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PolyMPC: An efficient and extensible tool for real‐time nonlinear model predictive tracking and path following for fast mechatronic systems

Petr Listov, Colin N. Jones

2020Optimal Control Applications and Methods18 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Model predictive controlComputer scienceWorkflowMechatronicsNonlinear systemControl engineeringKey (lock)Controller (irrigation)SoftwareControl theory (sociology)Pseudospectral optimal controlPath (computing)Control (management)Artificial intelligenceEngineeringPseudo-spectral methodMathematicsMathematical analysisPhysicsBiologyAgronomyQuantum mechanicsProgramming languageFourier transformFourier analysisComputer securityDatabaseAdvanced Control Systems OptimizationAdaptive Control of Nonlinear SystemsStability and Control of Uncertain Systems
PolyMPC: An efficient and extensible tool for real‐time nonlinear model predictive tracking and path following for fast mechatronic systems | Litcius