scholarly journals Prescribed performance adaptive fault-tolerant trajectory tracking control for an ocean bottom flying node

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141984194 ◽  
Author(s):  
Hongde Qin ◽  
Zheyuan Wu ◽  
Yanchao Sun ◽  
Yushan Sun
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Tracking Error ◽  
Approximation Error ◽  
Ocean Current ◽  
Ocean Bottom ◽  
Model Uncertainties ◽  
Trajectory Tracking Control ◽  
Prescribed Performance

The ocean bottom flying node is a novel autonomous underwater vehicle that explores the oil and gas resources in deep water. Thousands of the ocean bottom flying nodes track different predefined trajectories arriving at target points in a small ocean area, respectively. A class of prescribed performance adaptive trajectory tracking control method is investigated for the ocean bottom flying node trajectory tracking problem with ocean current disturbances, model uncertainties as well as thruster faults. Based on a predefined performance function and an error transformation, the ocean bottom flying node trajectory tracking error is restricted to prespecified bounds to ensure a desired transient and steady response. Radial basis function neural network is used to approximate the general uncertainty caused by ocean current disturbances, model uncertainties, and thruster faults. Further, the upper bound of approximation error is estimated by an adaptive law. Using the adaptive laws, we propose a prescribed performance adaptive trajectory tracking controller. The simulation examples on an ocean bottom flying node system show that the proposed control scheme can compensate for the effect of the general uncertainty while obtaining the fast transient process and expected trajectory tracking accuracy.

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.

Dynamic trajectory-tracking control method of robotic transcranial magnetic stimulation with end-effector gravity compensation based on force sensors

2018 ◽  
Vol 45 (6) ◽  
pp. 722-731
Author(s):  
ZeCai Lin ◽  
Wang Xin ◽  
Jian Yang ◽  
Zhang QingPei ◽  
Lu ZongJie
Keyword(s):  
Neural Networks ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Magnetic Stimulation ◽  
Control Method ◽  
Gravity Compensation ◽  
Trajectory Tracking Control ◽  
End Effector ◽  
Content Type ◽  
Dynamic Trajectory

Purpose This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment. Design/methodology/approach First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems. Findings The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller. Originality/value A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.

Prescribed performance trajectory tracking control of dynamic positioning ship under input saturation

2020 ◽  
pp. 014233122092888
Author(s):  
Yuanhui Wang ◽  
Haibin Wang ◽  
Mingyu Fu
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Degrees Of Freedom ◽  
Input Saturation ◽  
Small Neighborhood ◽  
Performance Criteria ◽  
Dynamic Positioning ◽  
Trajectory Tracking Control ◽  
Prescribed Performance ◽  
Control Scheme

This paper investigates concentrates on the trajectory tracking control problem of dynamic positioning (DP) ship, in the presence of the time-varying disturbance and input saturation. Firstly, a simplified mathematical model of three degrees of freedom is established. According to the characteristics of the DP ship, an adaptive backstepping controller which combine the prescribed performance function with disturbance observer is proposed. The control scheme can guarantee the transient and steady state performance of the trajectory tracking and meet the prescribed performance criteria. In addition, an auxiliary dynamic system is introduced into the controller to deal with the input saturation problem of the actuator, so that the DP ship can accomplish the task of trajectory tracking under the condition of actuator constraint. Subsequently, in combination of barrier Lyapunov function (BLF), it is proved that the DP system can stabilize and converge rapidly to the small neighborhood of the equilibrium point, which can achieve the prescribed performance. Finally, the effectiveness of the DP control law is demonstrated by a series of simulation experiments.

scholarly journals Prescribed Performance Tracking Control for Hypersonic Flight Vehicles with Model Uncertainties

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Siyuan Zhao ◽  
Xiaobing Li ◽  
Xiangwei Bu ◽  
Dongyang Zhang
Keyword(s):  
Tracking Control ◽  
Tracking Error ◽  
Longitudinal Motion ◽  
Model Uncertainties ◽  
Prescribed Performance ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Performance Tracking ◽  
Control Objective ◽  
Proportional Integral Controller

This paper proposes a novel prescribed performance tracking control for a hypersonic flight vehicle (HFV) with model uncertainties. Firstly, a HFV longitudinal motion model is decomposed into a velocity subsystem and an altitude subsystem. Meanwhile, considering the uncertainties of the model, the velocity subsystem and altitude subsystem are directly expressed as the forms with unknown nonaffine functions. Secondly, a novel performance function without initial error is proposed for limiting the tracking error into a prescribed range. Then, for the altitude subsystem, the control objective is changed by model transformation and the prescribed performance backstepping controller is designed. For the velocity subsystem, a prescribed performance proportional-integral controller is proposed which has better engineering practicability. The designed controller is not only simple in form but also has few calculating parameters. Finally, the simulation results show that the proposed controller has good practicability.

Dynamic modeling and trajectory tracking control method of segmented linkage cable-driven hyper-redundant robot

2020 ◽  
Vol 101 (1) ◽  
pp. 233-253
Author(s):  
Jianqing Peng ◽  
Wenfu Xu ◽  
Taiwei Yang ◽  
Zhonghua Hu ◽  
Bin Liang
Keyword(s):  
Dynamic Modeling ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Trajectory Tracking Control ◽  
Redundant Robot
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