3,525 research outputs found
Robust stability conditions for remote SISO DMC controller in networked control systems
A two level hierarchy is employed in the design of Networked Control Systems (NCSs) with bounded
random transmission delay. At the lower level a local controller is designed to stabilize the plant. At the higher
level a remote controller with the Dynamic Matrix Control (DMC) algorithm is implemented to regulate the
desirable set-point for the local controller. The conventional DMC algorithm is not applicable due to the
unknown transmission delay in NCSs. To meet the requirements of a networked environment, a new remote
DMC controller is proposed in this study. Two methods, maximum delayed output feedback and multi-rate
sampling, are used to cope with the delayed feedback sensory data. Under the assumption that the closed-loop
local system is described by one FIR model of an FIR model family, the robust stability problem of the
remote DMC controller is investigated. Applying Jury's dominant coefficient lemma and some stability results
of switching discrete-time systems with multiple delays; several stability criteria are obtained in the form of
simple inequalities. Finally, some numerical simulations are given to demonstrate the theoretical results
Average Consensus in the Presence of Delays and Dynamically Changing Directed Graph Topologies
Classical approaches for asymptotic convergence to the global average in a
distributed fashion typically assume timely and reliable exchange of
information between neighboring components of a given multi-component system.
These assumptions are not necessarily valid in practical settings due to
varying delays that might affect transmissions at different times, as well as
possible changes in the underlying interconnection topology (e.g., due to
component mobility). In this work, we propose protocols to overcome these
limitations. We first consider a fixed interconnection topology (captured by a
- possibly directed - graph) and propose a discrete-time protocol that can
reach asymptotic average consensus in a distributed fashion, despite the
presence of arbitrary (but bounded) delays in the communication links. The
protocol requires that each component has knowledge of the number of its
outgoing links (i.e., the number of components to which it sends information).
We subsequently extend the protocol to also handle changes in the underlying
interconnection topology and describe a variety of rather loose conditions
under which the modified protocol allows the components to reach asymptotic
average consensus. The proposed algorithms are illustrated via examples.Comment: 37 page
Information fusion architectures for security and resource management in cyber physical systems
Data acquisition through sensors is very crucial in determining the operability of the observed physical entity. Cyber Physical Systems (CPSs) are an example of distributed systems where sensors embedded into the physical system are used in sensing and data acquisition. CPSs are a collaboration between the physical and the computational cyber components. The control decisions sent back to the actuators on the physical components from the computational cyber components closes the feedback loop of the CPS. Since, this feedback is solely based on the data collected through the embedded sensors, information acquisition from the data plays an extremely vital role in determining the operational stability of the CPS. Data collection process may be hindered by disturbances such as system faults, noise and security attacks. Hence, simple data acquisition techniques will not suffice as accurate system representation cannot be obtained. Therefore, more powerful methods of inferring information from collected data such as Information Fusion have to be used.
Information fusion is analogous to the cognitive process used by humans to integrate data continuously from their senses to make inferences about their environment. Data from the sensors is combined using techniques drawn from several disciplines such as Adaptive Filtering, Machine Learning and Pattern Recognition. Decisions made from such combination of data form the crux of information fusion and differentiates it from a flat structured data aggregation. In this dissertation, multi-layered information fusion models are used to develop automated decision making architectures to service security and resource management requirements in Cyber Physical Systems --Abstract, page iv
Stability Analysis of Uncertain Temperature control system with two additive delays and nonlinear perturbation
In this paper, the problem of robust delay-dependent stability criterion is considered for a class of linear continuous time heat exchanger system with constant additive state-delays and bounded nonlinear perturbations using Lyapunov-Krasovskii (LK) functional approach. In the proposed delay-dependent stability analysis, the time-delays are considered to be time-invariant. In the proposed delay-dependent stability analysis, a candidate LK functional is considered, and take the time-derivative of the functional is bounded using the Jenson integral inequality. The proposed stability analysis finally culminates into a stability criterion in LMI framework. The effectiveness of the proposed stability criterion is illustrated using a network controlled temperature control of heat exchanger syste
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