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Register a new userVerifying Response Times in Networked Automation Systems Using Jitter Bounds
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Added by
Srinivasan Seshadhri
Publication date
2015
fields
Informatics Engineering
and research's language is
English
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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.
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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.
A MATLAB toolbox is presented, with the goal of checking occurrences of design errors typically found in fixed-point digital systems, considering finite word-length effects. In particular, the present toolbox works as a front-end to a recently introduced verification tool, known as Digital-System Verifier, and checks overflow, limit cycle, quantization, stability, and minimum phase errors, in digital systems represented by transfer-function and state-space equations. It provides a command-line version, with simplified access to specific functions, and a graphical-user interface, which was developed as a MATLAB application. The resulting toolbox is important for the verification community, since it shows the applicability of verification to real-world systems.
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.
In many large systems, such as those encountered in biology or economics, the dynamics are nonlinear and are only known very coarsely. It is often the case, however, that the signs (excitation or inhibition) of individual interactions are known. This paper extends to nonlinear systems the classical criteria of linear sign stability introduced in the 70s, yielding simple sufficient conditions to determine stability using only the sign patterns of the interactions.
This paper investigates the consensus problem of multiple uncertain Lagrangian systems. Due to the discontinuity resulted from the switching topology, achieving consensus in the context of uncertain Lagrangian systems is challenging. We propose a new adaptive controller based on dynamic feedback to resolve this problem and additionally propose a new analysis tool for rigorously demonstrating the stability and convergence of the networked systems. The new introduced analysis tool is referred to as uniform integral-L_p stability, which is motivated for addressing integral-input-output properties of linear time-varying systems. It is then shown that the consensus errors between the systems converge to zero so long as the union of the graphs contains a directed spanning tree. It is also shown that the proposed controller enjoys the robustness with respect to constant communication delays. The performance of the proposed adaptive controllers is shown by numerical simulations.
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