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Constrained discrete model predictive control of an arm‐manipulator using Laguerre function
Author(s) -
Pinheiro Tarcisio Carlos F.,
Silveira Antonio S.
Publication year - 2020
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2667
Subject(s) - model predictive control , laguerre polynomials , control theory (sociology) , weighting , trajectory , controller (irrigation) , linear quadratic regulator , multivariable calculus , computer science , optimal control , function (biology) , quadratic programming , mathematics , mathematical optimization , control engineering , control (management) , engineering , artificial intelligence , medicine , mathematical analysis , physics , astronomy , evolutionary biology , biology , agronomy , radiology
Summary This work presents a multivariable predictive controller applied on a redundant robotic manipulator with three degrees of freedom. The article focuses on the design of a discrete model‐based predictive controller (DMPC) using the Laguerre function as a control effort weighting method to enhance the solution of Hildreth's quadratic programming and to minimize the trade‐off problem in constrained case. The Laguerre functions are used to simplify and enhance the control horizon effect through parsimonious control trajectory, thus reducing the computational load required to find the optimal control solution. Furthermore, these results can be confirmed by simulations and experimental tests on the manipulator and comparing it to the traditional DMPC approach and the discrete linear quadratic regulator.