Showing papers in "IFAC Proceedings Volumes in 2009"

TL;DR: The aim of this paper is to present a comprehensive overview of SMC methods that have been proposed to perform static parameter estimation in general state-space models and discuss the advantages and limitations of these methods.

TL;DR: A benchmark model for simulation of fault detection and accommodation schemes of the wind turbine on a system level containing sensors, actuators and systems faults in the pitch system, drive train, generator and converter system is presented.

TL;DR: A model-free control and a control with a restricted model for finite-dimensional complex systems that may be viewed as a contribution to "intelligent" PID controllers, the tuning of which becomes quite straightforward, even with highly nonlinear and/or time-varying systems.

TL;DR: In this article, the authors highlight approaches and techniques that have successfully applied in practice and provide an overview of recent technological enhancements that are being made to MPC, including the design of the regulatory controls that receive setpoints from MPC.

TL;DR: In this article, the authors search for locally optimal solutions of a nonsmooth optimization problem that is built to incorporate minimization objectives and constraints for multiple plants, and report on the success of this approach using our public-domain matlab toolbox hifoo 2.0.

TL;DR: The uncertainty principle is a quantification of the notion that a matrix cannot be sparse while having diffuse row/column spaces and forms the basis for the decomposition method and its analysis.

TL;DR: In this paper, an overview on alarm analysis and design is given Some of the reasons for false and nuisance alarms are discussed and a few solutions to reduce them are studied False alarm rate, missed alarm rate and detection delay trade-offs in alarm design are also discussed

TL;DR: This paper investigates the effect of filtering of process data, adding alarm delay and using alarm deadband on accuracy of the alarm system and detection delay and proposes a framework for designing optimal filter, time delay and deadband to reduce false and missed alarm rates.

TL;DR: This paper provides a rigorous proof of convergence to global synchronization in the absence of process noise, measurement noise and communication delay, and its effectiveness through a number of experiments performed on a wireless sensor network.

TL;DR: In this paper, the authors describe a chain of tools aimed at the development and validation of energy management strategies for hybrid powertrains, which include an offline optimizer based on Pontryagin minimum principle (PMP) and the online equivalent consumption minimization strategy (ECMS), both implemented in a dynamic simulation platform and as a real-time controller in a semi-physical testing equipment.

TL;DR: A number of efficient and useful alternatives to the maximum-likelihood method have been developed over the years, including State-Variable filters combined with Instrumental Variable methods, including the simplified refined IV method.

TL;DR: In this article, the authors present a review on fault tolerance principles and general structural considerations, focusing on the scheme of an overall fault-tolerant control system, including actuators and drives.

TL;DR: The scope of the problem is described with reference to the scale and complexity of industrial processes, where multi-level hierarchical optimization and control are a must for efficient operation, but are also prone to hard or soft faults that lead to economic losses.

TL;DR: In this article, an internal model principle for consensus translating in necessary conditions for existence of solutions to the output and state consensus problem is proposed, where agents are modeled as linear time-invariant systems with potentially different state dimension and different dynamics.

TL;DR: In this paper, the authors developed a mathematical model that considers the type of polymer, the interaction between solvent and polymer, and the dynamics of solvent diffusion to predict the characteristics of the nanoparticle and also improve the process.

TL;DR: In this article, the authors stress the importance of selecting the right plantwide control structure and the need for a formalized approach that can encompass the many issues that arise in plant-wide control design.

TL;DR: In this paper, an unknown input observer is presented to estimate these faults in the converter and isolate them either to be an actuator fault or a sensor fault, since measurement of it is influenced by the turbulence around the rotor plane.

TL;DR: In this article, a coordination approach for thermostat-controlled household appliances is developed, which consists of a stepwise heuristic solution of a binary optimization problem, which serves to select a number of devices in each time step that are subject to compulsory switching, i.e. toggling the “on/off” state.

TL;DR: In this article, the issue of residual generation using structural analysis has been studied by several authors, and four recently proposed algorithms that solve this problem are presented and compared, and compared with each other.

TL;DR: A new strategy to address the problem of estimating the probability of failure of a system, in the challenging case where only an expensive-to-simulate model is available, is presented in the framework of sequential Bayesian planning.

TL;DR: The performance of the complete hierarchical control scheme is assessed through simulations and visualization in a virtual 3D environment, showing the ability of linear MPC to handle the strong couplings among the dynamical variables of the quadcopter under various torque and angle/position constraints, and the flexibility of hybrid MPC in planning the desired trajectory on-line.

TL;DR: In this paper, a brief overview of some of the theoretical and practical issues that arise in the process of developing advanced motion control systems for cooperative multiple autonomous marine vehicles (AMVs).

TL;DR: Surgical robotics and the basics of force control are introduced and different methods are presented to overcome the physical limitations of instrument sensorization, and force control algorithms tailored to medical robotic applications.

TL;DR: This research presents a meta-modelling architecture that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of manually cataloging and adapting systems to changing environmental conditions.

TL;DR: In this article, the authors investigated the formulation of nonlinear model-predictive control problems with economic objectives on an infinite horizon and proposed a solution method of the infinite horizon method through a transformation of the independent time variable.

TL;DR: The aim of the paper is to analyse identifiability of state noise parameters by means of the Bayesian approach and to summarise and compare the novel methods from both theoretical and numerical point of view.

TL;DR: A controller design approach that integrates RTO and MPC for the control of constrained uncertain nonlinear systems is proposed and relies on a novel set-based parameter estimation routine and a robust model predictive controller that takes into the effect of parameter estimation errors.

TL;DR: The integrated design of the hand finger and the sensors is reported and the motivations leading to this particular implementation are thoroughly addressed, taking into account both the mechanical constraints and the control requirements.

TL;DR: The main idea developed in this paper is first to derive an analytical expression for the boundaries of continuous flows, using interval Taylor methods and techniques for controlling the wrapping effect, and then to solve the problem of flow/sets intersection in an effective and reliable way.

TL;DR: In this paper, a control law for an underactuated vessel to follow a straight line path using a line-of-sight (LOS) guidance law is proposed, where a parameter of the LOS guidance law, the lookahead distance, is chosen to be timevarying and updated with a model predictive control (MPC) algorithm.