Adaptive supertwisting controller with reduced set of parameters
Mohammed Taleb, Franck Plestan
Abstract
In this paper, a new adaptive super-twisting algorithm is proposed. The novel adaptive law achieves finite time stability under perturbation with unknown bound, this latter being not required for gains tuning. Unlike many adaptive laws proposed in the literature, the proposed one is based on the definition of only two parameters that strongly reduces the tuning effort: the first parameter is acting on the gain variation velocity whereas the second one is linked to the targeted accuracy. The finite time stability is proved using Lyapunov’s approach. Simulations results are proposed to illustrate the performances of the proposed algorithm.
Topics & Concepts
Control theory (sociology)Perturbation (astronomy)Adaptive controlLyapunov stabilityStability (learning theory)Controller (irrigation)Computer scienceUpper and lower boundsAdaptive systemLyapunov functionSet (abstract data type)MathematicsArtificial intelligenceControl (management)Nonlinear systemPhysicsMathematical analysisBiologyQuantum mechanicsMachine learningAgronomyProgramming languageAdaptive Control of Nonlinear SystemsAdvanced Control Systems DesignChaos control and synchronization