Neural observer-based quantized output feedback control for MEMS gyroscopes with guaranteed transient performance

摘要

In this paper, a neural observer-based quantized output feedback control with guaranteed transient performance is developed for MEMS gyroscopes. Firstly, to generate piece-wise quantized control signals that can be performed in the digital control system, a hysteresis quantizer (HQ) is employed, meanwhile the undesirable chattering phenomena occurring universally in the traditional non-hysteresis quantizers can be also discarded. Subsequently, to provide prescribed specifications on the transient and steady-state behaviors of output tracking errors, asymmetric preselected boundaries and error transformation functions are constructed to convert the original constrained dynamics into an unconstrained one, such that the predetermined transient and steady-state performance can be achieved. Furthermore, with the aid of presented minimal learning parameter-based neural observer (MLP-NO), not only the unknown disturbances can be online identified, but also the notorious difficulties, known as the excessive occupation of the limited computational resource as well as the restriction of immeasurable velocity states, can be simultaneously circumvented. Also, the stability of resulting control law is analyzed via Lyapunov function and non-smooth analysis technique. The simulation results and comparisons validate the effectiveness of the proposed scheme. (C) 2020 Elsevier Masson SAS. All rights reserved.