Yiming Wan

Discrete time-varying fault detection filter for non-uniformly sampled-data systems

This paper investigates the fault detection problem for non-uniformly sampled-data systems. No periodic assumption is made for the sampling instants. In contrast to most currently available results that are limited to strictly proper systems, measurement noises are considered. With the operators introduced to capture the inter-sampling behaviors of disturbances and faults, an offline fault detection algorithm is first derived to optimize the ratio-type design objective. It is then equivalently transformed into a recursive algorithm consisting of a discrete time-varying fault detection filter and the corresponding residual evaluation function. As repeated computation of the parity vectors is avoided, the proposed fault detection filter can help reduce the online computational burden with comparison to the existing parity relation based fault detection method.

Distributed H∞ Filtering with Consensus Strategies in Sensor Networks: Considering Consensus Tracking Error

Abstract The existing distributed filtering with consensus strategies consists of two steps: the consensus step through locally communicating with neighboring sensor nodes and the local filtering step. In this paper, the influence of consensus tracking error on the local estimation error is analyzed, and a distributed H∞ filtering algorithm considering the consensus tracking error is proposed. When the number of consensus iterations per sampling period is limited, the proposed method can suppress the effect of consensus tracking error on local estimation error; when the number of consensus iterations per sampling period goes to infinity, i.e., the consensus tracking error converges to zero, the local filtering in the distributed algorithm reduces to the centralized filtering. Simulation shows the effectiveness of the proposed method.

Adaptive optimization for active queue management supporting TCP flows

An adaptive decentralized strategy for active queue management of TCP flows over communication networks is presented. The proposed strategy solves locally, at each link, an optimal control problem, minimizing a cost composed of residual capacity and buffer queue size. The solution of the optimal control problem exploits an adaptive optimization algorithm aiming at adaptively minimizing a suitable approximation of the Hamilton-Jacobi-Bellman equation associated with the optimal control problem. Simulations results, obtained by using a fluid flow based model of the communication network and a common network topology, show improvement with respect to the Random Early Detection strategy. Besides, it is shown that the performance of the proposed decentralized solution is comparable with the performance obtained with a centralized strategy, which solves the optimal control problem via a central unit that maintains the flow states of the entire network.

Fault detection of networked control systems utilizing limited possibilities of unknown packet transmission

Fault detection of networked control systems subject to long delay and packet dropouts is discussed in this paper. No assumption about the statistics of long delay and packet dropouts is required for the proposed approach. Long delay and packet dropouts in sensor-to-controller link, which are known to the fault detection system, are handled with non-uniform sampling technique. Due to the unknown delay and packet dropouts in controller-to-actuator link, the true control commands implemented by the actuator are unknown to the fault detection system. However, given the upper bounds of delay and the number of successive packet dropouts, in a time window the number of possibilities of packet transmission in controller-to-actuator link is limited; then the limited possibilities of the control commands implemented by the actuator can be determined from the control commands sent by the controller. This fact is useful but has not been utilized by existing methods for fault detection of networked control systems to the knowledge of the authors. Then, consistency of parity relations is tested by evaluating residuals generated with the received outputs and each possibility of the corresponding control commands implemented by the actuator. The effectiveness of the proposed method is illustrated by a simulation example.

Fault Detection of Networked Control Systems Subject to Uncertain Time-Varying Delay and Packet Dropout

This paper focuses on fault detection of networked control systems with both time-varying delay and packet dropout. Different from some existing results, in this paper, network-induced delay is not limited to be an integer multiple of the sampling period, and packet dropout is present in both sensor-to-controller link and controller-to-actuator link. The method in this paper can be regarded as an expansion of an existing work of the authors group, which deals only with network induced delay without considering packet dropout in the design.

Observer based Residual Generation and Evaluation of Networked Control Systems Subject to Random Packet Dropou

Abstract In this paper fault detection is addressed for networked control systems subject to random packet dropout in both sensor-to-controller link and controller-to-actuator link. First a new model of NCS is proposed, which directly eliminates influence of packet dropout in the sensor-to-controller link. Then adaptive threshold is given to ensure robustness to packet dropout in the controller-to-actuator link. False alarm rate analysis is also given, which is not addressed in most of the literature on fault detection of networked control systems. The fault detection scheme can ensure both robustness to packet dropout as well as disturbance and sensitivity to fault, which is superior to the existing approaches. Moreover, the residual generation can be achieved by using linear matrix inequality based convex optimization technique. Comparison with existing approaches illustrates advantages of our method.

Fault-tolerant reference generation for model predictive control with active diagnosis of elevator jamming faults: Fault-tolerant reference generation for model predictive control with active diagnosis of elevator jamming faults

This paper focuses on the longitudinal control of an Airbus passenger aircraft in the presence of elevator jamming faults. In particular, in this paper, we address permanent and temporary actuator jamming faults using a novel reconfigurable fault-tolerant predictive control design. Due to their different consequences on the available control authority and fault duration, the above 2 actuator jamming faults need to be distinguished so that appropriate control reconfigurations can be adopted accordingly. Their similarity in symptoms, however, prevents an effective discrimination of the root cause of the jamming when using only a passive fault-diagnosis approach. Hence, we propose the use of model predictive control (MPC) as a fault-tolerant controller to actively help the fault-detection (FD) unit discriminate between a permanent and a temporary jamming fault, while ensuring the performance of the aircraft. The MPC controller and the FD unit closely interact during the detection and diagnosis phases. In particular, every time a fault is detected, the FD module commands the MPC controller to perform a predefined sequence of reconfigurations to diagnose the root cause of the fault. An artificial reference signal that accounts for changes in the actuator operative ranges is used to guide the system through this sequence of reconfigurations. Our strategy is demonstrated on an Airbus passenger aircraft simulator.