Novel Strategy of Adaptive Predictive Control Based on a MIMO-ARX Model

Many industrial processes include MIMO (multiple-input, multiple-output) systems that are difficult to control by standard commercial controllers. This paper describes a MIMO case of a class of SISO-APC (single-input, single-output adaptive predictive controller) based upon an ARX (autoregressive wi...

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Bibliographic Details
Published in:Actuators 2022-01, Vol.11 (1), p.21
Main Authors: Piñón, Alejandro, Favela-Contreras, Antonio, Beltran-Carbajal, Francisco, Lozoya, Camilo, Dieck-Assad, Graciano
Format: Article
Language:English
Subjects:
Adaptation
Adaptive control
adaptive predictive control
Algorithms
ARX
Autoregressive models
Controllers
Embedded systems
Industrial applications
Mathematical models
MIMO (control systems)
MIMO systems control
Performance indices
Performance prediction
Predictive control
Process controls
SISO (control systems)
time-variant systems control
Variables
Water levels
Water tanks
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Summary:Many industrial processes include MIMO (multiple-input, multiple-output) systems that are difficult to control by standard commercial controllers. This paper describes a MIMO case of a class of SISO-APC (single-input, single-output adaptive predictive controller) based upon an ARX (autoregressive with exogenous variable) model. This class of SISO-APC based on ARX models has been successfully and extensively used in many industrial applications. This approach aims to minimize the barriers between the theory of predictive adaptive control and its application in the industrial environment. The proposed MIMO-APC (MIMO adaptive predictive controller) performance is validated with two simulated processes: a quadrotor drone and the quadruple tank process. In the first experiment the proposed MIMO APC shows ISE-IAE-ITAE performance indices improvements of up to 25%, 25.4% and 38.9%, respectively. For the quadruple tank process the water levels in the lower tanks follow closely the set points, with the exception of a 13% overshoot in tank 1 for the minimum phase behavior response. The controller responses show significant performance improvements when compared with previously published MIMO control strategies.
ISSN:2076-0825
2076-0825
DOI:10.3390/act11010021