Abstract
A survey of the recent literature concerning plasma-based processes reveals that direct feedback of plasma parameters for process control is currently being explored related to plasma-cleaning operations. Feedback from plasma monitoring systems such as in situ Langmuir probes would enable more sophisticated control characteristics such as disturbance rejection and adaptive control. Adaptive control schemes rely on predictive control algorithms that require some knowledge of system behavior. The combination of plasma feedback and adaptive control would enable very good disturbance rejection algorithms.
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Abbreviations
- \( {\mathit{\mathsf{M}}}_{\mathit{\mathsf{v}}} \) :
-
Command input to the physical plant
- \( {\mathit{\mathsf{M}}}_{\mathit{\mathsf{d}}} \) :
-
Disturbance model feedback to the MPC
- \( {\mathit{\mathsf{M}}}_0 \) :
-
Physical-plant feedback to the MPC
- LQR:
-
Linear quadratic regulator
- MIMO:
-
Multiple input multiple output
- MPC:
-
Model predictive control
- N4SID:
-
Numerical Subspace State-Space System Identification
- SVD:
-
Singular value decomposition
References
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Van Overschee P, De Moor B. N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems. Automatica. 1992;30:75–93.
Zhang Y, Keville BJ, Holohan A, Daniels S. Experimental implementation of robust multivariable real-time feedback control design for RIE plasma processing. AVS 58th international symposium and exhibition. Nashville: Zhang Y, 3 Nov 2011.
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Danyluk, M., Dhingra, A. (2015). Closing Chapter: Disturbance Rejection. In: Rolling Contact Fatigue in a Vacuum. Springer, Cham. https://doi.org/10.1007/978-3-319-11930-4_9
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DOI: https://doi.org/10.1007/978-3-319-11930-4_9
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