2,359 research outputs found
Sampled-data sliding mode observer for robust fault reconstruction: A time-delay approach
A sliding mode observer in the presence of sampled output information and its application to robust fault reconstruction is studied. The observer is designed by using the delayed continuous-time representation of the sampled-data system, for which sufficient conditions are given in the form of linear matrix inequalities (LMIs) to guarantee the ultimate boundedness of the error dynamics. Though an ideal sliding motion cannot be achieved in the observer when the outputs are sampled, ultimately bounded solutions can be obtained provided the sampling frequency is fast enough. The bound on the solution is proportional to the sampling interval and the magnitude of the switching gain. The proposed observer design is applied to the problem of fault reconstruction under sampled outputs and system uncertainties. It is shown that actuator or sensor faults can be reconstructed reliably from the output error dynamics. An example of observer design for an inverted pendulum system is used to demonstrate the merit of the proposed methodology compared to existing sliding mode observer design approaches
Robust sampled-data implementation of PID controller
We study a sampled-data implementation of the PID controller. Since the derivative is hard to measure directly, it is approximated using a finite difference giving rise to a delayed sampled-data controller. We suggest a novel method for the analysis of the resulting closed-loop system that allows to use only the last two measurements, while the existing results used a history of measurements. This method also leads to essentially larger sampling period. We show that, if the sampling period is small enough, then the performance of the closed-loop system under the sampled-data PID controller is preserved close to the one under the continuous-time PID controller. The maximum sampling period is obtained from LMIs derived using an appropriate Lyapunov-Krasovskii functional. These LMIs allow to consider systems with uncertain parameters. Finally, we develop an event-triggering mechanism that allows to reduce the amount of sampled control signals used for stabilization
Distributed event-triggered control of transport-reaction systems
We show that decentralized event-trigger can significantly reduce amount of transmitted measurements in network-based control of parabolic systems governed by a semilinear n-dimensional 1D diffusion PDEs. All measurements are sampled in time and space, quantized by a logarithmic quantizer, and are subject to time-varying network-induced delays
Event-triggered H∞ control : a switching approach
Event-triggered approach to networked control systems is used to reduce the workload of the communication network. For the static output-feedback continuous event-trigger may generate an infinite number of sampling instants in finite time (Zeno phenomenon) what makes it inapplicable to the real-world systems. Periodic event-trigger avoids this behavior but does not use all the available information. In the present paper we aim to exploit the advantage of the continuous-time measurements and guarantee a positive lower bound on the inter-event times by introducing a switching approach for finding a waiting time in the event-triggered mechanism. Namely, our idea is to present the closed-loop system as a switching between the system under periodic sampling and the one under continuous event-trigger and take the maximum sampling preserving the stability as the waiting time. We extend this idea to the L 2 -gain and ISS analysis of perturbed networked control systems with network-induced delays. By examples we demonstrate that the switching approach to event-triggered control can essentially reduce the amount of measurements to be sent through a communication network compared to the existing methods
Sampled-data H∞ filtering of a 2D heat equation under pointlike measurements
The existing sampled-data observers for 2D heat equations use spatially averaged measurements, i.e., the state values averaged over subdomains covering the entire space domain. In this paper, we introduce an observer for a 2D heat equation that uses pointlike measurements, which are modeled as the state values averaged over small subsets that do not cover the space domain. The key result, allowing for an efficient analysis of such an observer, is a new inequality that bounds the L 2 -norm of the difference between the state and its point value by the reciprocally convex combination of the L 2 -norms of the first and second order space derivatives of the state. The convergence conditions are formulated in terms of linear matrix inequalities feasible for large enough observer gain and number of pointlike sensors. The results are extended to solve the H ∞ filtering problem under continuous and sampled in time pointlike measurements
Dissolution, Reactor, and Environmental Behavior of ZrO 2 -MgO Inert Fuel Matrix Neutronic Evaluation of MgO-ZrO2 Inert Fuels
In the second year of the “Dissolution, Reactor, and Environmental Behavior of ZrO2-MgO Inert Fuel Matrix” project initiated and directed by UNLV, the Ben-Gurion University (BGU) group research was focused on the development of practical PWR core nuclear design fully loaded with Reactor Grade (RG) Pu fuel incorporated in fertile free matrix. The design strategy was based on the basic feasibility study results performed at BGU in the Year 1 of the project
A switching approach to event-triggered control
Event-trigger is used to obtain the measurements transmission instants in networked control systems. Under continuous measurements it can generate an infinite number of events in finite time (Zeno phenomenon) what makes it inapplicable to the real world systems. Periodic event-trigger avoids this behavior but does not use all the available information. In the present paper we aim to exploit the advantage of the continuous-time measurements and guarantee positive lower bound on the inter-event times. Our approach is based on a switching between periodic sampling and continuous event-trigger. It is applicable to the systems with polytopic-type uncertainties and assures the Input-to-State Stability in the presence of external disturbances and measurement noise. By an example we demonstrate that the switching approach to event-triggered control can reduce the network workload compared to periodic event-trigger
Dissolution, Reactor, and Environmental Behavior of ZrO2-MgO Inert Fuel Matrix: Neutronic Evaluation of ZrO2-MgO Inert Fuels
Various fuel cycle concepts for plutonium incineration in existing PWR loaded with Inert Matrix Fuel (IMF), in which uranium is replaced by neutron-transparent inert matrix material, are currently under investigation at BGU. Some of the studied designs include ZrO2-based IMF with annular fuel geometry and ZrO2-MgO based IMF with the relative amount of MgO varied from 30v/o to 70v/o. These concepts are analyzed via detailed three-dimensional full core simulation of existing PWR including thermal-hydraulic feedback. The whole core simulations are carried out with the SILWER code. The SILWER code, which is a part of the ELCOS1 system, performs three-dimensional neutronic calculations with thermal-hydraulic feedbacks of the full reactor core. Ability of the SILWER code to simulate the operation of a modern PWR loaded with all-UO2 fuel was demonstrated in the past2. However, two important limitations of the SILWER code with regards to the IMF analysis should be noted.
1. During fuel temperature calculations, SILWER thermal-hydraulic module employs the thermal conductivity of UO2. These data cannot be applied to IMF because the thermal conductivity of IMF differ from UO2 and depends on inert matrix material composition (Fig. 1).
2. Thermal-hydraulic module performs fuel temperature calculations assuming solid fuel pellet geometry even for the annular fuel. Thus, in order to adapt the SILWER code for simulation of PWR core loaded with IMF several modifications to the SILWER code were made
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