Showing papers by "Cédric Join published in 2019"
10 Jul 2019
TL;DR: Simulation results show that the proposed control architecture provides an effective control performance for the entire flight envelope and excellent disturbance rejections during the critical flight phases, such as transitioning and hovering flights in windy conditions.
Abstract: This paper discusses the development of a control architecture for hybrid Unmanned Aerial Vehicles (UAVs) based on model-free control (MFC) algorithms. Hybrid UAVs combine the beneficial features of fixed-wing UAVs with Vertical Take-Off and Landing (VTOL) capabilities to perform five different flight phases during typical missions, such as vertical takeoff, transitioning flight, forward flight, hovering and vertical landing. Based on model-free control principles, a novel control architecture that handles the hybrid UAV dynamics at any flight phase is presented. This unified controller allows autonomous flights without discontinuities of switching for the entire flight envelope with position tracking, velocity control and attitude stabilization. Simulation results show that the proposed control architecture provides an effective control performance for the entire flight envelope and excellent disturbance rejections during the critical flight phases, such as transitioning and hovering flights in windy conditions.
14 citations
Posted Content•
TL;DR: In this article, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis for supply chain management and inventory control.
Abstract: Supply chain management and inventory control provide most exciting examples of control systems with delays. Here, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis. Perishable inventories are also taken into account. The most intriguing ``bullwhip effect'' is explained and attenuated, at least in some important situations. Numerous convincing computer simulations are presented and discussed.
10 citations
23 Apr 2019
TL;DR: In this article, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis for supply chain management and inventory control.
Abstract: Supply chain management and inventory control provide most exciting examples of control systems with delays. Here, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis. Perishable inventories are also taken into account. The most intriguing “bullwhip effect” is explained and attenuated, at least in some important situations. Numerous convincing computer simulations are presented and discussed.
8 citations
Posted Content•
TL;DR: In this paper, an application to the computing resource allocation, via virtual machines, is sketched out, where a setting mixing algebraic estimation techniques and the daily seasonality behaves much better.
Abstract: Workload predictions in cloud computing is obviously an important topic. Most of the existing publications employ various time series techniques, that might be difficult to implement. We suggest here another route, which has already been successfully used in financial engineering and photovoltaic energy. No mathematical modeling and machine learning procedures are needed. Our computer simulations via realistic data, which are quite convincing, show that a setting mixing algebraic estimation techniques and the daily seasonality behaves much better. An application to the computing resource allocation, via virtual machines, is sketched out.
5 citations
02 Jul 2019
TL;DR: The air conditioning management of data centers, a key question with respect to energy saving, is here tackled via the recent model-free control synthesis, which shows excellent tracking performances in various realistic situations, like CPU load or temperature changes.
Abstract: The air conditioning management of data centers, a key question with respect to energy saving, is here tackled via the recent model-free control synthesis. Mathematical modeling becomes useless in this approach. The tuning of the corresponding intelligent proportional controller is straightforward. Computer simulations show excellent tracking performances in various realistic situations, like CPU load or temperature changes.
5 citations
TL;DR: In this paper, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis for supply chain management and inventory control.
Abstract: Supply chain management and inventory control provide most exciting examples of control systems with delays. Here, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis. Perishable inventories are also taken into account. The most intriguing "bullwhip effect" is explained and attenuated, at least in some important situations. Numerous convincing computer simulations are presented and discussed.
4 citations
Posted Content•
TL;DR: In this article, an application to the computing resource allocation, via virtual machines, is sketched out, where a setting mixing algebraic estimation techniques and the daily seasonality behaves much better.
Abstract: Workload predictions in cloud computing is obviously an important topic. Most of the existing publications employ various time series techniques, that might be difficult to implement. We suggest here another route, which has already been successfully used in financial engineering and photovoltaic energy. No mathematical modeling and machine learning procedures are needed. Our computer simulations via realistic data, which are quite convincing, show that a setting mixing algebraic estimation techniques and the daily seasonality behaves much better. An application to the computing resource allocation, via virtual machines, is sketched out.
3 citations
23 Apr 2019
TL;DR: Computer simulations via realistic data, which are quite convincing, show that a setting mixing algebraic estimation techniques and the daily seasonality behaves much better and an application to the computing resource allocation, via virtual machines, is sketched out.
Abstract: Workload predictions in cloud computing is obviously an important topic. Most of the existing publications employ various time series techniques, that might be difficult to implement. We suggest here another route, which has already been successfully used in financial engineering and photovoltaic energy. No mathematical modeling and machine learning procedures are needed. Our computer simulations via realistic data, which are quite convincing, show that a setting mixing algebraic estimation techniques and the daily seasonality behaves much better. An application to the computing resource allocation, via virtual machines, is sketched out.
2 citations
Posted Content•
TL;DR: In this paper, the air conditioning management of data centers, a key question with respect to energy saving, is tackled via the recent model-free control synthesis, and the tuning of the corresponding intelligent proportional controller is straightforward.
Abstract: The air conditioning management of data centers, a key question with respect to energy saving, is here tackled via the recent model-free control synthesis. Mathematical modeling becomes useless in this approach. The tuning of the corresponding intelligent proportional controller is straightforward. Computer simulations show excellent tracking performances in various realistic situations, like CPU load or temperature changes.
1 citations