Offset-Free Strategy by Double-Layered Linear Model Predictive Control

In the real applications, the model predictive control MPC technology is separated into two layers, that is, a layer of conventional dynamic controller, based on which is an added layer of steady-state target calculation. In the literature, conditions for offset-free linear model predictive control are given for combined estimator for both the artificial disturbance and system state , steady-state target calculation, and dynamic controller. Usually, the offset-free property of the double-layered MPC is obtained under the assumption that the system is asymptotically stable. This paper considers the dynamic stability property of the double-layered MPC

An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

From 3D Models to 3D Prints: an Overview of the Processing Pipeline

Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044

Lateral and Longitudinal Coordinated Control of Intelligent Vehicle Based on High-Precision Dynamics Model under High-Speed Limit Condition

This study focuses on improving the trajectorytracking control for intelligent vehicles in high-speed and largecurvature limit conditions. To this end, a high-precision fivedegree-of-freedom (5-DOF) dynamics model (HPM) that incorporates suspension characteristics is introduced. Furthermore, acoordinated lateral and longitudinal control system is developed.The lateral model predictive control (MPC) involves two crucialstages: initially, a desired trajectory with associated speed datais generated based on path curvature. Subsequently, using thehigh-precision 5-DOF dynamics model, an objective functionis formulated to minimize the difference between the vehicle’scurrent state and the desired state. This process determines theoptimal front wheel steering angle, taking into account vehiclepositional constraints and steering limitations. Additionally, adouble proportional–integral–derivative (PID) controller for longitudinal control adjusts the throttle and brake pressure basedon real-time position and speed data, ensuring integrated controlover both lateral and longitudinal movements. The effectivenessof this approach is confirmed through real vehicle testing andsimulation. Results show that the high-precision 5-DOF dynamicsmodel markedly enhances the accuracy of vehicle response modeling, and the coordinated control system successfully executesprecise trajectory tracking. In extreme scenarios of high-speedand large curvature, the enhanced model substantially improvestrajectory accuracy and driving stability, thus promoting safevehicle operation

Lateral and Longitudinal Coordinated Control of Intelligent Vehicle Based on High-Precision Dynamics Model under High-Speed Limit Condition

This study focuses on improving the trajectorytracking control for intelligent vehicles in high-speed and largecurvature limit conditions. To this end, a high-precision fivedegree-of-freedom (5-DOF) dynamics model (HPM) that incorporates suspension characteristics is introduced. Furthermore, acoordinated lateral and longitudinal control system is developed.The lateral model predictive control (MPC) involves two crucialstages: initially, a desired trajectory with associated speed datais generated based on path curvature. Subsequently, using thehigh-precision 5-DOF dynamics model, an objective functionis formulated to minimize the difference between the vehicle’scurrent state and the desired state. This process determines theoptimal front wheel steering angle, taking into account vehiclepositional constraints and steering limitations. Additionally, adouble proportional–integral–derivative (PID) controller for longitudinal control adjusts the throttle and brake pressure basedon real-time position and speed data, ensuring integrated controlover both lateral and longitudinal movements. The effectivenessof this approach is confirmed through real vehicle testing andsimulation. Results show that the high-precision 5-DOF dynamicsmodel markedly enhances the accuracy of vehicle response modeling, and the coordinated control system successfully executesprecise trajectory tracking. In extreme scenarios of high-speedand large curvature, the enhanced model substantially improvestrajectory accuracy and driving stability, thus promoting safevehicle operation

Nonlinear computational framework for hybrid ductile glulam joists

This paper starts by presenting a nonlinear algebraic analysis of hybrid glulam sections, including ductile compression-softening constitutive models obtained via regression analysis of material test data, to compute full-range admissible values of moment (M), co-existent curvature (κ) and excluded-area axial force (Fea) for the sections. The (M,κ,Fea) states, double-checked by treating the section alternately as discretised and as a continuum, are clustered into (M,κ) and (M,Fea) data-sets that permit regression-analysis of κ and Fea as polynomial functions of M. For any load on a glulam member the M profile is known, so κ(M) is a more efficient route to calculating deflections than is M(κ). The κ(M) and Fea(M) constitutive functions, which enable assessment of any section state without tedious recalculation, are fused with longitudinal compatibility and equilibrium requirements to predict the joists’ nonlinear responses up to ultimate. Using quartic or Glos compressive constitutive models, spreadsheet-coding of this framework is shown to predict nonlinear local (κ(M)) and global (load–deflection) responses close to test data, also axial and longitudinal-shear stress redistributions mimicking FE predictions for distributed- or point-loaded hybrid glulam joists comprising combinations of poplar, blue-gum, maritime-pine and larch. The results show that post-peak reductions on compressive stress–strain curves cause through-depth reversal of longitudinal-shear at high moments

The Iray Light Transport Simulation and Rendering System

While ray tracing has become increasingly common and path tracing is well understood by now, a major challenge lies in crafting an easy-to-use and efficient system implementing these technologies. Following a purely physically-based paradigm while still allowing for artistic workflows, the Iray light transport simulation and rendering system allows for rendering complex scenes by the push of a button and thus makes accurate light transport simulation widely available. In this document we discuss the challenges and implementation choices that follow from our primary design decisions, demonstrating that such a rendering system can be made a practical, scalable, and efficient real-world application that has been adopted by various companies across many fields and is in use by many industry professionals today