Adaptive optimization of run-to-run controllers: the EWMA example

This paper presents a recursive scheme for optimizing the gain of an exponentially weighted moving average (EWMA) controller under stability constraints. The objective is to minimize the asymptotic mean square error in the output with minimal a priori information. The algorithm hinges on a simple re...

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Bibliographic Details
Published in:IEEE transactions on semiconductor manufacturing 2000-02, Vol.13 (1), p.97-107
Main Authors: Patel, N.S., Jenkins, S.T.
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive control systems
Algorithms
Application specific integrated circuits
Applied sciences
Asymptotic properties
Automatic control
Controllers
Disturbances
Electronics
Exact sciences and technology
Feedback control
Gain
Microelectronic fabrication (materials and surfaces technology)
Noise measurement
Optimization
Programmable control
Semiconductor device manufacture
Semiconductor device noise
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Semiconductors
Stability
Working environment noise
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Summary:This paper presents a recursive scheme for optimizing the gain of an exponentially weighted moving average (EWMA) controller under stability constraints. The objective is to minimize the asymptotic mean square error in the output with minimal a priori information. The algorithm hinges on a simple representation of the optimal EWMA gain. Both step and drift disturbances are considered. It is shown that the gain sequence generated by the algorithm always yields a stable system. Furthermore, this sequence is shown to converge to a suboptimal value. Extensions to the algorithm to the case where there is model uncertainty are also presented. The algorithm is verified via simulation. Data from a manufacturing implementation are presented.
ISSN:0894-6507
1558-2345
DOI:10.1109/66.827349