Feedback Error Learning control for underactuated acrobat robot with Radial Basis Function based FIR filter

This paper presents a new feedback error learning (FEL) scheme with the application of radial basis function network (RBFN) based finite impulse response (FIR) filter to control underactuated systems. This method provides a stable feedback controller which is systematically derived from sequential backstepping control procedure. Besides, it also formulates a simple approach for FEL feedforward controller structure by employing the inverse dynamic model of the plant with physical parameters. The RBFN based FIR filter is used in obtaining the estimation of the state variables to produce an ideal feedforward control input. Simulation results on a two link acrobat robot with nonzero initial angular momentum in achieving a final desired posture angle are presented to show the validity of the proposed algorithm.