In this short note, the recently popular modifier-adaptation framework for real-time optimization is discussed in tandem with the well-developed trust-region framework of numerical optimization, and it is shown that the basic version of the former is simply a special case of the latter. This relation is then exploited to propose a globally convergent modifier-adaptation algorithm using already developed trust-region theory. Cases when the two are not equivalent are also discussed
Many real-time optimization schemes maximize process performance by performing a model-based optimiz...
In this paper, we propose a new class of adaptive trust region methods for unconstrained optimizatio...
This paper is concerned with a trust region approximation management framework (AMF) for solving the...
In the context of static real-time optimization (RTO) of uncertain plants, the standard modifier-ada...
Abstract. This paper presents an analytically robust, globally convergent approach to managing the u...
In classical trust-region optimization algorithms, the radius of the trust region is reduced, kept c...
This paper investigates a new class of modifier-adaptation schemes to overcome plant-model mismatch ...
Real-Time Optimization (RTO) via modifier adaptation is a class of methods for which measurements ar...
Real-Time Optimization (RTO) via modifier adaptation is a class of methods for which measurements ar...
This paper presents an overview of the recent developments of modifier-adaptation schemes for real-t...
In the context of real-time optimization, modifier-adaptation schemes update the model-based optimiz...
Typical model-based optimization approaches cannot handle plant-model mismatch, therefore the use of...
This paper presents an overview of the recent developments of modifier-adaptationschemes for real-ti...
summary:Trust region methods are a class of effective iterative schemes in numerical optimization. I...
AbstractIn model-based real-time optimization, plant-model mismatch can be handled by applying bias-...
Many real-time optimization schemes maximize process performance by performing a model-based optimiz...
In this paper, we propose a new class of adaptive trust region methods for unconstrained optimizatio...
This paper is concerned with a trust region approximation management framework (AMF) for solving the...
In the context of static real-time optimization (RTO) of uncertain plants, the standard modifier-ada...
Abstract. This paper presents an analytically robust, globally convergent approach to managing the u...
In classical trust-region optimization algorithms, the radius of the trust region is reduced, kept c...
This paper investigates a new class of modifier-adaptation schemes to overcome plant-model mismatch ...
Real-Time Optimization (RTO) via modifier adaptation is a class of methods for which measurements ar...
Real-Time Optimization (RTO) via modifier adaptation is a class of methods for which measurements ar...
This paper presents an overview of the recent developments of modifier-adaptation schemes for real-t...
In the context of real-time optimization, modifier-adaptation schemes update the model-based optimiz...
Typical model-based optimization approaches cannot handle plant-model mismatch, therefore the use of...
This paper presents an overview of the recent developments of modifier-adaptationschemes for real-ti...
summary:Trust region methods are a class of effective iterative schemes in numerical optimization. I...
AbstractIn model-based real-time optimization, plant-model mismatch can be handled by applying bias-...
Many real-time optimization schemes maximize process performance by performing a model-based optimiz...
In this paper, we propose a new class of adaptive trust region methods for unconstrained optimizatio...
This paper is concerned with a trust region approximation management framework (AMF) for solving the...