Title
Adaptive neuro fuzzy controller for adaptive compliant robotic gripper
Abstract
The requirement for new flexible adaptive grippers is the ability to detect and recognize objects in their environments. It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult @?@? control using conventional techniques. Here, a novel design of an adaptive neuro fuzzy inference strategy (ANFIS) for controlling input displacement of a new adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize particular shapes of the grasping objects. Since the conventional control strategy is a very challenging task, fuzzy logic based controllers are considered as potential candidates for such an application. Fuzzy based controllers develop a control signal which yields on the firing of the rule base. The selection of the proper rule base depending on the situation can be achieved by using an ANFIS controller, which becomes an integrated method of approach for the control purposes. In the designed ANFIS scheme, neural network techniques are used to select a proper rule base, which is achieved using the back propagation algorithm. The simulation results presented in this paper show the effectiveness of the developed method.
Year
DOI
Venue
2012
10.1016/j.eswa.2012.05.072
Expert Syst. Appl.
Keywords
Field
DocType
control signal,robot gripper,proper rule base,control purpose,adaptive compliant robotic gripper,control system,anfis controller,conventional control strategy,embedded sensor,adaptive neuro fuzzy controller,new adaptive compliant gripper,input displacement,fuzzy logic
Neuro-fuzzy,Nonlinear system,Control theory,Computer science,Fuzzy logic,Adaptive neuro fuzzy inference system,Control system,Artificial neural network,Robot,Grippers
Journal
Volume
Issue
ISSN
39
18
0957-4174
Citations 
PageRank 
References 
24
1.05
10
Authors
5
Name
Order
Citations
PageRank
Dalibor Petkovic122320.91
Mirna Issa2533.65
Nenad D. Pavlović3653.77
Lena Zentner4534.33
Arko OjbašIć5492.57