Graphical User Interface for Robust Control Education Based on 3DOF Helicopter System

Robustness is an important characteristic of feedback controllers. Many systems with non-linearities and parameter uncertainties usually require sucient robustness to stay stable. Robust control education is therefore very important for graduate students. However, many educational programs in robust control are exclusively theoretical. This thesis work aims at designing and developing a user-friendly Graphical User Interface (GUI) based on MATLAB for robust-control education based on a nonlinear and highly-coupled helicopter system. Although the control design method is limited to the S/KS mixed-sensitivity method, it oers a convenient and ready-to-use GUI for robust control design, dynamic response simulation, robust stability/robust performance assessment, and control implementation. Users can generate the controller by inputting parameters of two weighting functions. Linear and nonlinear simulations based on a discrete-time model are used to assess performance. Structured singular values are used to assess robust stability and robust performance conditions with three typical types of uncertainty. In the end, the designed controller can be loaded into Simulink to control the actual helicopter device. This robust-control educational experiment oers an easy way to test in practice fundamentals of robust control theory

Architecture of Environmental Risk Modelling: for a faster and more robust response to natural disasters

Demands on the disaster response capacity of the European Union are likely to increase, as the impacts of disasters continue to grow both in size and frequency. This has resulted in intensive research on issues concerning spatially-explicit information and modelling and their multiple sources of uncertainty. Geospatial support is one of the forms of assistance frequently required by emergency response centres along with hazard forecast and event management assessment. Robust modelling of natural hazards requires dynamic simulations under an array of multiple inputs from different sources. Uncertainty is associated with meteorological forecast and calibration of the model parameters. Software uncertainty also derives from the data transformation models (D-TM) needed for predicting hazard behaviour and its consequences. On the other hand, social contributions have recently been recognized as valuable in raw-data collection and mapping efforts traditionally dominated by professional organizations. Here an architecture overview is proposed for adaptive and robust modelling of natural hazards, following the Semantic Array Programming paradigm to also include the distributed array of social contributors called Citizen Sensor in a semantically-enhanced strategy for D-TM modelling. The modelling architecture proposes a multicriteria approach for assessing the array of potential impacts with qualitative rapid assessment methods based on a Partial Open Loop Feedback Control (POLFC) schema and complementing more traditional and accurate a-posteriori assessment. We discuss the computational aspect of environmental risk modelling using array-based parallel paradigms on High Performance Computing (HPC) platforms, in order for the implications of urgency to be introduced into the systems (Urgent-HPC).Comment: 12 pages, 1 figure, 1 text box, presented at the 3rd Conference of Computational Interdisciplinary Sciences (CCIS 2014), Asuncion, Paragua

Robust variance-constrained H∞ control for stochastic systems with multiplicative noises

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier Ltd.In this paper, the robust variance-constrained H∞ control problem is considered for uncertain stochastic systems with multiplicative noises. The norm-bounded parametric uncertainties enter into both the system and output matrices. The purpose of the problem is to design a state feedback controller such that, for all admissible parameter uncertainties, (1) the closed-loop system is exponentially mean-square quadratically stable; (2) the individual steady-state variance satisfies given upper bound constraints; and (3) the prescribed noise attenuation level is guaranteed in an H∞ sense with respect to the additive noise disturbances. A general framework is established to solve the addressed multiobjective problem by using a linear matrix inequality (LMI) approach, where the required stability, the H∞ characterization and variance constraints are all easily enforced. Within such a framework, two additional optimization problems are formulated: one is to optimize the H∞ performance, and the other is to minimize the weighted sum of the system state variances. A numerical example is provided to illustrate the effectiveness of the proposed design algorithm.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Nuffield Foundation of the UK under Grant NAL/00630/G, and the Alexander von Humboldt Foundation of Germany

On-line multiobjective automatic control system generation by evolutionary algorithms

Evolutionary algorithms are applied to the on- line generation of servo-motor control systems. In this paper, the evolving population of controllers is evaluated at run-time via hardware in the loop, rather than on a simulated model. Disturbances are also introduced at run-time in order to pro- duce robust performance. Multiobjective optimisation of both PI and Fuzzy Logic controllers is considered. Finally an on-line implementation of Genetic Programming is presented based around the Simulink standard blockset. The on-line designed controllers are shown to be robust to both system noise and ex- ternal disturbances while still demonstrating excellent steady- state and dvnamic characteristics

Damage Tolerant Active Contro l: Concept and State of the Art

Damage tolerant active control is a new research area relating to fault tolerant control design applied to mechanical structures. It encompasses several techniques already used to design controllers and to detect and to diagnose faults, as well to monitor structural integrity. Brief reviews of the common intersections of these areas are presented, with the purpose to clarify its relations and also to justify the new controller design paradigm. Some examples help to better understand the role of the new area

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

A Multifaceted Consideration of Motivation and Learning within ASSISTments

An approach to education gaining popularity in the modern classroom, adaptive tutoring systems offer interactive learning environments in which students can access immediate feedback and rich tutoring while teachers can achieve organized assessment for targeted interventions. Yet despite the benefits that these systems provide, a number of questions remain regarding the optimal inner workings of adaptive platforms. What is the recipe for optimal student performance within these platforms? What elements should be taken into consideration when designing these learning environments? Can facets of these platforms be harnessed to increase students’ motivation to learn and to improve both immediate and robust learning gains? This thesis combines work conducted over the past two years through versatile approaches toward the goal of enhancing student motivation and learning within the ASSISTments platform. Approaches considered include a) enhancing motivation and performance through altered feedback using hypermedia elements, b) instilling motivational messages alongside media enhanced content and feedback, c) allowing students to choose their feedback medium, thereby exerting control over their assignment, d) altering content delivery by interleaving skills to enhance solution strategy development, and e) establishing partial credit assessments to drive motivation and proper system usage while enhancing student modeling. After a brief introduction regarding the main tenants of this research, each chapter highlights a randomized controlled trial focused around one of these approaches. All studies presented have been conducted or are still running within ASSISTments. Much of this work has already been published at peer reviewed conference venues, some with stringent acceptance rates as low as 25% for full papers. Two of the studies presented here are second iterations of previously published work that are still in progress, and only preliminary analyses are available. A chapter on conclusions and future work is included to discuss the contributions that have been made to the Learning Sciences community thus far, and to briefly discuss potential directions for my continued research

Psychometrics in Practice at RCEC

A broad range of topics is dealt with in this volume: from combining the psychometric generalizability and item response theories to the ideas for an integrated formative use of data-driven decision making, assessment for learning and diagnostic testing. A number of chapters pay attention to computerized (adaptive) and classification testing. Other chapters treat the quality of testing in a general sense, but for topics like maintaining standards or the testing of writing ability, the quality of testing is dealt with more specifically.\ud All authors are connected to RCEC as researchers. They present one of their current research topics and provide some insight into the focus of RCEC. The selection of the topics and the editing intends that the book should be of special interest to educational researchers, psychometricians and practitioners in educational assessment