Backstepping Control of Gliding Robotic Fish for Trajectory Tracking in 3D Space

Purpose The purpose of this research on the control of three-axis aero-dynamic pendulum with disturbance is to facilitate the applications of equipment with similar pendulum structure in intelligent manufacturing and robot. Design/methodology/approach The controller proposed in this paper is mainly implemented in the following ways. First, the kinematic model of the three-axis aero-dynamic pendulum is derived in state space form to construct the predictive model. Then, according to the predictive model and objective function, the control problem can be expressed a quadratic programming (QP) problem. The optimal solution of the QP problem at each sampling time is the value of control variable. Findings The trajectory tracking and point stability tests performed on the 3D space with different disturbances are validated and the results show the effectiveness of the proposed control strategy. Originality/value This paper proposes a nonlinear unstable three-axis aero-dynamic pendulum with less power devices. Meanwhile, the trajectory tracking and point stability problem of the pendulum system is investigated with the model predictive control strategy.

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Trajectory Tracking of a Robotic Fish using Hybrid Controller

Intelligent Systems and Control / 742: Computational Bioscience ◽

10.2316/p.2011.744-094 ◽

2011 ◽

Author(s):

Tesfay G. Meressi

Keyword(s):

Trajectory Tracking ◽

Robotic Fish ◽

Hybrid Controller

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Neural-Based Command Filtered Backstepping Control for Trajectory Tracking of Underactuated Autonomous Surface Vehicles

IEEE Access ◽

10.1109/access.2020.2975898 ◽

2020 ◽

Vol 8 ◽

pp. 42481-42490

Author(s):

Chengju Zhang ◽

Cong Wang ◽

Yingjie Wei ◽

Jinqiang Wang

Keyword(s):

Trajectory Tracking ◽

Backstepping Control ◽

Autonomous Surface Vehicles

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Quadrotor trajectory tracking and obstacle avoidance by chaotic grey wolf optimization- based backstepping control with sliding mode extended state observer

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331219894401 ◽

2020 ◽

Vol 42 (9) ◽

pp. 1675-1689 ◽

Cited By ~ 1

Author(s):

Yingxun Wang ◽

Yan Ma ◽

Zhihao Cai ◽

Jiang Zhao

Keyword(s):

Obstacle Avoidance ◽

Trajectory Tracking ◽

Sliding Mode ◽

Backstepping Control ◽

Extended State Observer ◽

Grey Wolf ◽

Extended State ◽

Grey Wolf Optimization ◽

Control Scheme ◽

Virtual Target

In this paper, a new swarm intelligent-based backstepping control scheme is proposed for quadrotor trajectory tracking and obstacle avoidance. First, the sliding mode extended state observer (SMESO) is used to estimate different disturbances, and the tracking differentiator (TD) is integrated to enhance the performance of backstepping control scheme. Then, the chaotic grey wolf optimization (CGWO) is developed with chaotic initialization and chaotic search to optimize the parameters of attitude and position controllers. Further, the virtual target guidance approach is proposed for quadrotor trajectory tracking and obstacle avoidance. Comparative simulations and Monte Carlo tests are carried out to demonstrate the effectiveness and robustness of the CGWO-based backstepping control scheme and virtual target guidance approach.

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