David Quinn Mayne. 23 April 1930—27 May 2024

David Mayne was a pioneer and innovator who made numerous seminal contributions to systems and control science. His research work has had a lasting impact on the development of control theory and has inspired generations of researchers. He was also an exceptional leader and the founder of the world-renowned Control Group at Imperial College London. His research interests were centred on optimization and optimization-based design, control of constrained systems, filtering, adaptive control, and model predictive control (MPC). David pioneered the development of differential dynamic programming—a strong version of dynamic programming—laid the foundations for what is nowadays known as particle filtering, and contributed to the unification of model reference and estimation-based adaptive control. His major achievement was the development of a rigorous theory for MPC accompanied by performance guarantees. This made MPC the method of choice for several industrial applications: it is currently employed in tens of thousands of applications and is a core part of the advanced control technology used by hundreds of process control producers.

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Publication Details

Journal
Biographical Memoirs of Fellows of the Royal Society
Published
2025-06-02
DOI
https://doi.org/10.1098/rsbm.2024.0042
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
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article

David Quinn Mayne. 23 April 1930—27 May 2024

Alessandro Astolfi
Biographical Memoirs of Fellows of the Royal Society
Advanced Control Systems Optimization
article

David Quinn Mayne. 23 April 1930—27 May 2024

Alessandro Astolfi
article en

Abstract

David Mayne was a pioneer and innovator who made numerous seminal contributions to systems and control science. His research work has had a lasting impact on the development of control theory and has inspired generations of researchers. He was also an exceptional leader and the founder of the world-renowned Control Group at Imperial College London. His research interests were centred on optimization and optimization-based design, control of constrained systems, filtering, adaptive control, and model predictive control (MPC). David pioneered the development of differential dynamic programming—a strong version of dynamic programming—laid the foundations for what is nowadays known as particle filtering, and contributed to the unification of model reference and estimation-based adaptive control. His major achievement was the development of a rigorous theory for MPC accompanied by performance guarantees. This made MPC the method of choice for several industrial applications: it is currently employed in tens of thousands of applications and is a core part of the advanced control technology used by hundreds of process control producers.

Biographical Memoirs of Fellows of the Royal SocietyVol. 78
Imperial College London (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 87%
Advanced Control Systems Optimization
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