No Arabic abstract
Networked automation systems (NAS) are characterized by confluence of control, computation, communication and Information (C3I) technologies. Design decisions of one domain are affected by the constraints posed by others. Reliable NAS design should address the requirements of the system, and simultaneously meet the constraints posed by other domains and this is called co-design in literature. Co-design requires clear definition of interfaces among these domains. Control design in NAS is affected by the timing imperfections posed by other domains. In this investigation, we first study the different sources of timing imperfections in NAS, and classify them based on their occurrence. The concept of jitter is used to define the timing imperfections induced by various system components. Using this analysis, we classify the jitter based on their behavior and domain of occurrence. Our analysis shows that the jitter induced in NAS can be classified based on domain as- hardware, software and communication. Next, we use this analysis to model the jitter from the components of NAS. Modeling timing imperfections helps in capturing the interfaces among the domains, and we use the concept of design contracts to capture the interfaces. Design contracts describe the semantic mapping among the domains and are specified using the jitter margins. Implementing design contracts requires knowledge of the jitter margin and, the results from control theory are used to this extent.
Networked Automation Systems (NAS) have to meet stringent response time during operation. Verifying response time of automation is an important step during design phase before deployment. Timing discrepancies due to hardware, software and communication components of NAS affect the response time. This investigation uses model templates for verifying the response time in NAS. First, jitter bounds model the timing fluctuations of NAS components. These jitter bounds are the inputs to model templates that are formal models of timing fluctuations. The model templates are atomic action patterns composed of three composition operators- sequential, alternative, and parallel and embedded in time wrapper that specifies clock driven activation conditions. Model templates in conjunction with formal model of technical process offer an easier way to verify the response time. The investigation demonstrates the proposed verification method using an industrial steam boiler with typical NAS components in plant floor.
The topic of this paper is to use an intuitive model-based approach to design a networked controller for a recent benchmark scenario. The benchmark problem is to remotely control a two-wheeled inverted pendulum robot via W-LAN communication. The robot has to keep a vertical upright position. Incorporating wireless communication in the control loop introduces multiple uncertainties and affects system performance and stability. The proposed networked control scheme employs model predictive techniques and deliberately extends delays in order to make them constant and deterministic. The performance of the resulting networked control system is evaluated experimentally with a predefined benchmarking experiment and is compared to local control involving no delays.
A major hurdle to the deployment of quantum linear systems algorithms and recent quantum simulation algorithms lies in the difficulty to find inexpensive reversible circuits for arithmetic using existing hand coded methods. Motivated by recent advances in reversible logic synthesis, we synthesize arithmetic circuits using classical design automation flows and tools. The combination of classical and reversible logic synthesis enables the automatic design of large components in reversible logic starting from well-known hardware description languages such as Verilog. As a prototype example for our approach we automatically generate high quality networks for the reciprocal $1/x$, which is necessary for quantum linear systems algorithms.
In this paper, we study networked systems in the presence of Denial-of-Service (DoS) attacks, namely attacks that prevent transmissions over the communication network. Previous studies have shown that co-located architectures (control unit co-located with the actuators and networked sensor channel) can ensure a high level of robustness against DoS. However, co-location requires a wired or dedicated actuator channel, which could not meet flexibility and cost requirements. In this paper we consider a control architecture that approximates co-location while enabling remote implementation (networked sensor and actuator channels). We analyze closed-loop stability and quantify the robustness gap between this architecture and the co-located one.
In this paper, we consider the state controllability of networked systems, where the network topology is directed and weighted and the nodes are higher-dimensional linear time-invariant (LTI) dynamical systems. We investigate how the network topology, the node-system dynamics, the external control inputs, and the inner interactions affect the controllability of a networked system, and show that for a general networked multi-input/multi-output (MIMO) system: 1) the controllability of the overall network is an integrated result of the aforementioned relevant factors, which cannot be decoupled into the controllability of individual node-systems and the properties solely determined by the network topology, quite different from the familiar notion of consensus or formation controllability; 2) if the network topology is uncontrollable by external inputs, then the networked system with identical nodes will be uncontrollable, even if it is structurally controllable; 3) with a controllable network topology, controllability and observability of the nodes together are necessary for the controllability of the networked systems under some mild conditions, but nevertheless they are not sufficient. For a networked system with single-input/single-output (SISO) LTI nodes, we present precise necessary and sufficient conditions for the controllability of a general network topology.