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Open AccessJournal ArticleDOI

A comparison of classical and learning controllers

Joseph Sun de la Cruz, +2 more
- 01 Jan 2011 - 
- Vol. 44, Iss: 1, pp 1102-1107
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This article is published in IFAC Proceedings Volumes.The article was published on 2011-01-01 and is currently open access. It has received 4 citations till now. The article focuses on the topics: Open-loop controller & Control theory.

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Citations
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Journal ArticleDOI

Modelling and Control of Robot Manipulators

TL;DR: In this article, the authors tried to read modelling and control of robot manipulators as one of the reading material to finish quickly, and they found that reading book can be a great choice when having no friends and activities.
Proceedings ArticleDOI

Online learning of inverse dynamics via Gaussian Process Regression

TL;DR: The proposed approach for online learning of the inverse dynamics model using Gaussian Process Regression is compared to existing learning and fixed control algorithms and shown to be capable of fast initialization and learning rate.
Journal ArticleDOI

On-line Dynamic Model Learning for Manipulator Control

TL;DR: The proposed approach for online learning of the dynamic model of a robot manipulator is tested on an industrial robot, and shown to outperform independent joint and fixed model-based control.
Proceedings ArticleDOI

Accelerating Model Learning with Inter-Robot Knowledge Transfer

TL;DR: This work proposes a scheme for collecting a sample of correspondences from the robots for training transfer models, and demonstrates the benefit of knowledge transfer in accelerating online learning of the inverse dynamics model between several robots, including between a low-cost Interbotix PhantomX Pincher arm and a more expensive and relatively heavier Kuka youBot arm.
References
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Journal ArticleDOI

Smooth Robust Adaptive Sliding Mode Control of Manipulators With Guaranteed Transient Performance

TL;DR: In this article, a systematic way to combine adaptive control and sliding mode control (SMC) for trajectory tracking of robot manipulators in the presence of parametric uncertainties and uncertain nonlinearities is developed.
Journal ArticleDOI

Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning

TL;DR: This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks, and discusses two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly.
Journal ArticleDOI

Comparative experiments with a new adaptive controller for robot arms

TL;DR: In this paper, a model-based adaptive controller and proof of its global asymptotic stability with respect to the standard rigid-body model of robot-arm dynamics are presented.
Journal ArticleDOI

Learning to Control in Operational Space

TL;DR: The proposed method works in the setting of learning resolved motion rate control on a real, physical Mitsubishi PA-10 medical robotics arm and demonstrates feasibility for complex high degree-of-freedom robots.
Journal ArticleDOI

Categorization of parameters in the dynamic robot model

TL;DR: An algorithm is proposed that categorizes the dynamics parameters of a manipulator into three classes: uniquely identifiable, identifiable in linear combinations only, and unidentifiable, which makes it possible to determine if a chosen trajectory for estimation is persistently exciting.
Related Papers (5)
Frequently Asked Questions (2)
Q1. What have the authors stated for future works in "A comparison of classical and learning controllers" ?

Future studies will involve experimental validation on physical robots as well as incorporating a-priori knowledge of the dynamic model of the system to improve performance of learning methods outside of the trained regions. 

This paper focuses on evaluating Locally Weighted Projection Regression ( LWPR ) as an alternative control method to traditional model-based control schemes.