Remote maintenance of real time controller software over the internet

The aim of the work reported in this thesis is to investigate how to establish a standard platform for remote maintenance of controller software, which provides remote monitoring, remote fault identification and remote performance recovery services for geographically distributed controller software over the Internet. A Linear Quadratic Gaussian (LQG) controller is used as the benchmark for the control performance assessment; the LQG benchmark variances are estimated based on the Lyapunov equation and subspace matrices. The LQG controller is also utilized as the reference model of the actual controller to detect the controller failures. Discrepancies between control signals of the LQG and the actual controller are employed to a General Likelihood Ratio (GLR) test and the controller failure detection is characterized to detect sudden jumping points in the mean or variance of the discrepancies. To restore the degraded control performance caused by the controller failures, a compensator is designed and inserted into the post-fault control loop, which serially links with the faulty controller and recovers the degraded control performance into an acceptable range. Techniques of controller performance monitoring, controller failure detection and maintenance are extended into the Internet environment. An Internet-based maintenance system for controller software is developed, which provides remote control performance assessment and recovery services, and remote fault identification service over the Internet for the geographically distributed controller software. The integration between the mobile agent technology and the controller software maintenance is investigated. A mobile agent based controller software maintenance system is established; the mobile agent structure is designed to be flexible and the travelling agents can be remotely updated over the Internet. Also, the issue of heavy data process and transfer over the Internet is probed and a novel data process and transfer scheme is introduced. All the proposed techniques are tested on sirnulations or a process control unit. Simulation and experimental results illustrate the effectiveness of the proposed techniques.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Maintaining control performance in faulty control systems

Controller failures degrade a control system pedormance. In this paper, a novel main fenonce approach for controllerfailures is proposed fo restore fhe degraded peformance of the controller. The method is fo equivolenfly shifr any foulf occurring in a controller to the plant. Eased on the assumed process model, a compensafor with a serial link is designed to nlainfain the faulty controller in the SISO and MMO control systems. Several simulafioir results are given fo illustrate the procedure of using the metho

Fault detection in model predictive controller

Real-time monitoring and maintaining model predictive controller (MPC) is becoming an important issue with its wide implementation in the industries. In this paper, a measure is proposed to detect faults in MPCs by comparing the performance of the actual 'controller with the pedormance of the ideal controller. The ideal controller is derived from the dynamic matrix control @MC) in an ideal work situation and treated as a measure benchmark. A detection index based on the comparison is proposed to detect the state change of the target controller. This measure is illustrated through the implementation for a water tank process

MeaeQ: Mount Model Extraction Attacks with Efficient Queries

We study model extraction attacks in natural language processing (NLP) where attackers aim to steal victim models by repeatedly querying the open Application Programming Interfaces (APIs). Recent works focus on limited-query budget settings and adopt random sampling or active learning-based sampling strategies on publicly available, unannotated data sources. However, these methods often result in selected queries that lack task relevance and data diversity, leading to limited success in achieving satisfactory results with low query costs. In this paper, we propose MeaeQ (Model extraction attack with efficient Queries), a straightforward yet effective method to address these issues. Specifically, we initially utilize a zero-shot sequence inference classifier, combined with API service information, to filter task-relevant data from a public text corpus instead of a problem domain-specific dataset. Furthermore, we employ a clustering-based data reduction technique to obtain representative data as queries for the attack. Extensive experiments conducted on four benchmark datasets demonstrate that MeaeQ achieves higher functional similarity to the victim model than baselines while requiring fewer queries. Our code is available at https://github.com/C-W-D/MeaeQ.Comment: Accepted by EMNLP 2023 main conferenc

Remote maintenance of control system performance over the internet

The Internet provides a significant benefit for the remote maintenance and fault diagnosis of various devices and plants. One such example is the UK’s distributed aircraft maintenance environment (DAME) (www.cs.york.ac.uk/dame), which provides a genetic test bed for distributed diagnostics based on Grid-enabled technologies. This paper focuses on developing a systematic method for the design of such a remote maintenance systems specifically for process control systems. Design issues of Internet-based remote maintenance systems for process control such as that proposed here include control performance assessment, fault detection, control performance maintenance, and heterogeneous data transfer over the Internet. A back-end and front-end architecture is proposed, in which all the heavy calculations are carried out locally. Light data and the characteristics of any heavy data are sent to the front-end located on the remote server for consideration by remote experts. The remote maintenance system is illustrated by reference to the implementation in a process control rig

Reference model based maintenance of control system performance for industrial processes

In the last decade, fault tolerant controls (FTC) have enjoyed tremendous success to effectively accommodate defects in sensors, actuators, or plants. However, little of them considered what should be done once a control system performance is degraded during the operation. The aim of this paper is to maintain the performance of a control system at an acceptable level based on a pre-defined reference model. A maintenance approach is proposed and experimented in this paper. The method is to insert a compensator into the faulty control system and make the compensator and the faulty open loop system working together to track the pre-defined reference model. The proposed method is illustrated by reference to a mini process rig and shows the potential to industrial processes

Pulmonary alveolar type I cell population consists of two distinct subtypes that differ in cell fate.

Pulmonary alveolar type I (AT1) cells cover more than 95% of alveolar surface and are essential for the air-blood barrier function of lungs. AT1 cells have been shown to retain developmental plasticity during alveolar regeneration. However, the development and heterogeneity of AT1 cells remain largely unknown. Here, we conducted a single-cell RNA-seq analysis to characterize postnatal AT1 cell development and identified insulin-like growth factor-binding protein 2 (Igfbp2) as a genetic marker specifically expressed in postnatal AT1 cells. The portion of AT1 cells expressing Igfbp2 increases during alveologenesis and in post pneumonectomy (PNX) newly formed alveoli. We found that the adult AT1 cell population contains both Hopx+Igfbp2+ and Hopx+Igfbp2- AT1 cells, which have distinct cell fates during alveolar regeneration. Using an Igfbp2-CreER mouse model, we demonstrate that Hopx+Igfbp2+ AT1 cells represent terminally differentiated AT1 cells that are not able to transdifferentiate into AT2 cells during post-PNX alveolar regeneration. Our study provides tools and insights that will guide future investigations into the molecular and cellular mechanism or mechanisms underlying AT1 cell fate during lung development and regeneration

Reference Model Based Maintenance of Control System Performance for Industrial Processes

In the last decade, fault tolerant controls (FTC) have enjoyed tremendous success to effectively accommodate defects in sensors, actuators, or plants. However, little of them considered what should be done once a control system performance is degraded during the operation. The aim of this paper is to maintain the performance of a control system at an acceptable level based on a pre-defined reference model. A maintenance approach is proposed and experimented in this paper. The method is to insert a compensator into the faulty control system and make the compensator and the faulty open loop system working together to track the pre-defined reference model. The proposed method is illustrated by reference to a mini process rig and shows the potential to industrial processes

A universal optical modulator for synthetic topologically tuneable structured matter

Topologically structured matter, such as metasurfaces and metamaterials, have given rise to impressive photonic functionality, fuelling diverse applications from microscopy and holography to encryption and communication. Presently these solutions are limited by their largely static nature and preset functionality, hindering applications that demand dynamic photonic systems with reconfigurable topologies. Here we demonstrate a universal optical modulator that implements topologically tuneable structured matter as virtual pixels derived from cascading low functionality tuneable devices, altering the paradigm of phase and amplitude control to encompass arbitrary spatially varying retarders in a synthetic structured matter device. Our approach opens unprecedented functionality that is user-defined with high flexibility, allowing our synthetic structured matter to act as an information carrier, beam generator, analyser, and corrector, opening an exciting path to tuneable topologies of light and matter

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe