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Robustly ∞-Stable Implementation of the Adaptive Inverse Control Scheme for Noise Cancelation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Arancibia, Néstor O. Pérez Tsao, Tsu-Chin |
| Copyright Year | 2005 |
| Abstract | This paper addresses the issues relating to the enforcement of robust stability when implementing the Adaptive Inverse Control (AIC) scheme. In this scheme, an adaptive FIR filter is added to a closed-loop system in order to reduce the output error caused by external disturbances, enhancing the performance achieved by linear time-invariant controllers alone. A Small-Gain-Theorem-based sufficient stability condition, which accounts for the feedback interaction between the time-varying adaptive filter and the unmodeled dynamics existing in the closed-loop plant, is derived. This condition suggests that system stability can be imposed by reducing the feasible region where the FIR filter gains can lie. Thus, a constrained convex optimization problem is formulated and solved for the FIR filter form. A relation between this optimization problem and the recursive least-squares (RLS) algorithm is established. Also, a suboptimal solution, which is implementable recursively, is proposed. Finally, to demonstrate their effectiveness, these algorithms are implemented on a laser beam steering experiment. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://folk.ntnu.no/skoge/prost/proceedings/cdc-ecc05/pdffiles/papers/1445.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
