Constrained nonlinear MPC using hammerstein and wiener models: PLS framework

Methods of implementing an input‐constrained, nonlinear, model‐predictive controller in latent spaces using partial‐least‐squares (PLS)‐based Hammerstein and Wiener models are discussed. For multiple‐input, multiple‐output (MIMO) systems, the PLS flamework presents a viable alternative for identific...

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Published in:AIChE journal 1998-07, Vol.44 (7), p.1611-1622
Main Authors: Patwardhan, Rohit S., Lakshminarayanan, S., Shah, Sirish L.
Format: Article
Language:English
Subjects:
Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization
Applied sciences
Chemical engineering
Exact sciences and technology
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cited_by cdi_FETCH-LOGICAL-c3773-f800941933a52e55acde50c02b6f6ce4c04cb5fa98ba51497c0d87dd2a049eeb3
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description Methods of implementing an input‐constrained, nonlinear, model‐predictive controller in latent spaces using partial‐least‐squares (PLS)‐based Hammerstein and Wiener models are discussed. For multiple‐input, multiple‐output (MIMO) systems, the PLS flamework presents a viable alternative for identification and controller synthesis using Hammerstein and Wiener structures. The constraint mappings, which have to be taken into account during controller design in the PLS flamework, are highlighted. PLS‐based Wiener models are well suited for constrained control of nonlinear systems. The use of PLS‐based Hammerstein models for control involves solution of a nonlinear program as a result of the constraint mapping. The proposed approach is demonstrated on a simulated pH‐level control of an acid base neutralization process.
doi_str_mv 10.1002/aic.690440713
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subjects Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization
Applied sciences
Chemical engineering
Exact sciences and technology
title Constrained nonlinear MPC using hammerstein and wiener models: PLS framework
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