Due to the special working environment of teleoperation, there are usually uncertainties existing in the dynamics of teleoperating robots. In this paper, an adaptive bilateral control scheme is proposed for the nonlinear teleoperation with parameterized dynamic uncertainties and time delays. Compared to the existing time-delay adaptive bilateral controllers, the proposed scheme has the advantage of faster and more accurate parameter adaptation. In this way, the transient performance of teleoperators can be improved without increasing the control gains, which is helpful for stability of teleoperation. The adaptive bilateral controller is designed to be applicable both in free motion and in constrained motion. The synchronization errors in the unconstrained subspace are asymptotically convergent under time delays. In the constrained subspace, the contact force remains bounded with the proposed controller. The stability of teleoperation is proved using Lyapunov methods and the passivity theory. Simulation results demonstrate the effectiveness of the proposed method.

In this paper we consider the problem of scheduling, on a two-machine flowshop, a set ofunit-time operations subject to time delays with respect to the makespan. This problem isknown to be \hbox{${\cal NP}$}𝒩𝒫-hard in the strong sense. We propose an algorithm basedon a branch and bound enumeration scheme. This algorithm includes the implementation ofnew lower and upper bound procedures, and dominance rules. A computer simulation tomeasure the performance of the algorithm is provided for a wide range of testproblems.

A necessary consequence of the nature of neural transmission systems is that as change in the physical state of a time-varying event takes place, delays produce error between the instantaneous registered state and the external state. Another source of delay is the transmission of internal motor commands to muscles and the inertia of the musculoskeletal system. How does the central nervous system compensate for these pervasive delays? Although it has been argued that delay compensation occurs late in the motor planning stages, even the earliest visual processes, such as phototransduction, contribute significantly to delays. I argue that compensation is not an exclusive property of the motor system, but rather, is a pervasive feature of the central nervous system (CNS) organization. Although the motor planning system may contain a highly flexible compensation mechanism, accounting not just for delays but also variability in delays (e.g., those resulting from variations in luminance contrast, internal body temperature, muscle fatigue, etc.), visual mechanisms also contribute to compensation. Previous suggestions of this notion of “visual prediction” led to a lively debate producing re-examination of previous arguments, new analyses, and review of the experiments presented here. Understanding visual prediction will inform our theories of sensory processes and visual perception, and will impact our notion of visual awareness.

The paper extends earlier results by demonstrating that there is an optimal range of values for the period for amortizing valuation surpluses or deficiencies, in the case when there is a one year time delay between fixing a contribution rate and the accounting information about current fund levels. The optimal range is compared for the cases where there is no time delay and there is a one year time delay.