Adaptive backstepping control design for MEMS gyroscope based on function approximation techniques with input saturation and output constraints

Abstract

An efficient adaptive backstepping control method is presented in the current study for controlling the micro-electro-mechanical system (MEMS) triaxial gyroscope. In this approach, practical considerations, including output constraints and input saturation, are taken into account. A Barrier Lyapunov Function (BLF) is used so that non-transgression of the constraints is ensured. In the suggested control method, for approximating the lumped uncertainties and addressing the problem of explosion of complexity, Hermite polynomials are used as a simple but effective function approximation approach as a universal approximator. Therefore, the resulting control approach is much simpler with minimal learning parameters. The Lyapunov stability theory is used so that the semiglobally uniformly ultimately boundedness of the closed-loop signals with proper tracking error convergence is guaranteed. According to the results of the comparative simulation, the superiority of this approach is confirmed.