학술논문

Data-based Robust MPC with Componentwise Hölder Kinky Inference
Document Type
Conference
Source
2019 IEEE 58th Conference on Decision and Control (CDC) Decision and Control (CDC), 2019 IEEE 58th Conference on. :6449-6454 Dec, 2019
Subject
Aerospace
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Predictive models
Robustness
Data models
Estimation
Interpolation
Noise measurement
Language
ISSN
2576-2370
Abstract
The authors have recently developed predictive controllers based on prediction models derived from experimental data, by means of a class of Hölder interpolation called kinky inference. This paper provides a step forward by proposing a novel estimation method based on componentwise Hölder interpolation. This allows to explicitly consider the contribution of each component on each output, yielding better estimations. Following the procedure used in previous works, this estimation method is used to provide a predictor for a nonlinear robust data-based predictive controller, whose performance and robustness is enhanced by the new setting. The properties of the proposed controller are demonstrated in a case study.