An Adaptive Observer for Sensorless Control of the Levitated Ball Using Signal Injection
This work addresses the sensorless control problem for magnetic levitation systems, offering a method that does not require knowledge of electrical resistance and guarantees convergence, which is important for practical applications.
The paper presents an adaptive observer for sensorless control of a 1-DOF magnetic levitation system, using signal injection and a new filter based on dynamic regressor extension and mixing. The observer estimates the virtual output and electrical resistance, achieving exponential convergence without excitation assumptions, and is validated through simulations and experiments.
In this paper we address the problem of sensorless control of the 1-DOF magnetic levitation system. Assuming that only the current and the voltage are measurable, we design an adaptive state observer using the technique of signal injection. Our main contribution is to propose a new filter to identify the virtual output generated by the signal injection. It is shown that this filter, designed using the dynamic regressor extension and mixing estimator, outperforms the classical one. Two additional features of the proposed observer are that (i) it does not require the knowledge of the electrical resistance, which is also estimated on-line and (ii) exponential convergence to a tunable residual set is guaranteed without excitation assumptions. The observer is then applied, in a certainty equivalent way, to a full state-feedback control law to obtain the sensorless controller, whose performance is assessed via simulations and experiments.