scholarly journals Research of Robust Trajectory Tracking Control and Attenuated Chattering: Application on Quadrotor

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Guangli Zhou ◽  
Yongming Yao ◽  
Huiying Liu ◽  
Xupeng Bai ◽  
Jianbo Liu
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Linear Prediction ◽  
Sliding Mode ◽  
Lyapunov Theory ◽  
Superior Performance ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Chattering Phenomenon ◽  
Attitude Tracking

In this paper, we presented a strategy for accurate trajectory tracking control of a quadrotor with unknown disturbances. To guarantee that the tracking errors of all system state variables converge to zero in finite time and eliminate the chattering phenomenon caused by the switching control action, a control strategy that combines linear prediction model of disturbances and fuzzy sliding mode control (SMC) based on logical framework with side conditions (LFSC) was designed. LFSC was applied for both position and attitude tracking of the quadrotor. Firstly, a linear prediction method was devised to minimize the effects of external disturbances. Secondly, a new fuzzy law was implemented to eliminate the chattering phenomenon. In addition, the stabilities of position and attitude were demonstrated by using Lyapunov theory, respectively. Simulation results and comprehensive comparisons demonstrated the superior performance and robustness of the proposed LFSC scheme in the case of external disturbances.

scholarly journals Fixed-Time Trajectory Tracking Control of Autonomous Surface Vehicle with Model Uncertainties and Disturbances

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jiawen Cui ◽  
Haibin Sun
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
Fixed Time ◽  
Convergence Time ◽  
Model Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Integral Sliding Mode ◽  
Control Scheme

The issue of fixed-time trajectory tracking control for the autonomous surface vehicles (ASVs) system with model uncertainties and external disturbances is investigated in this paper. Particularly, convergence time does not depend on initial conditions. The major contributions include the following: (1) An integral sliding mode controller (ISMC) via integral sliding mode surface is first proposed, which can ensure that the system states can follow the desired trajectory within a fixed time. (2) Unknown external disturbances are absolutely estimated by means of designing a fixed-time disturbance observer (FTDO). By combining the FTDO and ISMC techniques, a new control scheme (FTDO-ISMC) is developed, which can achieve both disturbance compensation and chattering-free condition. (3) Aiming at reconstructing the unknown nonlinear dynamics and external disturbances, a fixed-time unknown observer (FTUO) is proposed, thus providing the FTUO-ISMC scheme that finally achieves trajectory tracking of ASVs with unknown parameters. Finally, simulation tests and detailed comparisons indicate the effectiveness of the proposed control scheme.

Chattering-suppression sliding mode control of an autonomous underwater vehicle based on nonlinear disturbance observer and power function reaching law

2021 ◽  
pp. 014233122198986
Author(s):  
Qirong Tang ◽  
Yinghao Li ◽  
Ruiqin Guo ◽  
Daopeng Jin ◽  
Yang Hong ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Autonomous Underwater Vehicle ◽  
Sliding Mode ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Nonlinear Disturbance Observer ◽  
Reaching Law ◽  
Nonlinear Disturbance

To improve the performance of autonomous underwater vehicle in trajectory tracking control, which is subject to system uncertainties and time-varying external disturbances, a nonlinear disturbance observer-based sliding mode controller is proposed in the study. First, a reaching law with a special power function and a hyperbolic tangent function is presented. Then an improved sliding mode controller based on the new reaching law is combined to decrease the reaching time and avoid chattering during the trajectory tracking control. Furthermore, to reduce the influence of the system uncertainties and external disturbances, a nonlinear disturbance observer is introduced to identify them. The error asymptotic convergence of the trajectory tracking control is proved by the Lyapunov-like function. Finally, under different environmental disturbances, plenty of simulations are carried out to verify the efficiency and robustness of the proposed method. Results show that when it is tracking different trajectories, the proposed method can suppress the chattering and reduce the disturbances effectively, while ensuring tracking performance.

scholarly journals Robust trajectory tracking control for an underactuated autonomous underwater vehicle based on bioinspired neurodynamics

2018 ◽  
Vol 15 (5) ◽  
pp. 172988141880674 ◽  
Author(s):  
Yunbiao Jiang ◽  
Chen Guo ◽  
Haomiao Yu
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Autonomous Underwater Vehicle ◽  
Sliding Mode ◽  
Underwater Vehicle ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Control Laws ◽  
Parameter Perturbations

This article investigates the three-dimensional trajectory tracking control problem for an underactuated autonomous underwater vehicle in the presence of parameter perturbations and external disturbances. An adaptive robust controller is proposed based on the velocity control strategy and adaptive integral sliding mode control algorithm. First, the desired velocities are developed using coordinate transformation and the backstepping method, which is the necessary velocities for autonomous underwater vehicle to track the time-varying desired trajectory. The bioinspired neurodynamics is used to smooth the desired velocities, which effectively avoids the jump problem of the velocity and simplifies the derivative calculation. Then, the dynamic control laws are designed based on the adaptive integral sliding mode control to drive the underactuated autonomous underwater vehicle to sail at the desired velocities. At the same time, the auxiliary control laws and the adaptive laws are introduced to eliminate the influence of parameter perturbations and external disturbances, respectively. The stability of the control system is guaranteed by the Lyapunov theorem, which shows that the system is asymptotically stable and all tracking errors are asymptotically convergent. At the end, numerical simulations are carried out to demonstrate the effectiveness and robustness of the proposed controller.

Adaptive neural finite-time trajectory tracking control of hydraulic excavators

2018 ◽  
Vol 232 (7) ◽  
pp. 909-925 ◽  
Author(s):  
Yong Li ◽  
Qingfeng Wang
Keyword(s):  
Trajectory Tracking ◽  
Finite Time ◽  
Tracking Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Approximation Error ◽  
Superior Performance ◽  
Observation Error ◽  
Trajectory Tracking Control ◽  
Terminal Sliding Mode

This article is focused on the high-performance trajectory tracking control of single actuator of a hydraulic excavator. A novel adaptive neural finite-time controller without tedious offline parameter identification and the complex backstepping scheme is put forward. By employing a coordinate transform, the original system can be represented in a canonical form. Consequently, the control objective is retained by controlling the transformed system, which allows a simple controller design without using backstepping. To estimate the immeasurable states of the transformed system, a high-order sliding mode observer is employed, of which observation error is guaranteed to be bounded in finite time. To guarantee finite-time trajectory tracking performance, an adaptive neural finite-time controller based on neural network approximation and terminal sliding mode theory is synthesized. During its synthesis, an echo state network is used to approximate the lumped uncertain system functions, and it guarantees an improved approximation with online-updated output weights. Besides, to handle the lumped uncertain nonlinearities resulting from observation error and neural approximation error, a robust term is employed. The influences of the uncertain nonlinearities are restrained with a novel parameter adaption law, which estimates and updates the upper bound of the lumped uncertain nonlinearities online. With this novel controller, the finite-time trajectory tracking error convergence is proved theoretically. The superior performance and the practical applicability of the proposed method are verified by comparative simulations and experiments.

Robust finite-time trajectory tracking control for a space manipulator with parametric uncertainties and external disturbances

2021 ◽  
pp. 095441002110147
Author(s):  
Qijia Yao
Keyword(s):  
Trajectory Tracking ◽  
Finite Time ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Parametric Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Space Manipulator ◽  
Tracking Controller

Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this study, a robust finite-time tracking control method is proposed for the rapid and accurate trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of parametric uncertainties and external disturbances. First, a baseline finite-time tracking controller is designed to track the desired position of the space manipulator based on the homogeneous method. Then, a finite-time disturbance observer is designed to accurately estimate the lumped uncertainties. Finally, a robust finite-time tracking controller is developed by integrating the baseline finite-time tracking controller with the finite-time disturbance observer. Rigorous theoretical analysis for the global finite-time stability of the whole closed-loop system is provided. The proposed robust finite-time tracking controller has a relatively simple structure and can guarantee the position and velocity tracking errors converge to zero in finite time even subject to lumped uncertainties. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance under the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control method.

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