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Robust Tracking as Constrained Optimization by Uncertain Dynamic Plant: Mirror Descent Method and ASG—Version of Integral Sliding Mode Control

Alexander Nazin (), Hussain Alazki and Alexander Poznyak
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Alexander Nazin: V. A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow 117997, Russia
Hussain Alazki: Facultad de Ingeniería, Universidad Autónoma del Carmen (UNACAR), Playa del Carmen 24180, Mexico
Alexander Poznyak: Automatic Control Department, Centro de Investigacion y Estudios Avanzados del Instituto Politecnico Nacional, Ciudad de Mexico 07360, Mexico

Mathematics, 2023, vol. 11, issue 19, 1-15

Abstract: A class of controlled objects is considered, the dynamics of which are determined by a vector system of ordinary differential equations with a partially known right-hand side. It is presumed that the state variables and their velocities can be measured. Designing a robust tracking controller under some constraints to admissible state variables is the research goal. This construction, which extends the results for the average subgradient technique (ASG), and is an update of the subgradient descent technique (SDM) and integral sliding mode (ISM) approach, is realized by using the Legendre–Fenchel transform. A two-link robot manipulator with three revolute joints, powered by individual PMDC motors, is presented as an illustrative example of the suggested approach implementation.

Keywords: robust control; trajectory tracking; convex constrained optimization; subgradient descent method; sliding mode; robot manipulator (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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