Litcius/Paper detail

Fractional-Order Ultra-Local Model-Based Optimal Model-Free Control for 7-DOF iReHave Upper-Limb Exoskeleton

Dingxin He, Haoping Wang, Yang Tian

2022IEEE Transactions on Circuits & Systems II Express Briefs21 citationsDOI

Abstract

This brief proposes a fractional-order <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ultra-local model</i> -based optimal model-free control (FO-OMFC) for trajectory tracking of 7-DOF iReHave upper-limb exoskeleton. This scheme is composed of fractional-order model-free controller (FO-MFC) and marine predators algorithm (MPA)-based parameter optimizer. Different from the existing model-free control, FO-MFC is designed based on a novel fractional-order <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ultra-local model</i> . Then, the FO-MFC incorporates fractional-order time-delay estimation (FOTDE) as well as fractional-order error convergence controller (FOECC). The referred FOTDE is used to eliminate the lumped disturbance of the controlled exoskeleton. And the FOECC guarantees the convergence of the exoskeleton’s trajectory tracking error. After that, the stability of closed-loop system is demonstrated by using Lyapunov theorem. Moreover, to obtain better control performance, the MPA is employed to search for optimal parameters of the FO-MFC. Finally, the co-simulation of iReHave exoskeleton based on SolidWorks and MATLAB is realized, and the results compared with other controllers and results under measurement noise are given to show the effectiveness and superiority of the proposed strategy.

Topics & Concepts

ExoskeletonController (irrigation)Control theory (sociology)TrajectoryFractional calculusConvergence (economics)Tracking errorComputer scienceMATLABStability (learning theory)MathematicsMathematical optimizationSimulationControl (management)Applied mathematicsArtificial intelligenceAstronomyEconomic growthPhysicsBiologyEconomicsAgronomyMachine learningOperating systemIterative Learning Control SystemsAdaptive Control of Nonlinear Systems