Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties

• Main Authors: Byung Woo Kim, Bong Seok Park
• Format: Article
• Language: English
• Published: MDPI AG 2016-06-01
• Series: Sensors
• Subjects: unknown control coefficient; Segway; prescribed performance function; Nussbaum gain technique; model uncertainty
• Online Access: http://www.mdpi.com/1424-8220/16/7/1000

The Segway, which is a popular vehicle nowadays, is an uncertain nonlinear system and has an unknown time-varying control coefficient. Thus, we should consider the unknown time-varying control coefficient and model uncertainties to design the controller. Motivated by this observation, we propose a robust control for the Segway with unknown control coefficient and model uncertainties. To deal with the time-varying unknown control coefficient, we employ the Nussbaum gain technique. We introduce an auxiliary variable to solve the underactuated problem. Due to the prescribed performance control technique, the proposed controller does not require the adaptive technique, neural network, and fuzzy logic to compensate the uncertainties. Therefore, it can be simple. From the Lyapunov stability theory, we prove that all signals in the closed-loop system are bounded. Finally, we provide the simulation results to demonstrate the effectiveness of the proposed control scheme.