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Published in:
Time-Optimal Path Planning Along Specified Trajectories Read chapter Read first chapter

2013 | OriginalPaper | Chapter

7. Norm-Optimal Iterative Learning Control for a Pneumatic Parallel Robot

Authors : Dominik Schindele, Harald Aschemann

Published in: Multibody System Dynamics, Robotics and Control

Publisher: Springer Vienna

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Abstract

Iterative learning control is a popular method for accurate trajectory tracking of systems that repeat the same motion many times. This paper presents a norm-optimal iterative learning control scheme for a fast two-degree-of-freedom parallel robot driven by two pairs of pneumatic muscle actuators. The robot consists of a light-weight closed-chain structure with four moving links connected by revolute joints. The two base joints are active and driven by pairs of pneumatic muscles by means of toothed belt and pulley. The proposed control has a cascade structure. The internal pressure of each pneumatic muscle is controlled by a fast underlying control loop. Hence, the control design for the outer control loop can be simplified by considering these controlled muscle pressures as ideal control inputs. The angles of the active joints as well as the corresponding angular velocities represent the controlled variables of the outer loop. The implemented ILC algorithm takes advantage of actual state information as well as of data from previous trials. Experimental results from an implementation on a test rig show an excellent control performance.

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previous chapter Passivity-Based Tracking Control of a Flexible Link Robot
next chapter Balance and Posture Control for Biped Robots
Footnotes
1
The super-vectors are marked by the omission of the time argument.
 
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Metadata
Title
Norm-Optimal Iterative Learning Control for a Pneumatic Parallel Robot
Authors
Dominik Schindele
Harald Aschemann
Copyright Year
2013
Publisher
Springer Vienna
Book
Multibody System Dynamics, Robotics and Control

Print ISBN: 978-3-7091-1288-5

Electronic ISBN: 978-3-7091-1289-2

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-7091-1289-2_7

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