A system that needs to interact with the physical world in a timely manner is called a real-time system. When such a system is composed of multiple subsystems, or nodes, each of which is a geographically separate system, such a system of systems is called a distributed real-time system. The computation at each node must adhere to the timing requirements, and the connecting communication channels must never cause delays that trigger further timing violations. In this paper, we introduce Deterministic Network Channels, a network construct using Time Sensitive Networking QoS mechanisms that add reliable and deterministic communication for distributed tasks. Introducing such network channels as a construct allows designers to focus on higher-level primitives when building distributed systems. We describe our reference implementation and evaluate it by extending Timed C with network channels. Building on this, we also perform a thorough performance evaluation to determine practical bounds for both Linux and TSN under heavy workloads and adverse network conditions to show how the proposed reference implementation performs in real-world scenarios. In our tests, we can synchronize two separate machines running commercial off-the-shelf hardware to within 15μs of each other under severe internal and external interference.

This paper investigates and implements a procedure for parameter identification of salient pole synchronous machines that is based on previous knowledge about the equipment and can be used for condition monitoring, online assessment of the electrical power grid, and adaptive control. It uses a Kalman filter to handle noise and correct deviations in measurements caused by uncertainty of instruments or effects not included in the model. Then it applies a recursive least squares algorithm to identify parameters from the synchronous machine model. Despite being affected by saturation effects, the proposed procedure estimates 8 out of 13 parameters from the machine model with minor deviations from data sheet values and is largely insensitive to noise and load conditions.

Two major challenges in securing reliable Optimal Power Flow (OPF) operations are: (i) fluctuations induced due to renewable generators and energy demand, and (ii) interaction and interoperability among the different entities. Addressing these issues requires handling both physical (e.g., power flows) and cyber aspects (computing and communication) of the energy grids, i.e, a cyber-physical systems (CPS) approach is necessitated. First, this investigation proposes a receding horizon control (RHC) based approach for solving OPF to deal with the uncertainties. It uses forecasts on renewable generation and demand and an optimization model solving a predictive control problem to secure energy balance while meeting the network constraints. Second, to handle the interoperability issues, a middleware using common information model (CIM) for exchanging information among applications and the associated profiles are presented. CIM profiles modelling various components and aspects of the RHC based OPF is proposed. In addition, a middleware architecture and services to collect information is discussed. The proposed CPS approach is illustrated in a distribution grid in Steinkjer, Norway having 85 nodes, 700 customers, three hydrogenerators, and various industrial loads. Our results demonstrate the benefits of CPS approach to implement OPF addressing also the interoperability issues.

This paper presents a new method for independent feed control in an automated sewing cell. This is important to match the corners of the parts as well as to compensate for uncertain material characteristics and variations in the length of the parts. In this method, the feed speed for the two parts is controlled independently, based on measurements of the endpoints of the parts while keeping an equal sewing force in both parts. Different strategies for correcting errors are presented and experiments are shown to evaluate the different strategies. Possibilities for using the methods to match reference points during the sewing are discussed.

This paper describes an automated sewing system that focuses on sewing of curved edge segments. The sewing cell includes an industrial sewing machine as well as three industrial robots that handle the parts during the sewing process. Based on experiences from previous work, several improvements are presented that address issues with previous implementations. The main contribution concerning the control system is a model-based generation of the feed-forward velocity for the robot tool movement, based on a geometric description of the parts. This approach increases performance, especially in the case of curved fabric, as well as robustness in case of faulty sensor data. Additionally, this paper describes hardware upgrades that address mechanical challenges that were described in former publications. Finally, the paper presents experiments comparing the model-based control approach with the former control system based on constant feed-forwards velocity and setpoints.

Automated sewing is a complicated task in manufacturing. Due to the non-rigid work pieces and variations in the material characteristics, sensor-based control has to be used to accomplish the sewing operation. This paper presents a strategy for velocity synchronization and corner matching in an automated sewing cell based on two industrial manipulators and a sewing machine. A hybrid force/motion control scheme is adopted using feedback from force/torque sensors for tension control and optical sensors to control the seam position. The strategy is based on switching between force control and displacement control using a leader/follower coordination scheme. This addresses the problem of corner mismatch occurring when two independent force controllers are used for controlling the two robots. Experiments verify that the proposed method gives a satisfactory corner matching, which is crucial for the presented sewing case.

This paper presents a study of the real-time control conditions for a robotic system with visual servo control. The system is based on an industrial manipulator with a modified controller allowing real-time joint-level control. The work is particularly concerned with delays and path deviations. The focus is on the Line-of-Sight based path tracking controller. The paper describes an analysis of the different delays in the sensor-robot system and a model is presented based on the overall delay. Further the stability of the modeled system is analyzed in respect to a specific control case. The correctness of the estimated system delay is indicated by comparison of simulated and experimental results.