Abstract: Extremum seeking is a form of adaptive control where the steady-state input-output characteristic is optimized, without requiring any explicit knowledge about this input-output characteristic other than that it exists and that it has an extremum. Because extremum seeking is model free, it has proven to be both robust and effective in many different application domains. Equally being model free, there are clear limitations to what can be achieved. Perhaps paradoxically, although being model free, extremum seeking is a gradient based optimization technique. Extremum seeking relies on an appropriate exploration of the process to be optimized to provide the user with an approximate gradient, and hence the means to locate an extremum. ...
This paper presents a practical extension to the classical gradient-based extremum seeking control f...
This thesis focuses on a class of real-time model-free optimization methods, the so-called extremum ...
This dissertation develops a new Extremum Seeking (ES) method, which has a long history as an optimi...
Abstract—We summarize a unifying design approach to continuous-time extremum seeking that was recent...
Abstract — A unifying, prescriptive framework is presented for the design of a family of adaptive ex...
The work in this thesis describes our attempts for theoretical advancements to and the experimental ...
Extremum seeking control tracks a varying maximum or minimum in a performance function such as a cos...
Extremum-seeking (also peak-seeking) controllers are designed to operate at an a priori unknown set-...
The objective of this paper is to present a survey on extremum seeking control methods and their app...
Extremum-seeking control is an adaptive-control methodology that optimizes the steady-state performa...
In many applications, there is a variable that indicates the overall performance and that must be ma...
Abstract—Traditionally, the design of extremum seeking algo-rithm treats the system as essentially a...
Extremum-seeking control is a powerful adaptive technique to optimize steady-state system performanc...
\u3cp\u3eThis paper presents an extension to the classical gradient-based extremum seeking control f...
Abstract: We revisit the extremum seeking scheme whose local stability properties were analyzed in (...
This paper presents a practical extension to the classical gradient-based extremum seeking control f...
This thesis focuses on a class of real-time model-free optimization methods, the so-called extremum ...
This dissertation develops a new Extremum Seeking (ES) method, which has a long history as an optimi...
Abstract—We summarize a unifying design approach to continuous-time extremum seeking that was recent...
Abstract — A unifying, prescriptive framework is presented for the design of a family of adaptive ex...
The work in this thesis describes our attempts for theoretical advancements to and the experimental ...
Extremum seeking control tracks a varying maximum or minimum in a performance function such as a cos...
Extremum-seeking (also peak-seeking) controllers are designed to operate at an a priori unknown set-...
The objective of this paper is to present a survey on extremum seeking control methods and their app...
Extremum-seeking control is an adaptive-control methodology that optimizes the steady-state performa...
In many applications, there is a variable that indicates the overall performance and that must be ma...
Abstract—Traditionally, the design of extremum seeking algo-rithm treats the system as essentially a...
Extremum-seeking control is a powerful adaptive technique to optimize steady-state system performanc...
\u3cp\u3eThis paper presents an extension to the classical gradient-based extremum seeking control f...
Abstract: We revisit the extremum seeking scheme whose local stability properties were analyzed in (...
This paper presents a practical extension to the classical gradient-based extremum seeking control f...
This thesis focuses on a class of real-time model-free optimization methods, the so-called extremum ...
This dissertation develops a new Extremum Seeking (ES) method, which has a long history as an optimi...