Control system of trajectory tracking of discretely-actuated manipulator based on computed torque method

Hydraulic thrust system is a critical part of shield tunneling machine. Automatic trajectory tracking control is a significant task of thrust system during tunnel excavation. In this article, plane mechanical structure diagram of the thrust system and path planning method are illustrated at first. An integrated control system is proposed to achieve the automatic control of the thrust trajectory. The control system consists of one trajectory planning controller for both cylinders and an individual cylinder controller for each of hydraulic cylinders. Trajectory planning controller is used to generate respective displacement signals of double-cylinder in every thrust stroke and each of cylinder controllers is used to realize the precise control of the given thrust trajectory. Variable-gain PID control strategy applied to achieve the precise tracking control of thrust trajectory under several typical working conditions are done at last. The experimental results demonstrate that variable-gain PID control have good performances with short response time and small overshoot regardless of changes of working conditions.

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Control system design for UAV trajectory tracking

10.1117/12.718010 ◽

2006 ◽

Author(s):

Haitao Wang ◽

Jinyuan Gao

Keyword(s):

Control System ◽

System Design ◽

Trajectory Tracking ◽

Control System Design

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USV trajectory tracking control system based on ADRC

2017 Chinese Automation Congress (CAC) ◽

10.1109/cac.2017.8244141 ◽

2017 ◽

Author(s):

Wang Changshun ◽

Zhang Huang ◽

You Yu

Keyword(s):

Control System ◽

Trajectory Tracking ◽

Tracking Control ◽

Trajectory Tracking Control

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Computed Torque Control of a Caterpillar Robot Manipulator Using Neural Network

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.15.106 ◽

2016 ◽

Vol 15 ◽

pp. 106-118 ◽

Cited By ~ 5

Author(s):

Mehran Rahmani ◽

Ahmad Ghanbari

Keyword(s):

Neural Network ◽

Trajectory Tracking ◽

Control Method ◽

Robot Manipulator ◽

Setting Time ◽

Torque Control ◽

Learning Ability ◽

Control Effort ◽

Better Than ◽

Computed Torque

This paper presents a neural computed torque controller, which employs to a Caterpillar robot manipulator. A description to exert a control method application neural network for nonlinear PD computed torque controller to a two sub-mechanisms Caterpillar robot manipulator. A nonlinear PD computed torque controller is obtained via utilizing a popular computed torque controller and using neural networks. The proposed controller has some advantages such as low control effort, high trajectory tracking and learning ability. The joint angles of two sub-mechanisms have been obtained by using the numerical simulations. The discovered figures show that the performance of the neural computed torque controller is better than a conventional computed torque controller in trajectory tracking and reduction of setting time. Finally, snapshots of gain sequences are demonstrated.

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Non-Autonomous Wheeled Mobile Robot Trajectory Tracking Control Based on the Navigation via WSN

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.457-458.1089 ◽

2012 ◽

Vol 457-458 ◽

pp. 1089-1095

Author(s):

Da Yong Lu ◽

Zhen Hua Luo ◽

Jian Lu Tian

Keyword(s):

Control System ◽

Trajectory Tracking ◽

Tracking Control ◽

Base Station ◽

Reference Trajectory ◽

Distributed Network ◽

Feedback Channel ◽

Wheeled Mobile Robots ◽

Trajectory Tracking Control ◽

Robot Trajectory

Trajectory tracking control is a major control problem in the application of the wheeled mobile robots (WMRs). However, many of the WMRs are autonomous which are equipped with several kinds of sensor to detect the position and orientation by itself, such as ultrasonic, laser, infrared and visual. This paper studies the implementation for a distributed network feedback control system and the trajectory tracking control algorithm for a non-autonomous WMR. The control system consists of a wireless sensor network (WSN) and a monitoring base station for measurement and feedback, and a non-autonomous WMR as controlled plant. To cope with the distributed and asynchronous measurements and slow response of the feedback channel, the sectional error amplitude limited algorithm is studied and the results show the system can effectively track a reference trajectory.

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