Design of robust sliding mode controller for nonlinear chaotic gyroscope system with input saturation

The gyroscope system is a highly efficient and nonlinear system widely used in various industries, including military, aerospace, and navigation applications. This paper proposes a robust sliding mode controller to regulate the gyroscope system's chaotic dynamics in the presence of noise, external disturbances, and input saturation. To counteract the negative impact of input saturation, a compensation system utilizing a first-type Chebyshev neural network is implemented. In the proposed design, the weights of the Chebyshev neural network are adjusted to ensure that the derivative of the Lyapunov function remains negative, thereby guaranteeing the stability of the closed-loop gyroscope system. The effectiveness of the proposed control approach is evaluated through comparisons with other control methods across various scenarios, demonstrating its robustness and superior performance.