Motor-mechanism dynamic model based neural network optimized computed torque control of a high speed parallel manipulator

Mechatronics ◽  
2007 ◽  
Vol 17 (7) ◽  
pp. 381-390 ◽  
Author(s):  
Zhiyong Yang ◽  
Jiang Wu ◽  
Jiangping Mei
Keyword(s):  
Neural Network ◽  
Dynamic Model ◽  
Parallel Manipulator ◽  
High Speed ◽  
Torque Control ◽  
Model Based ◽  
Computed Torque Control ◽  
Computed Torque

scholarly journals Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

10.5772/5650 ◽  
2008 ◽  
Vol 5 (1) ◽  
pp. 14 ◽  
Author(s):  
Zhiyong Yang ◽  
Jiang Wu ◽  
Jiangping Mei ◽  
Jian Gao ◽  
Tian Huang
Keyword(s):  
Parallel Manipulator ◽  
Torque Control ◽  
Model Based ◽  
Computed Torque Control ◽  
Computed Torque

A New Control Approach to Nonlinear Systems Undergoing Changes in a System Parameter

2000 ◽  
Author(s):  
Hyuk C. Nho ◽  
Peter Meckl
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Sudden Change ◽  
Torque Control ◽  
Tracking Performance ◽  
Control Architecture ◽  
Model Based ◽  
Payload Uncertainty ◽  
Payload Mass ◽  
Computed Torque

Abstract Conventional model-based computed torque control fails to produce good trajectory tracking performance in the presence of payload uncertainty and modeling error. The problem is how to provide accurate dynamics information to the controller. A new control architecture that incorporates a neural network, fuzzy logic and a simple proportional-derivative (PD) controller is proposed to control an articulated robot carrying a variable payload. A feedforward (multilayer) neural network is trained off-line to capture the nonlinear inverse dynamics of the system. The network is placed in the feedforward path to minimize tracking error. The network receives the same input signals as conventional computed torque as well as the payload mass estimate, which comes from a fuzzy logic mass estimator. The fuzzy logic, trained off-line to optimize the membership function, is developed to estimate the changing payload mass. The fuzzy logic estimator is based on joint acceleration error to improve the speed of detection and estimation of payload mass change. The effectiveness of the proposed architecture is demonstrated by experiment on a two-link planar manipulator with changing payload mass. Experiment results show that this control architecture achieves excellent tracking performance in the presence of payload uncertainty. The results of the control architecture are also compared with those of a model-based control architecture. This approach can be employed in any nonlinear mechanical system with a sudden change in a parameter.

scholarly journals Control par calculado para seguimiento de trayectoria aplicado a la dinámica de un robot de 3gdl con propósitos didácticos

2020 ◽  
pp. 1-8
Author(s):  
Juan Carlos Hernández-Durón ◽  
José Luis Ortiz-Simón ◽  
Martha Aguilera-Hernandez ◽  
Daniel Olivares-Caballero
Keyword(s):  
Dynamic Model ◽  
Degrees Of Freedom ◽  
Torque Control ◽  
Work Place ◽  
A Value ◽  
Computed Torque Control ◽  
Christoffel Symbols ◽  
Gravitational Vector ◽  
Three Degrees Of Freedom ◽  
Computed Torque

The article shows the needed procedure to obtain the dynamic model of a robot, with the purpose of being able to follow a planned path using the control law “CTC” Computed Torque Control. The robot was designed in a simple way for didactic reasons, this robot has three degrees of freedom, four links and three joints to move around in the work place. Two out of these joints are rotatory joints meanwhile the third one is a prismatic joint. The dynamic model of the robot is obtained using the Jacobians and Christoffel symbols of the center of mas of each link. Also including the Gravitational vector and the frictions of each joint. The objective of the dynamic model is to be able to simulate the robot in “Simulink” and test different paths using the computed torque control in which the gains of the control will be manipulated until a value that satisfies the desired path is found

A redundant dynamic model of parallel robots for model-based control

Robotica ◽  
2012 ◽  
Vol 31 (2) ◽  
pp. 203-216 ◽  
Author(s):  
Asier Zubizarreta ◽  
Itziar Cabanes ◽  
Marga Marcos ◽  
Charles Pinto
Keyword(s):  
Dynamic Model ◽  
Dynamic Performance ◽  
Dynamic Modelling ◽  
Parallel Robots ◽  
Torque Control ◽  
Computed Torque Control ◽  
Step Procedure ◽  
Exhaustive Study ◽  
Six Degree Of Freedom ◽  
Computed Torque

SUMMARYThe use of extra sensors in parallel robots can provide an increase in control performance, making it possible to fully exploit the potential of these mechanisms. In this paper, a comprehensive redundant dynamic modelling procedure for the six-degree-of-freedom Gough platform is presented. The proposed methodology makes it possible to define the model in terms of all sensorized joint variables in order to implement redundant information-based control, and an example, the Extended Computed Torque Control (Extended CTC) approach, is developed. This, applied to parallel robots, ensures better dynamic performance than the traditional CTC approach. In order to validate dynamic modelling, a two-step procedure is used in this paper. First, the redundant dynamic model is validated by comparing its dynamic performance with the previous research in the field. Second, an exhaustive study is carried out that demonstrates the advantages of the redundant dynamic model when used in the Extended CTC approach.

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