Adaptive fast finite time control of a class of uncertain nonlinear systems

This paper concerns the adaptive fast finite time control of a class of nonlinear uncertain systems of which the upper bounds of the system uncertainties are unknown. By using the fast non-smooth control Lyapunov function and the method of so-called adding a power integrator merging with adaptive technique, a recursive design procedure is provided, which guarantees the fast finite time stability of the closed-loop system. It is proved that the control input is bounded, and a simulation example is given to illustrate the effectiveness of the theoretical results.

Investigation of process dynamics and control of polystyrene batch reactor using hybrid model

The effects of operating conditions such as initiator and monomer concentration as well as reactor temperature of polymerization reactors are studied in this work. A recently developed hybrid model for polystyrene batch reactor is utilized in simulation study. The simulation results reveal the sensitivity of polymer properties and monomer conversion to variation of process operating conditions. In the second phase of this study, the optimization problem involving minimum time optimal temperature policy is considered for control study. An advanced neural network-based model predictive controller (NN-MPC) is designed and tested online. The experimental studies reveal that the developed controller is able to track the optimal setpoint with a minor oscillation and overshoot.

Examining the effect of time constraint on the online mastery learning approach towards improving postgraduate students' achievement

Time control plays a critical role within the online mastery learning (OML) approach. This paper examines the two commonly implemented mastery learning strategies – personalised system of instructions and learning for mastery (LFM) – by focusing on what occurs when there is an instructional time constraint. Using a large data set from a postgraduate finance course offered at an Australian university, we explore students' online quiz-completion patterns, then empirically investigate whether the imposition of an instructional time constraint in the OML approach has an impact on their final-examination performance. Our results suggest that the LFM strategy with an instructional time constraint has a positive impact on students' learning behaviour and contributes to better overall academic performance. Further, our findings suggest that facilitators should be encouraged to implement an instructional time constraint when adopting an OML approach.

Factors governing colonisation by forensically important blow flies in Victoria

This study investigated factors controlling blow fly infestation of simulated remains (meat baits) in Victoria. Temperature, light and dark and level of decay are most influential in determining infestation by maggots. This knowledge will assist in more accurate forensic estimations of the minimum time since death of a corpse.

Video abstraction : a systematic review and classification

The demand for various multimedia applications is rapidly increasing due to the recent advance in the computing and network infrastructure, together with the widespread use of digital video technology. Among the key elements for the success of these applications is how to effectively and efficiently manage and store a huge amount of audio visual information, while at the same time providing user-friendly access to the stored data. This has fueled a quickly evolving research area known as video abstraction. As the name implies, video abstraction is a mechanism for generating a short summary of a video, which can either be a sequence of stationary images (keyframes) or moving images (video skims). In terms of browsing and navigation, a good video abstract will enable the user to gain maximum information about the target video sequence in a specified time constraint or sufficient information in the minimum time. Over past years, various ideas and techniques have been proposed towards the effective abstraction of video contents. The purpose of this article is to provide a systematic classification of these works. We identify and detail, for each approach, the underlying components and how they are addressed in specific works. © 2007 ACM.

Nonlinear identification of backlash in robot transmissions

ABSTRACT This paper addresses the issue of automatic identification of backlash in robot transmissions. Traditionally, the backlash is measured manually either by the transmission manufacturer or the robot manufacturer. Before the robot can be delivered to the end-customer, the backlash must be within specified tolerances. For robots with motor measurements only, backlash is an example of an uncontrollable behaviour which directly affects the absolute accuracy of the robot’s tool-centrepoint. Even if we do not attempt to bring backlash under real-time control in this paper, we will describe a method to automatically identify/estimate the backlash in the robot transmissions from torque and position measurements. Hence, only the transmissions that do not meet the backlash requirements in the automatic tests need to be checked and adjusted manually.

Design of distributed adaptive neural traffic signal timing controller by cuckoo search optimization

This paper focuses on designing an adaptive controller for controlling traffic signal timing. Urban traffic is an inevitable part in modern cities and traffic signal controllers are effective tools to control it. In this regard, this paper proposes a distributed neural network (NN) controller for traffic signal timing. This controller applies cuckoo search (CS) optimization methods to find the optimal parameters in design of an adaptive traffic signal timing control system. The evaluation of the performance of the designed controller is done in a multi-intersection traffic network. The developed controller shows a promising improvement in reducing travel delay time compared to traditional fixed-time control systems.

Entomology-based methods for estimation of postmortem interval

Forensic entomology involves the use of insects and other arthropods to estimate the minimum time elapsed since death, referred to as minimum postmortem interval (minPMI). This is based on the assemblage of insects found in association with remains, and most often, the time required for development of the first colonizing insects to develop to their size/life stage at time of collection. This process involves the accumulation of appropriate data for the development of the species of insect at a variety of relevant temperatures and consideration of the other biotic and abiotic factors that may affect developmental rate. This review considers the approaches to the estimation of minPMI, focusing largely on the age estimation of specimens collected from remains and the limitations that accompany entomology-based PMI estimations. Recent advances and newly developed techniques in the field are reviewed in regard to future potential.

Distributed power control in cellular mobile radio systems with time-varying link gains

A simple distributed power control algorithm for communication systems with mobile users and unknown time-varying link gains is proposed. We prove that the proposed algorithm is exponentially converging. Furthermore, we show that the algorithm significantly outperforms the well-known Foschini and Miljanic algorithm in the case of quickly moving mobile users.

Delay control and parallel admission algorithms for real-time anycast flow

An anycast flow is a flow that can be connected to any one of the members in a group of designated (replicated) servers (called anycast group). In this paper, we derive a set of formulas for calculating the end-to-end delay bound for the anycast flows and present novel admission control algorithms for anycast flows with real-time constraints. Given such an anycast group, our algorithms can effectively select the paths for anycast flows' admission and connection based on the least end-to-end delay bounds evaluated. We also present a parallel admission control algorithm that can effectively calculate the available paths with a short delay bound for different destinations in the anycast group so that a best path with the shortest delay bound can be chosen.

Distributed power control in cellular mobile radio systems with time-varying link gains

A simple distributed power control algorithm for communication systems with mobile users and unknown timevarying link gains is proposed. We prove that the proposed algorithm is exponentially converging. Furthermore, we show that the algorithm significantly outperforms the well-known
Foschini and Miljanic algorithm in the case of quickly moving mobile users.

Observer-based robust finite-time cooperative consensus control for multi-agent networks

This paper studies the finite-time consensus tracking control for multi-agent networks. The time-varying control input and the velocity of the leader is unknown to any follower. Only the position of the leader is known to its neighbors. We first propose a new finite-time multiple-surface sliding mode observer to estimate the leader's velocity. It is seen that the estimation error of the observer can converge to zero in a finite time. Then, we prove that finite-time consensus tracking of multi-agent networks can be achieved on a new terminal sliding mode surface. Simulation results are presented to validate the analysis.

Improvement on delay dependent absolute stability of Lurie control systems with multiple time delays

Absolute stability of Lurie control systems with multiple time-delays is studied in this paper. By using extended Lyapunov functionals, we avoid the use of the stability assumption on the main operator and derive improved stability criteria, which are strictly less conservative than the criteria in [2,3].