Trajectory Tracking With Prescribed Performance for Underactuated Underwater Vehicles Under Model Uncertainties and External Disturbances

2017 ◽  
Vol 25 (2) ◽  
pp. 429-440 ◽  
Author(s):  
Charalampos P. Bechlioulis ◽  
George C. Karras ◽  
Shahab Heshmati-Alamdari ◽  
Kostas J. Kyriakopoulos
Keyword(s):  
Trajectory Tracking ◽  
Underwater Vehicles ◽  
Model Uncertainties ◽  
External Disturbances ◽  
Prescribed Performance

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.

scholarly journals Adaptive Fixed-Time Trajectory Tracking Control for Underactuated Hovercraft with Prescribed Performance in the Presence of Model Uncertainties

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Mingyu Fu ◽  
Tan Zhang ◽  
Fuguang Ding ◽  
Duansong Wang
Keyword(s):  
Trajectory Tracking ◽  
Degrees Of Freedom ◽  
Convergence Rates ◽  
Direct Method ◽  
Fixed Time ◽  
Model Uncertainties ◽  
Tracking Errors ◽  
Trajectory Tracking Control ◽  
Control Laws ◽  
Prescribed Performance

This paper develops an adaptive fixed-time trajectory tracking controller of an underactuated hovercraft with a prescribed performance in the presence of model uncertainties and unknown time-varying environment disturbances. It is the first time that the proposed method is applied to the motion control of the hovercraft. To begin with, based on the hovercraft's four degrees of freedom (DOF) model, the virtual control laws are designed using an error transforming function and the fixed-time stability theory to guarantee that the position tracking errors are constrained within the prescribed convergence rates and minimum overshoot. In addition, by combining the Lyapunov direct method and the adaptive radial basis function neural network (ARBFNN), the actual control laws are designed to ensure that the velocity tracking errors converge to a small region containing zero while handling model uncertainties and external disturbances effectively. Finally, all tracking errors of the closed-loop system are uniformly ultimately bounded and fixed-time convergent. Results from a comparative simulation study verify the effectiveness and advantage of the proposed method.

scholarly journals MPC Based Trajectory Tracking for An Automonous Deep-Sea Tracked Mining Vehicle

2021 ◽  
Vol 1 (2) ◽  
pp. 1-13
Author(s):  
Hongyun Wu ◽  
Yuheng Chen ◽  
Hongmao Qin
Keyword(s):  
Obstacle Avoidance ◽  
Kalman Filtering ◽  
Trajectory Tracking ◽  
Deep Sea ◽  
Autonomous Vehicles ◽  
External Disturbance ◽  
Kinematic Model ◽  
Vehicle Body ◽  
Model Uncertainties ◽  
External Disturbances

Model predictive control (MPC) has been successfully used in trajectory tracking for autonomous vehicles based on certain kinematic model under low external disturbance conditions, but when there are model uncertainties and external disturbances, autonomous vehicles will fail to follow the pre-set trajectory. This paper studies trajectory tracking control based on MPC for an autonomous deep-sea tracked mining vehicle in polymetallic nodule mines with model uncertainty and external disturbances. A MPC algorithm is designed for trajectory tracking. To address model uncertainties caused by vehicle body subsidence and track slippage, a drive wheel speed correction controller is designed by experimental data fitting, and Kalman filtering (KF) and adaptive Kalman filtering (AKF) are introduced to improve tracking performance by rejecting external disturbances especially during curve tracking. To handle dead zones and obstacles during actual operation, an obstacle avoidance strategy is proposed that uses the tri-circular arc obstacle avoidance trajectory with an equal curvature for path re-planning. Finally, Simulink&Recurdyn co-simulations validate the performance of the proposed MPC controller through a comparison with nonlinear MPC(NMPC).

scholarly journals Robust Backstepping Trajectory Tracking Control of a Quadrotor with Input Saturation via Extended State Observer

2019 ◽  
Vol 9 (23) ◽  
pp. 5184 ◽  
Author(s):  
Nguyen Xuan-Mung ◽  
Sung Kyung Hong
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Input Saturation ◽  
Extended State Observer ◽  
Control Input ◽  
Extended State ◽  
Model Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Aerial Vehicles

Quadrotor unmanned aerial vehicles have become increasingly popular in several applications, and the improvement of their control performance has been documented in several studies. Nevertheless, the design of a high-performance tracking controller for aerial vehicles that reliably functions in the simultaneous presence of model uncertainties, external disturbances, and control input saturation still remains a challenge. In this paper, we present a robust backstepping trajectory tracking control of a quadrotor with input saturation. The controller design accounts for both parameterized uncertainties and external disturbances, whereas a new auxiliary system is proposed to cope with control input saturation. Taking into account that only the position and attitude of the quadrotor are measurable, we devise an extended state observer to supply the estimations of unmeasured states, model uncertainties, and external disturbances. We strictly prove the stability of the closed-loop system by using the Lyapunov theory and demonstrate the effectiveness of the proposed algorithm through numerical simulations.

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