Dinesh Murugan MS Thesis Defense

Title: Advances in Modelling, Control, and Perception for Soft Robotics and Autonomous Vehicle Systems

Location on Campus: Snell Room

Committee Members:
Advisor: Prof. Milad Siami
Prof. Bahram Shafai
Prof. Rozhin Hajian – University of Massachusetts, Lowell

Abstract:
In this research project, we investigate the distributed consensus and vehicle platoons control problem. We first investigate the performance deterioration of commensurate fractional-order consensus networks under exogenous stochastic disturbances. We formulate fractional-order differential equations for the network dynamics using Caputo derivatives and the Laplace transform, and employ the H_2 norm of the dynamical system as a performance measure. By developing a graph-theoretic methodology, we relate the structural specifications of the underlying graphs to the performance measure and explicitly quantify fundamental limits on the best achievable levels of performance in fractional-order consensus networks. We also establish new connections between the sparsity of the network and the performance measure, characterizing fundamental tradeoffs that reveal the interplay between the two. Finally, we provide numerical illustrations to verify our theoretical results, which could help in the design of robust fractional-order control systems in the presence of disturbances.

Additionally, the study examines the real-time application of the theoretical advancements on Quanser’s Qcars, a scaled model vehicle used for academic purposes. The findings are highly relevant to the design and implementation of large-scale consensus networks and autonomous vehicle platoons, as they emphasize the importance of balancing network density and update cycle speed for optimal performance.

To extend the research’s findings to viscoelastic based networks, the interaction between agents is modeled as a fractional-order system.