽  
Yaw Rate ◽  
Path Following Control ◽  
Inequality Theory ◽  
Conflicting Objectives ◽  
Upper Level ◽  
Dynamics Stability

The path-following problem for four-wheel independent driving and four-wheel independent steering electric autonomous vehicles is investigated in this paper. Owing to the over-actuated characters of four-wheel independent driving and four-wheel independent steering autonomous vehicles, a novel yaw rate tracking-based path-following controller is proposed. First, according to the kinematic relationships between vehicle and the reference path, the yaw rate generator is designed by linear matrix inequality theory, with the ability to minimize the disturbances caused by vehicle side slip and varying curvature of path. Considering that the path-following objective and dynamics stability are in conflict with each other in some extreme path-following conditions, a coordinating mechanism based on yaw rate prediction is proposed to satisfy the two conflicting objectives. Then, according to the desired yaw rate and longitudinal velocity, a hierarchical structure is introduced for motion control. The upper-level controller calculates the generalized tracking forces while the allocation layer optimally distributes the generalized forces to tires considering tire vertical load and adhesive utilization. Finally, simulation results indicate that the proposed method can achieve excellent path-following performances in different driving conditions, while both path-following objective and dynamics stability can be satisfied.

Adaptive robust iterative learning control with application to a Delta robot

2020 ◽  
pp. 095965182093853
Author(s):  
Chems Eddine Boudjedir ◽  
Djamel Boukhetala
Keyword(s):  
Iterative Learning Control ◽  
Tracking Error ◽  
Learning Control ◽  
Iterative Learning ◽  
External Disturbances ◽  
Repetitive Tasks ◽  
Control Scheme ◽  
Derivative Type ◽  
Delta Robot ◽  
Proportional Derivative Controller

In this article, an adaptive robust iterative learning control is developed to solve the trajectory tracking problem of a parallel Delta robot performing repetitive tasks and subjected to external disturbances. The proposed control scheme is composed of an adaptive proportional–derivative controller to increase the convergence rate, a proportional–derivative-type iterative learning control to enhance the tracking performances through the repetitive trajectory as well as a robust term to compensate the repetitive and nonrepetitive disturbances. The practical assumption of alignment condition is introduced instead of the classical assumption of resetting conditions. The asymptotic convergence is proved using Lyaponuv analysis, and it is shown that the tracking error decreases through the iterations. Simulation and experiments are performed on a Delta robot to demonstrate the effectiveness and the superiority of the proposed controller over the traditional iterative learning control.

scholarly journals Coordinated path-following control for networked unmanned surface vehicles

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142093057
Author(s):  
Dong-Liang Chen ◽  
Guo-Ping Liu ◽  
Ru-Bo Zhang ◽  
Xingru Qu
Keyword(s):  
Predictive Control ◽  
Controller Design ◽  
Control Strategies ◽  
Path Following ◽  
Control Performance ◽  
Negative Effects ◽  
Unmanned Surface Vehicles ◽  
Path Following Control ◽  
Control Scheme ◽  
Networked Predictive Control

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.

Robust Guidance Control for Nonholonomic AGV Based on First Order Dynamic Sliding Mode Techniques

2013 ◽  
Vol 709 ◽  
pp. 583-588
Author(s):  
Jin Hua Ye ◽  
Di Li ◽  
Shi Yong Wang ◽  
Feng Ye
Keyword(s):  
High Performance ◽  
Sliding Mode ◽  
Path Following ◽  
Lyapunov Theory ◽  
External Disturbances ◽  
Guidance Control ◽  
First Order ◽  
Control Scheme ◽  
The Impact ◽  
Dynamic Sliding Mode

This paper develops a high performance guidance controller for automated guided vehicle (AGV) with nonholonomic constraint. In this controller, the path following method in the Serret-Frenet frame is used for driving the AGV onto a predefined path at a constant forward speed. Moreover, a first order dynamic sliding mode controller is proposed, not only to overcome the impact of unknown model uncertainties and external disturbances of the system, but also to weaken the chattering in the standard sliding mode control. The global asymptotic stability and robustness of the system is proven by the Lyapunov theory and LaSalles invariance principle. Simulation results show the validity of the proposed guidance control scheme.

Sign in / Sign up

Export Citation Format

Share Document