1 research outputs found
Stability analysis of the linear discrete teleoperation systems with stochastic sampling and data dropout
This paper addresses the stability conditions of the sampled-data
teleoperation systems consisting continuous time master, slave, operator, and
environment with discrete time controllers over general communication networks.
The output signals of the slave and master robots are quantized with stochastic
sampling periods which are modeled as being from a finite set. By applying an
input delay method, the probabilistic sampling system is converted into a
continuous-time system including stochastic parameters in the system matrices.
The main contribution of this paper is the derivation of the less conservative
stability conditions for linear discrete teleoperation systems taking into
account the challenges such as the stochastic sampling rate, constant time
delay and the possibility of data packet dropout. The numbers of dropouts are
driven by a finite state Markov chain. First, the problem of finding a lower
bound on the maximum sampling period that preserves the stability is
formulated. This problem is constructed as a convex optimization program in
terms of linear matrix inequalities (LMI). Next, Lyapunov Krasovskii based
approaches are applied to propose sufficient conditions for stochastic and
exponential stability of closed-loop sampled-data bilateral teleoperation
system. The proposed criterion notifies the effect of sampling time on the
stability transparency trade-off and imposes bounds on the sampling time,
control gains and the damping of robots. Neglecting this study undermines both
the stability and transparency of teleoperation systems. Numerical simulation
results are used to verify the proposed stability criteria and illustrate the
effectiveness of the sampling architecture