A performance analysis method for distributed real-time robotic systems: A case study of remote teleoperation

Robot coordination and control systems for remote teleoperation applications are by necessity implemented on distributed computers. Modeling and performance analysis of these distributed robotic systems is difficult, but important for economic system design. Performance analysis methods originally developed for conventional distributed computer systems are often unsatisfactory for evaluating real-time systems. The paper introduces a formal model of distributed robotic control systems; and a performance analysis method, based on scheduling theory, which can handle concurrent hard-real-time response specifications. Use of the method is illustrated by a case of remote teleoperation which assesses the effect of communication delays and the allocation of robot control functions on control system hardware requirements

Process and tool support for real-time performance analysis of integrated modular systems

This paper describes a real-time system performance analysis methodology and toolset that has been developed at SEIC to be an integral part of a broader BAE Systems Military Air Solutions (MAS) process and toolset for Integrated Modular Systems (IMS). The proposed modelling approach and toolset components provide some key ‘through-life’ real-time system engineering benefits relating to system performance, including : the ability to construct a performance prediction model during the early stages of system design and to independently model the timing behaviour of end-to-end transactions across a distributed system of shared processing and network resources

Fast Real-Time DC State Estimation in Electric Power Systems Using Belief Propagation

We propose a fast real-time state estimator based on the belief propagation algorithm for the power system state estimation. The proposed estimator is easy to distribute and parallelize, thus alleviating computational limitations and allowing for processing measurements in real time. The presented algorithm may run as a continuous process, with each new measurement being seamlessly processed by the distributed state estimator. In contrast to the matrix-based state estimation methods, the belief propagation approach is robust to ill-conditioned scenarios caused by significant differences between measurement variances, thus resulting in a solution that eliminates observability analysis. Using the DC model, we numerically demonstrate the performance of the state estimator in a realistic real-time system model with asynchronous measurements. We note that the extension to the AC state estimation is possible within the same framework.Comment: 6 pages; 7 figures; submitted in the IEEE International Conference on Smart Grid Communications (SmartGridComm 2017

System architecture evaluation using modular performance analysis: a case study

Performance analysis plays an increasingly important role in the design of embedded real-time systems. Time-to-market pressure in this domain is high while the available implementation technology is often pushed to its limit to minimize cost. This requires analysis of performance as early as possible in the life cycle. Simulation-based techniques are often not sufficiently productive. We present an alternative, analytical, approach based on Real-Time Calculus. Modular performance analysis is presented through a case study in which several candidate architectures are evaluated for a distributed in-car radio navigation system. The analysis is efficient due to the high abstraction level of the model, which makes the technique suitable for early design exploratio