scholarly journals ADP based trajectory-tracking control via backstepping method for underactuated AUV with unknown dynamics

2021 ◽  
Author(s):  
Gaofeng Che ◽  
Zhen Yu
Keyword(s):  
Neural Network ◽  
Control Problem ◽  
Dynamic Model ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Autonomous Underwater Vehicles ◽  
System Stability ◽  
Trajectory Tracking Control ◽  
Control Scheme ◽  
Underactuated Auv

Abstract This paper investigates trajectory-tacking control problem for underactuated autonomous underwater vehicles (AUV) with unknown dynamics. Different from existing adaptive dynamic programming (ADP) schemes, our proposed control scheme can achieve high-level system stability and tracking control accuracy. Firstly, the backstepping approach is introduced into the kinematic model of underactuated AUV and produces a virtual velocity control which is taken as the desired velocity input of the dynamic model of underactuated AUV. Secondly, the error tracking system is constructed according to the dynamic model of underactuated AUV. Thirdly, the critic neural network and the action neural network are employed to transform the trajectory-tracking control problem into optimal control problem based on policy iteration algorithm. At last simulation results are given to verify the effectiveness of the control scheme proposed in this paper.

Trajectory tracking control of robot manipulators using a neural-network-based torque compensator

1998 ◽  
Vol 212 (5) ◽  
pp. 361-372 ◽  
Author(s):  
Q Li ◽  
S K Tso ◽  
W J Zhang
Keyword(s):  
Neural Network ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
High Performance ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Lyapunov Stability Theory ◽  
System Stability ◽  
Trajectory Tracking Control ◽  
Modelling Uncertainties

In this paper, an adaptive neural-network-based torque compensator is developed for the trajectory-tracking control of robot manipulators. The overall control structure employs a classical non-linear decoupling controller for actuating torque computation based on an approximated robot dynamic model. To suppress the effects of uncertainties associated with the estimated model, a supplementary neural network algorithm is developed to generate compensation torques. The weight adaptation rule for this neuro-compensator is derived on the basis of the Lyapunov stability theory. Both global system stability and the error convergence can then be guaranteed. Simulation studies on a two-link robot manipulator demonstrate that high performance of the proposed control algorithm could be achieved under severe modelling uncertainties.

scholarly journals A Neural Network Based Dynamic Control Method for Soft Pneumatic Actuator with Symmetrical Chambers

Actuators ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 112
Author(s):  
Yiqing Li ◽  
Yan Cao ◽  
Feng Jia
Keyword(s):  
Neural Network ◽  
Dynamic Model ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Dynamic Control ◽  
The State ◽  
Pneumatic Actuator ◽  
Trajectory Tracking Control ◽  
Modeling And Control

Dynamic modeling and control of the soft pneumatic actuators are challenging research. In this paper, a neural network based dynamic control method used for a soft pneumatic actuator with symmetrical chambers is proposed. The neural network is introduced to create the dynamic model for predicting the state of the actuator. In this dynamic model, the effect of the uninflated rubber block on bending deformation is considered. Both pressures of the actuator are used for predicting the state of the actuator during the bending motion. The controller is designed based on this dynamic model for trajectory tracking control. Three types of trajectory tracking control experiments are performed to validate the proposed method. The results show that the proposed control method can control the motion of the actuator and track the trajectory effectively.

Modeling and Control of a Horizontal Two-Link Rigid/Flexible Robot

2005 ◽  
Author(s):  
Ho-Hoon Lee
Keyword(s):  
Dynamic Model ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Trajectory Control ◽  
Distributed Parameter ◽  
Mathematical Tool ◽  
Flexible Robot ◽  
Trajectory Tracking Control ◽  
Modeling And Control ◽  
Control Scheme

This paper proposes a trajectory control scheme for a horizontal two-link rigid/flexible robot having a payload at the free end. First, a new distributed-parameter dynamic model, consisting of two ordinary differential equations and one partial differential equation, is derived using the extended Hamilton’s principle, and then a trajectory-tracking control scheme is designed based on the distributed-parameter dynamic model, where the Lyapunov stability theorem is used as a mathematical tool. The proposed control is a collocated control, free from the so-called spillover instability. The proposed control consists of a PD control for the rigid dynamics, a proportional control for the flexible dynamics, and feed forward and dynamics compensation. With only two joint actuators, the proposed trajectory control guarantees stability throughout the entire trajectory-tracking control and asymptotic stability at desired goal positions. The theoretical results have been evaluated with control experiments.

Robust Tracking Control of Autonomous Underwater Vehicles in the Presence of Disturbance Inputs

2009 ◽  
Author(s):  
S. Singh ◽  
A. Sanyal ◽  
R. Smith ◽  
N. Nordkvist ◽  
M. Chyba
Keyword(s):  
Feedback Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Open Loop ◽  
Robust Tracking Control ◽  
Trajectory Tracking Control ◽  
Loop Control ◽  
Control Scheme

An autonomous underwater vehicle (AUV) is expected to operate in an ocean in the presence of poorly known disturbance forces and moments. The uncertainties of the environment makes it difficult to apply open-loop control scheme for the motion planning of the vehicle. The objective of this paper is to develop a robust feedback trajectory tracking control scheme for an AUV that can track a prescribed trajectory amidst such disturbances. We solve a general problem of feedback trajectory tracking of an AUV in SE (3). The feedback control scheme is derived using Lyapunov-type analysis. The results obtained from numerical simulations confirm the asymptotic tracking properties of the feedback control law. We apply the feedback control scheme to different mission scenarios, with the disturbances being initial errors in the state of the AUV.

A Robust Trajectory Tracking Control Scheme of Two-Link Flexible Manipulator

2011 ◽  
Vol 328-330 ◽  
pp. 2108-2112
Author(s):  
Jing Shuang Lu ◽  
Chun Mei Du ◽  
Rui Zhou ◽  
Na Li
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Vertical Plane ◽  
Flexible Manipulator ◽  
System Model ◽  
Error Signal ◽  
Dynamics Model ◽  
Trajectory Tracking Control ◽  
Control Scheme ◽  
Simulation Results

A simple dynamics model is established based on the two-link flexible manipulator moving within the vertical plane, and a robust simple control scheme is put forward. The advantages of this scheme are simple and good robustness. Only the error signal is needed when designing the control scheme and the acquirement of control signal does not depend on the system model. The simulation results show that this method has a good robustness and stability.

Real-time trajectory tracking control of Stewart platform using fractional order fuzzy PID controller optimized by particle swarm algorithm

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zafer Bingul ◽  
Oguzhan Karahan
Keyword(s):  
Dynamic Model ◽  
Fractional Order ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Fuzzy Pid ◽  
Simulation Environment ◽  
Trajectory Tracking Control ◽  
Content Type ◽  
Control Approach ◽  
Coupling Dynamic

Purpose The purpose of this paper is to address a fractional order fuzzy PID (FOFPID) control approach for solving the problem of enhancing high precision tracking performance and robustness against to different reference trajectories of a 6-DOF Stewart Platform (SP) in joint space. Design/methodology/approach For the optimal design of the proposed control approach, tuning of the controller parameters including membership functions and input-output scaling factors along with the fractional order rate of error and fractional order integral of control signal is tuned with off-line by using particle swarm optimization (PSO) algorithm. For achieving this off-line optimization in the simulation environment, very accurate dynamic model of SP which has more complicated dynamical characteristics is required. Therefore, the coupling dynamic model of multi-rigid-body system is developed by Lagrange-Euler approach. For completeness, the mathematical model of the actuators is established and integrated with the dynamic model of SP mechanical system to state electromechanical coupling dynamic model. To study the validness of the proposed FOFPID controller, using this accurate dynamic model of the SP, other published control approaches such as the PID control, FOPID control and fuzzy PID control are also optimized with PSO in simulation environment. To compare trajectory tracking performance and effectiveness of the tuned controllers, the real time validation trajectory tracking experiments are conducted using the experimental setup of the SP by applying the optimum parameters of the controllers. The credibility of the results obtained with the controllers tuned in simulation environment is examined using statistical analysis. Findings The experimental results clearly demonstrate that the proposed optimal FOFPID controller can improve the control performance and reduce reference trajectory tracking errors of the SP. Also, the proposed PSO optimized FOFPID control strategy outperforms other control schemes in terms of the different difficulty levels of the given trajectories. Originality/value To the best of the authors’ knowledge, such a motion controller incorporating the fractional order approach to the fuzzy is first time applied in trajectory tracking control of SP.

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