A singular perturbation based adaptive strategy for bounded controller design in feedback linearizable systems

The saturation of actuators is a critical issue in numerous industrial and robotic applications. The article presents a singular perturbation based adaptive control technique for solving the tracking problem in uncertain feedback linearizable systems. A high gain dynamic controller technique is utilized to enforce time scale separation and facilitating dynamic inversion. The resulting closed loop singularly perturbed system is proved to be partially contracting, and the existence of a unique isolated slow manifold is assured via contraction technique. The parameter adaptation ensures uncertainties compensation and subsequently bounded tracking performance. Further, the technique is extended for multi input multi output systems like mobile robots. The numerical simulations present the usability of the proposed methodology and its effectiveness.

Automated summary

The article introduces an adaptive control technique based on singular perturbation to address the issue of actuator saturation in industrial and robotic applications. By utilizing a high gain dynamic controller to enforce time scale separation, the technique ensures tracking performance and compensates for uncertainties. The methodology is also extended to multi input multi output systems like mobile robots, showing effectiveness through numerical simulations.