Mathematical control of complex systems

Copyright © 2013 ZidongWang et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Detection and Mitigation of Biasing Attacks on Distributed Estimation Networks

The paper considers a problem of detecting and mitigating biasing attacks on networks of state observers targeting cooperative state estimation algorithms. The problem is cast within the recently developed framework of distributed estimation utilizing the vector dissipativity approach. The paper shows that a network of distributed observers can be endowed with an additional attack detection layer capable of detecting biasing attacks and correcting their effect on estimates produced by the network. An example is provided to illustrate the performance of the proposed distributed attack detector.Comment: Accepted for publication in Automatic

Design of Fault Tolerant Control systems

This research designs a Fault Tolerant Control (FTC) approach that compensates for both actuator and sensor faults by using multiple observers. This method is shown to work for both linear time-variant and linear time-invariant systems. This work takes advantage of sensor redundancy to compensate for sensor faults. A method to calculate the rank of available sensor redundancy is developed to determine how many independent sensors can fail without losing observability. This rank is the upper bound on the number of simultaneous sensor failures that the system can tolerate. Based on this rank, a series of reduced order Kalman observers are created to remove sensors presumed faulty from the internal feedback of the estimators. Actuator redundancy is examined as a potential way to compensate for actuator faults. A method to calculate the available actuator redundancy is designed. This redundancy would allow for the correction of partial and full actuator failures, but few systems exhibit sufficient actuator redundancy. Actuator faults are instead tolerated by replacing the Kalman estimators with Augmented State Observers (ASO). The ASO adds estimates of the actuator faults as additional states of the system in order to isolate and estimate the actuator faults. Then a supervisor is designed to select the observer that correctly identifies the sensor fault set. From that observer, the supervisor collects state estimates and calculates estimates of the sensors and faults. These estimates are then used in feedback with a controller that performs pole placement on the original system

Integration of a failure monitoring within a hybrid dynamic simulation environment

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

Adaptive super-twisting observer for fault reconstruction in electro-hydraulic systems

An adaptive-gain super-twisting sliding mode observer is proposed for fault reconstruction in electro-hydraulic servo systems (EHSS) receiving bounded perturbations with unknown bounds. The objective is to address challenging problems in classic sliding mode observers: chattering effect, conservatism of observer gains, strong condition on the distribution of faults and uncertainties. In this paper, the proposed super-twisting sliding mode observer relaxes the condition on the distribution of uncertainties and faults, and the gain adaptation law leads to eliminate observer gain overestimation and attenuate chattering effects. After using the equivalent output-error-injection feature of sliding mode techniques, a fault reconstruction strategy is proposed. The experimental results are presented, confirming the effectiveness of the proposed adaptive super-twisting observer for precise fault reconstruction in electro-hydraulic servo systems.Comment: Final versio

Sliding Mode Based Dynamic State Estimation for Synchronous Generators in Power Systems

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record This letter deals with the design of a robust sliding mode observer for dynamic state estimation applied to synchronous generators in power systems. Assuming only the frequency deviation of the generator is measured via phasor measurement units, we use a robust sliding mode estimation technique to dynamically reconstruct the rotor angle and the transient voltage. The adopted estimation technique is insensitive to matched bounded uncertainties affecting the dynamics of the synchronous generator. A stability analysis and tuning rules for the observer are also provided. Numerical simulations confirm the validity of the approach