A New Switched State Jump Observer for Traffic Density Estimation in Expressways Based on Hybrid-Dynamic-Traffic-Network-Model

When faced with problems such as traffic state estimation, state prediction, and congestion identification for the expressway network, a novel switched observer design strategy with jump states is required to reconstruct the traffic scene more realistically. In this study, the expressway network is firstly modeled as the special discrete switched system, which is called the piecewise affine system model, a partition of state subspace is introduced, and the convex polytopes are utilized to describe the combination modes of cells. Secondly, based on the hybrid dynamic traffic network model, the corresponding switched observer (including state jumps) is designed. Furthermore, by applying multiple Lyapunov functions and S-procedure theory, the observer design problem can be converted into the existence issue of the solutions to the linear matrix inequality. As a result, a set of gain matrices can be obtained. The estimated states start to jump when the mode changes occur, and the updated value of the estimated state mainly depends on the estimated and the measured values at the previous time. Lastly, the designed state jump observer is applied to the Beijing Jingkai expressway, and the superiority and the feasibility are demonstrated in the application results

On-line computer control of turbine generators using state estimation and optimal feedback

Imperial Users onl

Sensorless Control of a Single-Phase AC-DC Boost Converter without Measuring Input Voltage and Current

It is well-known that the accurate measurement of input voltage and current, as the feedforward and feedback terms, plays a crucial role in the nonlinear controller design for power factor compensation of an AC-DC boost converter. This paper addresses the problem of the simultaneous estimation of the input voltage and current from the output voltage in a full-bridge AC-DC boost converter. In the lossless model of the system, those variables are unobservable from the output voltage when the control input is zero. To overcome this, the system dynamics are immersed in a proper form by a new filtered transformation. The phase and amplitude of the input voltage, along with the input current, are globally estimated from the output voltage by a fifth-dimensional estimator. Unlike some existing results, the stability of the proposed estimator does not rely on a priori knowledge about the parasitic resistances and is guaranteed exponentially under the persistence of excitation conditions on the control signal. An application of the proposed estimator is presented in conjunction with a dynamic controller to form a sensorless control algorithm that does not require any sensor on the input side and controls the system only by the feedback from the output voltage. Processor-in-the-loop (PIL) studies conducted by OPAL-RT OP 5700 are used to assess the performances of the proposed estimator and controller

Aeronautical Engineering. A continuing bibliography with indexes, supplement 156

This bibliography lists 288 reports, articles and other documents introduced into the NASA scientific and technical information system in December 1982

The ECB's monetary analysis revisited

Monetary aggregates continue to play an important role in the ECB's policy strategy. This paper revisits the case for money, surveying the ongoing theoretical and empirical debate. The key conclusion is that an exclusive focus on non-monetary factors alone may leave the ECB with an incomplete picture of the economy. However, treating monetary factors as a separate matter is a second-best solution. Instead, a general-equilibrium inspired analytical framework that merges the economic and monetary pillars of the ECB's policy strategy appears the most promising way forward. The role played by monetary aggregates in such unified framework may be rather limited. However, an integrated framework would facilitate the presentation of policy decisions by providing a clearer narrative of the relative role of money in the interaction with other economic and financial sector variables, including asset prices, and their impact on consumer prices. --ECB,monetary analysis,monetary pillar,New Keynesian model,DSGE model,P* model,Twopillar Phillips curve,VAR model,generalized dynamic factor model

Fault-tolerant supervisory control of discrete-event systems

In this dissertation, I introduce my study on fault-tolerant supervisory control of discrete event systems. Given a plant, possessing both faulty and nonfaulty behavior, and a submodel for just the nonfaulty part, the goal of fault-tolerant supervisory control is to enforce a certain specifcation for the nonfaulty plant and another (perhaps more liberal) specifcation for the overall plant, and further to ensure that the plant recovers from any fault within a bounded delay so that following the recovery the system state is equivalent to a nonfaulty state (as if no fault ever happened). My research includes the formulation of the notations and the problem, existence conditions, synthesizing algorithms, and applications

Wireless industrial intelligent controller for a non-linear system

Modern neural network (NN) based control schemes have surmounted many of the limitations found in the traditional control approaches. Nevertheless, these modern control techniques have only recently been introduced for use on high-specification Programmable Logic Controllers (PLCs) and usually at a very high cost in terms of the required software and hardware. This ‗intelligent‘ control in the sector of industrial automation, specifically on standard PLCs thus remains an area of study that is open to further research and development. The research documented in this thesis examined the effectiveness of linear traditional control schemes such as Proportional Integral Derivative (PID), Lead and Lead-Lag control, in comparison to non-linear NN based control schemes when applied on a strongly non-linear platform. To this end, a mechatronic-type balancing system, namely, the Ball-on-Wheel (BOW) system was designed, constructed and modelled. Thereafter various traditional and intelligent controllers were implemented in order to control the system. The BOW platform may be taken to represent any single-input, single-output (SISO) non-linear system in use in the real world. The system makes use of current industrial technology including a standard PLC as the digital computational platform, a servo drive and wireless access for remote control. The results gathered from the research revealed that NN based control schemes (i.e. Pure NN and NN-PID), although comparatively slower in response, have greater advantages over traditional controllers in that they are able to adapt to external system changes as well as system non-linearity through a process of learning. These controllers also reduce the guess work that is usually involved with the traditional control approaches where cumbersome modelling, linearization or manual tuning is required. Furthermore, the research showed that online-learning adaptive traditional controllers such as the NN-PID controller which maintains the best of both the intelligent and traditional controllers may be implemented easily and with minimum expense on standard PLCs

Reconceptualizing Social Impairment Using Informant Report

Psychological disorders would not be considered as such if they did not result in some form of dysfunction. Yet, the assessment of impairment remains considerably flawed. Typical instruments used to measure impairment are susceptible to criterion contamination (e.g., explicitly confounding symptoms with impairment, as a result of mood-biased responses involved in self report). Additionally, individuals with personality pathology seem likely to underreport impairment, either due to a lack of insight or because of the manifestations of impairment assessed. The current project aimed to demonstrate the concurrent validity of a newly-developed, informant-reported measure of social impairment (the Scale of Unpleasant Relational Conduct Effects, SOURCE). To do this, we used first used psychopathology to predict SOURCE scores, to establish that the SOURCE achieves a basic expected relationship. We then used the SOURCE to predict psychopathology, as well as pathology-related outcomes (e.g., legal trouble), while accounting for scores on a self-report social impairment measure. This was done to determine whether the SOURCE provided any added predictive benefit. Results demonstrate a robust relationship between the SOURCE and personality pathology, even after accounting for a more typical assessment of social impairment. Significant relationships were not found between the SOURCE and Major Depression, or between the SOURCE and substance use disorder diagnosis. Ancillary research questions identified the SOURCE as a potentially useful screening tool for personality pathology, as its demonstrated good specificity and negative predictive power. These results contribute to the growing literature supporting the utility of informant report in the assessment of personality pathology and related dysfunction. They also suggest that the kind of social impairment experienced by individuals with maladaptive personality traits might not be adequately captured by existing measures

The Baseline Design of The UiS Subsea Glider for Cargo and Liquid Carbon Dioxide Transportation

This dissertation presents the baseline design of the UiS subsea-freight glider (USFG) for cargo and liquid carbon dioxide transportation. The USFG is a cutting-edge autonomous vessel developed to be an alternative to active transportation technologies and satisfy the demands of small-scale fields for CO2 transportation. Usually, these smaller fields fail to economically justify the costs of large tanker or cargo ships or underwater pipelines on the seabed, as the transport volume is nominal compared to larger fields. The USFG can travel underwater at an operational depth of 200 meters, allowing the glider to carry freight operations without considering ideal weather windows. The length of the USFG is 5.50 meters, along with a beam of 50.25 meters, which allows the vessel to carry 518 m3 of CO2 while serving the storage needs of the carbon capture and storage (CCS) ventures on the Norwegian continental shelf. It can maneuver itself underwater by monitoring the flow between the ballast tanks. During the entire mission of the USFG, from capturing to injection locations, it follows a pre-laid route while experiencing transient loads from the ocean current. A planar mathematical model for the analysis of equilibrium glide paths of the USFG is presented. The model is developed using Simscape Multibody in MATLAB/Simulink to study the volatile dynamics of the glider. Subsequently, the gliding paths of USFG in the vertical plane are analyzed along with the observability and controllability of the steady equilibrium glides. Along with the control gliding design of the USFG, the mechanical design is also presented in this work. The maneuvering model of the USFG is presented along with two operational case studies: the equilibrium glide and the -38° dive. The extreme motion along the surge direction affects the range of the glider (vital for battery design) and the dynamic controller parameters concerning maneuverability. Finally, the averaged conditional exceedance rate (ACER) is employed to scrutinize the extreme motion (surge direction) of the USFG while gliding to a defined depth. This analysis is done when the glider is exposed to an average current velocity of 0.5 m/s and 1.0 m/s. The presented ACER method efficiently uses the available data points and accurately predicts the extreme surge responses precisely and accurately