Adaptive Artificial Time Delay Control for Robotic Systems

TL;DR

This paper explores an adaptive artificial time delay control method for nonlinear robotic systems, demonstrating its simplicity and robustness in controlling bipedal robots and quadrotors through experimental validation.

Contribution

It introduces a unified control approach using artificial time delay for different robotic systems, simplifying design and enhancing robustness against uncertainties.

Findings

Effective control of bipedal walking robots demonstrated

Quadrotor control validated through experiments

Simplified control design without complex constraint force calculations

Abstract

Artificial time delay controller was conceptualised for nonlinear systems to reduce dependency on precise system modelling unlike the conventional adaptive and robust control strategies. In this approach unknown dynamics is compensated by using input and state measurements collected at immediate past time instant (i.e., artificially delayed). The advantage of this kind of approach lies in its simplicity and ease of implementation. However, the applications of artificial time delay controllers in robotics, which are also robust against unknown state-dependent uncertainty, are still missing at large. This thesis presents the study of this control approach toward two important classes of robotic systems, namely a fully actuated bipedal walking robot and an underactuated quadrotor system. In the first work, we explore the idea of a unified control design instead of multiple controllers for different walking phases in adaptive bipedal walking control while bypassing computing constraint forces, since they often lead to complex designs. The second work focuses on quadrotors employed for applications such as payload delivery, inspection and search-and-rescue. The effectiveness of this controller is validated using experimental results.