Robust control of a planar snake robot based on interval type-2 Takagi–Sugeno fuzzy control using genetic algorithm

This paper presents trajectory tracking control of a snake robot in the presence of system uncertainty such as disturbances and parameter uncertainties. First, we derive a realistic dynamic model of the snake robot in the framework of the bond graph technique. Next, we present an interval type-2 Takagi–Sugeno fuzzy proportional–derivative (IT2FPD) control scheme, whose parameters are tuned using a genetic algorithm (GA) optimization approach. An improved optimization formulation with randomness is employed for robust near-optimal parameters. Under the assumption that forward velocity of the robot is always positive, we apply the proposed IT2FPD controller to the snake robot model so that the robot can have locomotion along the desired trajectory against uncertainties. To validate the performance of the proposed robot model and control scheme, we conduct in-depth numerical experiments using 20-sim software. Experimental results demonstrate that the snake robot embedded with the IT2FPD controller achieves a straight-line locomotion with the serpenoid gait function despite infiltration of external disturbances and parameter changes.