Pareto design of sliding-mode tracking control of a biped robot with aid of an innovative particle swarm optimization

Lately, many researchers have focused on the walking of biped robots in the sagittal plane. In one hand, biped robots require the capability to step merely laterally, in confronting the obstacles such as a wall. On the other hand, the dynamic equations of biped robots in the lateral plane are extremely nonlinear and heavy to control. Therefore, this paper presents a nonlinear sliding-mode tracking control for the biped robots that step purely in the lateral plane on slope. Both single support phase and double support phase have been negotiated to take the Zero Moment Point (ZMP) on inside of the support polygon. When the sliding-mode control is utilized to track the desired trajectories of the joints, there has to be a trade-off between tracking errors and control effort. Hence, an innovative particle swarm optimization algorithm is used to obtain the Pareto front of these non-commensurable objective functions to determine the sliding-mode parameters. The result dramatizes the superiority of innovative particle swarm optimization in terms of designing the control parameters.