Nilay Kant

Adebayo Olayinka Oke, Nilay Kant

This paper develops an impulse-supervised confined exploration framework for learning local optimal controller for a class of nonlinear systems. The proposed approach combines continuous-time approximate dynamic programming (ADP) with an impulsive supervisory layer, where impulsive braking confines the state within a prescribed region in which a local linear approximation of the nonlinear system is valid. This enables desired persistent excitation required for parameter convergence while preventing large state deviations that invalidate local optimality. The resulting hybrid closed-loop system enforces invariance of the exploration region through state-triggered braking inputs. Simulation results on a nonlinear mechanical system demonstrate effectiveness of the proposed approach.

Nilay Kant

This paper presents a state observer design for continuous linear time-invariant (LTI) systems subject to unknown bounded disturbances, that enforces a prescribed bound on the observer residual. The proposed observer augments a continuous-time Luenberger observer with state resets, triggered when the norm of the residual equals a pre-specified bound. The reset map guarantees contraction of the residual at jump instants while preserving the uniform boundedness properties of a standard Luenberger observer. The paper also establishes forward invariance of the residual envelope and non-expansiveness of the estimation error in a Lyapunov metric. Simulation results confirm the analysis. Under bounded disturbances, the residual stays within the prescribed bound. A standard Luenberger observer with the same gains violates this bound.

Ryan Thompson, Ethan Wang, Nilay Kant

A thermomagnetic pendulum is introduced as a coupled thermo-magnetic-mechanical system consisting of a ferromagnetic bob under gravity and an offset permanent magnet. Heating drives the bob temperature above and below the Curie point, causing magnetic attraction to vanish and recover as the bob moves and cools. A multiphysics model is developed in which the magnetic torque depends nonlinearly on the bob temperature field and pendulum configuration. The formulation couples transient three-dimensional heat transfer, a temperature-dependent magnetization law, and pendulum dynamics. Simulations show angular torque asymmetry, rapid force reduction near the Curie point, and sustained oscillations.

Nilay Kant, Ashrut Aryal, Rajiv Ranganathan et al.

This paper explores a novel approach to model strategies for flattening wrinkled cloth learning from humans. A human participant study was conducted where the participants were presented with various wrinkle types and tasked with flattening the cloth using the fewest actions possible. A camera and Aruco marker were used to capture images of the cloth and finger movements, respectively. The human strategies for flattening the cloth were modeled using a supervised regression neural network, where the cloth images served as input and the human actions as output. Before training the neural network, a series of image processing techniques were applied, followed by Principal Component Analysis (PCA) to extract relevant features from each image and reduce the input dimensionality. This reduction decreased the model's complexity and computational cost. The actions predicted by the neural network closely matched the actual human actions on an independent data set, demonstrating the effectiveness of neural networks in modeling human actions for flattening wrinkled cloth.

Aakash Khandelwal, Nilay Kant, Ranjan Mukherjee

The problem of nonprehensile manipulation of a stick in three-dimensional space using intermittent impulsive forces is considered. The objective is to juggle the stick between a sequence of configurations that are rotationally symmetric about the vertical axis. The dynamics of the stick is described by five generalized coordinates and three control inputs. Between two consecutive configurations where impulsive inputs are applied, the dynamics is conveniently represented by a Poincaré map in the reference frame of the juggler. Stabilization of the orbit associated with a desired juggling motion is accomplished by stabilizing a fixed point on the Poincaré map. The Impulse Controlled Poincaré Map approach is used to stabilize the orbit, and numerical simulations are used to demonstrate convergence to the desired juggling motion from an arbitrary initial configuration. In the limiting case, where consecutive rotationally symmetric configurations are chosen arbitrarily close, it is shown that the dynamics reduces to that of steady precession of the stick on a hoop.