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PolyMPC: An efficient and extensible tool for real‐time nonlinear model predictive tracking and path following for fast mechatronic systems
Author(s) -
Listov Petr,
Jones Colin
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.2566
Subject(s) - model predictive control , computer science , workflow , mechatronics , nonlinear system , control engineering , key (lock) , controller (irrigation) , software , control theory (sociology) , pseudospectral optimal control , path (computing) , control (management) , artificial intelligence , engineering , pseudo spectral method , mathematics , fourier analysis , agronomy , mathematical analysis , physics , computer security , quantum mechanics , database , fourier transform , biology , programming language
Summary This paper presents PolyMPC, an open‐source C++ library for pseudospectral‐based real‐time predictive control of nonlinear systems. It provides a necessary background on the computational aspects of the pseudospectral approximation of optimal control problems and explains how various model predictive control and parameter estimation algorithms can be implemented using the software. We discuss the key algorithmic modules and architectural features of the PolyMPC library. The workflow of a path following controller design for a highly nonlinear mechatronic system is demonstrated in a tutorial example. Another example illustrates how the core functionality might be used to approximate and solve a custom optimal control problem.