Journal article
Auto-tuning of parameters in estimation and adaptive control of robots with weaker PE conditions
IEEE transactions on automatic control, v 42(12), pp 1726-1730
01 Dec 1997
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Knowledge of a system's parameters is necessary for optimum performance of the system. A new class of parameter estimation and adaptive control algorithms was shown in Ahmad (1995), which was applied to the robotic system. These algorithms require relaxed conditions of persistent excitation for parameter convergence. Here we propose an enhancement of these algorithms via improved initialization resulting from sliding surface in parameter error space. As a result, we achieve faster convergence of parameters with proper initialization. Examples giving quantitative results from the robotics systems are provided, and the results are compared with the original algorithms and a classical approach of a gradient-type algorithm. (Author)
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Details
- Title
- Auto-tuning of parameters in estimation and adaptive control of robots with weaker PE conditions
- Creators
- Ziauddin Ahmad - Drexel UniversityAllon Guez
- Publication Details
- IEEE transactions on automatic control, v 42(12), pp 1726-1730
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; Nephrology (and Hypertension)
- Web of Science ID
- WOS:A1997YK06000015
- Scopus ID
- 2-s2.0-0031382033
- Other Identifier
- 991019168622404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Automation & Control Systems
- Engineering, Electrical & Electronic