No abstract

This paper presents a novel approach to reconstruct the output of linear systems in the case where the measured output is uniformly quantized. By fitting the quantized measurements with polynomials in a moving horizon manner, a smooth signal is reconstructed by solving a convex optimization problem with ℓ1‐norm regularization. The quantization feature and the system models are taken into account in the optimization. A numerical example is given to show the excellent reconstruction performance of the proposed method. In addition, the proposed method is implemented in a high‐precision linear stage through DSP, and its effectiveness is verified through experiments using a real positioning system.

No abstract

This paper proposes a new approach to estimate the velocity of mechanical system in the case where the optical incremental encoder is used as the position sensor. First, the actual angular position is reconstructed via moving horizon polynomial fitting method by taking account of quantization feature and the plant dynamics. Then, the reconstruction signal is applied to a classical observer to obtain the velocity estimation. Its robustness against the position sensor resolution and the degree of the polynomial is discussed by some numerical examples. Experiments with very low-resolution encoder in low speed range also confirm its effectiveness.

No abstract