Active Force Control with Nonlinear Predictive Control based on Receding-Horizon Cost Function Optimization for Five-Link Biped Model in Sagittal Plane

摘要

This paper discusses about the incorporation of Nonlinear Predictive Controller (NPC) with Active Force Control (AFC) that applied to a five-link biped robot model has been investigated and simulated. The NPC control law of the system is based on prediction model which is obtained via Taylor series expansion. From the receding horizon cost function minimization, the optimal control is computed directly. AFC gives an excellent trajectory performance and robust against various types of known/unknown uncertainties and able to cancel the disturbances' effects on the biped system. The five-link bipedal walking model consists an upper body and two legs (thigh and shank in every leg) which constraint within the sagittal plane. The effectiveness of the proposed technique is studied in this case. It is found that this technique gives robust and stable to the control system although it is under disturbances' influence.