Exponential Stability for Adaptive Control of a Class of First-Order Nonlinear Systems
| Autor: | Daniel E. Miller, Mohamad T. Shahab |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Adaptive control Estimation theory 020208 electrical & electronic engineering Convex set 02 engineering and technology Invariant (physics) Nonlinear system 020901 industrial engineering & automation Exponential stability Control and Systems Engineering Bounded function 0202 electrical engineering electronic engineering information engineering Applied mathematics Dykstra's projection algorithm Mathematics |
| Zdroj: | IFAC-PapersOnLine. 52:168-173 |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2019.12.639 |
| Popis: | In adaptive control it is typically proven that a weak asymptotic form of stability holds; furthermore, at best it is proven that a bounded noise yields a bounded state. Recently, however, it has been proven in a variety of scenarios that it is possible to carry out adaptive control for a linear-time invariant (LTI) discrete-time plant so that the closed-loop system enjoys exponential stability, a bounded gain on the noise, as well as a convolution bound on the effect of the exogenous inputs; the key idea is to carry out parameter estimation by using the ideal projection algorithm in conjunction with restricting the parameter estimates to a convex set. In this paper we extend the approach to a class of first-order nonlinear systems. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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