A Time Domain Passivity Control Scheme for Bilateral Teleoperation

Abstract

Conventional time domain passivity control inevitably embodies division. Zero division can occur under a tiny force or velocity, which may be inevitable, and will be the cause of control crash. To avoid the zero division problem and control crash, we propose a switching dissipation controller for guaranteed stability. The parametric design of the proposed approach is discussed. The switching time domain passivity control is then applied to teleoperation and safe operation is achieved. Simulation and experimental results are demonstrated to validate the effectiveness of the proposed control scheme.

Review of Control Methods for Upper Limb Telerehabilitation With Robotic Exoskeletons

“…One solution is to reset the PO when the absolute value of the rendered force is less than a specified threshold for a set amount of timemeaning, when the slave robot is not interacting with the environment [95]. Another disadvantage of this method can occur when the velocity or force variables are close to zero or are zero since control failure can occur due to zero division behavior [96]. Consequently, researchers have devised estimations for the conventional TDPC method to overcome these issues.…”

“…Consequently, researchers have devised estimations for the conventional TDPC method to overcome these issues. One example is Sheng et al's [96] switching dissipation controller which guarantees stability.…”

An Improved Composite State Convergence Scheme with Disturbance Compensation for Multilateral Teleoperation Systems

“…The slave robot interacts with the remote environment and sends information back to the master side. Many control approaches have been discussed in the specialized literature to deal with teleoperation systems such as robust H ∞ controller (Gormus et al, 2021;Yan & Salcudean, 1996) adaptive control (Chen et al, 2014), stability analysis via generalized inequalities (Datta et al, 2019), scattering method (Anderson 1989), wave variable approach (Ye & Liu, 2009), passivity control (Sheng et al, 2019), model predictive control (Uddin & Ryu, 2016), state convergence (Azorin et al, 2004) and composite state convergence (Asad et al, 2019). Recent advancements in designing advanced controllers achieve better stability in the presence of parametric uncertainties.…”