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See detailStates and unknown input estimation via non-linear sliding mode high-gain observers for a glucose-insulin system
Aguilera Gonzalez, Adriana UL; Voos, Holger UL; Darouach, Mohamed

in IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), Kuala Lumpur, Malaysia, 2016 (2016, December 04)

A meal-estimation algorithm is developed based on an extended mathematical model of the glucose-insulin system. The proposed model describes the dynamics of glucose levels in blood and in subcutaneous ... [more ▼]

A meal-estimation algorithm is developed based on an extended mathematical model of the glucose-insulin system. The proposed model describes the dynamics of glucose levels in blood and in subcutaneous layer, as well as the meal intake which is considered an unknown input of the system. This model seeks to represent in a more realistic manner, the pancreas malfunction in patients with Type 1 Diabetes Mellitus. Based on model, a non-linear high gain observer (NHGO) with a sliding mode is designed in order to estimate the unmeasured states and the external disturbances of the system. This scheme is useful to maintain frequent monitoring of glucose levels and any changes in its behaviour. The unknown input or disturbance is estimated through the sliding mode based only the estimation error. Data from a real patient is used to evaluate the effectiveness of the proposed estimation scheme. [less ▲]

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See detailGraph-based Software Knowledge: Storage and Semantic Querying of Domain Models for Run-Time Adaptation
Hochgeschwender, Nico UL; Schneider, Sven; Voos, Holger UL et al

in IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots SIMPAR, San Francisco, Dec 2016 (2016, December)

Software development for robots is a knowledge intensive exercise. To capture this knowledge explicitly and formally in the form of various domain models, roboticists have recently employed model-driven ... [more ▼]

Software development for robots is a knowledge intensive exercise. To capture this knowledge explicitly and formally in the form of various domain models, roboticists have recently employed model-driven engineering (MDE) approaches. However, these models are merely seen as a way to support humans during the robot's software design process. We argue that the robots themselves should be first-class consumers of this knowledge to autonomously adapt their software to the various and changing run-time requirements induced, for instance, by the robot's tasks or environment. Motivated by knowledge-enabled approaches, we address this problem by employing a graph-based knowledge representation that allows us not only to persistently store domain models, but also to formulate powerful queries for the sake of run time adaptation. We have evaluated our approach in an integrated, real-world system using the neo4j graph database and we report some lessons learned. Further, we show that the graph database imposes only little overhead on the system's overall performance. [less ▲]

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See detailA real-time model predictive position control with collision avoidance for commercial low-cost quadrotors
Dentler, Jan Eric UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in IEEE Multi-Conference on Systems and Control (MSC 2016), Buenos Aires, Argentina, 2016 (2016, September 20)

Unmanned aerial vehicles (UAVs) are the future technology for autonomous fast transportation of individual goods. They have the advantage of being small, fast and not to be limited to the local ... [more ▼]

Unmanned aerial vehicles (UAVs) are the future technology for autonomous fast transportation of individual goods. They have the advantage of being small, fast and not to be limited to the local infrastructure. This is not only interesting for delivery of private consumption goods up to the doorstep, but also particularly for smart factories. One drawback of autonomous drone technology is the high development costs, that limit research and development to a small audience. This work is introducing a position control with collision avoidance as a first step to make low-cost drones more accessible to the execution of autonomous tasks. The paper introduces a semilinear state-space model for a commercial quadrotor and its adaptation to the commercially available AR.Drone 2 system. The position control introduced in this paper is a model predictive control (MPC) based on a condensed multiple-shooting continuation generalized minimal residual method (CMSCGMRES). The collision avoidance is implemented in the MPC based on a sigmoid function. The real-time applicability of the proposed methods is demonstrated in two experiments with a real AR.Drone quadrotor, adressing position tracking and collision avoidance. The experiments show the computational efficiency of the proposed control design with a measured maximum computation time of less than 2ms. [less ▲]

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See detailUAV degradation identification for pilot notification using machine learning techniques
Manukyan, Anush UL; Olivares Mendez, Miguel Angel UL; Bissyande, Tegawendé François D Assise UL et al

in Proceedings of 21st IEEE International Conference on Emerging Technologies and Factory Automation ETFA 2016 (2016, September 06)

Unmanned Aerial Vehicles are currently investigated as an important sub-domain of robotics, a fast growing and truly multidisciplinary research field. UAVs are increasingly deployed in real-world settings ... [more ▼]

Unmanned Aerial Vehicles are currently investigated as an important sub-domain of robotics, a fast growing and truly multidisciplinary research field. UAVs are increasingly deployed in real-world settings for missions in dangerous environments or in environments which are challenging to access. Combined with autonomous flying capabilities, many new possibilities, but also challenges, open up. To overcome the challenge of early identification of degradation, machine learning based on flight features is a promising direction. Existing approaches build classifiers that consider their features to be correlated. This prevents a fine-grained detection of degradation for the different hardware components. This work presents an approach where the data is considered uncorrelated and, using machine learning <br />techniques, allows the precise identification of UAV’s damages. [less ▲]

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See detailOperational Space Control of a Lightweight Robotic Arm Actuated By Shape Memory Alloy (SMA) Wires
Quintanar Guzman, Serket UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in ASME 2016 Conferences on Smart Materials, Adaptive Structures and Intelligent Systems, Vermont 28-30 September 2016 (2016, September)

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See detailA Fast Model-Predictive Speed Controller for Minimised Charge Consumption of Electric Vehicles
Schwickart, Tim Klemens UL; Voos, Holger UL; Hadji-Minaglou, Jean-Régis UL et al

in Asian Journal of Control (2016), 18(5),

This paper presents the design of a real-time implementable energy-efficient model-predictive cruise controller for electric vehicles including the driving speed reference generation. The controller is ... [more ▼]

This paper presents the design of a real-time implementable energy-efficient model-predictive cruise controller for electric vehicles including the driving speed reference generation. The controller is designed to meet the properties of a series-production electric vehicle whose characteristics are identified and validated by measurements. The predictive eco-cruise controller aims at finding the best compromise between speed-reference tracking and energy consumption of the vehicle using an underlying dynamic model of the vehicle motion and charge consumption. The originally non-linear motion model is transformed into a linear model mainly by using a coordinate transform. To obtain a piecewise linear approximation of the charge consumption map, the measured characteristics are approximated by a convex piecewise linear function represented as the maximum of a set of linear constraint functions. The reformulations finally lead to a model-predictive control approach with quadratic cost function, linear prediction model and linear constraints that corresponds to a piecewise linear system behaviour and allows a fast real-time implementation with guaranteed convergence. Simulation results of the closed-loop operation finally illustrate the effectiveness of the approach. [less ▲]

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See detailInvariant Observer Applied to Anaerobic Digestion Model
Chaib Draa, Khadidja UL; Voos, Holger UL; Alma, Marouane et al

in IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), Berlin, Germany, 2016 (2016, September)

In this note, we design an invariant observer for a two step (acidogenesis-methanogenesis) mass balance nonlinear model, in order to estimate simultaneously all bacteria and substrate concentrations found ... [more ▼]

In this note, we design an invariant observer for a two step (acidogenesis-methanogenesis) mass balance nonlinear model, in order to estimate simultaneously all bacteria and substrate concentrations found in the anaerobic digestion process. The particularity of the designed observer is the use of only the methane flow rate which is cheap to measure and commonly measured online even at industrial scale. [less ▲]

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See detailAutomated Decision Support IoT Framework
Tessaro Lunardi, Willian UL; Amaral, Leonardo; Marczak, Sabrina et al

in IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), Berlin, Germany, 2016 (2016, September)

During the past few years, with the fast development and proliferation of the Internet of Things (IoT), many application areas have started to exploit this new computing paradigm. The number of active ... [more ▼]

During the past few years, with the fast development and proliferation of the Internet of Things (IoT), many application areas have started to exploit this new computing paradigm. The number of active computing devices has been growing at a rapid pace in IoT environments around the world. Consequently, a mechanism to deal with this different devices has become necessary. Middleware systems solutions for IoT have been developed in both research and industrial environments to supply this need. However, decision analytics remain a critical challenge. In this work we present the Decision Support IoT Framework composed of COBASEN, an IoT search engine to address the research challenge regarding the discovery and selection of IoT devices when large number of devices with overlapping and sometimes redundant functionality are available in IoT middleware systems, and DMS, a rule-based reasoner engine allowing to set up computational analytics on device data when it is still in motion, extracting valuable information from it for automated decision making. DMS uses Complex Event Processing to analyze and react over streaming data, allowing for example, to trigger an actuator when a specific error or condition appears in the stream. The main goal of this work is to highlight the importance of a decision support system for decision analytics in the IoT paradigm. We developed a system which implements DMS concepts. However, for preliminarily tests, we made a functional evaluation of both systems in terms of performance. Our initial findings suggest that the Decision Support IoT Framework provides important approaches that facilitate the development of IoT applications, and provides a new way to see how the business rules and decision-making will be made towards the Internet of Things. [less ▲]

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See detailA Generalized Interaction Wake Model with Its Variation for Control in Wind Farms
Pan, Lin UL; Voos, Holger UL; Darouach, Mohamed

in 35th Chinese Control Conference, Chengdu. China, 2016 (2016, July 28)

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See detailAn Extended Cooperative Adaptive Cruise Control (CACC) Algorithm for Efficient Energy Consumption & Traffic Density Formulation
Bayar, Bilgehan; Sajadi Alamdari, Seyed Amin UL; Viti, Francesco UL et al

in Traffic Flow Theory and Characteristics Committee (AHB45) 2016 Summer Meeting, Sydney, Australia, 2016 (2016, July 02)

Electric transportation, one of the most promising technologies of the century, can contribute to a greener environment as it is emission-free and sustainable. Although this technology promises a clean ... [more ▼]

Electric transportation, one of the most promising technologies of the century, can contribute to a greener environment as it is emission-free and sustainable. Although this technology promises a clean transportation style, it also has some drawbacks. One of the most significant one is cruising range, which needs to be addressed sustainably. The most eco-friendly solution is decreasing energy consumption by addressing driving behaviour. This can be achieved by taking the advantage of implementing an advancing vehicle automation technology which controls vehicles using a driver-assistance system such as Eco-Cruise Control (Eco-CC). Variety of systems already exist in the literature and a little known advanced version Eco-Adaptive Cruise Control (Eco-ACC) systems are developed as well. The next step of the vehicle automation is vehicle cooperation and information sharing, so-called Cooperative Adaptive Cruise Control (CACC). It is already developed and tested by various researcher. However, the largest deal of existing studies focus on assessing the performance in terms of safety, possible contributions to the energy consumption is not taken into account. This study covers the extension of Cooperative Adaptive Cruise Control systems while aiming to provide an energy efficient extended control algorithm to increase the energy efficiency and battery usage for electric vehicles. An energy efficient control algorithm is aimed to be derived to decrease the consumption of the vehicle. Cruising velocities and vehicle positions are received from the leading vehicles and accordingly traction force is adjusted to achieve efficient energy consumption. By providing vehicle to vehicle (V2V) communication tighter spacing gaps, lower time headway, are aimed to obtain while traffic disturbances are damped, whereas in the cases ACC applications amplify the disturbance. Traffic density formula is introduced by using V2V communication which might be useful for ADAS and ITS framework. As a result, increase in traffic stability, density, and reduction in the total energy consumption is expected. Moreover, possible reductions in air drag with tighter spacing gaps may lead reduction in energy consumption. For the energy calculations and the validation of the proposed method, vehicle dynamics and energy consumption of an electric car is formulated, which has completely different characteristics and limitations than combustion engine cars. Hence the study aims to provide additional understanding of behaviour of a fleet of CACC-equipped electric vehicles. Even though the proposed control algorithm is developed for Electric Vehicles, it can be extended to other vehicle types based on their energy consumption characteristics and vehicle dynamics. [less ▲]

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See detailLightweight robotic arm actuated by Shape Memory Alloy (SMA) Wires
Quintanar Guzman, Serket UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in 8th International Conference on Electronics, Computers and Artificial Intelligence, Ploiesti, Romania, 30 June-02 July 2016 (2016, July 01)

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See detailControl of Aerial Manipulation Vehicle in Operational Space
Kannan, Somasundar UL; Quintanar Guzman, Serket UL; Dentler, Jan Eric UL et al

in 8th International Conference on Electronics, Computers and Artificial Intelligence, Ploiesti, Romania, 30 June-02 July 2016 (2016, July 01)

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See detailImpact of Different Spacing Policies for Adaptive Cruise Control on Traffic and Energy Consumption of Electric Vehicles
Bayar, Bilgehan; Sajadi Alamdari, Seyed Amin UL; Viti, Francesco UL et al

in 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece, 2016 (2016, June 23)

This paper assesses the impact of different spacing policies for Adaptive Cruise Control (ACC) systems on traffic and environment. The largest deal of existing studies focus on assessing the performance ... [more ▼]

This paper assesses the impact of different spacing policies for Adaptive Cruise Control (ACC) systems on traffic and environment. The largest deal of existing studies focus on assessing the performance in terms of safety, while only few deal with the effect of ACC on the traffic flow and the environment. In particular, very little is know on traffic stability and energy consumption. In this study, the vehicles equipped with ACC are modelled and controlled by two different spacing policies. Besides, Human Driving Behavior (HDB) is modelled by using Gipps model for comparison and for simulating different penetration rates. As distinguished from other studies, vehicle dynamics and energy consumption of an electric car is formulated, which has completely different characteristics and limitations than combustion engine cars. Hence the study aims at providing additional understanding of how ACC-equipped electric vehicles will behave in dense traffic conditions. HDB and ACC vehicles are placed in a roundabout at different penetration rates. String stability and energy consumption are investigated by giving a shock wave to a stable traffic condition. It is found that ACC with quadratic spacing policy has significantly positive effects on string stability and energy consumption. [less ▲]

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See detailA Modularization Approach for Nonlinear Model Predictive Control of Distributed Fast Systems
Dentler, Jan Eric UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece, June 21-24, 2016 (2016, June 22)

Distributed interconnected systems are omnipresent today. The development of advanced control methods for such systems are still challenging. Herein, the real-time applicability, flexibility, portability ... [more ▼]

Distributed interconnected systems are omnipresent today. The development of advanced control methods for such systems are still challenging. Herein, the real-time applicability, flexibility, portability and ease of implementation are issues of the existing control solutions, especially for more advanced methods such as model predictive control. This paper is addressing these issues by presenting an efficient modular composition scheme for distributed fast nonlinear systems. The advantage of this modularization approach is the capability of changing control objectives, constraints, dynamics and system topology online while maintaining fast computation. This work analyzes the functions that have to be provided for a continuation generalized minimal residual method (CGMRES) model predictive controller based on the underlying control problem. The specific structure of these functions allows their decomposition into suitable fast modules. These modules are then used to recompose the functions which are required for the control of distributed systems in a computational efficient way, while maintaining the flexibility to dynamically exchange system parts. To validate this computational efficiency, the computation time of the proposed modular control approach is compared with a standard nonmodular implementation in a pursuit scenario of quadrotor unmanned aerial vehicles (UAV). Furthermore the real-time applicability is discussed for the given scenario. [less ▲]

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See detailNonlinear Model Predictive Extended Eco-Cruise Control for Battery Electric Vehicles
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece, 2016 (2016, June 22)

Battery Electric Vehicles are becoming a promising technology for road transportation. However, the main disadvantage is the limited cruising range they can travel on a single battery charge. This paper ... [more ▼]

Battery Electric Vehicles are becoming a promising technology for road transportation. However, the main disadvantage is the limited cruising range they can travel on a single battery charge. This paper presents a novel extended ecological cruise control system to increase the autonomy of an electric vehicle by using energy-efficient driving techniques. Driven velocity, acceleration profile, geometric and traffic characteristics of roads largely affect the energy consumption. An energy-efficient velocity profile should be derived based on anticipated optimal actions for future events by considering the electric vehicle dynamics, its energy consumption relations, traffic and road geometric information. A nonlinear model predictive control method with a fast numerical algorithm is adapted to determine proper velocity profile. In addition, a novel model to describe the energy consumption of a series- production electric vehicle is introduced. The hyperfunctions concept is used to model traffic and road geometry data in a new way. The proposed system is simulated on a test track scenario and obtained results reveal that the extended ecological cruise control can significantly reduce the energy consumption of an electric vehicle. [less ▲]

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See detailOn the Unknown Input Functional Observers Design: a Polytopic Takagi-Sugeno Approach
Bezzaoucha, Souad UL; Voos, Holger UL; Darouach, Mohamed

in 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece, 2016 (2016, June)

In this paper, a step by step algorithm is given to design functional unknown input observer for continuous nonlinear systems under the Polytopic Takagi-Sugeno (T-S) framework. To nullify the effect of ... [more ▼]

In this paper, a step by step algorithm is given to design functional unknown input observer for continuous nonlinear systems under the Polytopic Takagi-Sugeno (T-S) framework. To nullify the effect of unknown input (UI), classical approach of decoupling the UI for the linear case is extended to the polytopic system. Applying the Lyapunov theory and the L2 attenuation, Linear Matrix Inequalities (LMI)s conditions are achieved which are solved for feasibility to obtain observer design matrices. The novelty of the proposed approach consists in solving simultaneously both structural constraints and LMIs, which ensure a mean for the efficient design of the gains of the observers. To illustrate the proposed theoretical results, simulation example of a Waste Water Treatment Plant (WWTP), which is highly nonlinear and represented in a T-S polytopic form with unmeasurable premise variables and unknown inputs, is discussed. [less ▲]

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See detailA Polytopic Approach for the Nonlinear Unknown Input Functional Observers Design: Application to a Quadrotor Aerial Robots Landing
Bezzaoucha, Souad UL; Voos, Holger UL; Darouach, Mohamed

in 2016 European Control Conference (ECC), Aalborg, Denmark (2016, June)

This paper considers a method of designing functional observers for continuous time nonlinear systems subject to unknown inputs. The proposed approach consists in rewriting the nonlinear model in a ... [more ▼]

This paper considers a method of designing functional observers for continuous time nonlinear systems subject to unknown inputs. The proposed approach consists in rewriting the nonlinear model in a polytopic form (also known as multiple or Takagi-Sugeno models) applying the Sector Nonlinearity Transformation (SNT) and then apply the proposed algorithm for the observer design. Sufficient conditions for the asymptotic stability of the estimation error are given in terms of linear matrix inequalities (LMIs) and rank conditions. An application to a quadrotor aerial robots landing is then presented. [less ▲]

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See detailA Flexible Move Blocking Strategy to Speed up Model-Predictive Control while Retaining a High Tracking Performance
Schwickart, Tim Klemens UL; Voos, Holger UL; Darouach, Mohamed et al

in 2016 European Control Conference (ECC), Aalborg, Denmark (2016, June)

This paper presents a strategy to reduce the complexity and thus the computational burden in modelpredictive control (MPC) by a flexible online input move blocking algorithm. Model-predictive sampled-data ... [more ▼]

This paper presents a strategy to reduce the complexity and thus the computational burden in modelpredictive control (MPC) by a flexible online input move blocking algorithm. Model-predictive sampled-data control of constrained, LTI plants is considered. Move blocking is an input parameterisation in MPC where the control input is forced to be constant over several prediction sample steps to reduce the dimensionality of the underlying optimisation problem. Typically, the prediction sample steps where the control input is not allowed to vary (i. e. the block distribution) is predetermined offline and is kept constant throughout the control operation. However, the control performance and computational efficiency can be improved if the block length is adjusted to the specific operating conditions. In this work, a heuristic method to adjust the block length online according to the initial state of the system, reference signals, measured disturbances and constraints is presented. A numerical example shows the effectiveness of the approach. [less ▲]

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See detailGeneralized Wake Interaction Models and Optimal Control in Wind Farms
Pan, Lin UL; Voos, Holger UL; Darouach, Mohamed

in 28th Control and Decision Conference (CCDC), China, 2016 (2016, May 28)

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See detailVision-Based Steering Control, Speed Assistance and Localization for Inner-CityVehicles
Olivares Mendez, Miguel Angel UL; Sanchez Lopez, Jose Luis UL; Jimenez, Felipe et al

in Sensors (2016), 16(3), 362

Autonomous route following with road vehicles has gained popularity in the last few decades. In order to provide highly automated driver assistance systems, different types and combinations of sensors ... [more ▼]

Autonomous route following with road vehicles has gained popularity in the last few decades. In order to provide highly automated driver assistance systems, different types and combinations of sensors have been presented in the literature. However, most of these approaches apply quite sophisticated and expensive sensors, and hence, the development of a cost-efficient solution still remains a challenging problem. This work proposes the use of a single monocular camera sensor for an automatic steering control, speed assistance for the driver and localization of the vehicle on a road. Herein, we assume that the vehicle is mainly traveling along a predefined path, such as in public transport. A computer vision approach is presented to detect a line painted on the road, which defines the path to follow. Visual markers with a special design painted on the road provide information to localize the vehicle and to assist in its speed control. Furthermore, a vision-based control system, which keeps the vehicle on the predefined path under inner-city speed constraints, is also presented. Real driving tests with a commercial car on a closed circuit finally prove the applicability of the derived approach. In these tests, the car reached a maximum speed of 48 km/h and successfully traveled a distance of 7 km without the intervention of a human driver and any interruption. [less ▲]

Detailed reference viewed: 438 (35 UL)