Optimal Disturbance-observer-based Control of Electric Wheelchair Using NSGA-II

Abstract

Electric wheelchairs (EW) experience various terrains surfaces and slopesas well asoccupants with diverse weights. This, in turn, imparts a substantial amount of perturbation to the EWdynamics. In this paper we make use of a two-degree-of-freedom control architecture called disturbance observer (DOB) which reduces sensitivity to model uncertainties while enhancing rejection of disturbances caused due to entering slopes. The feedback loop which is designed via characteristic loci method (CLM) is then augmented with a DOB with a parametrized low-pass filter. According to disturbance rejection, sensitivity reduction, and noise rejection of the whole controller, three performance indices are definedwhich enable us to pick thefilter’s optimal parameters using a multi-objective optimization (MOO) approach callednon-dominated sorting genetic algorithm-II (NSGA-II). Finally, experimental results show desirable improvement in stiffness and disturbance rejection of the proposed controller as well as its robust stability.