Adaptive on-line parameter identification of a steer-by-wire system

Adaptive compliance control strategy can be a significant advantage for control of steer-by-wire systems. Initially the method is proposed for robotic applications where the main concern is the interaction forces between the robot and its environment. There are several studies about cooperative working of a robot and a human. As long as the steering system is a part of the vehicle where driver interaction is involved, it is reasonable to think that compliance control strategies can be adapted to steer-by-wire systems. Compliance control is a model reference control (MRC) strategy where the measured external force/torque is used as an input to a reference model to calculate its output and where the real system is controlled appropriately to track the reference system output. If a sensor is available to measure the external force/torque, system parameters need not to be estimated. A constant gain feedback controller can be used in such a case. However, if the parameter variations of the system are not within certain bounds, a model reference adaptive controller (MRAC) is needed. In addition to this, examining the change in the dynamics of the system due to the compliance of the driver arms is not possible by direct MRAC, because the driver effect is considered as a disturbance in this strategy. Therefore, in this study, instead of estimating controller parameters using direct MRAC where the main concern is the tracking performance, it is considered to use indirect MRAC in which the system parameters are estimated to observe their variations in the presence of parametric uncertainty and disturbances and to further examine the change in the dynamics of the system due to the compliance of the driver arms forming a closed kinematic structure by constraining the steering wheel. Hence, a steer-by-wire experimental setup including driver interaction and vehicle directional control units has been developed and three well-known adaptive on-line estimation methods, which are output-error method, equation-error method and modified recursive least squares method are evaluated on the driver interaction unit. These three methods are compared in terms of computational complexity, convergence, stability and applicability to real vehicles.