Indirect, Non-Adaptive Control of a Class of Nonlinear Uncertain Systems With Applications to Motion Control of Swimming Robots

Abstract

Motion control of bio-inspired mobile robotic platforms can prove a challenging problem. In particular, models for the considered type of systems may prove nonlinear, uncertain, and fairly complicated. To address these issues, use of an output predictor-based control algorithm was proposed. In particular, the approach relies on the design of a virtual system, constructed to emulate the actual system's input/output behavior. Then, a control law is designed to leverage the dynamic information contained within this predictor The resulting control scheme proves reasonably concise, and effectively circumvents issues related to partial state measurements and system uncertainty. Simulation results for an anguilliform swimming robot illustrate the control scheme's efficacy.