Model‐based vs data‐driven adaptive control: an overview
M Benosman - International Journal of Adaptive Control and …, 2018 - Wiley Online Library
In this paper, we present an overview of adaptive control by contrasting model‐based
approaches with data‐driven approaches. Indeed, we propose to classify adaptive …
approaches with data‐driven approaches. Indeed, we propose to classify adaptive …
Adaptive feedback control
KJ Astrom - Proceedings of the IEEE, 1987 - ieeexplore.ieee.org
Adaptive control is now finding its way into the marketplace after many years of effort. This
paper reviews some ideas used to design adaptive control systems. It covers early ideas …
paper reviews some ideas used to design adaptive control systems. It covers early ideas …
[BOOK][B] Model free adaptive control
During the past half century, modern control theory has developed greatly and many
branches and subfields have emerged, for example, linear system theory, optimal control …
branches and subfields have emerged, for example, linear system theory, optimal control …
Adaptive optimal control the thinking man's GPC
UC San Diego Page 1 UC San Diego UC San Diego Previously Published Works Title Adaptive
Optimal Control The Thinking Man's GPC Permalink https://escholarship.org/uc/item/01z3w6d7 …
Optimal Control The Thinking Man's GPC Permalink https://escholarship.org/uc/item/01z3w6d7 …
[BOOK][B] Adaptive control: algorithms, analysis and applications
Adaptive Control (second edition) shows how a desired level of system performance can be
maintained automatically and in real time, even when process or disturbance parameters …
maintained automatically and in real time, even when process or disturbance parameters …
Toward self‐driving processes: A deep reinforcement learning approach to control
Advanced model‐based controllers are well established in process industries. However,
such controllers require regular maintenance to maintain acceptable performance. It is a …
such controllers require regular maintenance to maintain acceptable performance. It is a …
Machine learning-based adaptive model identification of systems: Application to a chemical process
Many of the existing offline system identification methods cannot completely comprehend
the dynamics of an evolving complex process without relying on impractically large data …
the dynamics of an evolving complex process without relying on impractically large data …
[BOOK][B] Fundamental process control: Butterworths series in chemical engineering
DM Prett, CE García - 2013 - books.google.com
Fundamental Process Control focuses on the fundamental nature of process control, which
includes an extensive discussion on control methodologies. The first seven chapters are …
includes an extensive discussion on control methodologies. The first seven chapters are …
A machine learning approach to improving dynamic decision making
Decision strategies in dynamic environments do not always succeed in producing desired
outcomes, particularly in complex, ill-structured domains. Information systems often capture …
outcomes, particularly in complex, ill-structured domains. Information systems often capture …
Data-driven control: Overview and perspectives
Process systems are characterized by nonlinearity, uncertainty, large scales, and also the
need of pursuing both safety and economic optimality in operations. As a result they are …
need of pursuing both safety and economic optimality in operations. As a result they are …