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Indirect, Non-Adaptive Control of a Class of Nonlinear Uncertain Systems With Applications to Motion Control of Swimming Robots

[+] Author Affiliations
Yannick Morel, Auke J. Ijspeert

Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

Alexander Leonessa

Virginia Tech, Blacksburg, VA

Paper No. DSCC2012-MOVIC2012-8655, pp. 179-186; 8 pages
  • ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
  • Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems
  • Fort Lauderdale, Florida, USA, October 17–19, 2012
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4530-1
  • Copyright © 2012 by ASME


Motion control of bio-inspired mobile robotic platforms can prove a challenging problem. In particular, models for the considered type of systems may prove nonlinear, uncertain, and fairly complicated. To address these issues, use of an output predictor-based control algorithm was proposed. In particular, the approach relies on the design of a virtual system, constructed to emulate the actual system’s input/output behavior. Then, a control law is designed to leverage the dynamic information contained within this predictor. The resulting control scheme proves reasonably concise, and effectively circumvents issues related to partial state measurements and system uncertainty. Simulation results for an anguilliform swimming robot illustrate the control scheme’s efficacy.

Copyright © 2012 by ASME



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