PSO-Lyapunov motion/force control of robot arms with model uncertainties

A method for motion/force control of robot arms with model uncertainties is presented. Tracking control of complex trajectories is guaranteed using a Lyapunov approach with high-precision performance ensured using a particle swarm optimization (PSO) algorithm. Tracking performance and robustness are...

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Published inRobotica Vol. 34; no. 3; pp. 634 - 651
Main Authors Mehdi, Haifa, Boubaker, Olfa
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 01.03.2016
Subjects
Algorithms
Limbs
Mathematical models
Robot control
Robots
Swarm intelligence
Trajectories
Uncertainty
Stiffness control
Lyapunov theory
Robot arm
Motion/force control
Constrained motion
Model uncertainties
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Abstract A method for motion/force control of robot arms with model uncertainties is presented. Tracking control of complex trajectories is guaranteed using a Lyapunov approach with high-precision performance ensured using a particle swarm optimization (PSO) algorithm. Tracking performance and robustness are simulated for a robotic device for limb rehabilitation that is designed to be adapted easily to different subjects by considering model parameter uncertainties. Controller parameters are optimized offline using the PSO algorithm with Lyapunov stability conditions considered as inequality constraints. Using the control scheme, the robot can guide limbs on smooth and non-smooth trajectories, under model uncertainties and measurement noise.
AbstractList SUMMARY A method for motion/force control of robot arms with model uncertainties is presented. Tracking control of complex trajectories is guaranteed using a Lyapunov approach with high-precision performance ensured using a particle swarm optimization (PSO) algorithm. Tracking performance and robustness are simulated for a robotic device for limb rehabilitation that is designed to be adapted easily to different subjects by considering model parameter uncertainties. Controller parameters are optimized offline using the PSO algorithm with Lyapunov stability conditions considered as inequality constraints. Using the control scheme, the robot can guide limbs on smooth and non-smooth trajectories, under model uncertainties and measurement noise.
A method for motion/force control of robot arms with model uncertainties is presented. Tracking control of complex trajectories is guaranteed using a Lyapunov approach with high-precision performance ensured using a particle swarm optimization (PSO) algorithm. Tracking performance and robustness are simulated for a robotic device for limb rehabilitation that is designed to be adapted easily to different subjects by considering model parameter uncertainties. Controller parameters are optimized offline using the PSO algorithm with Lyapunov stability conditions considered as inequality constraints. Using the control scheme, the robot can guide limbs on smooth and non-smooth trajectories, under model uncertainties and measurement noise.
Author Mehdi, Haifa
Boubaker, Olfa
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  givenname: Olfa
  surname: Boubaker
  fullname: Boubaker, Olfa
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  organization: National Institute of Applied Sciences and Technology, INSAT, Centre Urbain Nord, BP 676-1080 Tunis Cedex, Tunisia
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Lyapunov theory
Robot arm
Motion/force control
Constrained motion
Model uncertainties
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Snippet A method for motion/force control of robot arms with model uncertainties is presented. Tracking control of complex trajectories is guaranteed using a Lyapunov...
SUMMARY A method for motion/force control of robot arms with model uncertainties is presented. Tracking control of complex trajectories is guaranteed using a...
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SubjectTerms Algorithms
Limbs
Mathematical models
Robot control
Robots
Swarm intelligence
Trajectories
Uncertainty
Title PSO-Lyapunov motion/force control of robot arms with model uncertainties
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