Communication time delay has been a major barrier to achieving high performance while maintaining stability in bilateral teleoperation. Building upon the results of our recent work in, a provably stable adaptive controller is proposed for variable delay teleoperation. The controller utilizes a model of the system dynamics and the time delay within a predictive control framework to improve the response transparency. It can also adapt to uncertainties in the user and environment dynamics. The performance objectives are delay-free position tracking between the master and slave and the establishment of a virtual mass-damper tool impedance between the user and environment. Delay reduction is accomplished based on a state observer and estimates of the system parameters. Using the delay reduced dynamics, an adaptive output regulation problem is formulated and solved. A Lyapunov-based analysis of the performance and stability of the resulting system is presented. Simulation results with a single-axis teleoperation setup demonstrate the effectiveness of the proposed approach.

The control of time-delay bilateral teleoperation systems involves a delicate tradeoff between the conflicting requirements of transparency and robust stability. The control design is complicated by latency in data communication between the master and slave sites, as well as uncertainties in the dynamics of operator, master, slave, and environment. This paper proposes a systematic design procedure for improving teleoperation fidelity while maintaining its stability in the presence of dynamic uncertainty and a constant time delay. In a two-step control approach, first local Lyapunov-based adaptive/nonlinear controllers are applied to linearize the system dynamics and eliminate dependency on the master and slave parameters. Teleoperation coordination, subject to parametric uncertainty in the user and environment dynamics, is then achieved by formulating an I/O time-delay$H_{\infty }$robust control synthesis that is solved via its decomposition to the so-calledadobeproblems. The transparency and robust stability properties of the proposed method is examined via numerical analysis. Furthermore, the results are successfully validated in experiments.

Robust stability constraints can largely limit the performance of bilateral teleoperation systems in the presence of communication time delay. In this paper, a stable decentralized model-based controller is proposed that can enhance the teleoperation transparency in the presence of constant delay. New state/observation transformations produce partially delay-free dynamics/measurement vectors. Using the transformed states/observastions, two local linear quadratic Gaussian (LQG) controllers are implemented at the master and slave stations. The closed-loop stability is analyzed employing the delay-dependent frequency sweeping test. Using the LQG controllers and a simple control switching strategy, a multi- model teleoperation controller is developed that can achieve delay-free position tracking and tool impedance shaping for free motion/soft contact, as well as position and force tracking for contact with rigid environments. Experimental results demonstrate the effectiveness of the proposed approach.

Control of time-delay bilateral teleoperation systems requires a delicate balance between the conflicting requirements of transparency and robust stability. This manuscript proposes a systematic design procedure for improving teleoperation fidelity while maintaining its stability in the presence of constant communication delay and dynamic uncertainty. In a two-step control approach, first local Lyapunov-based adaptive/nonlinear controllers linearize the master/slave dynamics. Teleoperation coordination is then achieved by formulating an input/output (I/O) time-delay Hinfinrobust control synthesis which is solved via decomposition to adobe problems. The effectiveness of the proposed approach is demonstrated via numerical analysis and experimental results.

While a conventional bilateral teleoperation system involves only one pair of master/slave robots, cooperative telerobotic systems can consist of multiple pairs of robotic manipulators. Due to dynamic interaction among slave manipulators as well as communication latency, the control of such systems can be particularly challenging. This paper presents a multimodel discrete-time controller for teleoperation in cooperative environments subject to a known constant communication delay. Discrete-time state-space models that explicitly incorporate signal delays are developed for free motion/soft contact and rigid contact phases of teleoperation. Mode-based linear quadratic Gaussian (LQG) controllers are proposed that can deliver a stable transparent response for each phase of operation. Switching among these controllers occur according to the identified phase of contact. The robustness of the controllers with respect to parametric uncertainty is examined via the Nyquist analysis. Simulation results demonstrate the effectiveness of the proposed approach

Prior efforts in bilateral teleoperation under communication delay have mainly yielded control algorithms that sacrifice performance in order to guarantee robust stability. In contrast, this paper proposes a multimodel predictive controller that can enhance the teleoperation transparency in the presence of a known constant delay. Separate controllers are designed for free motion/soft contact and contact with rigid environments, with switching between these mode-based control laws occurring according to the identified contact mode. Performance objectives such as position tracking and tool impedance shaping for free motion/soft contact, as well as position and force tracking for contact with rigid environments, are incorporated into a multi-input/multi-output state-space representation of the system dynamics. New Artstein-type state and measurement transformations are proposed to generate delay-free dynamics suitable for output-feedback control, based on the original dynamics with delays in various input and output channels. The application of the continuous-time linear quadratic Gaussian control synthesis to the resulting mode-based delay-free dynamics yields control laws that guarantee closed-loop stability and enhanced performance in each phase of teleoperation. The robustness of the mode-based controllers with respect to parametric uncertainty is analyzed. Experimental results with a single-axis teleoperation setup demonstrate the effectiveness of the proposed approach

This paper proposes a new adaptive control scheme for bilateral teleoperation in unknown environments. Traditional fixed-gain teleoperation methods often sacrifice performance in order to remain stable in the presence of large variations in the environment dynamics. In contrast, the proposed approach adjusts itself to the changes in the environment to maintain its stability without compromising performance. It is assumed that the dynamics of the environment are governed by a model from a finite set of environment models at any given time with Markov chain switching between these models. The first-order generalized pseudo-Bayesian (GPB1) multi-model estimation technique is used to identify the effective model at each time step given the sensory observations. The control action is a weighted sum of mode-based control laws that are designed for each mode of operation. Numerical and experimental studies demonstrate the effectiveness of the proposed method for teleoperation in free motion and in contact with rigid environments.