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A Velocity Algorithm for Nonlinear Model Predictive Control
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DOI：10.1109/TCST.2020.2979386.png)
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Abstract
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This brief presents a velocity-form nonlinear model predictive control (NMPC) scheme via velocity-based linearization. The main features of this approach are built-in offset-free control in the presence of disturbances, tracking of piecewise constant, possibly unreachable, reference signals, and simple implementation, as a parameterization of all equilibria is not necessary. Furthermore, the model in velocity form can be expressed as a quasi-linear parameter-varying (quasi-LPV) model, for which efficient online optimization algorithms exist. The proposed approach is experimentally validated on a 2-degree-of-freedom robotic manipulator, where its capabilities and efficiency are highlighted.
Keywords:
Computational modeling
Prediction algorithms
Predictive control
Optimization
Manipulators
Nonlinear systems
Linearization techniques
nonlinear control systems
predictive control
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