Low-frequency learning quantized control for MEMS gyroscopes accounting for full-state constraints

In this paper, a low-frequency learning quantized control scheme for micro-electro-mechanical systems (MEMS) gyroscopes subject to full-state constraints is proposed. In order to cope with asymmetric time-varying constraints imposed on MEMS gyroscope states, a nonlinear state-dependent transformation scheme is introduced via converting the constrained system into an equivalent