Daniela Constantinescu

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2papers

2 Papers

SYMar 21, 2018
Globally Stable Output Feedback Synchronization of Teleoperation with Time-Varying Delays

Yuan Yang, Daniela Constantinescu, Yang Shi

This paper presents a globally stable teleoperation control strategy for systems with time-varying delays that eliminates the need for velocity measurements through novel augmented Immersion and Invariance velocity observers. The new observers simplify a recent constructive Immersion and Invariance velocity observer to achieve globally convergent velocity estimation with only $n+2$ states, where $n$ is the number of degrees of freedom of the master and slave robots. They introduce dynamic scaling factors to accelerate the speed of convergence of the velocity estimates and, thus, to limit the energy generated by the velocity estimation errors and to guarantee sufficient estimate-based damping injection to dissipate the energy generated by the time-varying delays. The paper shows that Proportional plus damping control with the simplified and augmented Immersion and Invariance-based velocity observers can synchronize the free master and slave motions in the presence of time-varying delays without using velocity measurements. Numerical results illustrate the estimation performance of the new observers and the stability of a simulated two degrees-of-freedom nonlinear teleoperation system with time-varying delays under the proposed output feedback Proportional plus damping control.

SYSep 11, 2025
Off Policy Lyapunov Stability in Reinforcement Learning

Sarvan Gill, Daniela Constantinescu

Traditional reinforcement learning lacks the ability to provide stability guarantees. More recent algorithms learn Lyapunov functions alongside the control policies to ensure stable learning. However, the current self-learned Lyapunov functions are sample inefficient due to their on-policy nature. This paper introduces a method for learning Lyapunov functions off-policy and incorporates the proposed off-policy Lyapunov function into the Soft Actor Critic and Proximal Policy Optimization algorithms to provide them with a data efficient stability certificate. Simulations of an inverted pendulum and a quadrotor illustrate the improved performance of the two algorithms when endowed with the proposed off-policy Lyapunov function.