Fault Tolerant Control for Polynomial Linear Parameter Varying (LPV) Systems applied to the stabilization of a riderless bicycle

Steering Control and Stability Analysis for an Autonomous Bicycle through Reduced Dynamics with Servo-Constraints

“…The optimal linear preview control theory has been used in dealing with the trajectory-tracked problem of bicycles [27]. Some researchers attributed the balance of bicycles as a linear matrix inequality (LMI) feasibility problem [34,36,37]. Baquero-Surez et al [38] proposed a two-stage observer-based feedback control approach to stabilize the bicycle in its upright position.…”

“…Nevertheless, the linearized Carvallo-Whipple model is established based on the assumptions of small lean and steer angles as well as constant moving speed. Therefore, when extending the linearized Carvallo-Whipple model into the case of bicycles with a varying forward speed [36][37][38], it should be corrected by adding an additional stiffness term [39]. In addition, this model cannot be used to study the stability of bicycles in circular motion since the lean and steer angles in this case are no longer small [40].…”

Gain-scheduled linear quadratic regulator applied to the stabilization of a riderless bicycle

“…24 The control algorithm for trajectory tracking and balancing of an autonomous motorcycle has been developed with a nonlinear controller designed to handle the vehicle balancing 25 and, finally, studies related to the riderless bicycle system from the point of view of fault diagnosis and isolation and fault tolerant control can be found. 26–28 As shown through the research works previously mentioned, it is possible to conclude that the bicycle dynamics and gain-scheduling techniques are considered as an important and interesting research topic in many different areas. Thus, the results presented in this article are related to the stabilization of a riderless bicycle by means of a gain-scheduled linear quadratic regulator (LQR) control with integral action based on a Luenberger observer, aiming at its implementation on an instrumented prototype.…”