Fault tolerant control in an unmanned bicycle robot via sliding mode theory

Abstract

Abstract In this work, a new active fault tolerant control (FTC) is developed for an unmanned bicycle robot based on an integration between a sliding mode control (SMC), fault detection (FD), and fault estimation (FE) via a residual signal. A sliding surface in accordance with the fault tolerant sliding mode control (FTSMC) is designed for the bicycle robot to get multiple exciting features such as fast transient response with finite time convergence, small overshoot and quick stabilisation in the presence of an actuator fault. To obtain an effective performance for the FTSMC, a fault estimation system is employed and in order to attain estimation, an extended Kalman filter (EKF) as an estimator and a change detection algorithm called cumulative sum (CUSUM) as a residual evaluation function are developed. The innovative features of the proposed approach, that is FTSMC, are verified when compared with the other up‐to‐date control techniques like fault tolerant model‐based predictive control with feedback linearisation (FTMPC + FBL) and fault tolerant linear quadratic regulator with feedback linearisation (FTLQR + FBL) on an unmanned bicycle robot.

Keywords

• cumulative sum
• extended Kalman filter
• fault tolerant control
• feedback linearisation
• sliding mode control
• unmanned bicycle robot